Important factors that affect A1C results include anemia, recent blood loss, blood transfusions, changes in red-blood-cell lifespan, hemoglobin variants, pregnancy, kidney disease and differences between laboratory A1C and continuous glucose monitoring data. If your A1C does not match your glucose meter or CGM readings, do not assume that either result is automatically wrong. The difference should be reviewed with a qualified healthcare professional before medication, diet or insulin decisions are changed. Important: This page provides general educational information. It cannot determine whether your personal A1C result is accurate. Do not change diabetes medication, insulin or treatment goals based only on an online calculator or article.

Quick Answer: What Can Make an A1C Result Inaccurate?

A1C depends on both glucose exposure and the behavior of red blood cells. Anything that changes the amount of hemoglobin, the lifespan of red blood cells or the laboratory’s ability to measure glycated hemoglobin may alter the result. Conditions that shorten red-blood-cell survival generally leave less time for glucose to attach to hemoglobin and can produce a falsely low A1C. Conditions that cause red blood cells to remain in circulation longer may allow more glycation and can sometimes produce a falsely high result. However, the direction is not always predictable. Blood transfusions, kidney disease and hemoglobin variants can affect A1C differently depending on the person, treatment and testing method. The National Glycohemoglobin Standardization Program, or NGSP, advises that both biological factors and method-specific laboratory interference should be considered.

Summary Table: Factors That Affect A1C Results

Factor	Possible effect on A1C	Why it may happen	Practical next step
Iron-deficiency anemia	Often falsely high	Altered red-cell biology and increased glycation	Ask whether iron studies or another glucose measure are needed
Hemolytic anemia	Often falsely low	Red blood cells are destroyed sooner	Compare with glucose or CGM data
Recent major blood loss	Often falsely low	Younger red cells replace lost cells	Tell the clinician when the blood loss occurred
Blood transfusion	Unpredictable	Donor red cells have a different age and glucose exposure	Do not interpret A1C without discussing the transfusion
Erythropoietin treatment	May be falsely low	Production of young red cells increases	Consider direct glucose monitoring
Hemoglobin variant	Falsely high, low or unreportable	Some laboratory methods are affected	Identify the variant and assay method
Pregnancy	May be lower or less representative	Red-cell turnover and glucose patterns change	Use pregnancy-specific monitoring advised by the care team
Advanced kidney disease	May be falsely low or otherwise unreliable	Anemia, dialysis, erythropoietin and assay factors	Review A1C with glucose, CGM or another marker
CGM and A1C mismatch	Either direction	Different time periods and biological measurements	Compare complete dates, CGM wear and red-cell factors
Laboratory variation	Small increase or decrease	Equipment, sample handling and normal test variation	Repeat or confirm unexpected results

The table describes common patterns, not rules for every person. A healthcare professional should interpret the result using medical history, laboratory reports, medications and glucose-monitoring information.

How Does an A1C Test Work?

Hemoglobin is a protein inside red blood cells that carries oxygen. Glucose circulating in the blood gradually attaches to hemoglobin. The A1C test measures the percentage of hemoglobin that has become glycated. Because red blood cells circulate for several months, A1C provides a longer-term view of glucose exposure than a single fasting or after-meal glucose measurement. However, it is a weighted average rather than a simple three-month average. Glucose levels during the most recent month usually have more influence on the result than levels from earlier months. A1C does not show:

• Whether glucose frequently dropped dangerously low
• Whether glucose spiked after meals
• How much glucose changed from one day to another
• The exact glucose level at the time blood was collected
• Whether a high average came from consistently high readings or a mixture of highs and lows

This is one reason A1C, glucose-meter readings and CGM reports may need to be interpreted together.

1. Anemia Can Raise or Lower A1C

Anemia is one of the most frequently misunderstood factors that affect A1C results. It is incorrect to say that all anemia produces a high A1C or that all anemia produces a low A1C. The effect depends on the type of anemia and how it changes red-blood-cell production or survival.

Iron-deficiency anemia may cause a falsely high A1C

Significant iron deficiency has been associated with higher A1C values that may not fully reflect the person’s true glucose exposure. The NGSP notes that iron-replacement treatment can lower A1C in people with and without diabetes when iron deficiency is corrected. It recommends relying on alternative glucose assessment when significant iron-deficiency anemia is present until it has been treated. A person could therefore have:

• An A1C that suggests prediabetes
• Fasting glucose readings that are repeatedly within their expected range
• Low hemoglobin, ferritin or iron levels
• A lower A1C after iron deficiency is treated

This does not mean that every elevated A1C is caused by anemia. It means iron deficiency should be considered when A1C and direct glucose measurements do not agree.

