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AST Numbers: Understanding High, Low & Normal Results, Symptoms & Causes

What are normal AST levels. How do high AST levels affect liver health. What causes low AST levels. How is nonalcoholic fatty liver disease diagnosed. What are the treatment options for fatty liver disease. How can lifestyle changes impact AST levels. What role do medications play in managing elevated AST.

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Understanding AST: A Key Liver Enzyme

Aspartate aminotransferase (AST) is a crucial enzyme found primarily in liver cells, but also in heart, muscle, and kidney tissues. AST levels in the blood serve as an important indicator of liver health and function. When liver cells are damaged or die, AST is released into the bloodstream, causing elevated levels that can be detected through blood tests.

What are normal AST levels?

Normal AST levels typically range from 10 to 40 units per liter (U/L) of blood. However, these reference ranges may vary slightly depending on the laboratory and testing method used. It’s important to interpret AST results in conjunction with other liver function tests and clinical symptoms for a comprehensive evaluation of liver health.

High AST Levels: Causes and Implications

Elevated AST levels can indicate various liver conditions and other health issues. Some common causes of high AST include:

  • Nonalcoholic fatty liver disease (NAFLD)
  • Alcoholic liver disease
  • Viral hepatitis (types A, B, and C)
  • Cirrhosis
  • Liver cancer
  • Muscle damage or injury
  • Heart attack

How do high AST levels affect liver health?

Persistently elevated AST levels can signify ongoing liver damage and inflammation. This chronic liver injury may lead to fibrosis, cirrhosis, and increased risk of liver failure if left untreated. Regular monitoring of AST levels, along with other liver function tests, helps healthcare providers assess the progression of liver disease and adjust treatment plans accordingly.

Low AST Levels: Understanding the Implications

While high AST levels often indicate liver problems, low AST levels are generally not a cause for concern. In fact, AST levels below the normal range are rarely clinically significant.

What causes low AST levels?

Low AST levels can occur due to various factors, including:

  • Vitamin B6 deficiency
  • Pregnancy
  • Hemodialysis
  • Certain medications

In most cases, low AST levels do not require specific treatment. However, if accompanied by other abnormal liver function tests or symptoms, further evaluation may be necessary to rule out underlying health issues.

Nonalcoholic Fatty Liver Disease: A Growing Concern

Nonalcoholic fatty liver disease (NAFLD) is becoming increasingly prevalent, affecting up to 30% of adults in Western countries. NAFLD encompasses a spectrum of liver conditions, ranging from simple fatty liver (steatosis) to nonalcoholic steatohepatitis (NASH), which can progress to cirrhosis and liver failure.

How is nonalcoholic fatty liver disease diagnosed?

Diagnosing NAFLD typically involves a combination of approaches:

  1. Blood tests: Elevated liver enzymes, including AST and ALT, may indicate liver inflammation.
  2. Imaging studies: Ultrasound, CT, or MRI scans can detect fat accumulation in the liver.
  3. Liver biopsy: In some cases, a biopsy may be necessary to confirm the diagnosis and assess the severity of liver damage.

The ratio of AST to ALT (aspartate aminotransferase to alanine aminotransferase) can be particularly useful in differentiating NAFLD from alcoholic liver disease. A ratio less than 1 is more suggestive of NAFLD, while a ratio greater than 2 is more indicative of alcoholic liver disease.

Treatment Strategies for Fatty Liver Disease

Managing NAFLD and reducing elevated AST levels often involves a multifaceted approach targeting lifestyle modifications and, in some cases, medication.

What are the treatment options for fatty liver disease?

Treatment options for NAFLD may include:

  • Weight loss through diet and exercise
  • Dietary modifications (e.g., reducing sugar and saturated fat intake)
  • Increasing physical activity
  • Managing comorbid conditions (e.g., diabetes, hypertension)
  • Medications (in select cases)

How can lifestyle changes impact AST levels?

Lifestyle modifications play a crucial role in managing NAFLD and reducing elevated AST levels. Studies have shown that weight loss of 7-10% of body weight can lead to significant improvements in liver enzyme levels and reduce liver fat content. Regular exercise, even without significant weight loss, has been associated with decreased liver fat and improved insulin sensitivity.

Pharmacological Interventions for Fatty Liver Disease

While lifestyle changes remain the cornerstone of NAFLD treatment, certain medications may be prescribed to address specific aspects of the disease or associated conditions.

What role do medications play in managing elevated AST?

Several medications have been studied for their potential benefits in NAFLD treatment:

  • Metformin: May improve insulin sensitivity and liver enzyme levels in patients with NAFLD and type 2 diabetes.
  • Thiazolidinediones (e.g., pioglitazone, rosiglitazone): Can improve liver histology and reduce liver fat in NASH patients.
  • Vitamin E: May have antioxidant effects and improve liver histology in non-diabetic NASH patients.
  • Ursodeoxycholic acid: Has shown mixed results in NAFLD treatment but may be beneficial in select cases.
  • Statins: While primarily used for cholesterol management, statins may also have beneficial effects on liver enzymes in NAFLD patients.

