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* Elevated RBC parameters may skew A1c measurements, making it essential to consider these factors when interpreting results, especially in individuals with conditions such as polycythemia, androgen replacement, dehydration, or other disorders affecting RBC parameters.
Author block
Jose Gomez-Garcia, UMass Chan Medical School, UMass Memorial Medical Center, Framingham, Massachusetts; Caixia Bi, Quest Diagnostics, Madison, New Jersey; L.V. Rao, Quest Diagnostics/Umass Chan Medical School, Worcester, Massachusetts.
Abstract body
Background
Hemoglobin (A1c) is a key marker for long-term glycemic control and reflects the average blood glucose levels over the preceding 3-4 months. High levels of red blood cell (RBC) parameters—such as RBC count, hemoglobin (Hgb), hematocrit (HCT), red cell distribution width (RDW), mean corpuscular volume (MCV), and mean corpuscular hemoglobin concentration (MCHC)—can affect the rate of glycation's, RBC's lifespan, and the proportion of glycated hemoglobin, potentially leading to discrepancies between the A1C value and the actual average glucose concentration. Understanding how these RBC parameters influence A1c is crucial for accurate diabetes diagnosis and management, particularly in individuals with conditions that cause erythrocytosis. This study investigated whether A1C results are associated with RBC parameters in patients with type 2 diabetes.
Methods
A retrospective data analysis using the Quest Diagnostics database identified all patients with type 2 diabetes who received A1C and RBC parameters testing from the years 2022 to 2024. A1c test results were evaluated in patients diagnosed with type II diabetes along with their corresponding RBC parameters. The nonlinear correlation test (nlcor in R) was employed to assess statistically significant correlation between A1c and each of the RBC parameters.
Results
Over one million A1C results with corresponding RBC parameters were identified during the study period. The A1c values demonstrated a strong correlation with other markers except for RDW (Figure). Higher levels of Hgb, HCT, and RBC counts were associated with increased A1c levels, whereas higher MCV and MCHC levels were associated with decreased A1c levels. There are no differences between correlation patterns between males and females and the data was combined. The P-values are calculated based on the non-linear correlation test between A1c and each of the RBC parameters and are significant at <0.001.
Conclusion
Elevated RBC parameters may skew A1c measurements, making it essential to consider these factors when interpreting results, especially in individuals with conditions such as polycythemia, androgen replacement, dehydration, or other disorders affecting RBC parameters. This study provides valuable insights for clinicians seeking to accurately interpret A1c results and could lead to improved diabetes management and better patient care for those affected by conditions influencing erythrocytosis.
Author block
Jose Gomez-Garcia, UMass Chan Medical School, UMass Memorial Medical Center, Framingham, Massachusetts; Caixia Bi, Quest Diagnostics, Madison, New Jersey; L.V. Rao, Quest Diagnostics/Umass Chan Medical School, Worcester, Massachusetts.
Abstract body
Background
Hemoglobin (A1c) is a key marker for long-term glycemic control and reflects the average blood glucose levels over the preceding 3-4 months. High levels of red blood cell (RBC) parameters—such as RBC count, hemoglobin (Hgb), hematocrit (HCT), red cell distribution width (RDW), mean corpuscular volume (MCV), and mean corpuscular hemoglobin concentration (MCHC)—can affect the rate of glycation's, RBC's lifespan, and the proportion of glycated hemoglobin, potentially leading to discrepancies between the A1C value and the actual average glucose concentration. Understanding how these RBC parameters influence A1c is crucial for accurate diabetes diagnosis and management, particularly in individuals with conditions that cause erythrocytosis. This study investigated whether A1C results are associated with RBC parameters in patients with type 2 diabetes.
Methods
A retrospective data analysis using the Quest Diagnostics database identified all patients with type 2 diabetes who received A1C and RBC parameters testing from the years 2022 to 2024. A1c test results were evaluated in patients diagnosed with type II diabetes along with their corresponding RBC parameters. The nonlinear correlation test (nlcor in R) was employed to assess statistically significant correlation between A1c and each of the RBC parameters.
Results
Over one million A1C results with corresponding RBC parameters were identified during the study period. The A1c values demonstrated a strong correlation with other markers except for RDW (Figure). Higher levels of Hgb, HCT, and RBC counts were associated with increased A1c levels, whereas higher MCV and MCHC levels were associated with decreased A1c levels. There are no differences between correlation patterns between males and females and the data was combined. The P-values are calculated based on the non-linear correlation test between A1c and each of the RBC parameters and are significant at <0.001.
Conclusion
Elevated RBC parameters may skew A1c measurements, making it essential to consider these factors when interpreting results, especially in individuals with conditions such as polycythemia, androgen replacement, dehydration, or other disorders affecting RBC parameters. This study provides valuable insights for clinicians seeking to accurately interpret A1c results and could lead to improved diabetes management and better patient care for those affected by conditions influencing erythrocytosis.
