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Average age of ms diagnosis: Multiple sclerosis – Symptoms and causes

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Multiple Sclerosis FAQs | National Multiple Sclerosis Society

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What is multiple sclerosis?

Multiple sclerosis is a chronic, unpredictable disease of the central nervous system (CNS), which is made up of the brain, spinal cord and optic nerves. It is thought to be an immune-mediated disorder, in which the immune system incorrectly attacks healthy tissue in the CNS.

In multiple sclerosis, damage in the central nervous system (CNS) interferes with the transmission of nerve signals between the brain and spinal cord and other parts of the body.

Most people are diagnosed between the ages of 20 and 50, although children and older adults may develop it. 



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Who gets MS?



Anyone may develop MS but there are some patterns. More than two to three times as many women as men develop MS and this gender difference has been increasing over the past 50 years. Studies suggest that genetic factors increase the risk of developing MS, but there is no evidence that MS is directly inherited. Environmental factors, such as low Vitamin D and cigarette smoking have also been shown to increase the risk of MS. MS occurs in most ethnic groups, including African-Americans, Asians and Hispanics/Latinos, but is most common in Caucasians of northern European ancestry.
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How many people have MS?

Worldwide, more than 2.3 million people have a diagnosis of MS. In the United States a recently completed prevalence study, funded by the National MS Society, has estimated that nearly 1 million people over the age of 18 live with a diagnosis of MS.  In 2016, the 21st Century Cures Act was signed into law, authorizing the Centers for Disease Control and Prevention (CDC) to create a National Neurological Conditions Surveillance System (NNCSS) to collect data on neurologic conditions to improve research and public health data on these conditions. The NNCSS received its first 5-year period of funding starting in fiscal year 2019 and the Society will ask Congress to continue its $5 million investment in this important System in fiscal year 2020.

The CDC is using multiple sclerosis and Parkinson’s disease, as demonstration projects to inform the creation of the Surveillance system and help the CDC determine the appropriate methodologies to use and identify areas of biggest impact. Using innovative methods and complex data sources, the CDC will gather information for these diseases and use similar methods to extend the NNCSS to other neurologic disease conditions. 

This system will be informed by the Society’s prevalence initiative, a four-year study that used millions of health records to get a more accurate count of the number of people in the US living with MS.  The study showed that nearly 1 million people in the United State live with MS – more than twice the number previously thought.



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What are the different types of MS?



While there is no way to predict with any certainty how MS will progress, four basic disease courses have been defined:

  • Clinically isolated syndrome-first episode of neurologic symptoms caused by inflammation and demyelination in the central nervous system.
  • Relapsing-remitting MS -characterized by periods of relapses (new symptoms or a new worsening of older symptoms also called attacks or exacerbations) that subside, with full or partial recovery, and no disease progression (worsening) between attacks.
  • Secondary progressive MS- follows relapsing-remitting MS in some people and is characterized by a more progressive course, with or without relapses or new MRI activity.
  • Primary progressive MS is characterized by a gradual but steady progression of disability from the onset of symptoms, with few or no relapses or remissions.


 Read more about the types of MS.
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What are the typical symptoms of MS?



Symptoms of MS are unpredictable and vary in type and severity from one person to another and in the same person over time. Symptoms may disappear or remit completely, or they may persist and may worsen over time.

The most common symptoms of MS include fatigue, numbness and tingling, blurred vision, double vision, weakness, poor coordination, imbalance, pain, depression and problems with memory and concentration. Less commonly MS may cause tremor, paralysis and blindness.

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What causes the symptoms?

Symptoms of MS occur because of damage within the central nervous system (brain, spinal cord and visual nerves). Inflammation from the MS immune process causes damage to myelin, (the protective insulation surrounding nerve fibers), oligodendrocytes (cells that make CNS myelin) and also the underlying nerve fibers. Symptoms may be temporary or permanent and may worsen over time.

 

 



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Does MS always cause paralysis?



No. Moreover, the majority of people with MS do not become severely disabled. Two-thirds of people who have MS remain able to walk, though many will need an aid, such as a cane or crutches, and some will use a scooter or wheelchair because of fatigue, weakness, balance problems, or to assist with conserving energy. 
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Is MS fatal?

Life expectancy has increased over time. We believe this is due to treatment breakthroughs, improved healthcare and lifestyle changes. Research indicates that the average life expectancy of people with MS is about seven years less than the general population because of disease complications or other medical conditions. Many of these complications are preventable or manageable. Attention to overall health and wellness can help reduce the risk of other medical conditions, such as heart disease and stroke, that can contribute to a shortened life expectancy. In very rare instances, MS can progress rapidly from disease onset and can be fatal.



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Is MS contagious or inherited?



No. MS is not contagious or directly inherited. Studies do indicate that genetic factors and certain environmental factors may make certain individuals more susceptible to the disease.
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Can MS be cured?

Not yet. There are now FDA-approved medications that have been shown to “modify” the course of MS by limiting new areas of damage in the CNS, reducing the number of relapses and delaying progression of disability. In addition, many therapeutic and technological advances are helping with more effective symptom management. Advances in treating and understanding MS are made every year, hopefully moving research closer to identifying a cure.



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What can be done about MS now?



If you have been diagnosed with MS, the National MS Society recommends you consider treatment with one of the FDA-approved “disease-modifying” drugs as soon as possible following the definite diagnosis of MS with active or relapsing disease. These medications help to reduce the frequency and severity of MS attacks, the number of new lesions in the CNS and may slow the progression of disability. These medications are approved for relapsing forms of multiple sclerosis, which include clinically isolated syndrome, relapsing-remitting disease (RRMS) and active secondary progressive disease (SPMS with relapses).

In addition to these medications that address the disease process, there are many medications and other strategies to manage MS symptoms. You should consult a knowledgeable MS care provider to develop a comprehensive plan to manage your MS.

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Why is early treatment important?



Early damage in the CNS can occur even before you are experiencing any symptoms. Studies show that the best chance for reducing long-term disability is during the early relapsing phase of the disease, which is characterized by inflammation. Given that the medications currently available all primarily target inflammation, early and ongoing treatment helps to minimize this inflammation and also reduces damage to nerve fibers (axons) and loss of brain tissue.
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Why is MS so difficult to diagnose?



Diagnosing MS can be a challenging process. In early MS, symptoms may be non-specific and suggestive of several disorders of the nervous system. Early symptoms that come and go may be ignored. While no single laboratory test is yet available to prove or rule out MS, magnetic resonance imaging (MRI) is a great help in reaching a definitive diagnosis.   Diagnostic criteria that incorporate MRI findings and spinal fluid analysis have been developed and revised by experts in the field to help providers make an accurate and timely diagnosis.

How Age Affects Multiple Sclerosis Symptoms and Progression

Most people with multiple sclerosis (MS) are diagnosed between age 20 and 50, though it can occur in children as well as in older adults, according to the National Multiple Sclerosis Society (NMSS).

About 85 percent of people diagnosed with MS are initially diagnosed with the relapsing form of the condition, usually referred to as relapsing-remitting MS, which is characterized by periods of active symptoms — sometimes called flares or exacerbations — alternating with periods of less-severe symptoms.

Eventually, as many as 90 percent of these people reach a stage known as secondary-progressive MS (SPMS), in which symptoms gradually worsen and a person experiences increasing levels of disability. That might include more difficulty walking, loss of stamina, and cognitive problems. Some people with SPMS continue to experience relapses, but many don’t.

The transition from relapsing-remitting MS to secondary-progressive MS appears to be age dependent, with the forties being the most common period to experience it, according to a review article published in April 2021 in Frontiers in Neurology.

However, the authors of the review say, because there is no consensus among experts regarding any specific diagnostic criteria for disability progression, nor are there any definitive biomarkers of progression, a diagnosis of SPMS can only be retrospective (after the fact). That limits doctors’ ability to treat MS progression in its early stages.

Age at Diagnosis and MS Progression

The thinking used to be that MS progressed more quickly in people diagnosed at an older age. Indeed, research published in the Journal of Neurology, Neurosurgery & Psychiatry found that children diagnosed with MS took longer to develop secondary-progressive disease (32 years) than adults diagnosed with MS (18 years), and they also took longer to reach disability milestones.

But the study authors note that those diagnosed as children hit disability milestones at a younger age and therefore could be considered to have a poorer prognosis.

Helen Tremlett, PhD, Canada research chair in neuroepidemiology and multiple sclerosis and a professor at the University of British Columbia in Vancouver, says that her work since 2006 has shown that late-onset MS does not necessarily mean “a worse outcome for the patient.”

Dr. Tremlett participated in a study published in April 2015 in the European Journal of Neurology, which investigated whether the use of the widely prescribed MS drugs known as beta interferons delays the onset of secondary-progressive MS; it found that they do not.

However, a study published in January 2019 in the Journal of the American Medical Association suggests otherwise. When researchers compared MS medications including beta interferons, glatiramer (Copaxone, Glatopa), fingolimod (Gilenya), natalizumab (Tysabri), and alemtuzumab (Campath, Lemtrada) versus no treatment at all, they found that treatment with any of these medications was associated with a lower risk of transition to SPMS.

In particular, fingolimod, natalizumab, and alemtuzumab were associated with the lowest risk of progression to SPMS, and treatment was especially beneficial when started sooner — less than five years after disease onset — rather than later.

Tremlett also coauthored a systematic review of MS research published in July 2017 in the journal Neurotoxicology that looked at risk factors associated with onset, relapses, and progression in MS. The review focused on factors that are modifiable, and among these, smoking appeared to accelerate disease progression.

A more recent study, published in April 2020 in the journal Neurology, also identified smoking, along with older age, greater disability, motor and brain stem dysfunction, and spinal lesions at the time of diagnosis, as risk factors for transitioning from relapsing-remitting MS to secondary-progressive MS.

MS in Children

Up to 10 percent of MS cases are diagnosed in children and teens, according to the MS International Federation.  Although MS in children is generally understood to be the same disease as MS in adults, there are some key differences.

“Children experience similar MS symptoms to adults, including motor symptoms and weakness, but children tend to have more relapses than adults,” says Tanuja Chitnis, MD, a professor of neurology at Harvard Medical School and director of the Partners Pediatric Multiple Sclerosis Center at Massachusetts General Hospital for Children in Boston.

A study published in June 2019 in Neurology further confirmed a higher relapse rate in children with MS than in adults and showed that children are more likely to be diagnosed with relapsing forms of the disease and often experience longer diagnostic delays than adults.

Dr. Chitnis adds, “There is a slower course of progression, and kids have less disability early on in their disease course.”

Still, she says, it’s important to note that a 30-year-old with pediatric-onset MS will have more disability than a 30-year-old with adult-onset MS. “Better treatment strategies are required in kids,” she says.

There have been new initiatives to conduct clinical trials in children with MS to better understand effective treatment options in this age group.

MS After 50: Aging and MS Symptoms Overlap

Only a small percentage of people with MS receive their diagnosis after age 50. In some cases, these people have late-onset MS. But for some, the diagnosis represents a delayed identification of years — or even decades — of unrecognized symptoms.

Mental and physical changes associated with aging can be similar to, or overlap with, symptoms of MS. Such symptoms may include muscle weakness, balance problems, fatigue, visual changes, cognitive impairment (such as problems thinking and remembering), and sleep disturbances.

Older people with MS are also more prone to such MS complications as urinary tract infections, pneumonia, septicemia (infection of the blood), and cellulitis (bacterial skin infection) than peers who don’t have MS, according to the NMSS.

In addition, age impacts your ability to recover from an MS relapse. A study published in October 2018 in the Multiple Sclerosis Journal showed that it’s more difficult to rebound from a relapse as you get older.

The combination of aging and MS-related symptoms can exacerbate any of the health problems a person has. For instance, people with mobility problems due to MS may have difficulty traveling to and from healthcare appointments, so they may forgo these trips and miss needed care — for both their MS and other medical conditions.

Decreased mobility can also be hard on the heart: Being less active is a known risk factor for heart disease.

Research is mixed on the emotional effects of MS on older people. A study published in 2015 in the journal Psychology, Health & Medicine found evidence suggesting that older people with MS experience less psychological distress in response to impaired physical functioning than younger people with MS.

But a study published in the Journal of Psychosomatic Research found that people age 65 and older who have MS were four times as likely to engage in suicidal thoughts as younger people with MS.

At any age, depression and thoughts of suicide shouldn’t be ignored. If you or a friend or family member who has MS experiences signs of depression or is thinking about suicide, seek help from your doctor or a mental health professional.

Effect of MS on Life Span

Ultimately, MS is a chronic illness, not a terminal one. While it can slightly shorten life span, Chitnis says the reduction is unsubstantial: “I have seen many MS patients who live to be 70 or 80 years old.”

A study published in July 2015 in the journal Neurology that used health data from Manitoba, Canada, confirms Chitnis’s observation. In the population studied, people with MS had a median life span of 75.9 years, while for people without MS, it was 83.4 years.

According to the study, “The most common causes of death in the MS population were diseases of the nervous system and diseases of the circulatory system. Mortality rates due to infectious diseases and diseases of the respiratory system were higher in the MS population.

A study published online in July 2017 in the Journal of Neurology, Neurosurgery, and Psychiatry yielded similar findings.

Among 1,388 Norwegians who developed MS between 1953 and 2012, the average life expectancy was found to be 74.7 years among people with MS compared with 81.8 years in the general population — but survival of MS increased over time, researchers noted.

Additional reporting by Beth W. Orenstein and Christina Vogt.

Does early-onset multiple sclerosis differ from adult-onset form in Iranian people

J Res Med Sci. 2010 Mar-Apr; 15(2): 94–99.

Fereshteh Ashtari

aDepartment of Neurology, School of Medicine, Isfahan University of Medical Sciences, Isfahan, Iran

bIsfahan University of Medical Sciences, Isfahan, Iran

cIsfahan Medical Education Research Center, Isfahan, Iran

Vahid Shaygannejad

aDepartment of Neurology, School of Medicine, Isfahan University of Medical Sciences, Isfahan, Iran

bIsfahan University of Medical Sciences, Isfahan, Iran

Ziba Farajzadegan

cIsfahan Medical Education Research Center, Isfahan, Iran

Ali Amin

dSchool of Medicine, Isfahan University of Medical Sciences, Isfahan, Iran

aDepartment of Neurology, School of Medicine, Isfahan University of Medical Sciences, Isfahan, Iran

bIsfahan University of Medical Sciences, Isfahan, Iran

cIsfahan Medical Education Research Center, Isfahan, Iran

dSchool of Medicine, Isfahan University of Medical Sciences, Isfahan, Iran

Received 2009 Jul 29; Accepted 2009 Nov 15.

Copyright © Journal of Research in Medical Sciences

This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

This article has been cited by other articles in PMC.

Abstract

BACKGROUND:

Few studies have attempted to delineate the clinical profile of multiple Sclerosis (MS) among people of Asia. This study sought to identify the characteristics of early-onset Multiple Sclerosis (EOMS) comparison to adult-onset form (AOMS) in Isfahan, IRAN.

METHODS:

This prospective study was conducted on 104 youths with multiple sclerosis beginning before the age of 16 years and 123 patients with adult-onset multiple sclerosis. Patients were observed for a mean period of 5 years. The common presenting symptoms, MRI finding, course of disease and disability score were compared between the two groups.

RESULTS:

The mean onset age of disease in youths and adults were 14 ± 1.9 and 27.7 ± 8.06 years, respectively. Female/male ratio was 4.47:1 in EOMS and 3.92:1 in AOMS, this ratio was 7:1 in early childhood MS (≤ 10 year). The most common presenting symptom was optic neuritis in the EOMS group and paresthesia in AOMS. Optic neuritis was common in AOMS too, but brainstem/cerebellar signs were more common in EOMS than AOMS. Seizure occurred more frequently in EOMS than in the AOMS group (12.6% vs. 1.6%, respectively, p < 0.001). MRI showed that brainstem plaques were more prevalent in the EOMS compared with the AOMS group.

