Glycemic assessment when hemoglobin A1c is unreliable: a clinical-laboratory framework for kidney disease, anemia, and hemoglobinopathies.

Hemoglobin A1c is central to diabetes diagnosis and monitoring, but its interpretation becomes clinically fragile when red-cell biology, hemoglobin composition, assay behavior, kidney failure, protein turnover, or glucose-data quality affects the assumptions behind the result. Existing reviews have described many causes of hemoglobin A1c-glycemia mismatch; the remaining practical problem is how clinicians and laboratories can choose a safer, decision-appropriate metric when the result is discordant with glucose data, symptoms, phenotype, or treatment response. This review synthesizes evidence from diabetes care, laboratory medicine, nephrology, hematology, and diabetes technology to propose a decision-oriented clinical-laboratory framework for selected high-risk settings: advanced chronic kidney disease and dialysis, anemia or altered red-cell turnover, and hemoglobin variants or hemoglobinopathies. The framework does not replace hemoglobin A1c with a single alternative marker. Instead, it asks which clinical decision is being made, whether hemoglobin A1c is biologically and analytically interpretable, whether comparator glucose data are adequate, and which adjunct metric is least likely to mislead in that scenario. Continuous glucose monitoring, structured self-monitoring, laboratory plasma glucose, glycated albumin, fructosamine, and selected secondary constructs are considered according to their decision value and failure modes. The proposed approach is an interpretive aid for clinician-laboratory communication, not a validated guideline, diagnostic algorithm, or therapeutic pathway.