Evaluation of the Impact of an Inpatient Hyperglycemia Protocol on Glycemic Control
Bibliographic record
Abstract
PURPOSE: Inpatient hyperglycemia is associated with poor outcomes. Existing research assessing inpatient hyperglycemia protocols has shown improvements in average blood glucose levels with inconsistent results regarding rates of hypoglycemia and hyperglycemia. The objective of this study was to evaluate the impact of an inpatient hyperglycemia protocol on glycemic control. METHODS: This retrospective cohort study at a large, community teaching hospital included adult patients in non-critical care units requiring insulin administration for glycemic control. The intervention examined was utilization of an inpatient hyperglycemia protocol, comprised of a computerized physician order entry order set and provider education at the time of implementation. Two cohorts, a pre-protocol implementation group and a post-protocol implementation group, were compared. The primary outcome was the incidence of blood glucose values within 70-180 mg/dL over a 72-hour period between groups. Key secondary outcomes included the incidence of hypoglycemia (less than 70 mg/dL), severe hyperglycemia (above 300 mg/dL), total insulin use, and hospital length of stay. RESULTS: The primary outcome was significantly improved following protocol implementation (54.2% vs. 58.4%, p = 0.001). Compared to the pre-protocol group, the post-protocol group had lower incidence of hypoglycemia (3.1% vs. 1.2%, p < 0.001), severe hyperglycemia (9.9% vs. 6.7%, p < 0.001), less total insulin use (1.1 units/kg vs. 0.6 units/kg, p < 0.001), and shorter length of stay (5.1 days vs. 3.7 days, p < 0.001). CONCLUSIONS: The implementation of an inpatient hyperglycemia protocol was associated with improved glycemic control, decreased incidence of both hypoglycemia and severe hyperglycemia, and less total insulin use.
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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 | 0.010 | 0.024 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 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".