It’s important to note that medication use in NAFLD should be carefully considered and monitored by a healthcare provider, as some drugs may have potential side effects or interactions.

Monitoring and Long-term Management of Liver Health

Regular monitoring of liver function, including AST levels, is essential for patients with NAFLD or other liver conditions. This allows healthcare providers to assess disease progression, evaluate treatment effectiveness, and make necessary adjustments to management strategies.

How often should AST levels be checked in patients with liver disease?

The frequency of AST monitoring depends on various factors, including the severity of liver disease, treatment response, and overall health status. Generally, patients with NAFLD or other chronic liver conditions may have their liver enzymes checked every 3-6 months, or more frequently if there are significant changes in symptoms or treatment regimens.

In addition to blood tests, periodic imaging studies may be recommended to assess liver fat content and monitor for complications such as fibrosis or hepatocellular carcinoma in high-risk patients.

Emerging Therapies and Future Directions

Research into NAFLD and liver enzyme management continues to evolve, with several promising therapies on the horizon.

What new treatments are being developed for fatty liver disease?

Some emerging therapies and areas of research include:

  • FXR agonists: Drugs that target the farnesoid X receptor (FXR) to improve liver metabolism and reduce inflammation.
  • PPAR agonists: Medications that activate peroxisome proliferator-activated receptors (PPARs) to improve insulin sensitivity and reduce liver fat.
  • Anti-fibrotic agents: Compounds designed to slow or reverse liver fibrosis progression.
  • Gut microbiome modulation: Probiotics and other interventions targeting the gut-liver axis.
  • Combination therapies: Approaches that combine multiple mechanisms of action to address various aspects of NAFLD pathogenesis.

As our understanding of liver disease mechanisms continues to grow, new therapeutic targets and treatment strategies are likely to emerge, offering hope for improved management of NAFLD and related conditions.

In conclusion, understanding AST levels and their implications is crucial for maintaining liver health and managing conditions like NAFLD. By combining lifestyle modifications, appropriate medical interventions, and regular monitoring, patients can work towards improving their liver function and overall well-being. As research progresses, new therapies and management strategies will continue to enhance our ability to address liver health concerns effectively.

Nonalcoholic Fatty Liver Disease – American Family Physician

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16. Uygun A,
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17. Neuschwander-Tetri BA,
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2003;38:1008–17.

18. Promrat K,
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2004;39:770–8.

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2000;136:734–8.

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25. Harrison SA,
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Vitamin E and vitamin C treatment improves fibrosis in patients with nonalcoholic steatohepatitis. Am J Gastroenterol.
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26. Miglio F,
Rovati LC,
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2000;50:722–7.

27. Abdelmalek MF,
Angulo P,
Jorgensen RA,
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2001;96:2711–7.

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Aljadhey H,
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2004;126:1287–92.

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2005;142:37–46.

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The natural history of nonalcoholic fatty liver disease: a clinical histopathological study. Am J Gastroenterol.
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SRA | Unsolicited telephone calls from “AST Accident Investigation and AST Personal Liability”








Warning: Unsolicited telephone calls from “AST Accident Investigation and AST Personal Liability”



30 July 2020


Members of the public have received unsolicited telephone calls claiming to be from “AST Accident Investigation” and “AST Personal Liability”.

What is the scam?

The SRA has been informed that members of the public have received unsolicited telephone calls from individuals claiming to be from “AST Accident Investigation” and “AST Personal Liability”, in connection with  personal injury claims.

The SRA has been informed that recent telephone calls were made from various telephone numbers and areas, including “07441 399 342”.

The SRA does not authorise or regulate a firm of solicitors called “AST Accident Investigation” or “AST Personal Liability”.

Any business or transactions through “AST Accident Investigation” “AST Personal Liability” or the above telephone  number are not undertaken by a solicitor’s practice or an individual authorised and regulated by the SRA.


Is there a genuine firm or person?

The SRA authorises and regulates a genuine firm of solicitors called AST Hampsons LLP trading as AST Hampsons.  The genuine firm’s telephone number is 01706 653 322.

AST Hampsons LLP has confirmed to the SRA that they have no connection to the telephone number and calls reported in the above alert, and that they do not make ‘cold calls’


What should I do?


When a firm’s or individual’s identity has been copied exactly (or cloned), due diligence is necessary. If you receive correspondence claiming to be from the above firm(s) or individual(s), or information of a similar nature to that described, you should conduct your own due diligence by checking the authenticity of the correspondence by contacting the law firm directly by reliable and established means. You can contact the SRA to find out if individuals or firms are regulated and authorised by the SRA and verify an individual’s or firm’s practising details. Other verification methods, such as checking public records (e.g. telephone directories and company records) may be required in other circumstances.



















What are significant figures? | TechTip

What are significant figures/digits and what are they used for?

Significant figures are numbers that carry a contribution to a measurement and are useful as a rough method to round a final calculation. For more complex systems such as the uncertainty of a dosimetry system, or estimating the bioburden of a product, more accurate methods should be used, such as those found in NIST Technical Note 1297 (TN1297), “Guidelines for Evaluating and Expressing the Uncertainty of NIST Measurement Results”

What makes a number “significant” or not significant?