CONCLUSIONS:

It was concluded that early-onset MS does not significantly differ from adult form in terms of major clinical manifestation and course of disease, however Seizure is more common in EOMS, and brainstem and cerebellar symptoms as presenting symptom are more common.

Keywords: Multiple Sclerosis, Optic Neuritis, Adulthood

Multiple Sclerosis (MS) is a chronic inflammatory demylinating and disabling disease, which primarily affect young adults between 20 and 40 years of age. In 0.4% to 10.5% of cases, onset occurs in childhood (before the age of 16 years).1,2

Although the onset of MS in childhood is recognized worldwide, several barriers exist to its prompt diagnosis in children.3 Many clinicians consider MS as an exclusively adult-onset disease. Therefore, they may not suggest such diagnosis in a child. Moreover, the clinical and radiographic diagnostic criteria for MS have not been validated clearly in the pediatric age group.4

As a result of variability of the clinical features and course and long term prognosis of early onset multiple sclerosis (EOMS), sometimes there is delay in diagnose and therapy of young patients.5,6

Natural history studies provide important information about MS course and prognosis that might help in treatment approaches.7,8 However, prognosis of MS according to its age of onset remains controversial. Some researchers reported better outcome in EOMS, whereas others found more favorable prognosis in AOMS than EOMS. 9 It is suggested that although the course of MS might be slower in children compared to adults, significant disability may be accumulated in early adulthood and the patient will be disabled at a younger age.10 Nevertheless, some researchers found no influence of age of onset on the prognosis.11

Considering the importance of early treatment of MS in adult, the necessity of understanding the natural history of EOMS becomes more evident.12

In addition, understanding the differences between MS in children and adults is helpful, since research findings in adults could be extrapolated to children and teenagers.

The objective of this survey was to highlight the clinical and demographic features of EOMS in Isfahan, Iran and to compare the clinical and paraclinical features of EOMS with adult onset MS (AOMS).

Methods

The sample of this study consisted of 106 MS patients in whom the first attack occurred before the age of 16 years. Simultaneously 130 clinically definite MS patients with adult onset disease and about same duration of disease randomly allocated from Isfahan MS clinics. Diagnosis of MS was confirmed by two neurologists according to McDonald criteria.13 Patients were monitored from January 2000 to August 2006 through routine clinical visits and regular telephone interviews.

All patients underwent brain MRI with field strengths of 1.0 Tesla superconductive system. Axial, sagittal, and coronal, T1-weighted, T2-weighted, fluid attenuated inversion recovery (FLAIR), and proton density sequence imaging were performed. MRI findings were analyzed by the Barkhof’s criteria.14

Two patients in EOMS and seven in AOMS were excluded from the study because follow-up was ceased.

Data Collection

A clinical reporting form was designed for every patient and was used in the follow-up course.

The baseline data included familial MS history, age, sex and detailed clinical and MRI characteristics, seizure, and amount of disabilities in the beginning and after 5 years follow-up according to Kurtzke’s Expanded Disability Status Scale (EDSS),15 which was detected at least by two neurologists. Certain laboratory tests such as measurement of serum antinuclear antibodies (ANA), antineutrophil cytoplasmic antibodies (ANCA), antiphospholipids and anticardiolipin IgG and IgM antibodies, lupus anticoagulant were performed for all of patients to rule out common differential diagnosis of MS.

All MRI scans were reviewed by observers blinded to the clinical course.

The data collected for disease course included the characteristics of subsequent attacks and occurrence of any disability. Data were obtained directly from the medical records kept by the neurologists.

The mean duration of follow up was 4.9 years in EOMS patients and 5.1 years in AOMS.

Clinical course was classified according to standardized definitions.

The Ethics Committee of the Faculty of Medicine and Biomedical Sciences of the Isfahan University of Medical Sciences approved the study.

Statistical Analysis

The demographic and clinical data were stored in a database and were analyzed by SPSS version 11. Qualitative variables were compared using chi square test. Variables with p < 0.05 were considered significant.

Results

Ultimately 227 MS patients were studied, of which, 104 patients had onset-age less than 16 years of age (EOMS) and 123 patients had onset in adult age (AOMS).

In total, the mean age at onset was 21.46 ± 9.1 years while it was 27.7 ± 8.06 (range: 19-40 years) in the AOMS group and 14 ± 1.9 (range: 5-16 years) in the EOMS group.

In the EOMS group 77.8% showed a clinical onset between 14 to 16 years; in 8 out of 104 patients (7.7%) the disease started at age 10 years or less. The latter group was considered as a true childhood-onset MS.

In EOMS group 81.7% (85 patients) and in AOMS group 79.7% (98 patients) were female (p = 0.696) and the female/male ratio was 4.47:1 vs. 3.92:1 in the two groups, respectively. The proportion of girl to boy was 7:1 in childhood-onset MS group, and female predominance was significant.

The most frequent clinical course in both MS groups was relapsing-remitting and 83. 7% of EOMS and 84.6% of AOMS patients had this type of course (p = 0.85).

The most common presenting symptoms in EOMS patients were optic neuritis followed by brainstem/cerebellar symptoms, while they were paresthesia followed by optic neuritis and brainstem/cerebellar involvement in AOMS (). One of EOMS patient had encephalopathy picture at onset; the disease was repeated approximately 3 months later and was recovered, but after 5 months she had another relapse and got secondary progressive course.

Table 1

The Characteristics of patients in both MS groups

AOMS n = 123 EOMS n = 104 P value
Mean age of onset 27.7 ± 8.06 14 ± 1.9
Female/male (ratio) 98/25 (3.92/1) 85/19 (4.47/1)
Disease course:
 Relapsing-remitting 104 (84.6%) 87 (83.7%) 0.85
 Secondary progressive 16 (13.0%) 14 (13.5%) 0.92
 Primary progressive 3 (2.4%) 3 (2.9%) 0.83
Optic neuritis at onset 36 (29.3%) 35 (33.7%) 0.48
Parasthesias at onset 45 (36.6%) 15 (15.4%) 0.9
Cerebellar/brainstem at onset 23 (18.7%) 32 (30.8%) 0.034
Motor at onset 18 (14.6%) 15 (14.4%) 0.9
 Others at onset (seizure, sphincter symptom) 1 (0.8%) 4 (3.8%) 0.12
EDSS (after 5 years):
 < 3.5 104 (84.6%) 84 (80.8%) 0.46
 ≥ 3.5 19 (15.4%) 20 (19.2%)
MRI finding:
 Periventricular 93 (75.6%) 77 (74%) 0.78
 Cerebellar/brainstem 14 (11.4%) 18 (17.3%) 0.2
Seizure 2 (1.6%) 13 (12.6%) 0.00

Family history was investigated in all MS patients; 8.7% (n = 9 cases) of EOMS and 12.2% (n = 15 cases) of AOMS patients had a positive family history (p = 0.51). None of the cases of childhood MS patients reported a positive family history for MS.

In the brain MRI, periventricular plaque was the most frequent finding in both EOMS and AOMS groups. A high number of patients (74% in EOMS vs. 75.6% in AOMS) had periventricular white matter lesion compatible with MS plaques in T2 W and FLAIR imaging, without significant difference (p = 0.78). The most common finding of MRI in childhood-onset MS was also periventricular plaques (75%). Brainstem plaques were more frequent in the EOMS than in AOMS group, but the differences were not significant (17.3% vs. 11.4% respectively, p = 0.2).

Seizure occurred more frequently in EOMS than in the AOMS group (12.6% vs. 1.6% respectively, p < 0.001).

After 5 years follow up, 80.8 percent of the patients in the EOMS group and 84.6 percent of the patients in the AOMS group had EDSS of less than 3.5 with no significant difference (p = 0.46). One case of EOMS died after two years.

Discussion

The present study showed that although, EOMS is less common, but it does not differ significantly from AOMS. However, some EOMS aspects are peculiar.

In the present series, the youngest age-onset was 5 years. The youngest known patient with MS was a 24 months old child reported by Bejar in 1984.16

It is well documented that MS is more common in women than men. According to the results of this study, the female/male ratio in the EOMS was 4.47:1 and in AOMS was 3.92:1, and 7:1 in childhood MS. These ratios are higher than many other studies, such as the one in Canada in which female to male ratio in childhood-onset MS was reported 3.2:1,17 and the one in Turkey which reported a ratio of 2.5:1.10 Several authors reported a higher frequency of MS among women especially during puberty age. In the study of Ghezzi et al female/male ratio was 4.7 in EOMS with age 12 years, suggesting role of hormonal changes in triggering MS onset.18 But in the present study, sex ratio in prepubertal period was not lower than pubertal period. So present findings may not support the role of hormonal changes in triggering MS.

Although the higher female to male ratio in childhood cases has been documented in some previous studies,19,20 the results of Simon et al showed significant male preponderance in the group age of less than 10 years.2

In the present study, the most common initial symptom was optic neuritis in EOMS and paresthesia in AOMS. Brainstem and cerebellar symptoms were significantly more common in EOMS and optic neuritis was common presentation in both groups. These findings agree with previous collaboration studies, which showed brainstem and cerebellar symptoms at onset were more common in EOMS patients.5

On the other hand, in a multicenter study of 125 patients with childhood MS, Duquette et al reported that sensory disturbances were the most common initial manifestation of disease occurring in 26.4% of cases, followed by optic neuritis.19 A cooperative retrospective study of 3375 MS patients (149 cases of EOMS) reported higher frequency of brainstem dysfunction in the EOMS group than in the AOMS group.21

Contrary to present findings, the most common presenting symptoms in Taiwan were limb weakness (62%) and visual disturbance (43%).22

Seizure was reported more frequent in MS patients than in general population and it has occurred in 10% of Indian multiple sclerotic patients.23 Overall seizure occurs in about 5% of children with MS, but it is much more common in children under age of 10 years.3,24,25 In the present study, 12.6% of EOMS had seizure that occurred in first two years of disease and 1.6% of AOMS had also seizure (p = 0.001). All of the patients had good prognosis and seizure was controlled completely by one antiepileptic drug, as in Striano et al study.25

Consistent with previous studies in EOMS, the clinical course was predominantly Relapsing-Remitting form (83.7%) and only 2.9% had primary progressive course.19

The family history was positive in 8.7% of EOMS and 12.2% of AOMS in the present study, while it was 13.2% in the study of Ozakbas et al.11 Periventricular plaques were common MRI findings in both groups, as it was in previous study and 90% of EOMS patients fulfilled Barkof’s criteria of MS. But brainstem plaques were more frequent in EOMS, which may explain more common brainstem finding in them.

There are several studies about the prognosis of EOMS patients.26 According to these studies after a long period of time from onset of the disease, clinical disabilities in EOMS are less than in AOMS, but ultimately clinical disabilities in EOMS reach a high degree in younger ages compared to the patients in the AOMS groups.1,21 The results of the present study showed no differences of disabilities in the two groups but a longer follow-up is necessary to decide about this point.

Conclusions

The findings of this study suggest that EOMS should be similar to AOMS in many aspects but there are some differences such as more Brainstem/cerebellar signs at presentation and more seizure in course of disease, so paying attention to these symptoms is important.

Footnotes

Conflict of Interest

Authors have no conflict of interests.

Authors’ Contributions

FA carried out the design and coordinated the study and prepared the manuscript. VS and AA provided assistance in patients follow-up and data collection. ZF coordinated in statistical analysis. All authors have read and approved the content of manuscript.

References

1. Renoux C, Vukusic S, Mikaeloff Y, Edan G, Clanet M, Dubois B, et al. Natural history of multiple sclerosis with childhood onset. N Engl J Med. 2007;356(25):2603–13. [PubMed] [Google Scholar]2. Simone IL, Carrara D, Tortorella C, Liguori M, Lepore V, Pellegrini F, et al. Course and prognosis in early-onset MS: comparison with adult-onset forms. Neurology. 2002;59(12):1922–8. [PubMed] [Google Scholar]3. Banwell B, Ghezzi A, Bar-Or A, Mikaeloff Y, Tardieu M. Multiple sclerosis in children: clinical diagnosis, therapeutic strategies and future direction. Lancet Neurol. 2007;6(10):887–902. [PubMed] [Google Scholar]4. Banwell BL. Pediatric multiple sclerosis. Curr Neurol Neurosci Rep. 2004;4(3):245–52. [PubMed] [Google Scholar]5. Deryck O, Ketelaer P, Dubois B. Clinical characteristics and long term prognosis in early onset multiple sclerosis. J Neurol. 2006;253(6):720–3. [PubMed] [Google Scholar]6. Gadoth N. Multiple sclerosis in children. Brain Dev. 2003;25(4):229–32. [PubMed] [Google Scholar]7. Martin CL, Phillips BA, Kilpatrick TJ, Butzkueven H, Tubridy N, McDonald E, et al. Gait and balance impairment in early multiple sclerosis in the absence of clinical disability. Mult Scler. 2006;12(5):620–8. [PubMed] [Google Scholar]8. Montalban X. The importance of long-term data in multiple sclerosis. J Neurol. 2006;253(Suppl 6):vi9–15. [Google Scholar]9. Simone IL, Carrara D, Tortorella C, Ceccarelli A, Livrea P. Early onset multiple sclerosis. Neurol Sci. 2000;21(4 Suppl 2):S861–3. [PubMed] [Google Scholar]10. Ness JM, Chabas D, Sadovnick AD, Pohl D, Banwell B, Weinstock-Guttman B, et al. Clinical features of children and adolescents with multiple sclerosis. Neurology. 2007;68(16 Suppl 2):S37–45. [PubMed] [Google Scholar]11. Ozakbas S, Idiman E, Baklan B, Yulug B. Childhood and juvenile onset multiple sclerosis: clinical and paraclinical features. Brain Dev. 2003;25(4):233–6. [PubMed] [Google Scholar]12. Compston A, McDonald IR, Noseworthy J, Lassman H, Miller DH, Smith KH, et al. 4 th ed. London: Churchill Livingstone; 2005. McAlpine’s multiple sclerosis. [Google Scholar]13. Polman Ch, Reingold SC, Edan G, Filippi M, Hartung HP, Kappos L, et al. Diagnostic criteria for multiple sclerosis: 2005 revision to the “McDonald Criteria” Ann Neurol. 2005;58(6):840–6. [PubMed] [Google Scholar]14. Barkhof F, Filippi M, Miller DH, Scheltens P, Campi A, Polman CH, et al. Comparison of MRI criteria at first presentation to predict conversion to clinically definite multiple sclerosis. Brain. 1997;120(Pt 11):2059–69. [PubMed] [Google Scholar]15. Kurtzke JF. Rating neurologic impairment in multiple sclerosis: an expanded disability status scale (EDSS) Neurology. 1983;33(11):1444–52. [PubMed] [Google Scholar]16. Bejar JM, Ziegler DK. Onset of multiple sclerosis in a 24-month-old child. Arch Neurol. 1984;41(8):881–2. [PubMed] [Google Scholar]17. Orton SM, Herrera BM, Yee IM, Valdar W, Ramagopalan SV, Sadovnick AD, et al. Sex ratio of multiple sclerosis in Canada: a longitudinal study. Lancet Neurol. 2006;5(11):932–6. [PubMed] [Google Scholar]18. Ghezzi A, Pozzilli C, Liguori M, Marrosu MG, Milani N, Milanese C, et al. Prospective study of multiple sclerosis with early onset. Mult Scler. 2002;8(2):115–8. [PubMed] [Google Scholar]19. Duquette P, Murray TJ, Pleines J, Ebers GC, Sadovnick D, Weldon P, et al. Multiple sclerosis in childhood: clinical profile in 125 patients. J Pediatr. 1987;111(3):359–63. [PubMed] [Google Scholar]20. Ruggieri M, Polizzi A, Pavone L, Grimaldi LM. Multiple sclerosis in children under 6 years of age. Neurology. 1999;53(3):478–84. [PubMed] [Google Scholar]21. Ghezzi A, Deplano V, Faroni J, Grasso MG, Liguori M, Marrosu G, et al. Multiple sclerosis in childhood: clinical features of 149 cases. Mult Scler. 1997;3(1):43–6. [PubMed] [Google Scholar]22. Weng WC, Yang CC, Yu TW, Shen YZ, Lee WT. Multiple sclerosis with childhood onset: report of 21 cases in Taiwan. Pediatr Neurol. 2006;35(5):327–34. [PubMed] [Google Scholar]23. Ganguly G, Barma P, Das SK, Roy T. Seizure in multiple sclerosis in Eastern India. Neurology Asia. 2006;11:123–7. [Google Scholar]24. Nicoletti A, Sofia V, Biondi R, Lo Fermo S, Reggio E, Patti F, et al. Epilepsy and multiple sclerosis in Sicily: a population-based study. Epilepsia. 2003;44(11):1445–8. [PubMed] [Google Scholar]25. Striano P, Orefice G, Brescia Morra V, Boccella P, Sarappa C, Lanzillo R, et al. Epileptic seizures in multiple sclerosis: clinical and EEG correlations. Neurol Sci. 2003;24(5):322–8. [PubMed] [Google Scholar]26. Liguori M, Marrosu MG, Pugliatti M, Giuliani F, De Robertis F, Cocco E, et al. Age at onset in multiple sclerosis. Neurol Sci. 2000;21(Suppl 2):S825–9. [PubMed] [Google Scholar]

Epidemiology and treatment of multiple sclerosis in elderly populations

  • 1.