Hemolytic anemia may cause a falsely low A1C

Hemolytic anemia causes red blood cells to be destroyed sooner than expected. The cells have less time to be exposed to glucose, so less glycated hemoglobin may be measured. Conditions that shorten red-cell survival can cause a falsely low A1C regardless of which assay method the laboratory uses.

Practical tip

Do not look only at the word “anemia” on a medical record. Ask which type of anemia is present. Useful questions may include:

• Is this iron-deficiency anemia?
• Is there evidence of hemolysis?
• Are red blood cells being lost, destroyed or produced differently?
• Has treatment recently started?
• Should A1C be compared with glucose-meter or CGM data?

2. Recent Blood Loss Can Falsely Lower A1C

Recent significant blood loss is another important factor that can affect A1C results. After blood is lost, the body increases production of replacement red blood cells. These newer cells have had less time to circulate and less time for glucose to attach to their hemoglobin. As a result, an A1C collected during recovery from major blood loss may be lower than expected. The NGSP specifically identifies recovery from acute blood loss as a condition that can falsely lower A1C. NIDDK also lists recent blood loss among changes in red blood cells that can alter A1C levels. Relevant events may include:

• Major surgery
• Gastrointestinal bleeding
• Heavy menstrual bleeding
• Injury involving substantial blood loss
• Frequent therapeutic blood removal
• Recent blood donation, depending on the amount and timing

Example

A person’s glucose meter shows readings that are regularly above their target range, but their A1C has unexpectedly fallen. They had major surgery with blood loss several weeks earlier. The lower A1C may not represent a true improvement in glucose management. The clinician may review current glucose readings and repeat the A1C after red-blood-cell production has stabilized.

What to tell your healthcare professional

Share:

• The approximate date of the blood loss
• The cause
• Whether a transfusion was required
• Whether anemia was diagnosed
• Whether iron, vitamin or erythropoietin treatment was started

3. Blood Transfusions Can Make A1C Difficult to Interpret

A recent blood transfusion can make an A1C result unreliable or difficult to interpret. This is because the blood sample contains a mixture of the recipient’s red blood cells and donor red blood cells. The donor cells may have:

• A different average age
• A different previous glucose exposure
• Different hemoglobin characteristics
• Been stored before transfusion

Because of these variables, a transfusion does not always move A1C in one predictable direction. The result may appear lower or higher depending on the circumstances. NIDDK, the CDC and current diabetes-care guidance identify blood transfusion as a situation in which A1C may be inaccurate.

Practical answer

An A1C taken soon after a transfusion should not be interpreted as though every measured red blood cell reflects the recipient’s previous three months of glucose exposure. Ask the treating clinician:

• Is this A1C usable after my transfusion?
• Should we rely temporarily on finger-stick or CGM data?
• When should A1C be repeated?
• Would another laboratory marker be appropriate?

The best timing for repeat testing depends on the reason for the transfusion, ongoing anemia, red-cell production and the person’s overall health.

4. Changes in Red-Blood-Cell Lifespan Affect A1C

Red-blood-cell lifespan is central to understanding factors that affect A1C results.

Shorter red-cell lifespan usually lowers A1C

When red blood cells leave circulation earlier than expected, they have less time to accumulate glycated hemoglobin. Possible causes include:

• Hemolytic anemia
• Recovery after major blood loss
• Some hemoglobin disorders
• Certain complications of kidney disease
• Erythropoietin treatment
• Hemodialysis
• Increased red-cell production

NIDDK lists blood loss, sickle cell disease, erythropoietin treatment, hemodialysis and transfusion as conditions that can change A1C by altering red blood cells or hemoglobin.

Longer red-cell exposure may raise A1C

When older red blood cells remain in circulation longer, they have additional time to be exposed to glucose. This can make A1C appear higher than expected in some circumstances. However, a person should not attempt to identify the cause from A1C alone. A complete blood count, iron studies, medical history and other tests may be needed.

A useful rule

• Younger average red-cell population: A1C may look lower.
• Older average red-cell population: A1C may look higher.
• Mixed or complex red-cell changes: The direction may be unpredictable.