All numbers which are not leading or trailing zeros are considered significant unless the trailing zero comes after a decimal point (i. e. 3.00 would have 3 significant figures, while 300 would only have 1 significant figure). In the case of a measurement instrument, if the instrument is only calibrated to a certain decimal place, any digit after that calibration range is not considered significant. For example, if a weight scale is calibrated to the tenths place (0.0), but provides a reading to the hundredths place (0.00), only an estimate of the tenths place may be accurately reported using traditional rounding methods.

Example: A weight scale calibrated to the tenths place reads a weight of 11.35 lbs. The reading would be rounded to the tenths place and reported as 11.4 lbs.

What rules about significant figures should be followed when adding and subtracting numbers?

For addition and subtraction, the final result may only have the result reported to the same decimal place as the least precise measurement.

Example: The length of a building is 372.71 ft. measured using a tape measure calibrated to the hundredths place. The width of the same building is 174.2 ft measured using a ruler calibrated to the tenths place. What is the perimeter of the building?

The perimeter is:
P = 372.71 + 174.2 + 372.71 + 174.2
P = 1093.82 ft.

However, since the width of the building is only known to the tenths place, our result can only be reported to the tenths place. The final result is:
P = 1093.8 ft.

What rules about significant figures should be followed when multiplying and dividing numbers?

For multiplication and division, the final result may only have the same number of significant figures as the least precise measurement.

Example: If the mass of a box is measured to be 6.817 kg, and the volume is measured to be 18.39 cm3 what is the density of the box?

We calculate density (ρ) by dividing the mass of the box by the volume of the box. So:
p=
6.817kg /
18.39cm3
ρ = 0.370……kg/cm3

Since the volume only has significant digits to the hundredths place while mass has significant digits to the thousandths place, we report the final density to the hundredths place as:
ρ =0. 37kg/cm3

How are constants handled when performing calculations with significant figures?

Recall the formula for the circumference of a circle is:
C = 2πr
In this equation, the r represents a measurable quantity, the radius of the circle, and π is a constant. In the case of π, we know infinitely many digits beyond the decimal place, so the least accurate reading would be from our measurement of the radius. However, this is not the case for all constants.

In general, when performing calculations with constants, it is best to use one more digit than the least precise measurement. So if we calculate the circumference of a circle with a radius of 4.2 in., we would use 3.14 as a minimum estimate of π (the radius is significant to the tenths place, so for π, we go out one more digit to the hundredths place).

When calculating a value with multiple steps, when do we make the significant figures estimate?

Significant figures estimates should be made at the final step of the calculation. Going back to our density example, if our mass is now 5.312 kg, and we have a box measuring 2.54 cm x 2.54 cm x 2.54 cm, we would calculate the volume as:
V = (2.54cm) × ((2.54cm)) x (2.54cm)
V = 16.3871…cm3

And to calculate the density, we would use:
ρ = 0.3242…kg /cm3

And our final density is reported to the hundredths place based on the accuracy of the length, width, and height of the box:
ρ = 0.32kg / cm3

VITEK® 2 AST Cards – clinical diagnostics products

When a patient presents with an illness due to an infectious organism, knowing the best treatment options requires more than species identification, especially as many organisms are becoming resistant to antimicrobials. Antimicrobial Susceptibility Testing (AST) and resistance detection is also important to making the best patient-care decisions. Designed for VITEK®2 automated instruments, VITEK®2 AST cards offer rapid, accurate AST results.

Proven accuracy, rapid results

Ready-to-use, flexible VITEK® 2 AST cards are designed for use on the innovative, automated VITEK® 2 family of instruments. They provide AST results and resistance detection for clinically important Gram-positive cocci, Gram-negative bacilli and yeasts. The system is proven to be rapid, reliable and accurate. Bacterial AST results are available in as little as 4 hours and yeast AST results in as little as 13 hours. The VITEK® 2 Advanced Expert System further provides validation of every susceptibility test result with an accurate phenotype profile of the bacterial resistance mechanism(s) for each isolate tested, using color-coded indicators.

  • Inoculation with a simple, standardized saline suspension of organism
  • Closed disposable for optimal user safety
  • Minimal hazardous waste decreases disposal costs
  • Pre-applied barcodes for maximum traceability
  • High level of automation decreases hands on time

Expanding range

Recognizing the importance of good diagnostic tools for infectious organisms and the ever-growing needs in the field of microbiology, bioMérieux is dedicated to ensuring a high-quality, expansive offer. The VITEK® 2 AST card range offers a number of antimicrobials and resistance tests (ESBL, cefoxitin screen, high level aminoglycoside resistance, inducible clinidamycin resistance, etc.), as well as phenotype recognition with the Advanced Expert System.

