A Rare Hemoglobin Variant (β51Pro → His) Causing Misleading Measurements of Hemoglobin A1c
Bibliographic record
Abstract
Abstract Glycated hemoglobin A1c (HbA1c) is considered the standard of care for the testing and monitoring of diabetes. Its ability to accurately reflect glycemia, however, is imperfect. Hemoglobin variants—mutant forms of hemoglobin caused by genetic variation present in 7% of the population—are known to adversely affect the ability of HbA1c measurement to reflect glycemic control. We report an illustrative case of a 64-year-old nondiabetic man with a steadily decreasing HbA1c and no symptoms of hypoglycemia or concerning family history. Preliminary investigative workup returned nothing of significance. Genetic sequencing, however, identified a rare benign hemoglobin variant: a heterozygous missense mutation in the gene encoding the hemoglobin β chain (c.155C > A, p.Pro51His). This variant has been reported only once previously, and the report predates genetic sequence data of the variant. Although this variant had no clinical implications for the patient, it was the cause of falsely low HbA1c levels on high-performance ion-exchange chromatography. This case highlights the importance of considering the effect of hemoglobin variants on the measurement of HbA1c. When available, family history should be carefully considered. Clinicians should suspect hemoglobin variants when HbA1c is too high or low, or discordant with the clinical picture.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.004 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".