Higher ICU Capacity Strain Is Associated With Increased Acute Mortality in Closed ICUs*
Bibliographic record
Abstract
OBJECTIVES: To determine whether patients admitted to an ICU during times of strain, when compared with its own norm (i.e. accommodating a greater number of patients, higher acuity of illness, or frequent turnover), is associated with a higher risk of death in ICUs with closed models of intensivist staffing. DESIGN: We conducted a large, multicenter, observational cohort study. Multilevel mixed effects logistic regression was used to examine relationships for three measures of ICU strain (bed census, severity-weighted bed census, and activity-weighted bed census) on the day of admission with risk-adjusted acute hospital mortality. SETTING: Pooled case mix and outcome database of adult general ICUs participating in the Intensive Care National Audit and Research Centre Case Mix Programme. MEASUREMENTS AND MAIN RESULTS: The analysis included 149,310 patients admitted to 215 adult general ICUs in 213 hospitals in United Kingdom, Wales, and Northern Ireland. A relative lower strain in ICU capacity as measured by bed census on the calendar day (daytime hours) of admission was associated with decreased risk-adjusted acute hospital mortality (odds ratio, 0.94; 95% CI, 0.90-0.99; p = 0.01), whereas a nonsignificant association was seen between higher strain and increased acute hospital mortality (odds ratio, 1.04; 95% CI, 1.00-1.10; p = 0.07). The relationship between periods of high ICU strain and acute hospital mortality was strongest when bed census was composed of higher acuity patients (odds ratio, 1.05; 95% CI, 1.01-1.10; p = 0.03). No relationship was seen between high strain and ICU mortality. CONCLUSIONS: In closed staffing models of care, variations in bed census within individual ICUs was associated with patient's predicted risk of acute hospital mortality, particularly when its standardized bed census consisted of sicker patients.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".