The effect of hypoglycaemia during hospital admission on health‐related outcomes for people with diabetes: a systematic review and meta‐analysis
Bibliographic record
Abstract
AIM: To assess the health-related outcomes of hypoglycaemia for people with diabetes admitted to hospital; specifically, hospital length of stay and mortality. METHODS: We conducted a systematic review and meta-analysis of studies relating to hypoglycaemia (< 4 mmol/l) for hospitalized adults (≥ 16 years) with diabetes reporting the primary outcomes of interest, hospital length of stay or mortality. Final papers for inclusion were reviewed in duplicate and the adjusted results of each were pooled, using a random effects model then undergoing further prespecified subgroup analysis. RESULTS: In total, 15 studies were included in the meta-analysis. The pooled mean difference in length of stay for ward-based inpatients exposed to hypoglycaemia was 4.1 days longer [95% confidence interval (CI) 2.36 to 5.79; I² = 99%] compared with those without hypoglycaemia. This association remained robust across the pre-specified subgroup analyses. The pooled relative risk (RR) of in-hospital mortality was greater for those exposed to hypoglycaemia (RR 2.09, 95% CI 1.64 to 2.67; I² = 94%, n = 7 studies) but not in intensive care unit mortality (RR 0.75, 95% CI 0.49 to 1.16; I² =0%, n = 2 studies). CONCLUSION: There is an association between inpatient hypoglycaemia and longer length of stay and greater in-hospital mortality. Studies examining this association were heterogenous in terms of both clinical populations and effect size, but the overall direction of the association was consistent. Therefore, glucose concentration should be considered a potential tool to aid the identification of inpatients at risk of poor health-related outcomes.
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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 | 0.029 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.019 | 0.039 |
| Bibliometrics | 0.006 | 0.006 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".