A Patient-Level Meta-Analysis of Intensive Glucose Control in Critically Ill Adults
Bibliographic record
Abstract
BACKGROUND: Whether intensive glucose control reduces mortality in critically ill patients remains uncertain. Patient-level meta-analyses can provide more precise estimates of treatment effects than are currently available. METHODS: We pooled individual patient data from randomized trials investigating intensive glucose control in critically ill adults. The primary outcome was in-hospital mortality. Secondary outcomes included survival to 90 days and time to live cessation of treatment with vasopressors or inotropes, mechanical ventilation, and newly commenced renal replacement. Severe hypoglycemia was a safety outcome. RESULTS: Of 38 eligible trials (n=29,537 participants), 20 (n=14,171 participants) provided individual patient data including in-hospital mortality status for 7059 and 7049 participants allocated to intensive and conventional glucose control, respectively. Of these 1930 (27.3%) and 1891 (26.8%) individuals assigned to intensive and conventional control, respectively, died (risk ratio, 1.02; 95% confidence interval [CI], 0.96 to 1.07; P=0.52; moderate certainty). There was no apparent heterogeneity of treatment effect on in-hospital mortality in any examined subgroups. Intensive glucose control increased the risk of severe hypoglycemia (risk ratio, 3.38; 95% CI, 2.99 to 3.83; P<0.0001). CONCLUSIONS: Intensive glucose control was not associated with reduced mortality risk but increased the risk of severe hypoglycemia. We did not identify a subgroup of patients in whom intensive glucose control was beneficial. (Funded by the Australian National Health and Medical Research Council and others; PROSPERO number CRD42021278869.).
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.009 | 0.006 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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 teacher head, 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".