    Marrie, R. A., Yu, N., Blanchard, J., Leung, S. & Elliott, L. The rising prevalence and changing age distribution of multiple sclerosis in Manitoba. Neurology 74, 465–471 (2010).

    CAS 
    PubMed 

    Google Scholar 

  • 2.

    Finlayson, M. Concerns about the future among older adults with multiple sclerosis. Am. J. Occup. Ther. 58, 54–63 (2004).

    PubMed 

    Google Scholar 

  • 3.

    Tutuncu, M. et al. Onset of progressive phase is an age-dependent clinical milestone in multiple sclerosis. Mult. Scler. 19, 188–198 (2013).

    PubMed 

    Google Scholar 

  • 4.

    Scalfari, A., Neuhaus, A., Daumer, M., Muraro, P. A. & Ebers, G. C. Onset of secondary progressive phase and long-term evolution of multiple sclerosis. J. Neurol. Neurosurg. Psychiatry 85, 67–75 (2014).

    PubMed 

    Google Scholar 

  • 5.

    Koch-Henriksen, N., Laursen, B., Stenager, E. & Magyari, M. Excess mortality among patients with multiple sclerosis in Denmark has dropped significantly over the past six decades: a population based study. J. Neurol. Neurosurg. Psychiatry 88, 626–631 (2017).

    PubMed 

    Google Scholar 

  • 6.

    Hirst, C., Swingler, R., Compston, D. A., Ben-Shlomo, Y. & Robertson, N. P. Survival and cause of death in multiple sclerosis: a prospective population-based study. J. Neurol. Neurosurg. Psychiatry 79, 1016–1021 (2008).

    CAS 
    PubMed 

    Google Scholar 

  • 7.

    Hurwitz, B. J. Analysis of current multiple sclerosis registries. Neurology 76 (Suppl. 1), S7–S13 (2011).

    PubMed 

    Google Scholar 

  • 8.

    Lunde, H. M. B., Assmus, J., Myhr, K. M., Bo, L. & Grytten, N. Survival and cause of death in multiple sclerosis: a 60-year longitudinal population study. J. Neurol. Neurosurg. Psychiatry 88, 621–625 (2017).

    PubMed 
    PubMed Central 

    Google Scholar 

  • 9.

    Kingwell, E. et al. Relative mortality and survival in multiple sclerosis: findings from British Columbia. J. Neurol. Neurosurg. Psychiatry 83, 61–66 (2012).

    CAS 
    PubMed 

    Google Scholar 

  • 10.

    Minden, S. L., Frankel, D., Hadden, L. S., Srinath, K. P. & Perloff, J. N. Disability in elderly people with multiple sclerosis: an analysis of baseline data from the Sonya Slifka Longitudinal Multiple Sclerosis Study. Neurorehabilitation 19, 55–67 (2004).

    PubMed 

    Google Scholar 

  • 11.

    Rotstein, D. L. et al. Temporal trends in multiple sclerosis prevalence and incidence in a large population. Neurology 90, e1435–e1441 (2018).

    PubMed 

    Google Scholar 

  • 12.

    Grytten, N., Torkildsen, O. & Myhr, K. M. Time trends in the incidence and prevalence of multiple sclerosis in Norway during eight decades. Acta Neurol. Scand. 132, 29–36 (2015).

    CAS 
    PubMed 
    PubMed Central 

    Google Scholar 

  • 13.

    Alla, S., Pearson, J., Debernard, L., Miller, D. & Mason, D. The increasing prevalence of multiple sclerosis in New Zealand. Neuroepidemiology 42, 154–160 (2014).

    PubMed 

    Google Scholar 

  • 14.

    Dilokthornsakul, P. et al. Multiple sclerosis prevalence in the United States commercially insured population. Neurology 86, 1014–1021 (2016).

    PubMed 
    PubMed Central 

    Google Scholar 

  • 15.

    Solaro, C. et al. The changing face of multiple sclerosis: prevalence and incidence in an aging population. Mult. Scler. 21, 1244–1250 (2015).

    CAS 
    PubMed 

    Google Scholar 

  • 16.

    Barnett, M. H., Williams, D. B., Day, S., Macaskill, P. & McLeod, J. G. Progressive increase in incidence and prevalence of multiple sclerosis in Newcastle, Australia: a 35-year study. J. Neurol. Sci. 213, (1–6 (2003).

    Google Scholar 

  • 17.

    Simpson, S. Jr. et al. Trends in the epidemiology of multiple sclerosis in Greater Hobart, Tasmania: 1951 to 2009. J. Neurol. Neurosurg. Psychiatry 82, 180–187 (2011).

    PubMed 

    Google Scholar 

  • 18.

    Sarasoja, T., Wikstrom, J., Paltamaa, J., Hakama, M. & Sumelahti, M. L. Occurrence of multiple sclerosis in central Finland: a regional and temporal comparison during 30 years. Acta Neurol. Scand. 110, 331–336 (2004).

    CAS 
    PubMed 

    Google Scholar 

  • 19.

    Mayr, W. T. et al. Incidence and prevalence of multiple sclerosis in Olmsted County, Minnesota, 1985–2000. Neurology 61, 1373–1377 (2003).

    CAS 
    PubMed 

    Google Scholar 

  • 20.

    Daltrozzo, T., Hapfelmeier, A., Donnachie, E., Schneider, A. & Hemmer, B. A systematic assessment of prevalence, incidence and regional distribution of multiple sclerosis in Bavaria from 2006 to 2015. Front. Neurol. 9, 871 (2018).

    PubMed 
    PubMed Central 

    Google Scholar 

  • 21.

    Grassivaro, F. et al. Multiple sclerosis incidence and prevalence trends in the province of Padua, northeast Italy, 1965–2018. Neuroepidemiology 52, 41–46 (2018).

    PubMed 

    Google Scholar 

  • 22.

    Ribbons, K., Lea, R., Tiedeman, C., Mackenzie, L. & Lechner-Scott, J. Ongoing increase in incidence and prevalence of multiple sclerosis in Newcastle, Australia: a 50-year study. Mult. Scler. 23, (1063–1071 (2017).

    Google Scholar 

  • 23.

    Koch-Henriksen, N. & Sorensen, P. S. The changing demographic pattern of multiple sclerosis epidemiology. Lancet Neurol. 9, 520–532 (2010).

    Google Scholar 

  • 24.

    Bermel, R. A., Rae-Grant, A. D. & Fox, R. J. Diagnosing multiple sclerosis at a later age: more than just progressive myelopathy. Mult. Scler. 16, 1335–1340 (2010).

    PubMed 

    Google Scholar 

  • 25.

    Poser, C. M. & Brinar, V. V. Diagnostic criteria for multiple sclerosis: an historical review. Clin. Neurol. Neurosurg. 106, 147–158 (2004).

    PubMed 
    PubMed Central 

    Google Scholar 

  • 26.

    Gafson, A., Giovannoni, G. & Hawkes, C. H. The diagnostic criteria for multiple sclerosis: from Charcot to McDonald. Mult. Scler. Relat. Disord. 1, 9–14 (2012).

    PubMed 

    Google Scholar 

  • 27.

    Polliack, M. L., Barak, Y. & Achiron, A. Late-onset multiple sclerosis. J. Am. Geriatr. Soc. 49, 168–171 (2001).

    CAS 
    PubMed 

    Google Scholar 

  • 28.

    Delalande, S., De Seze, J., Ferriby, D., Stojkovic, T. & Vermersch, P. Late onset multiple sclerosis [French]. Rev. Neurol. (Paris) 158, 1082–1087 (2002).

    CAS 

    Google Scholar 

  • 29.

    Tremlett, H. & Devonshire, V. Is late-onset multiple sclerosis associated with a worse outcome? Neurology 67, 954–959 (2006).

    PubMed 

    Google Scholar 

  • 30.

    Hooge, J. P. & Redekop, W. K. Multiple sclerosis with very late onset. Neurology 42, 1907–1910 (1992).

    CAS 
    PubMed 

    Google Scholar 

  • 31.

    Koch-Henriksen, N., Thygesen, L. C., Stenager, E., Laursen, B. & Magyari, M. Incidence of MS has increased markedly over six decades in Denmark particularly with late onset and in women. Neurology 90, e1954–e1963 (2018).

    PubMed 

    Google Scholar 

  • 32.

    Marrie, R. A. et al. A systematic review of the incidence and prevalence of comorbidity in multiple sclerosis: overview. Mult. Scler. 21, 263–281 (2015).

    PubMed 
    PubMed Central 

    Google Scholar 

  • 33.

    Capkun, G. et al. Mortality and comorbidities in patients with multiple sclerosis compared with a population without multiple sclerosis: an observational study using the US Department of Defense administrative claims database. Mult. Scler. Relat. Disord. 4, 546–554 (2015).

    PubMed 

    Google Scholar 

  • 34.

    Marrie, R. A. et al. Comorbidity delays diagnosis and increases disability at diagnosis in MS. Neurology 72, 117–124 (2009).

    CAS 
    PubMed 
    PubMed Central 

    Google Scholar 

  • 35.

    Manouchehrinia, A., Tanasescu, R., Tench, C. R. & Constantinescu, C. S. Mortality in multiple sclerosis: meta-analysis of standardised mortality ratios. J. Neurol. Neurosurg. Psychiatry 87, 324–331 (2016).

    PubMed 

    Google Scholar 

  • 36.

    Scalfari, A. et al. Mortality in patients with multiple sclerosis. Neurology 81, 184–192 (2013).

    PubMed 
    PubMed Central 

    Google Scholar 

  • 37.

    Kaufman, D. W. et al. Survival in commercially insured multiple sclerosis patients and comparator subjects in the U.S. Mult. Scler. Relat. Disord. 3, 364–371 (2014).

    CAS 
    PubMed 

    Google Scholar 

  • 38.

    Bronnum-Hansen, H., Koch-Henriksen, N. & Stenager, E. Trends in survival and cause of death in Danish patients with multiple sclerosis. Brain 127, 844–850 (2004).

    PubMed 

    Google Scholar 

  • 39.

    Ragonese, P., Aridon, P., Salemi, G., D’Amelio, M. & Savettieri, G. Mortality in multiple sclerosis: a review. Eur. J. Neurol. 15, 123–127 (2008).

    CAS 
    PubMed 

    Google Scholar 

  • 40.

    Warren, S. A., Janzen, W., Warren, K. G., Svenson, L. W. & Schopflocher, D. P. Multiple sclerosis mortality rates in Canada, 1975–2009. Can. J. Neurol. Sci. 43, 134–141 (2016).

    PubMed 

    Google Scholar 

  • 41.

    Amezcua, L., Rivas, E., Joseph, S., Zhang, J. & Liu, L. Multiple sclerosis mortality by race/ethnicity, age, sex, and time period in the United States, 1999–2015. Neuroepidemiology 50, 35–40 (2018).

    PubMed 

    Google Scholar 

  • 42.

    Hemmer, B., Kerschensteiner, M. & Korn, T. Role of the innate and adaptive immune responses in the course of multiple sclerosis. Lancet Neurol. 14, 406–419 (2015).

    CAS 

    Google Scholar 

  • 43.

    Weissert, R. The immune pathogenesis of multiple sclerosis. J. Neuroimmune Pharmacol. 8, 857–866 (2013).

    PubMed 

    Google Scholar 

  • 44.

    Garg, N. & Smith, T. W. An update on immunopathogenesis, diagnosis, and treatment of multiple sclerosis. Brain Behav. 5, e00362 (2015).

    PubMed 
    PubMed Central 

    Google Scholar 

  • 45.

    Fletcher, J. M., Lalor, S. J., Sweeney, C. M., Tubridy, N. & Mills, K. H. G. T cells in multiple sclerosis and experimental autoimmune encephalomyelitis. Clin. Exp. Immunol. 162, 1–11 (2010).

    CAS 
    PubMed 
    PubMed Central 

    Google Scholar 

  • 46.

    ‘t Hart, B. A. et al. A B cell-driven autoimmune pathway leading to pathological hallmarks of progressive multiple sclerosis in the marmoset experimental autoimmune encephalomyelitis model. Front. Immunol. 8, 804 (2017).

    PubMed 
    PubMed Central 

    Google Scholar 

  • 47.

    Reich, D. S., Lucchinetti, C. F. & Calabresi, P. A. Multiple sclerosis. N. Engl. J. Med. 378, 169–180 (2018).

    CAS 

    Google Scholar 

  • 48.

    Gandhi, R., Laroni, A. & Weiner, H. L. Role of the innate immune system in the pathogenesis of multiple sclerosis. J. Neuroimmunol. 221, 7–14 (2010).

    CAS 
    PubMed 
    PubMed Central 

    Google Scholar 

  • 49.

    Kasper, L. H. & Shoemaker, J. Multiple sclerosis immunology: the healthy immune system versus the MS immune system. Neurology 74 (Suppl. 1), S2–S8 (2010).

    CAS 
    PubMed 

    Google Scholar 

  • 50.

    Frischer, J. M. et al. The relation between inflammation and neurodegeneration in multiple sclerosis brains. Brain 132, 1175–1189 (2009).

    PubMed 
    PubMed Central 

    Google Scholar 

  • 51.

    Frischer, J. M. et al. Clinical and pathological insights into the dynamic nature of the white matter multiple sclerosis plaque. Ann. Neurol. 78, 710–721 (2015).

    PubMed 
    PubMed Central 

    Google Scholar 

  • 52.

    Lassmann, H., van Horssen, J. & Mahad, D. Progressive multiple sclerosis: pathology and pathogenesis. Nat. Rev. Neurol. 8, 647–656 (2012).

    CAS 
    PubMed 

    Google Scholar 

  • 53.

    Stephenson, E., Nathoo, N., Mahjoub, Y., Dunn, J. F. & Yong, V. W. Iron in multiple sclerosis: roles in neurodegeneration and repair. Nat. Rev. Neurol. 10, 459–468 (2014).

    CAS 
    PubMed 

    Google Scholar 

  • 54.

    Grebenciucova, E. & Berger, J. R. Immunosenescence: the role of aging in the predisposition to neuro-infectious complications arising from the treatment of multiple sclerosis. Curr. Neurol. Neurosci. Rep. 17, 61 (2017).

    PubMed 

    Google Scholar 

  • 55.

    Lassmann, H. Pathology and disease mechanisms in different stages of multiple sclerosis. J. Neurol. Sci. 333, 1–4 (2013).

    CAS 
    PubMed 

    Google Scholar 

  • 56.

