‘Glycometrics' – Standardized Metrics for Inpatient Glycemic Control Quality Performance Evaluation.
Bibliographic record
Abstract
INTRODUCTION: For patients with diabetes, the quality of outpatient glycemic control is readily assessed by hemoglobin A1c. In contrast, standardized measures for assessing the quality of blood glucose (BG) management in hospitalized patients are lacking. We sought to evaluate candidate models to measure the quality of inpatient glycemic control. METHODS: A cross-sectional and nationwide survey was conducted from July/2010 to January/2012. Eligible patients were ≥18 years old, had a diagnosis of diabetes and hospitalization length of stay ≥72 hours. Information on all blood glucose (BG) readings for a maximum of 20 consecutive days of hospitalization was collected by chart review. We used three analytical models: patient-day (grouped BG levels by calendar day for each patient), patient-stay (each patient's mean BG level for the entire hospitalization) and patient-sample (all BG levels individually, without grouping). For each model we calculated the glycemic average level, the median BG, the percentage of BG measurements in range, and the percentage of hypoglycemic and hyperglycemic events.
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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 | 0.043 | 0.120 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.010 | 0.015 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".