This rule is useful for understanding the test, but it is not a diagnostic tool.

5. Hemoglobin Variants Can Interfere With Some A1C Tests

Hemoglobin variants are inherited forms of hemoglobin. Common variants that may affect A1C testing include hemoglobin S, C, D and E, as well as elevated fetal hemoglobin. A hemoglobin variant can influence A1C in two different ways:

1. It may alter the survival or behavior of red blood cells.
2. It may interfere with the specific laboratory method used to measure A1C.

The result can be falsely high, falsely low or occasionally not measurable by a particular method. NGSP maintains a regularly updated table showing which common testing methods are affected by specific variants.

Who may have a hemoglobin variant?

Hemoglobin variants can occur in anyone, but some are more common among people whose families come from parts of:

• Africa
• The Mediterranean
• South Asia
• Southeast Asia
• The Middle East
• The Caribbean
• Central or South America

Ancestry alone does not prove that someone has a variant. A blood test is needed to identify it.

Signs that a hemoglobin variant may be affecting A1C

A clinician may consider a variant when:

• A1C is very different from meter or CGM readings
• A1C changes sharply without a clear reason
• Different laboratories report inconsistent results
• The laboratory cannot report an A1C value
• There is a personal or family history of a hemoglobin disorder
• A1C does not match fasting glucose or an oral glucose-tolerance test

NIDDK recommends considering hemoglobin variants when A1C does not match other diabetes tests or when there is a relevant family background or blood-disorder history.

Practical tip

Ask the laboratory or healthcare professional:

• Which A1C assay method was used?
• Is that method affected by my specific hemoglobin variant?
• Can the sample be tested using another NGSP-certified method?
• Should glucose monitoring or another marker be used instead?

Having a hemoglobin variant does not automatically make every A1C test inaccurate. Some testing methods are not significantly affected by particular variants.

6. Pregnancy Changes How A1C Should Be Interpreted

Pregnancy is another of the major factors that affect A1C results. Normal physiological changes during pregnancy increase red-blood-cell turnover, which can cause A1C to fall. A1C may also fail to capture important after-meal glucose elevations. Additional interpretation problems include:

• Early-pregnancy A1C may partly reflect glucose exposure before pregnancy.
• Iron deficiency may develop or worsen later in pregnancy.
• Glucose targets during pregnancy differ from usual nonpregnancy targets.
• Post-meal glucose elevations can be clinically important even when A1C appears acceptable.
• A1C is not the standard test used to diagnose gestational diabetes.

NIDDK states that A1C may be used early in pregnancy to look for previously unrecognized diabetes in people with risk factors. Gestational diabetes is usually assessed using a glucose challenge or oral glucose-tolerance test between 24 and 28 weeks.

Practical answer

A pregnant person should not use a general online A1C calculator to diagnose gestational diabetes or set treatment goals. Pregnancy-related monitoring may involve:

• Fasting glucose
• After-meal glucose
• CGM data
• Glucose challenge testing
• Oral glucose-tolerance testing
• A1C interpreted within the full pregnancy context

The obstetric and diabetes-care teams should determine which measurements are appropriate.

7. Kidney Disease Can Make A1C Less Reliable

Kidney disease can affect A1C through several overlapping mechanisms. The problem is more common in advanced kidney failure, particularly when anemia, dialysis, erythropoietin treatment or altered red-cell survival is present. The NGSP notes that interpreting A1C in chronic renal failure is complex. Renal anemia, erythropoietin use and dialysis may affect the relationship between A1C and actual glucose exposure. Reports have suggested that A1C can underestimate glycemia in some people receiving dialysis. Possible factors include:

• Anemia related to kidney disease
• Shortened red-cell lifespan
• Blood loss during dialysis or medical procedures
• Erythropoietin-stimulating medication
• Iron treatment
• Recent transfusions
• Assay interference from chemically modified hemoglobin
• Rapid changes in glucose management

The CDC also lists kidney failure as a condition that can falsely increase or decrease A1C accuracy.

What should be compared?

A healthcare professional may review:

• A1C trend
• CGM average glucose
• Time in range
• Finger-stick glucose records
• Hemoglobin level
• Iron status
• Dialysis status
• Erythropoietin treatment
• Recent transfusions
• Other glycemic markers, when appropriate

No single alternative measurement is automatically best for every person with kidney disease. The choice depends on the stage of kidney disease, treatment and other medical conditions.