    Sanai, S. A. et al. Aging and multiple sclerosis. Mult. Scler. 22, 717–725 (2016).

    PubMed 

    Google Scholar 

  • 57.

    Plaza-Zabala, A., Sierra-Torre, V. & Sierra, A. Autophagy and microglia: novel partners in neurodegeneration and aging. Int. J. Mol. Sci. 18, E598 (2017).

    PubMed 

    Google Scholar 

  • 58.

    Aguilera, M. O., Delgui, L. R., Romano, P. S. & Colombo, M. I. Chronic infections: a possible scenario for autophagy and senescence cross-talk. Cells 7, E162 (2018).

    PubMed 

    Google Scholar 

  • 59.

    Alirezaei, M. et al. Elevated ATG5 expression in autoimmune demyelination and multiple sclerosis. Autophagy 5, 152–158 (2009).

    CAS 
    PubMed 
    PubMed Central 

    Google Scholar 

  • 60.

    Peterson, J. W. & Trapp, B. D. Neuropathobiology of multiple sclerosis. Neurol. Clin. 23, 107–129 (2005).

    PubMed 

    Google Scholar 

  • 61.

    Dutta, R. & Trapp, B. D. Relapsing and progressive forms of multiple sclerosis: insights from pathology. Curr. Opin. Neurol. 27, 271–278 (2014).

    PubMed 
    PubMed Central 

    Google Scholar 

  • 62.

    Cevenini, E., Monti, D. & Franceschi, C. Inflamm-ageing. Curr. Opin. Clin. Nutr. Metab. Care 16, 14–20 (2013).

    CAS 
    PubMed 

    Google Scholar 

  • 63.

    Franceschi, C. et al. Inflamm-aging. An evolutionary perspective on immunosenescence. Ann. NY Acad. Sci. 908, 244–254 (2000).

    CAS 
    PubMed 

    Google Scholar 

  • 64.

    Thewissen, M. et al. Analyses of immunosenescent markers in patients with autoimmune disease. Clin. Immunol. 123, 209–218 (2007).

    CAS 
    PubMed 

    Google Scholar 

  • 65.

    Childs, B. G. et al. Senescent cells: an emerging target for diseases of ageing. Nat. Rev. Drug Discov. 16, 718–735 (2017).

    CAS 
    PubMed 
    PubMed Central 

    Google Scholar 

  • 66.

    Aw, D. & Palmer, D. B. The origin and implication of thymic involution. Aging Dis. 2, 437–443 (2011).

    PubMed 
    PubMed Central 

    Google Scholar 

  • 67.

    Haegert, D. G. Multiple sclerosis: a disorder of altered T cell homeostasis. Mult. Scler. Int. 2011, 461304 (2011).

    PubMed 
    PubMed Central 

    Google Scholar 

  • 68.

    Musella, A. et al. Interplay between age and neuroinflammation in multiple sclerosis: effects on motor and cognitive functions. Front. Aging Neurosci. 10, 238 (2018).

    PubMed 
    PubMed Central 

    Google Scholar 

  • 69.

    Budni, J., Bellettini-Santos, T., Mina, F., Garcez, M. L. & Zugno, A. I. The involvement of BDNF, NGF and GDNF in aging and Alzheimer’s disease. Aging Dis. 6, 331–341 (2015).

    PubMed 
    PubMed Central 

    Google Scholar 

  • 70.

    Rist, J. M. & Franklin, R. J. Taking ageing into account in remyelination-based therapies for multiple sclerosis. J. Neurol. Sci. 274, 64–67 (2008).

    CAS 
    PubMed 

    Google Scholar 

  • 71.

    Luchetti, S. et al. Progressive multiple sclerosis patients show substantial lesion activity that correlates with clinical disease severity and sex: a retrospective autopsy cohort analysis. Acta Neuropathol. 135, 511–528 (2018).

    CAS 
    PubMed 
    PubMed Central 

    Google Scholar 

  • 72.

    Correale, J., Gaitan, M. I., Ysrraelit, M. C. & Fiol, M. P. Progressive multiple sclerosis: from pathogenic mechanisms to treatment. Brain 140, 527–546 (2017).

    PubMed 

    Google Scholar 

  • 73.

    Buck, D. & Hemmer, B. Treatment of multiple sclerosis: current concepts and future perspectives. J. Neurol. 258, 1747–1762 (2011).

    CAS 
    PubMed 

    Google Scholar 

  • 74.

    Thompson, A. J. et al. Diagnosis of multiple sclerosis: 2017 revisions of the McDonald criteria. Lancet Neurol. 17, 162–173 (2018).

    PubMed 

    Google Scholar 

  • 75.

    Hammond, K. E. et al. Quantitative in vivo magnetic resonance imaging of multiple sclerosis at 7 Tesla with sensitivity to iron. Ann. Neurol 64, 707–713 (2008).

    PubMed 

    Google Scholar 

  • 76.

    Bagnato, F. et al. Tracking iron in multiple sclerosis: a combined imaging and histopathological study at 7 Tesla. Brain 134, 3602–3615 (2011).

    PubMed 

    Google Scholar 

  • 77.

    Absinta, M. et al. Identification of chronic active multiple sclerosis lesions on 3 T MRI. AJNR Am. J. Neuroradiol. 39, 1233–1238 (2018).

    CAS 
    PubMed 
    PubMed Central 

    Google Scholar 

  • 78.

    Vellinga, M. M. et al. Pluriformity of inflammation in multiple sclerosis shown by ultra-small iron oxide particle enhancement. Brain 131, 800–807 (2008).

    PubMed 

    Google Scholar 

  • 79.

    Dwyer, M. G. et al. Atrophied brain lesion volume: a new imaging biomarker in multiple sclerosis. J. Neuroimaging 28, 490–495 (2018).

    PubMed 

    Google Scholar 

  • 80.

    Calabrese, M. et al. Cortical lesion load associates with progression of disability in multiple sclerosis. Brain 135, 2952–2961 (2012).

    PubMed 
    PubMed Central 

    Google Scholar 

  • 81.

    Calabrese, M. et al. Exploring the origins of grey matter damage in multiple sclerosis. Nat. Rev. Neurosci. 16, 147–158 (2015).

    CAS 
    PubMed 

    Google Scholar 

  • 82.

    Filippi, M. et al. Imaging cortical damage and dysfunction in multiple sclerosis. JAMA Neurol. 70, 556–564 (2013).

    PubMed 

    Google Scholar 

  • 83.

    Absinta, M., Sati, P. & Reich, D. S. Advanced MRI and staging of multiple sclerosis lesions. Nat. Rev. Neurol. 12, 358–368 (2016).

    CAS 
    PubMed 
    PubMed Central 

    Google Scholar 

  • 84.

    Zurawski, J., Lassmann, H. & Bakshi, R. Use of magnetic resonance imaging to visualize leptomeningeal inflammation in patients with multiple sclerosis: a review. JAMA Neurol. 74, 100–109 (2016).

    Google Scholar 

  • 85.

    Zivadinov, R. et al. Leptomeningeal contrast enhancement is associated with progression of cortical atrophy in MS: a retrospective, pilot, observational longitudinal study. Mult. Scler. 23, 1336–1345 (2016).

    PubMed 

    Google Scholar 

  • 86.

    Harrison, D. M. et al. Leptomeningeal enhancement at 7 T in multiple sclerosis: frequency, morphology, and relationship to cortical volume. J. Neuroimaging 27, 461–468 (2017).

    PubMed 
    PubMed Central 

    Google Scholar 

  • 87.

    Miller, D. H., Barkhof, F., Frank, J. A., Parker, G. J. & Thompson, A. J. Measurement of atrophy in multiple sclerosis: pathological basis, methodological aspects and clinical relevance. Brain 125, 1676–1695 (2002).

    PubMed 

    Google Scholar 

  • 88.

    Zivadinov, R. et al. Clinical relevance of brain atrophy assessment in multiple sclerosis. Implications for its use in a clinical routine. Expert Rev. Neurother. 16, 777–793 (2016).

    CAS 
    PubMed 

    Google Scholar 

  • 89.

    De Stefano, N. et al. Establishing pathological cut-offs of brain atrophy rates in multiple sclerosis. J. Neurol. Neurosurg. Psychiatry 87, 93–99 (2016).

    PubMed 

    Google Scholar 

  • 90.

    Hedman, A. M., van Haren, N. E., Schnack, H. G., Kahn, R. S. & Hulshoff Pol, H. E. Human brain changes across the life span: a review of 56 longitudinal magnetic resonance imaging studies. Hum. Brain Mapp. 33, 1987–2002 (2012).

    PubMed 

    Google Scholar 

  • 91.

    Fisher, E., Lee, J. C., Nakamura, K. & Rudick, R. A. Gray matter atrophy in multiple sclerosis: a longitudinal study. Ann. Neurol. 64, 255–265 (2008).

    PubMed 

    Google Scholar 

  • 92.

    Fisniku, L. K. et al. Gray matter atrophy is related to long-term disability in multiple sclerosis. Ann. Neurol. 64, 247–254 (2008).

    PubMed 

    Google Scholar 

  • 93.

    Steenwijk, M. D. et al. Cortical atrophy patterns in multiple sclerosis are non-random and clinically relevant. Brain 139, 115–126 (2016).

    PubMed 

    Google Scholar 

  • 94.

    Eshaghi, A. et al. Progression of regional grey matter atrophy in multiple sclerosis. Brain 141, 1665–1677 (2018).

    PubMed 
    PubMed Central 

    Google Scholar 

  • 95.

    Stankoff, B. & Louapre, C. Can we use regional grey matter atrophy sequence to stage neurodegeneration in multiple sclerosis? Brain 141, 1580–1583 (2018).

    PubMed 

    Google Scholar 

  • 96.

    Cristofanilli, M. et al. Progressive multiple sclerosis cerebrospinal fluid induces inflammatory demyelination, axonal loss, and astrogliosis in mice. Exp. Neurol. 261, 620–632 (2014).

    CAS 
    PubMed 

    Google Scholar 

  • 97.

    Vidaurre, O. G. et al. Cerebrospinal fluid ceramides from patients with multiple sclerosis impair neuronal bioenergetics. Brain 137, 2271–2286 (2014).

    PubMed 
    PubMed Central 

    Google Scholar 

  • 98.

    Haider, L. et al. The topograpy of demyelination and neurodegeneration in the multiple sclerosis brain. Brain 139, 807–815 (2016).

    PubMed 
    PubMed Central 

    Google Scholar 

  • 99.

    Eshaghi, A. et al. Deep grey matter volume loss drives disability worsening in multiple sclerosis. Ann. Neurol. 83, 210–222 (2018).

    CAS 
    PubMed 
    PubMed Central 

    Google Scholar 

  • 100.

    Azevedo, C. J. et al. Thalamic atrophy in MS: an MRI marker of neurodegeneration throughout disease. Ann. Neurol. 83, 223–234 (2018).

    PubMed 
    PubMed Central 

    Google Scholar 

  • 101.

    Cocozza, S. et al. Cerebellar lobule atrophy and disability in progressive MS. J. Neurol. Neurosurg. Psychiatry 88, 1065–1072 (2017).

    PubMed 

    Google Scholar 

  • 102.

    Moroso, A. et al. Posterior lobules of the cerebellum and information processing speed at various stages of multiple sclerosis. J. Neurol. Neurosurg. Psychiatry 88, 146–151 (2016).

    PubMed 

    Google Scholar 

  • 103.

    Kearney, H., Miller, D. H. & Ciccarelli, O. Spinal cord MRI in multiple sclerosis — diagnostic, prognostic and clinical value. Nat. Rev. Neurol. 11, 327–338 (2015).

    PubMed 

    Google Scholar 

  • 104.

    Abdel-Aziz, K. et al. Evidence for early neurodegeneration in the cervical cord of patients with primary progressive multiple sclerosis. Brain 138, 1568–1582 (2015).

    PubMed 
    PubMed Central 

    Google Scholar 

  • 105.

    Tsagkas, C. et al. Preferential spinal cord volume loss in primary progressive multiple sclerosis. Mult. Scler. https://doi.org/10.1177/1352458518775006 (2018).

    Article 
    PubMed 

    Google Scholar 

  • 106.

    Schlaeger, R. et al. Association between thoracic spinal cord gray matter atrophy and disability in multiple sclerosis. JAMA Neurol. 72, 897–904 (2015).

    PubMed 
    PubMed Central 

    Google Scholar 

  • 107.

    Tsagkas, C. et al. Spinal cord volume loss: a marker of disease progression in multiple sclerosis. Neurology 91, e349–e358 (2018).

    PubMed 

    Google Scholar 

  • 108.

    Zeydan, B. et al. Cervical spinal cord atrophy: an early marker of progressive MS onset. Neurol. Neuroimmunol. Neuroinflamm. 5, e435 (2018).

    PubMed 
    PubMed Central 

    Google Scholar 

  • 109.

    Murtonen, A., Kurki, S., Hanninen, K., Soilu-Hanninen, M. & Sumelahti, M. L. Common comorbidities and survival in MS: risk for stroke, type 1 diabetes and infections. Mult. Scler. Relat. Disord. 19, 109–114 (2018).

    CAS 
    PubMed 

    Google Scholar 

  • 110.

    Tettey, P., Simpson, S. Jr., Taylor, B. V. & van der Mei, I. A. Vascular comorbidities in the onset and progression of multiple sclerosis. J. Neurol. Sci. 347, 23–33 (2014).

    PubMed 

    Google Scholar 

  • 111.

    Hussein, W. I. & Reddy, S. S. Prevalence of diabetes in patients with multiple sclerosis. Diabetes Care 29, 1984–1985 (2006).

    PubMed 

    Google Scholar 

  • 112.

    Kang, J. H., Chen, Y. H. & Lin, H. C. Comorbidities amongst patients with multiple sclerosis: a population-based controlled study. Eur. J. Neurol. 17, 1215–1219 (2010).

    PubMed 

    Google Scholar 

  • 113.

    Marrie, R. A. et al. Vascular comorbidity is associated with more rapid disability progression in multiple sclerosis. Neurology 74, 1041–1047 (2010).

    CAS 
    PubMed 
    PubMed Central 

    Google Scholar 

  • 114.

    Christiansen, C. F. et al. Risk of arterial cardiovascular diseases in patients with multiple sclerosis: a population-based cohort study. Neuroepidemiology 35, 267–274 (2010).

    PubMed 

    Google Scholar 

  • 115.

    Jadidi, E., Mohammadi, M. & Moradi, T. High risk of cardiovascular diseases after diagnosis of multiple sclerosis. Mult. Scler. 19, 1336–1340 (2013).

    PubMed 

    Google Scholar 

  • 116.

    Marrie, R. A. et al. Rising prevalence of vascular comorbidities in multiple sclerosis: validation of administrative definitions for diabetes, hypertension, and hyperlipidemia. Mult. Scler. 18, 1310–1319 (2012).

    PubMed 

    Google Scholar 

  • 117.

    Geraldes, R. et al. The current role of MRI in differentiating multiple sclerosis from its imaging mimics. Nat. Rev. Neurol. 14, 199–213 (2018).

    PubMed 

    Google Scholar 

  • 118.

    Zivadinov, R. et al. Cerebral microbleeds in multiple sclerosis evaluated on susceptibility-weighted images and quantitative susceptibility maps: a case-control study. Radiology 281, 884–895 (2016).

    PubMed 
    PubMed Central 

    Google Scholar 

  • 119.

    Ter Telgte, A. et al. Cerebral small vessel disease: from a focal to a global perspective. Nat. Rev. Neurol. 14, 387–398 (2018).

    PubMed 

    Google Scholar 

  • 120.

    Sati, P. et al. The central vein sign and its clinical evaluation for the diagnosis of multiple sclerosis: a consensus statement from the North American Imaging in Multiple Sclerosis Cooperative. Nat. Rev. Neurol. 12, 714–722 (2016).

    PubMed 
    PubMed Central 

    Google Scholar 

  • 121.