VITEK® 2 AST cards are offered for a wide variety of organisms:

  • Enterobacteriaceae
  • Non-fermenters
  • Staphylococci
  • Enterococci
  • Streptococci (including S. pneumoniae, S. viridans and beta-hemolytic Streptococci)
  • Yeast

bioMérieux continuously invests in VITEK® 2 AST testing, for example:

  • Continuous CLSI and EUCAST updates
  • Development of new antimicrobials (Ceftaroline available in 2014)
  • Redevelopment of existing antimicrobials for better resistance detection (imipenem and meropenem for improved detection of carbapenem resistance)
  • Menu expansion (More antimicrobials available for testing of Streptococci sp. in 2014)
  • Addition of new phenotypes to AES database

VITEK

® 2 card size

10 cm x 6 cm x 0.5 cm, 16 grams

Please contact your local bioMérieux representative for a list of VITEK 2 AST cards available in your country.

 

Telman Ismailov left the AST group

The businessman left the owners of the AST group, which previously owned the Cherkizovsky market, Voentorg, the Prague restaurant and other assets, his sons and nephew got his share, Vedomosti newspaper reported on Monday.

The newspaper, referring to the data of the Unified State Register of Legal Entities, reported that currently Ismailov’s sons Alekper and Sarkhan each own 37.5% in the company AST Group – 89 – the parent company of the AST group. The billionaire’s nephew, Zaur Mardanov, owns the remaining 25% of the shares.Telman Ismailov himself, who at the end of 2013 owned 25% of the AST group, had no shares left. But he continues to be the president of the AST group.

The deal that deprived Telman Ismailov of his stake in the AST group is technical, a source close to the owners of the AST group told the newspaper. He did not name the reasons for such a deal.

Advertising on Forbes

AST Group is a diversified holding, which before the crisis included 31 companies engaged in various types of business: hotel, construction, security, restaurant, passenger transportation, jewelry production.The company’s annual turnover in the pre-crisis period reached $ 2 billion, the estimated value of assets was $ 3 billion.

The Cherkizovsky market in Moscow was considered the largest asset of AST. After the discovery of counterfeit goods worth $ 2 billion, the speech of Prime Minister Vladimir Putin with a question about the “landing” and the subsequent demolition of trade pavilions, Ismailov was forced to leave for Turkey in 2009. In this country, he opened the luxurious Mardan Palace Hotel, named after the businessman’s father. The implementation of an ambitious project worth over $ 1 billion abroad has displeased the Russian authorities.

According to unofficial information, the entrepreneur was able to achieve the right to return to his homeland after confirming his readiness to build a complex of two hotels with 5000 rooms in the Imeretinskaya lowland in Sochi for the 2014 Olympics. In January 2012, Telman Ismailov’s Sochi project went to the structures. The Voentorg business center was sold.

It is not known what assets are included in AST today, Vedomosti writes.

AST and Eksmo won a lawsuit against Telegram over books by King and Glukhovsky – RBK

The court satisfied the requirement for interim measures and ordered Roskomnadzor to block access to pirated copies of works

Photo: Denis Grishkin / AGN “Moscow”

Publishing houses AST and Eksmo, which are part of the Eksmo-AST group, filed a lawsuit against the Telegram messenger over pirated copies of books. Kommersant drew attention to this. Roskomnadzor is obliged to block access to books.

AST and Eksmo filed two lawsuits against Telegram on July 20, it follows from the Moscow City Court’s card index. AST complained about pirated copies of Stephen King’s 11/22/63 and Doctor Sleep, Napoleon Hill’s Think and Grow Rich, Dmitry Glukhovsky’s Metro 2033, posted on the Telegram mobile application and Telegram channels. The reason for the claim “Eksmo” was the placement in the messenger of copies of the books “Ni Sy” by Jen Sinsero and “Mara and Darkness” by Lee Arden.

In both cases, the court satisfied the requirement for interim measures and ordered Roskomnadzor to “stop creating technical conditions to ensure the placement, distribution and other use” of pirated content in Telegram.

As the newspaper notes, these are the first lawsuits against Telegram from Eksmo-AST. Previously, publishers used the messenger and Apple and Google directly to seek the removal of pirated content. However, the Association for the Protection of Copyright on the Internet (AZAPI, representing Eksmo-AST in court) is seeking the introduction of digital fingerprints technology, which would make it possible to systematically remove pirated content.Now AZAPI is trying to gain a “critical mass” of court decisions, which would allow blocking Telegram for repeated violations, said Maxim Ryabyko, a member of the board of the association.

Glucocorticoids / Consultant Plus

Glucocorticoids

HA block the synthesis of a wide range of “pro-inflammatory” mediators, an increase in the concentration of which within the “cytokine storm” is associated with a poor prognosis in COVID-19 and the risk of developing ARDS and sepsis.Glucocorticoids remain the key first-line drugs for the treatment of primary and secondary HPS. In studies of the effectiveness of GC in COVID-19, it was shown that mortality among patients receiving dexamethasone or methylprednisolone was lower than in patients who did not receive GC. The decision to start GC therapy is based on the severity of the systemic inflammatory response, the degree of dyspnea (with or without signs of ARDS), and changes in the X-ray picture of the lungs. The optimal doses of HA and the modes of their use for secondary COVID-19-associated HPS have not yet been developed and are at the research stage.

