Sex and Mortality of Hospitalized Adults After Admission to an Intensive Care Unit
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
BACKGROUND: After admission to intensive care, women have higher mortality rates than do men. The reasons for the greater mortality in women are not fully understood. OBJECTIVE: To determine if increased mortality in women was due to delays in the recognition of critical illness or to delays in timely admission to intensive care. METHODS: A total of 241 consecutive admissions to intensive care from medical and surgical units during a 12-month period were analyzed retrospectively. Patients' demographics, illness severity, and delay between the time the patients would have fulfilled criteria for calling a medical emergency team and consultation with and admission to intensive care were analyzed. RESULTS: Delay from fulfillment of criteria for calling a medical emergency team and consultation with intensive care and from consultation to admission to intensive care did not differ between sexes. Despite similar delays in admission to intensive care, women had a higher 30-day mortality than did men (44.9% vs 30.5%; P = .02). The increased mortality was more pronounced in the medical patients (53% vs 34%; P = .02). Multivariate analysis of mortality data yielded a mortality odds ratio of 0.35 (95% CI, 0.16-0.74) for men, significantly different from values for women (P = .006). CONCLUSION: After admission to intensive care from medical or surgical units, women had higher mortality rates than did men, and the difference was more pronounced in medical patients. The difference in mortality between sexes was not explained by delayed recognition of critical illness or delayed admission to intensive care.
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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) | 0.000 | 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 it