    Moon, S. Y. et al. Prospective associations between white matter hyperintensities and lower extremity function. Neurology 90, e1291–e1297 (2018).

    PubMed 

    Google Scholar 

  • 122.

    Srinivasa, R. N. et al. Cardiovascular risk factors associated with smaller brain volumes in regions identified as early predictors of cognitive decline. Radiology 278, 198–204 (2016).

    PubMed 

    Google Scholar 

  • 123.

    Kappus, N. et al. Cardiovascular risk factors are associated with increased lesion burden and brain atrophy in multiple sclerosis. J. Neurol. Neurosurg. Psychiatry 87, 181–187 (2016).

    PubMed 

    Google Scholar 

  • 124.

    Jakimovski, D. et al. Hypertension and heart disease are associated with development of brain atrophy in multiple sclerosis: a 5-year longitudinal study. Eur. J. Neurol. 26, 87 (2019).

    CAS 
    PubMed 

    Google Scholar 

  • 125.

    Kneebone, I. I., Dunmore, E. C. & Evans, E. Symptoms of depression in older adults with multiple sclerosis (MS): comparison with a matched sample of younger adults. Aging Ment. Health 7, 182–185 (2003).

    CAS 
    PubMed 

    Google Scholar 

  • 126.

    Chwastiak, L. et al. Depressive symptoms and severity of illness in multiple sclerosis: epidemiologic study of a large community sample. Am. J. Psychiatry 159, 1862–1868 (2002).

    PubMed 

    Google Scholar 

  • 127.

    Patten, S. B., Metz, L. M. & Reimer, M. A. Biopsychosocial correlates of lifetime major depression in a multiple sclerosis population. Mult. Scler. 6, 115–120 (2000).

    CAS 
    PubMed 

    Google Scholar 

  • 128.

    Beal, C. C., Stuifbergen, A. K. & Brown, A. Depression in multiple sclerosis: a longitudinal analysis. Arch. Psychiatr. Nurs. 21, 181–191 (2007).

    PubMed 
    PubMed Central 

    Google Scholar 

  • 129.

    Roy, S. et al. Preliminary investigation of cognitive function in aged multiple sclerosis patients: challenges in detecting comorbid Alzheimer’s disease. Mult. Scler. Relat. Disord. 22, 52–56 (2018).

    PubMed 

    Google Scholar 

  • 130.

    U.S. Food and Drug Administration. FDA News Release: FDA approves new oral treatment for multiple sclerosis. FDA https://www.fda.gov/NewsEvents/Newsroom/PressAnnouncements/ucm634837.htm (2019).

  • 131.

    U.S. Food and Drug Administration. FDA News Release: FDA approves new oral drug to treat multiple sclerosis. FDA https://www.fda.gov/NewsEvents/Newsroom/PressAnnouncements/ucm634469.htm (2019).

  • 132.

    National Multiple Sclerosis Society. Disease-modifying therapies for MS. NationalMSSociety https://www.nationalmssociety.org/NationalMSSociety/media/MSNationalFiles/Brochures/Brochure-MS-Disease-Modifying-Medications.pdf (2018).

  • 133.

    Johnson, K. P. et al. Copolymer 1 reduces relapse rate and improves disability in relapsing-remitting multiple sclerosis: results of a phase III multicenter, double-blind placebo-controlled trial. The Copolymer 1 Multiple Sclerosis Study Group. Neurology 45, 1268–1276 (1995).

    CAS 
    PubMed 

    Google Scholar 

  • 134.

    IFNβ Multiple Sclerosis Study Group. Interferon beta-lb is effective in relapsing-remitting multiple sclerosis. I. Clinical results of a multicenter, randomized, double-blind, placebo-controlled trial. 1993 [classical article]. Neurology 57 (Suppl. 5), S3–S9 (2001).

    Google Scholar 

  • 135.

    Polman, C. H. et al. A randomized, placebo-controlled trial of natalizumab for relapsing multiple sclerosis. N. Engl. J. Med. 354, 899–910 (2006).

    CAS 
    PubMed 

    Google Scholar 

  • 136.

    CAMMS223 Trial Investigators et al. Alemtuzumab versus interferon beta-1a in early multiple sclerosis. N. Engl. J. Med. 359, 1786–1801 (2008).

    Google Scholar 

  • 137.

    Cohen, J. A. et al. Alemtuzumab versus interferon beta 1a as first-line treatment for patients with relapsing-remitting multiple sclerosis: a randomised controlled phase 3 trial. Lancet 380, 1819–1828 (2012).

    CAS 
    PubMed 

    Google Scholar 

  • 138.

    Jacobs, L. D. et al. Intramuscular interferon beta-1a for disease progression in relapsing multiple sclerosis. The Multiple Sclerosis Collaborative Research Group (MSCRG). Ann. Neurol. 39, 285–294 (1996).

    CAS 
    PubMed 

    Google Scholar 

  • 139.

    PRISMS (Prevention of Relapses and Disability by Interferon β-1a Subcutaneously in Multiple Sclerosis) Study Group. Randomised double-blind placebo-controlled study of interferon β-1a in relapsing/remitting multiple sclerosis. Lancet 352, 1498–1504 (1998).

    Google Scholar 

  • 140.

    Gold, R. et al. Placebo-controlled phase 3 study of oral BG-12 for relapsing multiple sclerosis. N. Engl. J. Med. 367, 1098–1107 (2012).

    CAS 
    PubMed 

    Google Scholar 

  • 141.

    Fox, R. J. et al. Placebo-controlled phase 3 study of oral BG-12 or glatiramer in multiple sclerosis. N. Engl. J. Med. 367, 1087–1097 (2012).

    CAS 
    PubMed 

    Google Scholar 

  • 142.

    Kappos, L. et al. A placebo-controlled trial of oral fingolimod in relapsing multiple sclerosis. N. Engl. J. Med. 362, 387–401 (2010).

    CAS 
    PubMed 

    Google Scholar 

  • 143.

    Cohen, J. A. et al. Oral fingolimod or intramuscular interferon for relapsing multiple sclerosis. N. Engl. J. Med. 362, 402–415 (2010).

    CAS 
    PubMed 

    Google Scholar 

  • 144.

    O’Connor, P. et al. Randomized trial of oral teriflunomide for relapsing multiple sclerosis. N. Engl. J. Med. 365, 1293–1303 (2011).

    PubMed 

    Google Scholar 

  • 145.

    Miller, A. E. et al. Oral teriflunomide for patients with a first clinical episode suggestive of multiple sclerosis (TOPIC): a randomised, double-blind, placebo-controlled, phase 3 trial. Lancet Neurol. 13, 977–986 (2014).

    CAS 
    PubMed 

    Google Scholar 

  • 146.

    US National Library of Medicine. ClinicalTrials.gov https://clinicaltrials.gov/ct2/show/NCT03523858 (2019).

  • 147.

    Kappos, L. et al. Siponimod versus placebo in secondary progressive multiple sclerosis (EXPAND): a double-blind, randomised, phase 3 study. Lancet 391, 1263–1273 (2018).

    CAS 
    PubMed 

    Google Scholar 

  • 148.

    Zhang, T. et al. Examining the effects of comorbidities on disease-modifying therapy use in multiple sclerosis. Neurology 86, 1287–1295 (2016).

    PubMed 
    PubMed Central 

    Google Scholar 

  • 149.

    Devonshire, V. et al. Relapse and disability outcomes in patients with multiple sclerosis treated with fingolimod: subgroup analyses of the double-blind, randomised, placebo-controlled FREEDOMS study. Lancet Neurol. 11, 420–428 (2012).

    CAS 
    PubMed 
    PubMed Central 

    Google Scholar 

  • 150.

    Motl, R. W. et al. Validity of the timed 25-foot walk as an ambulatory performance outcome measure for multiple sclerosis. Mult. Scler. 23, 704–710 (2017).

    PubMed 
    PubMed Central 

    Google Scholar 

  • 151.

    Hervault, M., Balto, J. M., Hubbard, E. A. & Motl, R. W. Reliability, precision, and clinically important change of the Nine-Hole Peg Test in individuals with multiple sclerosis. Int. J. Rehabil. Res. 40, 91–93 (2017).

    PubMed 

    Google Scholar 

  • 152.

    Kapoor, R. et al. Effect of natalizumab on disease progression in secondary progressive multiple sclerosis (ASCEND): a phase 3, randomised, double-blind, placebo-controlled trial with an open-label extension. Lancet Neurol. 17, 405–415 (2018).

    CAS 
    PubMed 

    Google Scholar 

  • 153.

    Shirani, A. et al. Multiple sclerosis in older adults: the clinical profile and impact of interferon beta treatment. Biomed. Res. Int. 2015, 451912 (2015).

    PubMed 
    PubMed Central 

    Google Scholar 

  • 154.

    Giovannoni, G. et al. Is multiple sclerosis a length-dependent central axonopathy? The case for therapeutic lag and the asynchronous progressive MS hypotheses. Mult. Scler. Relat. Disord. 12, 70–78 (2017).

    PubMed 

    Google Scholar 

  • 155.

    Montalban, X. et al. Ocrelizumab versus placebo in primary progressive multiple sclerosis. N. Engl. J. Med. 376, 209–220 (2017).

    CAS 
    PubMed 

    Google Scholar 

  • 156.

    Paz Soldan, M. M. et al. Relapses and disability accumulation in progressive multiple sclerosis. Neurology 84, 81–88 (2015).

    PubMed 
    PubMed Central 

    Google Scholar 

  • 157.

    Wolinsky, J. S. et al. Evaluation of no evidence of progression or active disease (NEPAD) in patients with primary progressive multiple sclerosis in the ORATORIO trial. Ann. Neurol. 84, 527–536 (2018).

    CAS 
    PubMed 
    PubMed Central 

    Google Scholar 

  • 158.

    Fox, E. J. et al. Ocrelizumab reduces progression of upper extremity impairment in patients with primary progressive multiple sclerosis: findings from the phase III randomized ORATORIO trial. Mult. Scler. 24, 1862–1870 (2018).

    CAS 
    PubMed 
    PubMed Central 

    Google Scholar 

  • 159.

    Manouchehrinia, A. et al. Age related multiple sclerosis severity score: disability ranked by age. Mult. Scler. 23, 1938–1946 (2017).

    PubMed 
    PubMed Central 

    Google Scholar 

  • 160.

    Kister, I. Disease-modifying therapies can be safely discontinued in an individual with stable relapsing-remitting MS — YES. Mult. Scler. 23, 1188–1190 (2017).

    PubMed 

    Google Scholar 

  • 161.

    Tobin, W. O. & Weinshenker, B. G. Disease-modifying therapies can be safely discontinued in an individual with stable relapsing-remitting MS — NO. Mult. Scler. 23, 1190–1192 (2017).

    PubMed 

    Google Scholar 

  • 162.

    Tremlett, H., Zhao, Y., Joseph, J. & Devonshire, V. Relapses in multiple sclerosis are age- and time-dependent. J. Neurol. Neurosurg. Psychiatry 79, 1368–1374 (2008).

    CAS 
    PubMed 

    Google Scholar 

  • 163.

    Hua, L. H., Fan, T. H., Conway, D., Thompson, N. & Kinzy, T. G. Discontinuation of disease-modifying therapy in patients with multiple sclerosis over age 60. Mult. Scler. https://doi.org/10.1177/1352458518765656 (2018).

    Article 
    PubMed 

    Google Scholar 

  • 164.

    Kister, I. et al. Discontinuing disease-modifying therapy in MS after a prolonged relapse-free period: a propensity score-matched study. J. Neurol. Neurosurg. Psychiatry 87, 1133–1137 (2016).

    PubMed 

    Google Scholar 

  • 165.

    Weideman, A. M., Tapia-Maltos, M. A., Johnson, K., Greenwood, M. & Bielekova, B. Meta-analysis of the age-dependent efficacy of multiple sclerosis treatments. Front. Neurol. 8, 577 (2017).

    PubMed 
    PubMed Central 

    Google Scholar 

  • 166.

    Sormani, M. P. et al. Autologous hematopoietic stem cell transplantation in multiple sclerosis: a meta-analysis. Neurology 88, 2115–2122 (2017).

    PubMed 

    Google Scholar 

  • 167.

    Muraro, P. A. et al. Autologous haematopoietic stem cell transplantation for treatment of multiple sclerosis. Nat. Rev. Neurol. 13, 391–405 (2017).

    CAS 
    PubMed 

    Google Scholar 

  • 168.

    Muraro, P. A. et al. Long-term outcomes after autologous hematopoietic stem cell transplantation for multiple sclerosis. JAMA Neurol. 74, 459–469 (2017).

    PubMed 
    PubMed Central 

    Google Scholar 

  • 169.

    US National Library of Medicine. ClinicalTrials.gov https://clinicaltrials.gov/ct2/show/NCT03073603 (2019).

  • 170.

    Moss, B. P., Rensel, M. R. & Hersh, C. M. Wellness and the role of comorbidities in multiple sclerosis. Neurotherapeutics 14, 999–1017 (2017).

    CAS 
    PubMed 
    PubMed Central 

    Google Scholar 

  • 171.

    Ramanujam, R. et al. Effect of smoking cessation on multiple sclerosis prognosis. JAMA Neurol. 72, 1117–1123 (2015).

    PubMed 

    Google Scholar 

  • 172.

    D’Hooghe, M. B., Haentjens, P., Nagels, G. & De Keyser, J. Alcohol, coffee, fish, smoking and disease progression in multiple sclerosis. Eur. J. Neurol. 19, 616–624 (2012).

    PubMed 

    Google Scholar 

  • 173.

    Manouchehrinia, A. et al. Tobacco smoking and disability progression in multiple sclerosis: United Kingdom cohort study. Brain 136, 2298–2304 (2013).

    PubMed 
    PubMed Central 

    Google Scholar 

  • 174.

    Sandroff, B. M., Motl, R. W., Scudder, M. R. & DeLuca, J. Systematic, evidence-based review of exercise, physical activity, and physical fitness effects on cognition in persons with multiple sclerosis. Neuropsychol. Rev. 26, 271–294 (2016).

    PubMed 

    Google Scholar 

  • 175.

    Sandroff, B. M., Johnson, C. L. & Motl, R. W. Exercise training effects on memory and hippocampal viscoelasticity in multiple sclerosis: a novel application of magnetic resonance elastography. Neuroradiology 59, 61–67 (2017).

    PubMed 

    Google Scholar 

  • 176.

    US National Library of Medicine. ClinicalTrials.gov https://clinicaltrials.gov/ct2/show/NCT02282878 (2017).

  • 177.

    US National Library of Medicine. ClinicalTrials.gov https://clinicaltrials.gov/ct2/show/NCT03718247 (2018).

  • 178.

    US National Library of Medicine. ClinicalTrials.gov https://clinicaltrials.gov/ct2/show/NCT03808545 (2019).

  • 179.

    Ploughman, M. et al. Factors influencing healthy aging with multiple sclerosis: a qualitative study. Disabil. Rehabil. 34, 26–33 (2012).

    PubMed 

    Google Scholar 

  • 180.

    Harrison, T., Blozis, S. & Stuifbergen, A. Longitudinal predictors of attitudes toward aging among women with multiple sclerosis. Psychol. Aging 23, 823–832 (2008).

    PubMed 
    PubMed Central 

    Google Scholar 

  • 181.

    Julian, L. J. Cognitive functioning in multiple sclerosis. Neurol. Clin. 29, 507–525 (2011).

    PubMed 

    Google Scholar 

  • 182.

    Bodling, A. M., Denney, D. R. & Lynch, S. G. Cognitive aging in patients with multiple sclerosis: a cross-sectional analysis of speeded processing. Arch. Clin. Neuropsychol. 24, 761–767 (2009).

    PubMed 

    Google Scholar 

  • 183.

    Roy, S. et al. Differential effects of aging on motor and cognitive functioning in multiple sclerosis. Mult. Scler. 23, 1385–1393 (2017).

    PubMed 

    Google Scholar 

  • 184.