The indications for the appointment of GC are clinical and laboratory signs of Kawasaki-like syndrome and / or early laboratory signs of the development of macrophage activation syndrome (secondary HPS): an increase in the level of serum ferritin> 600 ng / ml or a combination of two of the following indicators: a decrease in the number of platelets blood 180 * 10 9 / l, leukocytes 3.0 * 10 9 / l, lymphopenia or a rapid decrease in the number of platelets and / or leukocytes (during the day) by more than two times against the background of persisting high inflammatory activity, an increase AST activity, serum triglycerides> 156 mg / dL; decrease in blood fibrinogen 360 mg / dl.

For the treatment of multisystem inflammatory syndrome, dexamethasone is used at a dose of 10 mg / m2 / day intravenously for 1 or 2 injections for 3 to 4 days. Dexamethasone is the drug of choice for the treatment of hemophagocytic syndrome. The rate of withdrawal of HA for intravenous administration depends on the patient’s condition.

It is possible to use methylprednisolone at a dose of 0.5-1 mg / kg for intravenous administration every 12 hours. A number of experts recommend using higher doses of methylprednisolone: ​​1 – 2 mg / kg / IV every 8 hours in children weighing 50 kg; 120 – 125 mg / intravenous injection every 8 hours – in children weighing> 50 kg for 3 – 4 days.

The benefits of different HA dosing regimens in COVID-19-associated multisystem inflammatory syndrome currently require study and justification.

In the future, the need for a maintenance dose of methylprednisolone at a dose of 8-12 mg / day and the duration of therapy depend on the clinical situation. HA should be administered in combination with anticoagulant therapy with low molecular weight heparins.

A decrease in the dose of intravenously administered HA begins with the relief of fever, a stable decrease in the serum CRP level.Methylprednisolone / dexamethasone is canceled evenly for each administration, the dose of the drug is reduced by 15-20% every 1 to 2 days for 3 to 4 days and by 50% every 1 to 2 days under the control of indicators of the activity of multisystem inflammation (fever, CRP, ferritin , ALT, AST, serum LDH, the number of leukocytes, blood platelets, ESR), until complete cancellation.

Complete abolition of HA is possible only with the normalization of indicators of the activity of inflammation. With an increase in the activity indicators of the secondary HPS, the decrease in the HA dose should be suspended until a decision is made on the correction of therapy.

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These functions allow you to create and manage table values.

Table Design

Function Description
ItemExpression.From Returns the AST for the body of the function.
ItemExpression.Item An AST node representing an item in an item expression.
RowExpression.Column Returns an AST representing the access to the column in a string expression.
RowExpression.From Returns the AST for the body of the function.
RowExpression.Row An AST node representing a string in a string expression.
Table.FromColumns Returns a table from a list containing nested lists with column names and values.
Table.FromList Converts a list to a table by applying the specified split function to each item in the list.
Table.FromRecords Returns a table from a list of records.
Table.FromRows Creates a table from a list, in which each list item is a list containing the column values ​​for one row.
Table.FromValue Returns a table with a column containing the specified value or a list of values.
Table.FuzzyGroup Based on a fuzzy match, groups the rows of a table with the row values ​​of the specified column.
Table.FuzzyJoin Joins rows from two tables that have a fuzzy match on the given keys.
Table.FuzzyNestedJoin Performs a fuzzy join between tables on the specified columns and prints the join result in a new column.
Table.Split Splits the specified table into a list of tables with the specified page size.
Table.View Creates or extends a table using user-defined query and action handlers.
Table.ViewFunction Creates a function that can be intercepted by the handler defined in the view (via Table.View ).

Conversions

Function Description
Table.ToColumns Returns a list of nested lists, each representing a column of values ​​in the input table.
Table.ToList Returns a table to a list by applying the specified join function to each row of values ​​in the table.
Table.ToRecords Returns a list of records from the input table.
Table.ToRows Returns a nested list of values ​​from the input table.

Details

Function Description
Table.ApproximateRowCount Returns the approximate number of rows in a table.
Table.ColumnCount Returns the number of columns in a table.
Table.IsEmpty Returns true if the table contains no rows.
Table.Profile Returns the column profile of the table.
Table.RowCount Returns the number of rows in a table.
Table.Schema Returns a table that contains a description of the columns (for example, a schema) for the specified table.
Tables.GetRelationships Returns relationships between a set of tables.

