Mortality associated with timing of admission to and discharge from ICU: a retrospective cohort study
Bibliographic record
Abstract
BACKGROUND: Although the association between mortality and admission to intensive care units (ICU) in the "after hours" (weekends and nights) has been the topic of extensive investigation, the timing of discharge from ICU and outcome has been less well investigated. The objective of this study was to assess effect of timing of admission to and discharge from ICUs and subsequent risk for death. METHODS: Adults (≥ 18 years) admitted to French ICUs participating in Outcomerea between January 2006 and November 2010 were included. RESULTS: Among the 7,380 patients included, 61% (4,481) were male, the median age was 62 (IQR, 49-75) years, and the median SAPS II score was 40 (IQR, 28-56). Admissions to ICU occurred during weekends (Saturday and Sunday) in 1,708 (23%) cases, during the night (18:00-07:59) in 3,855 (52%), and on nights and/or weekends in 4,659 (63%) cases. Among 5,992 survivors to ICU discharge, 903 (15%) were discharged on weekends, 659 (11%) at night, and 1,434 (24%) on nights and/or weekends. After controlling for a number of co-variates using logistic regression analysis, admission during the after hours was not associated with an increased risk for death. However, patients discharged from ICU on nights were at higher adjusted risk (odds ratio, 1.54; 95% confidence interval, 1.12-2.11) for death. CONCLUSIONS: In this study, ICU discharge at night but not admission was associated with a significant increased risk for death. Further studies are needed to examine whether minimizing night time discharges from ICU may improve outcome.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| 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".