8. Why A1C and CGM Readings May Not Match

A1C and CGM do not measure the same thing. A1C measures glucose attached to hemoglobin in circulating red blood cells. A CGM estimates glucose in interstitial fluid at frequent intervals. A CGM report may calculate a Glucose Management Indicator, or GMI, from the recorded average sensor glucose. A1C and GMI can therefore differ even when both measurements are functioning as expected. Current diabetes-care guidance notes that comparability depends on:

• The number of days the CGM was worn
• Whether sufficient CGM data were captured
• The dates of CGM use compared with the A1C collection date
• CGM calibration and accuracy
• Glucose-meter accuracy
• The delay between blood glucose and interstitial glucose
• Health, activity and hydration-related factors
• Conditions affecting A1C or red-blood-cell turnover

Common reasons for an A1C–CGM mismatch

The time periods are different

An A1C reflects several months, with recent glucose having greater influence. A 14-day CGM report reflects only those 14 days. If glucose improved recently, CGM may look better before A1C fully reflects that improvement. If glucose recently worsened, a short CGM period may look worse than the longer A1C average.

The CGM period was not representative

A person may have worn the sensor during:

• An illness
• Travel
• A medication change
• A period of unusual eating
• A particularly active or inactive period

That short period may not represent the previous three months.

A biological factor is affecting A1C

Anemia, blood loss, transfusion, pregnancy, kidney disease or a hemoglobin variant may alter A1C without causing the same change in CGM average glucose.

Sensor data are incomplete

Frequent gaps, compression lows, sensor problems or insufficient wear can affect the calculated average.

What difference is considered important?

There is no single online cutoff that can determine whether a mismatch is harmless or medically significant for every person. A persistent difference deserves review when it could change:

• Medication decisions
• Insulin dosing
• Hypoglycemia risk assessment
• Whether a person is considered at goal
• Diagnosis or classification
• Pregnancy management

Do not change treatment merely to make A1C and GMI produce the same number.

9. Laboratory and Testing Variation

Even when no medical condition interferes, A1C is not infinitely precise. Small differences may occur because of:

• Testing equipment
• Calibration
• Sample handling
• Temperature
• Method-specific performance
• Normal analytical variation
• Differences between point-of-care and laboratory testing

NIDDK explains that repeated measurement of the same blood sample may produce slightly different A1C values. It gives the example that a result reported as 6.8% could fall within a range of approximately 6.4% to 7.2% when repeated, although modern quality-control standards have improved precision. That example does not mean every result varies by 0.4 percentage points. It shows why a small difference should be interpreted as part of a trend rather than automatically treated as a major change.

Laboratory test versus point-of-care test

For diagnosing diabetes or prediabetes, NIDDK advises using a venous blood sample analyzed by a laboratory with an NGSP-certified method. Point-of-care A1C tests performed in a clinic should not be used by themselves for diagnosis.

Practical testing tips

• Use the same laboratory when monitoring trends, when possible.
• Check whether the laboratory method is NGSP-certified.
• Tell the clinician about hemoglobin variants or recent transfusions.
• Repeat an unexpected result before making major conclusions.
• Compare A1C with direct glucose information.
• Do not compare a home A1C kit with a laboratory result as though the methods are identical.

Other Overlooked Factors That May Affect A1C Accuracy

Although anemia, transfusion and kidney disease receive the most attention, other conditions may also affect interpretation.

Liver disease

The CDC and NIDDK list liver disease among conditions associated with false A1C results. The effect may relate to anemia, bleeding, altered red-cell survival or other complications rather than one simple mechanism.

Certain medications

The CDC notes that certain medicines, including opioids and some HIV medications, may affect A1C accuracy. Medication effects can vary, so people should not stop a prescribed medicine because of an A1C result. Instead, provide the complete medication list to the healthcare professional interpreting the test.

Rapid recent glucose changes

A1C may remain elevated after glucose has recently improved, or remain lower after glucose has recently worsened. This is not necessarily laboratory interference. It can occur because A1C combines glucose exposure from different parts of the previous several months.

A1C calculators

An A1C calculator converts A1C to an estimated average glucose or estimates A1C from average glucose using a population-based equation. It cannot detect anemia, blood loss, kidney disease, pregnancy or a hemoglobin variant. A calculator result should therefore be labeled as an estimate, not a diagnosis or guaranteed personal average.