Line operations

Function Description
Table.AlternateRows Returns a table containing a row-interleaving pattern from a table.
Table.Combine Returns the resulting table from the concatenation of a list of tables. All tables must have the same structure of row types.
Table.FindText Returns a table containing only rows with the specified text in one or part of the cells.
Table.First Returns the first row of the table.
Table.FirstN Returns the first rows of the table, depending on the countOrCondition parameter.
Table.FirstValue Returns the first column of the first row of a table, or a specified default.
Table.FromPartitions Returns the table that is the result of joining a set of partitioned tables into new columns. If necessary, you can specify the type of the column. The default is any.
Table.InsertRows Returns a table with a list of rows inserted into the table by index. Each inserted row must match the type of table row.
Table.Last Returns the last row of the table.
Table.LastN Returns the last rows of the table, depending on the countOrCondition parameter.
Table.MatchesAllRows Returns true if all rows in the table match the condition.
Table.MatchesAnyRows Returns true if any rows in the table match the condition.
Table.Partition Partitions a table into a list of table groups based on the column value of each row and a hash function. The hash function is applied to the column value of the row to obtain the hash value for the row. The remainder of the hash values ​​division determines in which of the returned tables the row will be placed.
Table.PartitionValues ​​ Returns information about how the table is partitioned.
Table.Range Returns a specified number of rows from a table, starting at offset.
Table.RemoveFirstN Returns a table with the specified number of rows removed from the table, starting at the first row. The number of rows deleted depends on the optional countOrCondition parameter.
Table.RemoveLastN Returns a table with the specified number of rows removed from the table, starting with the last row.The number of rows deleted depends on the optional countOrCondition parameter.
Table.RemoveRows Returns a table with a specified number of rows removed from the table, starting at offset.
Table.RemoveRowsWithErrors Returns a table with all rows removed from the table that contain an error in at least one cell in the row.
Table.Repeat Returns a table containing table rows that repeat a specified number of times.
Table.ReplaceRows Returns a table in which the specified number of rows starting at offset are replaced with the provided rows.
Table.ReverseRows Returns a table with rows in reverse order.
Table.SelectRows Returns a table containing only those rows that match a condition.
Table.SelectRowsWithErrors Returns a table with only table rows that contain an error in at least one cell in the row.
Table.SingleRow Returns one row from a table.
Table.Skip Returns a table that does not contain the first row or rows of the table.
Table.SplitAt Returns a list containing the specified number of first lines and remaining lines.

Column operations

Function Description
Table.Column Returns the values ​​of a column in a table.
Table.ColumnNames Returns the name of the columns in the table.
Table.ColumnsOfType Returns a list with column names that match the specified types.
Table.DemoteHeaders Demotes the header row to the first row in the table.
Table.DuplicateColumn Duplicates the column with the specified name.The values ​​and type are copied from the original column.
Table.HasColumns Returns true if the table contains the specified column or columns.
Table.Pivot If there is a table and attribute column that contains pivotValues, creates new columns for each of the pivot values, and assigns the values ​​from valueColumn to them. You can provide the optional aggregationFunction to handle multiple occurrences of the same key value in an attribute column.
Table.PrefixColumns Returns a table where all columns are prefixed with a text value.
Table.PromoteHeaders Promotes the first row of the table to the header or column names.
Table.RemoveColumns Returns a table that does not have a specific column or columns.
Table.ReorderColumns Returns a table with specific columns in the specified order relative to each other.
Table.RenameColumns Returns a table with columns renamed as specified.
Table.SelectColumns Returns a table containing only specific columns.
Table.TransformColumnNames Converts column names using the provided function.
Table.Unpivot If a list of table columns exists, converts those columns to attribute-value pairs.
Table.UnpivotOtherColumns Converts all columns other than the specified set to attribute-value pairs, concatenated with the rest of the values ​​in each row.

Parameters

Parameter values ​​ Description
JoinKind.Inner Possible value for optional parameter JoinKind in Table.Join . The resulting inner join table contains one row for each pair of rows from the specified tables that were determined to match based on the specified key columns.
JoinKind.LeftOuter Possible value for optional parameter JoinKind in Table.Join . The left outer join ensures that all rows in the first table are displayed in the result.
JoinKind.RightOuter Possible value for optional parameter JoinKind in Table.Join . The right outer join ensures that all rows in the second table are displayed in the result.
JoinKind.FullOuter Possible value for optional parameter JoinKind in Table.Join . A full outer join ensures that all rows in both tables are displayed in the result. Rows that are not matched in another table are joined to a default row that contains NULL values ​​for all of its columns.
JoinKind.LeftAnti Possible value for optional parameter JoinKind in Table.Join .A left anti-join returns all rows in the first table that do not have a match in the second table.
JoinKind.RightAnti Possible value for optional parameter JoinKind in Table.Join . A right anti-join returns all rows in the second table that do not have a match in the first table.
MissingField.Error An optional parameter in records and table functions that specifies that missing fields should result in an error.(This is the default setting.)
MissingField.Ignore Optional parameter in records and table functions that specifies that missing fields should be ignored.
MissingField.UseNull Optional parameter in records and table functions that specifies that missing fields should be included with NULL values.
GroupKind.Global A global group is formed from all rows in the input table that have the same key value.
GroupKind.Local A local group is formed from a sequence of rows in the input table that have the same key value.
ExtraValues.List If the partition function returns more columns than the table expects, they will be collected into a list.
ExtraValues.Ignore If the partition function returns more columns than the table expects, they will be skipped.
ExtraValues.Error If the partition function returns more columns than the table expects, an error is thrown.
JoinAlgorithm.Dynamic Automatically selects a join algorithm by checking the initial rows and metadata of both tables.
JoinAlgorithm.PairwiseHash Buffers rows from the table on the left and the table on the right until one of the tables is fully buffered, and then executes the LeftHash or RightHash algorithm depending on which table was fully buffered.This algorithm is only recommended for small tables.
JoinAlgorithm.SortMerge Performs a stream merge assuming that both tables are sorted by join keys. This algorithm is efficient, but returns incorrect results if the tables are not sorted as expected.
JoinAlgorithm.LeftHash Places the rows from the table on the left into the lookup table, which is used as a buffer, and streams the rows from the table on the right.For each row from the table on the right, the buffered lookup table is searched for the corresponding row from the table on the left. It is recommended to use this algorithm when the table on the left is small and it is expected that most of the rows in the table on the right will have corresponding rows in the table on the left.
JoinAlgorithm.RightHash Places the rows from the table on the right into the lookup table, which is used as a buffer, and streams the rows from the table on the left. For each row from the table on the left, the buffered lookup table is searched for the corresponding row from the table on the right.It is recommended to use this algorithm when the table on the right is small and most of the rows on the left are expected to have corresponding rows in the table on the right.
JoinAlgorithm.LeftIndex Uses keys from the table on the left and dispatches predicate-based query packets to the table on the right. It is recommended to use this algorithm when the table on the right is large, supports collapsing Table.SelectRows, and contains few rows for which matches are expected in the table on the left.
JoinAlgorithm.RightIndex Uses keys from the table on the right and sends predicate-based query packets to the table on the left. It is recommended to use this algorithm when the table on the left is large, supports collapsing Table.SelectRows, and contains few rows for which matches are expected in the table on the right.
JoinSide.Left Indicates the left join table.
JoinSide.Right Indicates the right join table.