    Sumowski, J. F., Chiaravalloti, N. & DeLuca, J. Cognitive reserve protects against cognitive dysfunction in multiple sclerosis. J. Clin. Exp. Neuropsychol. 31, 913–926 (2009).

    PubMed 

    Google Scholar 

  • 185.

    Benedict, R. H., Morrow, S. A., Weinstock Guttman, B., Cookfair, D. & Schretlen, D. J. Cognitive reserve moderates decline in information processing speed in multiple sclerosis patients. J. Int. Neuropsychol. Soc. 16, 829–835 (2010).

    PubMed 

    Google Scholar 

  • 186.

    Charvet, L. E., Shaw, M. T., Haider, L., Melville, P. & Krupp, L. B. Remotely-delivered cognitive remediation in multiple sclerosis (MS): protocol and results from a pilot study. Mult. Scler. J. Exp. Transl Clin. 1, 2055217315609629 (2015).

    CAS 
    PubMed 
    PubMed Central 

    Google Scholar 

  • 187.

    Perez-Martin, M. Y., Gonzalez-Platas, M., Eguia-Del Rio, P., Croissier-Elias, C. & Jimenez Sosa, A. Efficacy of a short cognitive training program in patients with multiple sclerosis. Neuropsychiatr. Dis. Treat. 13, 245–252 (2017).

    CAS 
    PubMed 
    PubMed Central 

    Google Scholar 

  • 188.

    Grasso, M. G. et al. Evaluation of the impact of cognitive training on quality of life in patients with multiple sclerosis. Eur. Neurol. 78, 111–117 (2017).

    PubMed 

    Google Scholar 

  • 189.

    O’Carroll, C. B. et al. Is donepezil effective for multiple sclerosis-related cognitive dysfunction? A critically appraised topic. Neurologist 18, 51–54 (2012).

    PubMed 

    Google Scholar 

  • 190.

    Villoslada, P., Arrondo, G., Sepulcre, J., Alegre, M. & Artieda, J. Memantine induces reversible neurologic impairment in patients with MS. Neurology 72, 1630–1633 (2009).

    CAS 
    PubMed 

    Google Scholar 

  • 191.

    Peyro Saint Paul, L. et al. Efficacy and safety profile of memantine in patients with cognitive impairment in multiple sclerosis: a randomized, placebo-controlled study. J. Neurol. Sci. 363, 69–76 (2016).

    PubMed 

    Google Scholar 

  • 192.

    Hartung, H. P. et al. Mitoxantrone in progressive multiple sclerosis: a placebo-controlled, double-blind, randomised, multicentre trial. Lancet 360, 2018–2025 (2002).

    PubMed 

    Google Scholar 

  • 193.

    Confavreux, C. et al. Oral teriflunomide for patients with relapsing multiple sclerosis (TOWER): a randomised, double-blind, placebo-controlled, phase 3 trial. Lancet Neurol. 13, 247–256 (2014).

    CAS 
    PubMed 
    PubMed Central 

    Google Scholar 

  • 194.

    Hauser, S. L. et al. Ocrelizumab versus interferon beta-1a in relapsing multiple sclerosis. N. Engl. J. Med. 376, 221–234 (2017).

    CAS 
    PubMed 

    Google Scholar 

  • Survival and cause of death in multiple sclerosis: a 60-year longitudinal population study

    Introduction

    Longitudinal studies have revealed a promising change in longevity prognosis in multiple sclerosis (MS) with increased life expectancies in MS over the last decades.1–4 Similar survival trends have been seen also in the general population, questioning whether the gap in survival incidence between MS and the general population has changed over time.5 Patients with MS, on average, have shortened life expectancies by 7–14 years.4–7 Gender inequality for standardised mortality ratio (SMR) in disfavour of females has been reported despite a slower disability progression rate reported among women with MS and a longer life expectancy.8 9 In terms of disease course and mortality, a higher mortality rate among patients with primary progressive MS (PPMS) has been shown with respect to patients with relapsing-remitting MS (RRMS).2 4 MS, as noted on the death certificates has been reported as the the most common cause of death (COD) in patients with MS, and this trend has remained stable over time.2 7 10

    COD analyses are important to quantify the nature and magnitude of underlying diseases, and, where possible, to compare COD in MS with COD in matched reference subjects. Here, we present results based on an observation time of ­60 years on MS survival and cause-specific mortality, the longest follow-up study reported to date. This population-based study included all patients with incident MS in Hordaland County, Western Norway. Our main objective was to determine life expectancy in MS and to identify a potential change in survival between patients with MS and the general population during the observation period. Second, we aimed to compare mortality rates of cause-specific deaths in MS to the matched general population.

    Methods

    Settings and study design

    All patients with onset of MS during 1953–2012 in Hordaland County were included in the study. Patient’s identification was obtained from patient records at the Departments of Neurology at Haukeland University Hospital and Haugesund Hospital, the only departments of neurology in Hordaland county, Western Norway. Additional records for patients with optic neuritis at the department of Ophthalmology, Haukeland University Hospital, were evaluated. For several decades, repeated surveys of MS epidemiology have been performed in these departments to maintain a continuous oversight and update of MS incidence and prevalence data.11 Patients were diagnosed as having definite or probable MS according to the criteria of Poser until 1 January 2001 and according to McDonald diagnostic criteria from 2001 and revised McDonald criteria (2010).12–14 Year of birth, age and age at onset (first clinical symptom) and at diagnosis, gender, disease course at onset (RRMS and PPMS), time period (year) for onset and diagnosis and COD were registered. Patient records were linked to the COD Registry at Statistics Norway for obtaining date and COD, classified according to the International Classification of Diseases (ICD-6, ICD-10). We used all entries recorded on the death certificates to ensure inclusion of all COD. However, only the primary COD was used in the sensitivity analysis, as all other causes were insufficiently recorded. The follow-up period ended 31 December 2012.

    Expected life expectancy for the general Norwegian population according to age, gender and calendar year was based on yearly population mortality tables obtained from The Human Mortality Data Base (http://www.mortality.org/Public/CitationGuidelines.php).

    The study was approved by the Regional Committee for Medical Research Ethics in Western Norway.

    Statistical analysis

    Descriptive methods were used to characterise the sample (demographic and clinic properties) The Fisher’s exact test was used to compare six categorical COD: MS, cardiovascular and cerebrovascular diseases, cancer, respiratory and infectious diseases, accidents and suicide and others according to gender and disease courses RRMS and PPMS.15 Survival curves for the observed MS population and in MS subgroups (gender, disease course) were assessed by Kaplan-Meier (log-rank) both from birth and from disease onset and compared with the (expected) mortality in the general Norwegian population.

    The mortality rates for MS, MS subgroups (gender, initial disease course), age at onset and diagnosis, time period for onset and diagnosis and COD were compared with the general Norwegian population and assessed by SMRs.16 The SMR is the ratio of the observed patient mortality to the mortality for the general Norwegian population (expected) corresponding to age, gender and calendar year.16

    All computation has been done in R.17

    Discussion

    In this 60-year incidence-based population cohort from Western Norway, we demonstrated a median reduction in life expectancy of 7.1 years and overall an almost threefold increase in mortality rate in MS compared with the matched general population.

    Our findings correspond to previous reports of MS mortality, and recent reports of 6–6.5 years survival reduction in similar studies in Canada and Spain.2 4 18 The median survival from disease onset was 41 years in MS, this is more than twice as long as reported in the first study on the topic in 1969 (17 years), reflecting a time trend towards a strong increase in life expectancy.4 19 Similar to others, we also found that patients with younger age at onset had a higher relative risk of dying (higher SMR) than patients with an older age at onset.2 4 Women with MS had 5-year longer life expectancy (77.2 years) than men with MS (72.2 years) irrespective of measured from birth or from disease onset. The same 5-year gender age difference in life expectancy was found in the general population, indicating that the longer survival age found in women with MS reflects the longer survival age found in women in the general population. In our study, the SMR for women (2.9) was significantly higher than for men (2.5), confirming data from previous studies.7 9 A Swedish nationwide study found an increased risk of heart failure and stroke in women with MS, similar to a previous Danish report.7 20 Women with PPMS have also been reported to have an increased hazard compared with men with PPMS.4 If women with MS truly have an increased mortality risk compared with men, further studies designed to investigate such a difference are, therefore, warranted. Global cardiovascular risk in MS, estimated by the Framingham Cardiovascular Risk Score, has recently been associated with increased MS disability and disease progression.21 With regards to investigating gender differences in mortality, added insight into the impact of gender-linked disparities in cardiovascular and lifestyle risk factors as well as treatment strategies and biological disease mechanisms would be warranted.20 22

    Life expectancy has increased enormously in the general population during the 20th century.23 In most European countries, the life expectancy at birth was around 50 years in the early 1900s and has increased to approximately 75 years for men and 81 years for women in the year of 2000.23 One important reason for this improved survival has been the marked decline in cardiovascular diseases in advanced ages observed during the last decades.24 Multiple other factors have also likely contributed to this shift, such as general improvement in healthcare, better disability rehabilitation, socioeconomic development, better treatment for comorbid disorders, medical advances and lifestyle changes (smoking, diet, exercise, use of alcohol). In particular, the observed decline in smoking since the 1970–1980s have had a favourable impact on life expectancy.25

    According to disease course in MS, we found that patients with RRMS outlived patients with PPMS by almost 7 years from birth, and the mortality risk (SMR) was twofold higher in PPMS compared with in RRMS. Consistent with our results, two previous studies reported similar observations.4 5 On the other hand, they found similar survival ages in RRMS and in PPMS, which was different from the findings of our study.

    Whether the increased life expectancy and lower mortality rate in RRMS is/was influenced by the availability of efficient disease modifying treatments for RRMS as opposed to in PPMS is currently unknown.26 27

    Analyses of COD patterns show that MS was the leading COD in more than half of cases, in line with existing data.2 7 18 27 However, no significant differences regarding the number of cause-specific deaths were observed between genders or disease courses. Also, when estimating the mortality (SMR) of cause-specific deaths no significant differences were found between the two populations. However, these results are probably influenced by the limited sample size in each category of listed causes of deaths.

    The main strength of our study was the long duration of follow-up of a population-based incidence cohort, which increases the likelihood of the measured outcome to occur, as well as completeness and validity of data. The long period of observation also improves both quantity and quality of data on competing risks, as health problems can manifest themselves at all stages in life, although the occurrence of health issues more commonly increase with ageing. The main limitation of our study was the limited number of participants. Other limitations were mainly confined to the lack of information on lifestyle factors and comorbidities. The use of CODs based solely on death certificates have some limitations. The physicians responsible for filling out the death certificate forms are in many instances not the patient’s primary care physician and may lack relevant clinical information on the patients medical history. There is variation in coding practices and in accuracy in identification of COD.28 Moreover, COD listed on death certificates have shown discrepancies to the main diagnosis given at hospital discharge in patients who had been hospitalised during their final year of life and are also rarely autopsy confirmed.29 The time lag from onset to diagnosis of MS have decreased over recent years, hence, the incidence rates of MS at the beginning of this study might also have been underestimated. The study is a population-based study comprising all patients with disease onset during the study period and may include fewer benign cases in the first decades and more such cases in the latest years. However, since MS usually lead to increased disability with time, benign cases in the first decades were probably diagnosed later and included in the 60-year follow-up, limiting this possible bias. Improved diagnostic tools and diagnostic criteria as well as advancement in general healthcare have made earlier diagnosis of MS possible, factors that potentially could play a role in the observed improvement in MS survival in recent decades. However, our results are compatible with most previous studies in showing improved life expectancy in MS over time. Thus, indicating a probable effect from increasingly effective MS therapies and improved overall MS care, leading to reduction in complications from MS in advanced disease stages.30

    When estimating the overall SMR during this 60-year follow-up time, a nearly threefold higher mortality rate in MS compared with the general population was recorded.9 Yet, irrespective of SMRs being measured from onset or from diagnosis, an overall significant increase in survival in MS compared with the general population was observed during the entire 60-year follow-up period. However, in the most recent time period (1997–2012), which showed a similar SMR (0.7) to the general population, the patients were in their early adulthood, and this SMR result should, therefore, be interpreted with uttermost caution. We studied the natural course of MS, and the availability of disease modifying therapies from mid-1990s could likely not have influenced our results. Also, incomplete treatment data and heterogeneous treatment strategies would have caused biases on treatment effect, if analysed. However, recent findings from a pivotal trial of the first available therapy of interferon beta 1b, showed a decreased mortality in the active treatment arm ­21 years­ later.31 The rapid development of new disease therapies in MS and overall improved caretaking of the disabled during the last decades are thus promising for future improvements of survival and life expectancy in MS.

    However, to estimate future trends in life expectancy more accurately, it is crucial to facilitate and take advantage of MS registries with detailed information on the use of disease modifying treatment as well as comorbidities and lifestyle factors.

    Young-Onset Parkinson’s Disease | Johns Hopkins Medicine

    It’s not common to see Parkinson’s disease in people younger than 50, but for a small subset of sufferers, the disease strikes early. While people are diagnosed with Parkinson’s at an average age of 60, anything younger than 50 is considered young-onset Parkinson’s, or YOPD. Rarely, Parkinson’s disease may be diagnosed in people younger than 40 — current estimates are that about 2 percent of the 1 million people with Parkinson’s were diagnosed earlier than age 40.

    Although people who are diagnosed young face a different set of challenges, they may also have reasons for hope and optimism based on their age. Here’s what you need to know.

    What’s Different About Young-Onset Parkinson’s

    The age of diagnosis matters for a variety of reasons, from probable causes of early cases to symptoms and treatment:

    • Genetics. As with any case of Parkinson’s disease, the exact cause is usually unknown. That said, “The young-onset cases of Parkinson’s disease are, on average, a bit more likely to be familial or genetic,” says Gregory Pontone, M.D., director of the Johns Hopkins Movement Disorders Psychiatry Clinic.
    • Symptoms. In many patients with YOPD, dystonia (stiffness or cramping in a muscle or limb) is an early symptom. People with YOPD also report more dyskinesia (involuntary body movements). They also tend to exhibit cognitive problems, such as dementia and memory issues, less frequently.
    • Progression. Patients with young-onset Parkinson’s appear to have a slower progression of the disease over time, says Pontone. “They tend to have a milder course, staying functional and cognitively intact for much longer.”
    • Treatment. Most patients with Parkinson’s take the medication levodopa. However, other drugs, such as MAO-B inhibitors, anticholinergics, amantadine, and dopamine receptor agonists, may be used before levodopa.

    Challenges of Young-Onset Parkinson’s

    One major difference involves the stage of life you may be in if you have Parkinson’s disease in your 40s or 50s, versus later in life. For one, you may be at the peak of your career and parenting children or adolescents still at home. This situation makes focusing on your own wellness and care more difficult.

    The ‘Plus’ Side of an Early Diagnosis

    The news is not nearly all bad for those with young-onset Parkinson’s. For one thing, patients with YOPD are better candidates for surgical procedures and medical innovations being used or developed to treat Parkinson’s disease. For another, younger patients are less likely to be coping with other health problems at the same time.

    Symptoms, Causes, Diagnosis & Treatments

    Overview

    What is multiple sclerosis (MS)?

    Multiple sclerosis (MS) is an autoimmune disease. With these conditions, your immune system mistakenly attacks healthy cells. In people with MS, the immune system attacks cells in the myelin, the protective sheath that surrounds nerves in the brain and spinal cord.

    Damage to the myelin sheath interrupts nerve signals from your brain to other parts of your body. The damage can lead to symptoms affecting your brain, spinal cord and eyes.