What to Do When A1C Does Not Match Your Glucose Readings

Step 1: Confirm the dates

Write down:

• Date of the A1C test
• Dates covered by the CGM report
• Number of valid CGM days
• Any periods without sensor data
• Dates of major illness, surgery or medication changes

A recent 10- or 14-day improvement may not yet align with a three-month A1C result.

Step 2: Review recent medical events

Tell the clinician about:

• Bleeding
• Blood donation
• Surgery
• Transfusion
• Pregnancy
• Dialysis
• Iron treatment
• Erythropoietin treatment
• New medication
• Known blood disorder

Step 3: Check blood counts and related tests

Depending on the situation, a clinician may review a complete blood count, iron studies, kidney function, evidence of hemolysis or testing for hemoglobin variants. These tests should be ordered and interpreted by a qualified healthcare professional.

Step 4: Review the A1C assay

Ask which method the laboratory used, especially when a hemoglobin variant is known or suspected. NGSP provides method-specific interference information for common variants.

Step 5: Compare more than one glucose measure

Useful information may include:

• Fasting laboratory glucose
• Glucose-meter records
• CGM average
• Time in range
• Time below range
• Time above range
• Glucose variability
• Meal-related patterns

Step 6: Repeat or use another test when advised

A clinician may repeat A1C or use another measurement when the first result is unexpected. Do not select an alternative test without considering conditions that may also affect that marker.

Practical Examples

Example 1: High A1C with normal CGM average

A person has an A1C of 7.2%, but their recent CGM data suggest a lower average glucose. Laboratory testing also shows significant iron-deficiency anemia. Iron deficiency may be contributing to a falsely high A1C. The care team may place more emphasis on direct glucose data while the iron deficiency is evaluated and treated.

Example 2: Low A1C after surgery

A person’s A1C falls unexpectedly after surgery involving major blood loss. Their glucose readings have not improved. Recovery from acute blood loss can create a younger red-cell population and produce a falsely low A1C.

Example 3: A1C differs from GMI

A person’s laboratory A1C is 7.8%, while a 14-day CGM report shows a lower GMI. The CGM period began after a medication change that improved glucose. The results may differ because they represent different time periods. More CGM data and a later A1C may provide a clearer comparison.

Example 4: Unexpected result after transfusion

A person receives a blood transfusion and has an A1C test soon afterward. The result includes information from both the person’s and donor’s red blood cells. Direct glucose monitoring may be more useful temporarily until the clinician decides that A1C can again be interpreted reliably.

Questions to Ask Your Healthcare Professional

Take these questions to your appointment:

1. Does my A1C match my glucose-meter or CGM records?
2. Could anemia be affecting my result?
3. Does my type of anemia usually raise or lower A1C?
4. Could recent bleeding or transfusion make the result unreliable?
5. Is my kidney disease or dialysis treatment affecting A1C?
6. Could I have a hemoglobin variant?
7. Which A1C assay method did the laboratory use?
8. Should my A1C be repeated?
9. Should we use another glucose measurement temporarily?
10. Should I avoid changing treatment until the discrepancy is reviewed?

Final Takeaway

A1C is a valuable tool, but it is an indirect measurement influenced by glucose exposure, hemoglobin and red-blood-cell lifespan. The most important factors that affect A1C results include:

• Different types of anemia
• Recent blood loss
• Blood transfusions
• Shortened or prolonged red-cell survival
• Hemoglobin variants
• Pregnancy
• Kidney disease
• Erythropoietin and dialysis
• Differences between A1C and CGM time periods
• Laboratory and assay variation

An unexpected A1C should be investigated rather than ignored or treated in isolation. The safest approach is to compare the result with direct glucose information, review recent medical events and determine whether a condition affecting red blood cells or the testing method may be present.

Medical Review Information

Written by: [Full name and relevant qualification] Medically reviewed by: [Licensed clinician’s full name, degree and specialty] Original publication date: [Month Day, Year] Last medically reviewed: [Month Day, Year] Next scheduled review: [Month Year] Editorial note: This page should be reviewed whenever major diabetes-testing guidance or NGSP assay-interference information changes.

Medical Disclaimer

This content is intended for general education and does not replace diagnosis, testing or treatment from a licensed healthcare professional. A1C calculators provide estimates and cannot identify anemia, pregnancy-related changes, kidney disease, hemoglobin variants or laboratory interference. Seek professional medical advice before changing medication, insulin, diet or glucose targets.