Conversion

Parameters for group parameters

  • GroupKind.Global = 0;

  • GroupKind.Local = 1;

Parameters for connection types

  • JoinKind.Inner = 0;

  • JoinKind.LeftOuter = 1;

  • JoinKind.RightOuter = 2;

  • JoinKind.FullOuter = 3;

  • JoinKind.LeftAnti = 4;

  • JoinKind.RightAnti = 5

Connection Algorithm

The following JoinAlgorithm values ​​can be specified for Table.Join

  •   JoinAlgorithm.Dynamic 0,
      
  •   JoinAlgorithm.PairwiseHash 1,
      
  •   JoinAlgorithm.SortMerge 2,
      
  •   JoinAlgorithm.LeftHash 3,
      
  •   JoinAlgorithm.RightHash 4,
      
  •   JoinAlgorithm.LeftIndex 5,
      
  •   JoinAlgorithm.RightIndex 6,
      
Parameter values ​​ Description
JoinSide.Left Indicates the left join table.
JoinSide.Right Indicates the right join table.

Sample Data

The following tables are used in the examples in this section.

Customers Table

  Customers = Table.FromRecords ({
  
  [CustomerID = 1, Name = "Bob", Phone = "123-4567"],
  
  [CustomerID = 2, Name = "Jim", Phone = "987-6543"],
  
  [CustomerID = 3, Name = "Paul", Phone = "543-7890"],
  
  [CustomerID = 4, Name = "Ringo", Phone = "232-1550"]
  
}
  

Table Orders

  Orders = Table.FromRecords ({
  
  [OrderID = 1, CustomerID = 1, Item = "Fishing rod", Price = 100.0],
  
  [OrderID = 2, CustomerID = 1, Item = "1 lb. worms", Price = 5.0],
  
  [OrderID = 3, CustomerID = 2, Item = "Fishing net", Price = 25.0],
  
  [OrderID = 4, CustomerID = 3, Item = "Fish tazer", Price = 200.0],
  
  [OrderID = 5, CustomerID = 3, Item = "Bandaids", Price = 2.0],
  
  [OrderID = 6, CustomerID = 1, Item = "Tackle box", Price = 20.0],
  
  [OrderID = 7, CustomerID = 5, Item = "Bait", Price = 3.25],
  
  [OrderID = 8, CustomerID = 5, Item = "Fishing Rod", Price = 100.0],
  
  [OrderID = 9, CustomerID = 6, Item = "Bait", Price = 3.25]
  
})
  
