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Variables extracted from database.

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NIAID Data Ecosystem2026-05-10 收录
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https://figshare.com/articles/dataset/Variables_extracted_from_database_/30274414
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Background HbA1c is a marker for diabetes mellitus that reflects average glucose concentrations over the previous eight to twelve weeks. It is used to aid in the diagnosis and management of diabetes. Variation in within-individual measured HbA1c may affect its clinical utility but estimates of this are based on limited data that is often not generalisable to real-world settings. Methods A retrospective cohort study was performed using data on HbA1c results and sociodemographic, lifestyle and comorbidity covariates extracted from the IQVIA Medical Research Database (IMRD) database using the DEXTER tool. A minimum of four measurements in the same individual was the only inclusion criterion. Within-individual measured variation was calculated as a coefficient of variation (CV) using a linear regression random effects model for the whole population and various subgroups. Results 587,023 participants were included in this study, making it the largest study of variation of HbA1c to date. The overall measured within-individual coefficient of variation (CVT) was 0.20 (95%CI 0.20 to 0.20). This is around three times higher than reported in a previous systematic review. CVT increased with patient mean HbA1c level. Strengths and limitations The large number of participants and the real-world nature of the results are important strengths of this study. Weaknesses included the problem of accounting for confounding by indication. Conclusions Estimated within-individual variation in this analysis of real-world data is very high and is higher than previously reported. Variation increases with patient mean HbA1c, that is with more severe disease status. This has important implications for the diagnosis, monitoring and clinical decision-making for diabetes.
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2025-10-03
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