530 INTERPRETATION OF HBA1C VALUES IN GERIATRIC PATIENTS WITH TYPE 2 DIABETES: LARGE DIVERGENCE BETWEEN CLINICAL PRACTICE GUIDELINES
Bibliographic record
Abstract
Abstract Introduction An individualised glycated haemoglobin (HbA1c) target according to the patients’ health status is central in the glycaemic management of geriatric people with type 2 diabetes (T2D) in order to avoid hypoglycaemic events through an appropriate management of the glucose-lowering therapy (GLT). Current clinical practice guidelines (CPGs) provide different recommendations for patients’ HbA1c targets. Using real-life data from geriatric patients, this study aimed at assessing the concordance in interpretation of HbA1c values according to three current major CPGs from the Diabetes Canada-2018 (DC18), the Endocrine Society-2019 (ES19) and the American Diabetes Association-2020 (ADA20). Introduction Retrospective study in consecutive older patients (≥75 years) with T2D admitted to a Belgian geriatric ward, with GLT before admission and HbA1c measurement during the hospital stay. Patients were classified into three categories of HbA1c values according to the CPGs recommendations: in-target HbA1c (appropriate-GLT), too-low HbA1c (GLT-overtreatment) and too-high HbA1c (GLT-undertreatment). Concordance of health status classifications and GLT categories between the three CPGs was assessed using Cohen’s and Fleiss’ κ, respectively. Results Of the 318 patients (median age 84 years, 54% women), one-third were in intermediate health and two-thirds in poor health (κ = 0.86; excellent concordance). According to the DC18, ES19 and ADA20 CPGs, HbA1c was in-target for respectively 46%, 25% and 82% of the patients, and too-low HbA1c (GLT-overtreatment) was present in 28%, 57% and 0% (κ = 0.36; low concordance). Results Patients’ HbA1c values are interpreted differently according to these major CPGs, mainly because of differences in their recommendations about HbA1c target individualisation and specifically the definition of a too-low HbA1c value. In clinical practice, these diverging interpretations regarding overtreatment may lead to unsafe GLT prescribing and thereby to hypoglycaemic events in this high-risk population.
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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 | 0.024 | 0.081 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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".