Function Description
Table.AddColumn Adds a column named newColumnName to the table.
Table.AddFuzzyClusterColumn Adds a new column with representative values ​​obtained by fuzzy grouping the values ​​of the specified column in the table.
Table.AddIndexColumn Returns a table with a new column with the specified name, which, for each row, contains the row index in the table.
Table.AddJoinColumn Performs a nested join between table1 and table2 from specific columns and creates the join result as column newColumnName for each row in table1.
Table.AddKey Adding a key to a table.
Table.AggregateTableColumn Combines tables nested in a specific column into multiple columns containing the concatenated values ​​for those tables.
Table.CombineColumns Table.CombineColumns combines columns using the join function to create a new column. Table.CombineColumns is the opposite of Table.SplitColumns.
Table.CombineColumnsToRecord Concatenates the specified columns into a new column of value records, in which each record contains field names and values ​​that correspond to the names and values ​​of the columns being merged.
Table.ConformToPageReader This function is for internal use only.
Table.ExpandListColumn After retrieving the original column of lists in the table, creates a copy of the row for each value in the list.
Table.ExpandRecordColumn Expands a column of records into columns with each value.
Table.ExpandTableColumn Expands a column of records or a column of tables into multiple columns in the containing table.
Table.FillDown Replaces NULL values ​​in the specified column or table columns with the most recent non-NULL values ​​in the column.
Table.FillUp Returns a table from the specified table, where the next cell value extends to the null cells above in the specified column.
Table.FilterWithDataTable This function is for internal use only.
Table.Group Groups table rows by key column values ​​for each row.
Table.Join Concatenates the rows of table1 with the rows of table2 based on the equality of the values ​​of the key columns selected in table1, key1 and table2, key2.
Table.Keys Returns a list of key column names from a table.
Table.NestedJoin Joins table rows based on key equality.The results are entered in a new column.
Table.ReplaceErrorValues ​​ Replaces the error values ​​in the specified columns with the corresponding specified values.
Table.ReplaceKeys Returns a new table with the new key information specified in the keys argument.
Table.ReplaceRelationshipIdentity
Table.ReplaceValue Replaces oldValue with newValue in specific table columns using the provided replacement function, such as text.Replace or Value.Replace.
Table.SplitColumn Returns a new set of columns from one column, applying a split function to each value.
Table.TransformColumns Converts columns from a table using a function.
Table.TransformColumnTypes Converts column types from a table using a type.
Table.TransformRows Converts rows from a table using a conversion function.
Table.Transpose Returns a table with columns converted to rows and rows converted to columns from the input table.

Membership

Parameters for membership checks

Entry specification

  •   Occurrence.First = 0
      
  •   Occurrence.Last = 1
      
  •   Occurrence.All = 2
      
Component Description
Table.Contains Determines whether the record appears as a row in the table.
Table.ContainsAll Determines whether all specified records appear as rows in the table.
Table.ContainsAny Determines whether any of the specified records appear as rows in the table.
Table.Distinct Removes duplicate rows from the table, ensuring that all remaining rows are unique.
Table.IsDistinct Determines if the table contains only unique rows.
Table.PositionOf Defines the position or positions of the row in the table.
Table.PositionOfAny Defines the position or positions of any of the specified rows in the table.
Table.RemoveMatchingRows Removes all occurrences of rows from the table.
Table.ReplaceMatchingRows Replaces specific rows from the table with new rows.

Ordering

Sample data

The following tables are used in the examples in this section.

Employees table

  Employees = Table.FromRecords (
  
    {[Name = "Bill", Level = 7, Salary = 100000],
  
     [Name = "Barb", Level = 8, Salary = 150000],
  
     [Name = "Andrew", Level = 6, Salary = 85000],
  
     [Name = "Nikki", Level = 5, Salary = 75000],
  
     [Name = "Margo", Level = 3, Salary = 45000],
  
     [Name = "Jeff", Level = 10, Salary = 200000]},
  
type table [
  
    Name = text,
  
    Level = number,
  
    Salary = number
  
])
  
Component Description
Table.Max Returns the largest row or rows from a table using a comparisonCriteria.
Table.MaxN Returns the number of N longest rows from the table. After sorting the rows, you must specify the countOrCondition parameter to further filter the results.
Table.Min Returns the smallest row or rows from a table using a comparisonCriteria.
Table.MinN Returns the number, N, of the smallest rows in the specified table.After sorting the rows, you must specify the countOrCondition parameter to further filter the results.
Table.Sort Sorts the rows in a table using a comparisonCriteria or default order if not specified.

Other

Component Description
Table.Buffer Places a table in a memory buffer, isolating it from external changes during evaluation.

Parameter values ​​

Output Column Naming

This parameter is a list of text values ​​that indicate the names of the columns in the resulting table. This parameter is commonly used in table building functions such as Table.FromRows and Table.FromList.

Comparison criteria

The comparison criterion can be supplied as one of the following values:

  • Numeric value to indicate the sort order.See the section on sort order in the section on parameter values.

  • You can use a function with one argument to calculate the key used for sorting.

  • To select a key and order, the comparison criterion can be a list containing the key and order.

  • To completely control the comparison, you can use a two-argument function that returns -1, 0, or 1 given the relationship between the left and right inputs.Value.Compare is a method that you can use to delegate this logic.

See Table.Sort for examples.

Quantity criterion or condition

This criterion is commonly used for ordering or string operations. It determines the number of rows returned in the table and can take two forms – a number or a condition:

  • The number indicates how many values ​​to return and the corresponding function.

  • If a condition is specified, a string is returned containing the values ​​that initially match the condition. If the value does not match the condition, further values ​​are ignored.

See Table.FirstN or Table.MaxN.

Processing additional values ​​

Used to indicate how the function should handle additional values ​​in a string. This parameter is specified as a number that maps to the parameters below.

  ExtraValues.List = 0
  
ExtraValues.Error = 1
  
ExtraValues.Ignore = 2
  

For more information, see Table.FromList.

Handle Missing Columns

Used to indicate how the function should work with missing columns. This parameter is specified as a number that maps to the parameters below.

  MissingField.Error = 0;
  
MissingField.Ignore = 1;
  
MissingField.UseNull = 2;
  

Used in transformations or column operations. See Table.TransformColumns for examples.