    There are four types of multiple sclerosis:

    • Clinically isolated syndrome (CIS): When someone has a first episode of MS symptoms, healthcare providers often categorize it as CIS. Not everyone who has CIS goes on to develop multiple sclerosis.
    • Relapsing-remitting MS (RRMS): This is the most common form of multiple sclerosis. People with RRMS have flare-ups — also called relapse or exacerbation — of new or worsening symptoms. Periods of remission follow (when symptoms stabilize or go away).
    • Primary progressive MS (PPMS): People diagnosed with PPMS have symptoms that slowly and gradually worsen without any periods of relapse or remission.
    • Secondary progressive MS (SPMS): In many cases, people originally diagnosed with RRMS eventually progress to SPMS. With secondary-progressive multiple sclerosis, you continue to accumulate nerve damage. Your symptoms progressively worsen. While you may still experience some relapses or flares (when symptoms increase), you no longer have periods of remission afterward (when symptoms stabilize or go away).

    How common is multiple sclerosis (MS)?

    Nearly 1 million adults in the U.S. are living with multiple sclerosis. MS commonly affects more women than men. Most people with MS receive a diagnosis between the ages of 20 and 40.

    Symptoms and Causes

    What causes multiple sclerosis (MS)?

    Experts still don’t know for sure what causes multiple sclerosis. Research is ongoing to help identify what causes the disease. Factors that may trigger MS include:

    • Exposure to certain viruses or bacteria: Some research suggests that being exposed to certain infections (such as Epstein-Barr virus) can trigger MS later in life.
    • Where you live: Your environment may play a role in your risk for developing MS. Certain parts of the world have significantly higher rates of the disease than others. Areas farther from the equator have higher rates of MS. That may be because these regions receive less intense sun. People who get less sun have lower levels of vitamin D, a risk factor for developing MS.
    • How your immune system functions: Multiple sclerosis is an autoimmune disease. Researchers are working to figure out what causes some people’s immune cells to mistakenly attack healthy cells.
    • Gene mutations: Having a family member with MS does increase your risk of the disease. But it’s still unclear exactly how and which genes play a role in triggering multiple sclerosis.

    What are the symptoms of multiple sclerosis?

    Vision problems — such as optic neuritis (blurriness and pain in one eye) — are often one of the first signs of multiple sclerosis. Other common symptoms include:

    • Changes in gait.
    • Fatigue.
    • Loss of balance or coordination.
    • Muscle spasms.
    • Muscle weakness.
    • Tingling or numbness, especially in your legs or arms.

    What are the complications of multiple sclerosis?

    If MS progresses, worsening symptoms may lead to complications such as:

    • Difficulty walking that may result in needing a cane, walker or wheelchair.
    • Loss of bowel or bladder control.
    • Memory problems.
    • Sexual difficulties.

    ###

    Diagnosis and Tests

    Who diagnoses multiple sclerosis (MS)?

    Many conditions could cause similar neurological symptoms. Getting an accurate diagnosis is sometimes difficult. Some people see multiple providers over years before receiving a diagnosis. While the search can be frustrating, it’s important to keep looking for answers. Identifying and treating MS as soon as possible can help slow the disease’s progression.

    If your primary care provider suspects you may have MS, you will need to see a neurologist. A neurologist is a doctor who specializes in treating conditions that affect the nervous system, which includes your brain and spinal cord.

    How is multiple sclerosis diagnosed?

    No one test can provide a definitive MS diagnosis. To understand what’s causing symptoms, your healthcare provider will do a physical exam. You may also have blood tests and imaging tests, such as MRI. An MRI looks for evidence of lesions (areas of damage) in the brain or spinal cord that indicate multiple sclerosis. Lesions develop as a result of damage to the myelin sheath surrounding the nerves. A spinal tap (lumbar puncture) may also need to be done.

    If these tests don’t provide a clear answer, your neurologist may recommend an evoked potentials test. This test checks your nerve function by measuring electrical activity in the brain and spinal cord.

    Management and Treatment

    How is multiple sclerosis (MS) managed or treated?

    There is currently no cure for MS. Treatment focuses on managing symptoms, reducing relapses (periods when symptoms worsen) and slowing the disease’s progression. Your comprehensive treatment plan may include:

    • Disease-modifying therapies (DMTs): Several medications have FDA approval for long-term MS treatment. These drugs help reduce relapses (also called flare-ups or attacks). They slow down the disease’s progression. And they can prevent new lesions from forming on the brain and spinal cord.
    • Relapse management medications: If you have a severe attack, your neurologist may recommend a high dose of corticosteroids. The medication can quickly reduce inflammation. They slow damage to the myelin sheath surrounding your nerve cells.
    • Physical rehabilitation: Multiple sclerosis can affect your physical function. Staying physically fit and strong will help you maintain your mobility.
    • Mental health counseling: Coping with a chronic condition can be emotionally challenging. And MS can sometimes affect your mood and memory. Working with a neuropsychologist or getting other emotional support is an essential part of managing the disease.

    Prevention

    How can I prevent a multiple sclerosis flare-up?

    Disease-modifying therapies are the most effective way to reduce the number of flare-ups (also called relapses or attacks) you experience. Leading a healthy lifestyle is also important. The choices you make can help slow disease progression. Good care can also lessen your symptoms and improve your quality of life.

    Lifestyle changes that can improve your condition include:

    • Eating a healthy diet: There is no magic MS diet. Experts recommend a balanced diet that includes lots of fruit and vegetables, whole grains, healthy fats and lean protein. You should also limit your intake of added sugars, unhealthy fats and processed foods.
    • Getting regular exercise: Multiple sclerosis can cause muscle weakness, loss of balance and difficulty walking. Aerobic exercise, flexibility and strength training are essential to help keep muscles strong and maintain physical function.
    • Managing stress: Stress can take a physical and emotional toll. It can also interfere with sleep, which can worsen MS-related fatigue. It’s important to find ways to manage stress — such as yoga, meditation, exercise, and working with a mental health provider.
    • Not smoking and limiting alcohol intake: Smoking and alcohol are linked to worsening MS symptoms and could speed the disease’s progression. Quitting smoking will support your health.

    Outlook / Prognosis

    What is the prognosis (outlook) for people with multiple sclerosis (MS)?

    In some cases, multiple sclerosis does lead to disability and loss of some physical or mental function. But thanks to advances in treatment, most people with MS will continue to lead full, active and productive lives. Taking steps to manage your health and lifestyle can help improve your long-term outcome.

    Is it common for people with multiple sclerosis (MS) to experience depression?

    Depression is very common in people with multiple sclerosis (MS). In fact, symptoms of depression severe enough to require medical intervention affect up to half of all people with MS at some point during their illness.

    Depression may be the result of a difficult situation or stress. It is easy to understand how having MS, with its potential for progressing to permanent disability, can bring on depression.

    Depression might be actually caused by MS. MS may affect the insulating myelin that surrounds nerves which transmit signals affecting mood.

    Depression is also a side effect of some drugs used to treat MS, such as steroids or interferon.

    How does heat or humidity impact people with multiple sclerosis (MS)?

    Heat or high humidity can cause many people with MS to experience a temporary worsening of their symptoms. Doctors believe that this occurs because heat causes nerves (whose myelin covering has been removed by MS) to conduct electrical signals even less efficiently.

    For reasons that are not well understood, extremely cold temperatures and changes in temperature can also cause MS symptoms, usually spasticity (muscle stiffness), to flare.

    ###

    Living With

    When should I call the doctor?

    You should call your healthcare provider if you experience:

    • Feeling overly sensitive to heat.
    • Feeling unsteady or off balance.
    • Memory problems.
    • Numbness or tingling, especially in your arms or legs.
    • Sudden vision changes.
    • Weakness in your arms or legs.

    What questions should I ask my doctor?

    You may want to ask your healthcare provider:

    • How do we know for sure that I have multiple sclerosis and not another neurological condition?
    • Do I need to start taking disease-modifying therapy medication?
    • What are the benefits and risks of various DMTs?
    • Will I need to stay on medication for the rest of my life?
    • What lifestyle changes can I make to help manage MS?

    A note from Cleveland Clinic

    Multiple sclerosis is a disease that affects the central nervous system (brain, spinal cord and optic nerves). It is an autoimmune disease that causes your immune cells to mistakenly attack your healthy nerve cells. These attacks lead to inflammation and damage to the myelin sheath that covers and protects your nerve cells. This damage causes neurological symptoms — such as loss of balance, vision problems and muscle weakness. Several effective treatments exist for MS. These medications reduce relapses and help slow the progression of the disease. Most people with MS are able to manage their symptoms and lead full, active lives.

    90,000 Novosibirsk “obesity paradox” – 1% of healthy fat men – Science – Kommersant

    The term “metabolically healthy obesity” (MHO, in English MHO – metabolically healthy obesity) appeared in medical science in 1982, another name for this phenomenon in the scientific literature – “obesity paradox”. They introduced the term MLO, of course, not to describe the state of moderately overweight people, why should they be ill? MLO is a diagnosis only for patients with a body mass coefficient of about 30 or more, that is, “obese”.

    According to the NHANES (National Health and Nutrition Examination Survey) obesity database, in the United States, 31.7% of obese people (29.2% of men and 35.4% of women) aged 18–80 years are metabolically healthy. If we exclude young people from the statistics, whose body is still able to compensate for the development of obesity-related ailments, then the proportion of healthy fat men decreases. According to medical statistics, such, for example, in Germany 12.5% ​​(average age of the sample 59.6 years), in Italy 11.5% (average age 54.9 years).

    In our country, there is no national statistics of this kind, but there are cities. For example, in Novosibirsk, the prevalence of obesity in the general population of 45–69 years was 35% (for men – 20.7%, for women – 47%), and of these 35% of very fat Novosibirsk residents, 41.8% belonged to the MLO cohort.

    It turned out that almost every second obese resident of Novosibirsk, who is far from young, remains a practically healthy person, and there are more of them here than in the USA, not to mention Italy and Germany.There was no reason to doubt the results of the analyzes of scientists, which means that something was wrong with medical statistics in the field of obesity.

    Chaos really reigns in it, and for this reason. When scientists agreed on what to consider as metabolically healthy obesity, they decided that it should include obese patients who are diagnosed with no more than two complications associated with obesity.

    And there are a lot of such complications. Visceral obesity, high blood pressure, an increase in blood triglycerides (TG) and glucose levels, a decrease in cholesterol in the form of high density lipoproteins (HDL cholesterol, that is, “good” cholesterol) and an increase in it in the form of low and very low density lipoproteins (they are and form cholesterol plaques on the walls of blood vessels).As well as other disorders associated with dyslipidemia, arterial hypertension, cardiovascular diseases and some forms of cancer.

    But if a patient is diagnosed, for example, only with HDL cholesterol, or only high blood pressure along with a high content of TG in the blood, or no more than any two other signs of diseases associated with obesity in all possible combinations, then such patients automatically fall into the column “metabolically healthy obesity »Medical statistics.

    This looks like nonsense.But the introduction of the concept of MHO was a forced measure, since there is such a “cohort” among patients, as doctors say, then in evidence-based (scientific) medicine there should be its name. The term itself, or rather, the presence of the word “healthy” in it, initially did not like the medical scientists. At scientific conferences, they repeatedly, most recently at a symposium in the Dominican Republic in 2014, tried to cancel it and forget it. Well, a person weighing 120–160 kg cannot be healthy! But how to name this cohort of healthy and “not very sick” fat men in return, they did not come up with, and the “obesity paradox” still appears in the science of obesity as a “paradox”, although for the paradox of healthy people among obese people, judging by medical statistics, a bit too much.

    Why scientists did not immediately limit the concept of “metabolically healthy obesity” to the complete absence in the patient of any diagnostic signs of metabolic diseases accompanying obesity is a mystery that cannot be explained, like many other “paradoxes” of medical statistics. But common sense seems to be starting to win.

    Specialists of the European biobanking consortium BioSHaRE have proposed to consider the MLO as such only in the absence of any metabolic complication and are now bringing their statistics in line with this understanding of the MLO criterion.And scientists of the Novosibirsk Research Institute of Therapy and Preventive Medicine last year estimated the proportion of metabolically healthy people (without a single metabolic syndrome) among obese Novosibirsk residents aged 45 to 69 years. There are only 1% of them.

    This is probably the first truly objective assessment of the effects of obesity on human health, and the statistics on the incidence of metabolic syndromes to obesity will have to be revised both at the national levels and at the level of the World Health Organization.And then the fact that obesity is a very serious and dangerous disease will become even more evident.

    There is only one thing that pleases me. Although there are very few of them, only every hundredth of obese people, there are still fat people who have practically no signs of type 2 diabetes for almost their entire life (at least up to 70 years old, according to Novosibirsk scientists), their blood pressure is normal, order with the heart and other ailments associated with obesity are not observed. They do not suffer from anything other than the everyday inconveniences associated with being very overweight.The phenotype, as geneticists say, is like that. Someone is skinny all their lives thanks to their genes, someone is of normal physique, someone is fat, and someone is very fat.

    90,000 Blood lipids and cytokines in cholelithiasis and metabolic syndrome

    With the aim to assess blood sera lipids and cytokines levels were examined 133 patients (mean age 52.9 ± 1.7 years) with gallstone disease (GSD) and metabolic syndrome (MS). GSD diagnosis was confirmed by ultrasonography. MS criteria meet the requirements of NCEP (ATP-III, 2001).Among all patients significantly highest levels of total cholesterol, LDL cholesterol, triglycerides, and tumor necrosis factor alpha (TNF-α) were observed in patients with GSD in combination with MS (6.06 ± 0.15, 3.91 ± 0, 14, 2.02 ± 0.11 mmol / l and 4.61 ± 0.51 pg / ml respectively). Medium lipids and TNF-α levels were significantly higher in patients with postcholecystectomy syndrome (PCS) with MS than in patients with PCS without MS. Interleukin 1beta (IL-1β) levels did not differ in all patients.Abdominal pain and dyspepsia met more often in patients with GSD with MS than in patients with GSD without MS. The presence of MS impairs lipid profile, TNF-α levels and clinical course of GSD.

    In order to assess the levels of lipids and cytokines in the blood serum, 133 patients (mean age 52.9 ± 1.7 years) with cholelithiasis (GSD) and metabolic syndrome (MS) were examined. The diagnosis of gallstones was confirmed by ultrasonography. MS criteria were consistent with the NCEP requirements (ATP-III, 2001).Among all examined, the significantly highest levels of total cholesterol, LDL cholesterol, TG and tumor necrosis factor alpha (TNF-α) in the blood (6.06 ± 0.15, 3.91 ± 0.14, 2.02 ± 0.11 mmol / l and 4.61 ± 0.51 pg / ml, respectively) were detected in patients with cholelithiasis in combination with MS. In the presence of postcholecystectomy syndrome (PCES) in patients with cholelithiasis in combination with MS, the mean levels of blood lipids and TNF-α were significantly higher than in patients with PCES without MS. The mean values ​​of interleukin-1 blood did not differ in the examined patients.Patients with cholelithiasis in combination with MS complained of abdominal pain and dyspepsia significantly more often than patients with cholelithiasis without MS. The presence of MS worsens the lipid profile, TNF-α indices and the clinical course of gallstone disease.

    90,000 OSAS – Possibilities of Holter monitoring in assessing the relationship between cardiac arrhythmias and conduction disturbances with episodes of apnea

    Authors:
    Tikhonenko V.M., Aparina I.V.

    Obstructive sleep apnea (OSAS) is often accompanied by disturbances in the rhythm and conduction of the heart, and in the treatment of such arrhythmias, the therapy of respiratory disorders comes to the fore [1, 2].However, using traditional diagnostic methods, such as Holter ECG monitoring, exercise and pharmacological tests, electrophysiological studies, it is impossible to assess the relationship between respiratory and heart rhythm disorders. Sleep laboratory research can help diagnose, but its prevalence is far from comparable to the magnitude of the problem. So, for example, in St. Petersburg in sleep laboratories no more than 25 people can be examined per day, while with the prevalence of OSAS in the adult population [3, 4], at least 350 thousand people need to identify apnea.Obviously, even with an increase in the number of sleep laboratories, they will not be able to screen everyone in need, and simpler and more widespread methods are needed to effectively detect and treat respiratory disorders.

