Estimating Glycemia From HbA1c and CGM: Analysis of Accuracy and Sources of Discrepancy.

OBJECTIVE: To examine the accuracy of different periods of continuous glucose monitoring (CGM), hemoglobin A1c (HbA1c), and their combination for estimating mean glycemia over 90 days (AG90). RESEARCH DESIGN AND METHODS: We retrospectively studied 985 CGM periods of 90 days with <10% missing data from 315 adults (86% of whom had type 1 diabetes) with paired HbA1c measurements. The impact of mean red blood cell age as a proxy for nonglycemic effects on HbA1c was estimated using published theoretical models and in comparison with empirical data. Given the lack of a gold standard measurement for AG90, we applied correction methods to generate a reference (eAG90) that we used to assess accuracy for HbA1c and CGM. RESULTS: Using 14 days of CGM at the end of the 90-day period resulted in a mean absolute error (95th percentile) of 14 (34) mg/dL when compared with eAG90. Nonglycemic effects on HbA1c led to a mean absolute error for average glucose calculated from HbA1c of 12 (29) mg/dL. Combining 14 days of CGM with HbA1c reduced the error to 10 (26) mg/dL. Mismatches between CGM and HbA1c >40 mg/dL occurred more than 5% of the time. CONCLUSIONS: The accuracy of estimates of eAG90 from limited periods of CGM can be improved by averaging with an HbA1c-based estimate or extending the monitoring period beyond ∼26 days. Large mismatches between eAG90 estimated from CGM and HbA1c are not unusual and may persist due to stable nonglycemic factors.

Hematologic setpoints are a stable and patient-specific deep phenotype.

The complete blood count is an important screening tool for healthy adults and is the most commonly ordered test at periodic physical exams. However, results are usually interpreted relative to one-size-fits-all reference intervals, undermining the goal of precision medicine to tailor medical care to the needs of individual patients based on their unique characteristics. Here we show that standard complete blood count indices in healthy adults have robust homeostatic setpoints that are patient-specific and stable, with the typical healthy adult's set of 9 blood count setpoints distinguishable from 98% of others, and with these differences persisting for decades. These setpoints reflect a deep physiologic phenotype, enabling improved detection of both acquired and genetic determinants of hematologic regulation, including discovery of multiple novel loci via GWAS analyses. Patient-specific reference intervals derived from setpoints enable more accurate personalized risk assessment, and the setpoints themselves are significantly correlated with mortality risk, providing new opportunities to enhance patient-specific screening and early intervention. This study shows complete blood count setpoints are sufficiently stable and patient-specific to help realize the promise of precision medicine for healthy adults.