    For screening of respiratory disorders, several methods have become widespread – identification of characteristic changes in heart rate during episodes of apnea, detection of episodes of hypoxemia accompanying apnea, and analysis of the presence of apnea on a pneumogram. The present study was conducted to assess the diagnostic value of these methods in identifying OSAS, assessing its severity and in determining the relationship between apnea and arrhythmias.

    MATERIAL AND RESEARCH METHODS

    A total of 81 patients were examined and referred to the North-West Center for the Diagnostics and Treatment of Arrhythmias to clarify the nature of rhythm disturbances and to choose a treatment strategy. The study included patients in whom, on the basis of complaints and physical data, it was possible to assume the presence of OSAS. Among them there were 18 women (0.22) and 63 men aged 37 to 80 years (the average age was 57.1 ± 2.3 years).

    All patients underwent cardiorespiratory monitoring using the Cardiotechnika-04-3RM apparatus (INCART, St. Petersburg, Russia).The monitor recorded 12 ECG leads, one lead of a rheopneumogram (RPG), peripheral pulse and blood oxygenation by pulse oximetry, motor activity and position of the patient’s body using a built-in two-position accelerometer during the day. During sleep (day and night), a nasal catheter was installed, with the help of which the air flow (spirogram) and sound phenomena (snoring) were additionally recorded – see Fig. 1.

    During monitoring, a system of modified 12 standard leads was recorded, in which the electrodes from the arms and legs were transferred to the trunk (sacrum and to the distal part of the clavicles).The electrodes from which the RPG was removed were installed along the right and left middle axillary line in the 5th intercostal space, so that the recorded respiratory curve reflected the respiratory movements of both the right and left lungs, both during thoracic and diaphragmatic breathing. It should be noted that RPG was recorded in the Kardiotekhnika-04-3RM monitor from the same electrodes from which the ECG was taken (common electrode and V6 lead electrode). This is convenient, since it does not require additional sensors to be installed.Pulse oximetry was recorded using a finger sensor placed on the ring finger of the left hand.

    When analyzing the records, the daily dynamics of the heart rate was assessed, rhythm and conduction disturbances were identified, classified and counted, episodes of ischemic ECG changes accompanied by a ST segment displacement of more than 1 mm were determined. The spirogram revealed episodes of hypopnea (decrease in the amplitude of respiration by 50% or more for 10 s or more) and apnea (decrease in amplitude by 90%), their duration and number were calculated.If the spirogram was not suitable for analysis for at least 3 night hours, then the patients were excluded from the analysis.

    During episodes of apnea and hypopnea, the presence of hypoxemia (decrease in oxygen levels by 3% or more), bradycardia (decrease in heart rate by 10% or more), as well as the presence of hypopnea or apnea on RPG were additionally evaluated (Fig. 1).

    OBTAINED RESULTS AND THEIR DISCUSSION

    Sixty of the 81 examined patients initially had sinus rhythm (0.74), 13 had a permanent form of atrial fibrillation (0.16), one had persistently recurrent ventricular tachycardia, and 7 had a pacemaker rhythm (0.09).In addition, in 5 patients (0.06), there was a violation of intraventricular conduction in the form of complete blockade of the left (2 patients) or right bundle branch (1 patient) or incomplete blockade of the branches of the left leg (2 patients). During the day, the examinees revealed the following rhythm and conduction disturbances (Table 1).

    It can be seen that the majority of patients had ventricular or supraventricular extrasystoles – single or paired. In 11 patients, paroxysms of tachycardia lasting from 3 complexes to 65 minutes were observed.Violations of atrioventricular conduction were found in 7 cases (one patient was diagnosed with atrioventricular block and 1 and 2 degrees), and in 6 cases the pause duration was more than 2000 ms, and in 4 – more than 3000 ms. (up to 5500 ms). Stopping the sinus node also in all cases led to pauses of more than 2000 ms, and in 5 patients pauses of more than 3000 ms (up to 7900 ms) were revealed.

    Active arrhythmias (extrasystoles and paroxysms of tachycardia) more often had a daytime or mixed type of distribution, and only in 12 patients (0.15) the number of extrasystoles significantly increased at night.Pauses due to atrioventricular or sinoauricular block, on the contrary, appeared or increased at night. In 10 of 13 patients, pauses of more than 2000 ms appeared only at night, and long pauses of more than 3000 ms were observed in all 9 cases at night.

    During the night, patients had from 3 to 527 episodes of apnea (mean 221 ± 23). The maximum duration of respiratory arrest ranged from 20 to 135 s. OSAS was diagnosed in 0.78 patients, with OSAS 1 severity in 21 patients (0.26), OSAS 2 severity in 13 patients (0.16) and OSAS 3 severity in 29 patients (0.36).

    The relationship between rhythm and conduction disturbances and episodes of apnea was found in 18 patients. Most often (in 12 cases) pauses were associated with respiratory arrests due to atrioventricular (5 cases) or sinoatrial (7 cases) blockade (Fig. 2), and they always appeared in the apnea phase (usually in the second half or at the end of the episode) … In 0.92 cases of detection of pauses, they were associated with periods of apnea, and in many patients this relationship was absolute – outside of apnea pauses were not observed in them.But in other cases, when pauses were encountered both during periods of calm breathing and during apnea, in the latter case there were more of them and they were longer.

    In 6 patients with breathing disorders, the appearance of ventricular (4 patients) or supraventricular (2 patients) extrasystoles was associated. This was observed much less frequently – in 0.07 of all patients with active arrhythmias or in half of patients with nocturnal type of such disorders. It could be seen that active arrhythmias were more often observed in the hyperpnea phase (Fig.3).

    In total, out of 25 patients with nocturnal type of rhythm and conduction disturbances, 18 (0.72) were found to have a connection between arrhythmias and respiratory arrest. This confirms the opinion of many authors about the leading role of apnea in the genesis of nocturnal arrhythmias [5, 6]. Probably, one must agree with the opinion that the detection of nocturnal rhythm disturbances is an absolute indication for examining the patient for the presence of OSAS (respiratory monitoring). In the group examined by us, 9 patients (0.11) had clinically significant arrhythmias leading to asystole and requiring prompt determination of treatment tactics.This confirms that the problem of rhythm and conduction disorders associated with apnea is not only of scientific interest, but also of great clinical significance.

    The association of arrhythmias with apnea was more often observed in severe OSAS, but the severity of arrhythmias did not always correlate with the severity of OSAS. In five cases, long pauses were found in mild OSAS, and the longest period of asystole (up to 7900 ms) was observed in a patient with mild OSAS (apnea index 5). Thus, the identification of the relationship between arrhythmias and apnea should be performed regardless of the severity of OSAS.

    The frequent identification of serious arrhythmias associated with apnea in patients with mild OSAS raises the question of choosing the correct treatment tactics for such patients. It is known that nocturnal pauses occurring in patients with severe OSAS are effectively treated with positive pressure therapy (CPAP therapy). Some authors even note the complete disappearance of heart rhythm pauses against the background of effective therapy [5]. However, with a mild degree of OSAS, the adherence of patients to CPAP therapy is very low – they refuse to carry it out or sleep in a mask not all night, but only a small part of it [6].Their pauses may persist, and it is likely that such patients are still candidates for the installation of a stimulator.

    Considering that all patients with nocturnal arrhythmias, especially pauses in the heart rhythm due to sinoauricular or atrioventricular blockade, need to diagnose apnea and assess the relationship between rhythm disturbances and respiratory disorders, screening for respiratory disorders in this group is of particular importance. To assess the diagnostic value of screening methods in detecting apnea, the sensitivity and specificity of such signs as the presence of episodes of bradycardia, the appearance of hypoxemia, or the detection of apnea / hypopnea by RPG were determined.The results are presented in table. 2.

    As can be seen from the presented data, the dynamics of RR-intervals allows one to suspect the presence of apnea in only half of the patients, and even with severe OSAS this number increases insignificantly – only up to 0.63. The specificity of such diagnostics is also low – in 0.30 cases, a similar dynamics of RR intervals could be observed outside of apnea episodes. In addition, in 0.26 patients, the dynamics of RR intervals could not be correctly assessed due to the presence of atrial fibrillation or other pronounced rhythm disturbances or due to the presence of an implanted stimulator.Such a large proportion of patients with arrhythmias is due to the fact that the patients were examined at the antiarrhythmic center – there will probably be fewer of them in the population, but this limitation should still be taken into account.

    In the presence of sinus rhythm, however, not all of them could see characteristic episodes of bradycardia, and they were absent not only in the rigid rhythm, but also in a number of patients with high variability of RR intervals (see Fig. 1). Thus, the dynamics of RR-intervals cannot be an independent diagnostic method, but only allows one to suspect OSAS in some patients.The accuracy of the quantitative assessment of apnea episodes by heart rate dynamics, respectively, was not evaluated.

    Episodes of a decrease in oxygen in the blood were more clearly combined with apnea – the sensitivity of the method was 0.56 with a very high specificity of 0.96. This specificity was due to the fact that hypoxemia outside apnea was almost never encountered (only isolated cases of errors with interference). Lower sensitivity numbers were formed due to the fact that during short episodes of apnea or hypopnea, the oxygen content in the blood did not have time to decrease, and such episodes were not reliably visible on the oxyhemoglobin content graph.

    The sensitivity of this method increased in patients with OSAS (up to 0.71) and with an increase in its severity – from 0.57 in mild and to 0.80 in severe form of the syndrome. However, even with severe OSAS, when patients had up to 400-670 episodes of respiratory arrest per night, in 0.20 of them the oxygen level did not decrease significantly and these episodes could not be reliably detected by recording the oxyhemoglobin content (Fig. 4). It should be noted that in three patients (0.04) the oxygen content could not be estimated due to the dislocation of the sensor.

    Due to the fact that some of the apnea was not accompanied by a significant decrease in oxygen, the method underestimated the number of episodes by almost two times (by 0.41). In patients with severe OSAS, this error was lower, but nevertheless, only two-thirds of the apnea episodes were manifested by severe hypoxemia. Thus, the detection of episodes of hypoxemia can confirm the presence of severe OSAS with high specificity – this method is not very suitable for the diagnosis of initial forms. In addition, devices for long-term monitoring of the oxygen content in the blood are not widely used in practical health care facilities, which also makes this method less suitable as a screening method.

    The highest sensitivity was obtained when using RPG – 0.81 in general with an increase to 0.91 in patients with OSAS. Only in some patients (mainly with episodes of hypopnea) during a sharp decrease in the respiratory flow on the spirogram there was no significant decrease in respiratory movements according to RPG (see Fig. 3). It should be noted that even in these cases one could see a characteristic “crest” on the RPG, at the appearance of which one could suspect the presence of respiratory disorders.However, according to formal criteria, hypopnea was not observed on RPG and such cases reduced sensitivity.

    RPG specificity was lower – only 0.85. In 0.15 patients, changes in RPG that mimic those in apnea could be obtained due to interference. In our opinion, the screening method should have a high sensitivity in order not to miss patients, even if with a lower specificity, since the verification of the diagnosis should be carried out using more specific methods, such as cardiorespiratory monitoring.

    The high sensitivity of the RPG method is also noted by other authors, who cite figures from 67 to 100% in their works [6, 7]. It should be noted that the RPG method made it possible to obtain data from all examined patients, and without the need to install any additional sensors. The number of apnea episodes by RPG was also underestimated, although not so significantly – 0.79 of them were identified. It is important that the correctness of the estimation of the number of apnea practically did not differ in patients with both mild and severe OSAS.

    Note that when using screening methods (both RPG and pulse oximetry), the number of apnea / hypopnea episodes may be underestimated. In some patients, this leads to a decrease in the severity of OSAS or even to the assignment of patients to the normal group (for example, if the number of episodes in a patient with an apnea index of 6 is twice underestimated). It can be concluded that when using pulse oximetry or RPG methods, it is necessary to identify a group of patients with an intermediate number of episodes (from 2 to 5 per hour), which requires clarification of the diagnosis.

    The question is often asked – why do we see respiratory arrest in OSAS on RPG, while in obstructive apnea, in contrast to central apnea, chest movements should be preserved and there should be no episodes of lack of respiratory movements? Indeed, if a patient with OSAS has single apnea against the background of regular breathing, then the movements of the chest are usually preserved (Fig. 5a). But with a large number and severity of respiratory stops, when they take up a significant part of the time, hyperventilation is observed in the respiratory phase (dyspnea phase) – the severity of respiratory movements is much greater than with calm breathing.Hyperventilation leads to the washing out of carbon dioxide from the blood and, accordingly, to inhibition of the respiratory center and reflex cessation of breathing for 15-30 s. During this time, the cessation of breathing is really of central origin, and if the apnea lasts longer, then the movements of the chest are activated and oscillations can be seen on the RPG (Fig.5b). Such apnea is commonly referred to as “mixed”.

    Thus, due to the above mechanism, in almost the majority of patients with OSA, one can see apnea by RPG – if not with every cessation of breathing at the level of the nasopharynx, then at least with the most pronounced episodes.In most patients, a wavy RPG curve can initially be seen, and with severe apnea, an isoelectric curve (RPG apnea). In a smaller number of patients, at first, apnea is practically not manifested on RPG (respiratory movements of the chest during apnea are comparable to those during breathing), but with longer episodes, apnea on RPG still appears.

    For clinical practice, it is important that Holter monitors with an RPG channel are quite widespread in Russia, since they have been produced since 2003.firm INCART (St. Petersburg) [7], and recently by several manufacturers. This allows all patients with nocturnal arrhythmias to be screened for respiratory distress. Moreover, in many cases, the RPG recording is already in the Holter recording made for the assessment of arrhythmias, and it only needs to be carefully analyzed.

    A significant advantage of RPG in contrast to pulse oximetry in the group of cardiac patients was that the data were recorded together with the ECG, and the identified episodes of apnea could be compared with the data on rhythm disturbances and myocardial ischemia.

    OUTPUTS

    1. Nocturnal rhythm and conduction disturbances in most patients are associated with episodes of apnea, and severe arrhythmias – up to asystole – can be triggered by episodes of respiratory arrest, regardless of the severity of OSAS, therefore, patients with nocturnal heart rhythm pauses need to be diagnosed with respiratory disorders.
    2. The rheopneumogram (up to 0.81) shows the highest sensitivity among the investigated screening methods for detecting apnea, while in pulse oximetry it is lower even in severe OSAS, and the dynamics of heart rate can only suspect the presence of apnea.
    3. Holter monitoring with rheopneumogram control allows not only to identify episodes of apnea, but also to assess their effect on rhythm disturbances and the occurrence of episodes of myocardial ischemia. This method is quite widespread and most convenient in clinical use, since it does not require the installation of additional sensors.

    REFERENCES

    1. Chazova I.E. Obstructive sleep apnea syndrome and associated cardiovascular complications // Russian Journal of Cardiology – 2006.- N 1.- p. 75 – 86.
    2. Dursunoglu D. Cardiovascular diseases in obstructive sleep apnea // Tuberkuloz ve Toraks Dergisi. – 2006. – Vol 54, No. 4 – p. 382-296.
    3. Vein A.M., Eligulashvili E.S., Poluektov M.G. Sleep apnea syndrome and other sleep-related respiratory disorders: clinical picture, diagnosis, treatment. – M., Eidos Media. – 2002. – p. 310.
    4. Punjabi N.M. The epidemiology of adult obstructive sleep apnea. // Proc. Am. Thoracic Society 2008 V.5 N2- p. 136-143.
    5. Pekmezovic Z., Konjevic M. Holter monitoring in sleep apnea. // Bulletin of arrhythmologists. – 2009, Appendix A. – p. 129.
    6. Buzunov R.V. Treatment of obstructive sleep apnea syndrome with positive airway pressure. – M., – 2004.- p. 13.
    7. Lyshova O.V., Ivannikova S.V., Smolyaninov S.V. Screening methods in the diagnosis of sleep apnea syndrome. // VGMA them. N.N.Burdenko, Voronezh. – 2009. – p. 24.

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