Characteristics and Outcomes for Low-Risk Hospital Admissions Admitted to the ICU: A Multisite Cohort Study
Bibliographic record
Abstract
IMPORTANCE: Prognostication following ICU admission can often be determined based on known risk factors, including demographics and illness severity; however, little is known about outcomes of patients deemed to be "low-risk" at the time of hospital admission who subsequently are admitted to the ICU. OBJECTIVES: The objectives of this study were to determine the characteristics, outcomes, and costs for patients requiring ICU admission despite having lower predicted mortality when they were admitted to the hospital. DESIGN SETTING AND PARTICIPANTS: In this historical cohort study, we used a prospectively maintained ICU registry that included all ICU admissions to The Ottawa Hospital for patients 18 years or older from January 2011 to December 2016. We classified patients as low-risk using the Hospital-patient 1-year Mortality Risk at admission score, a hospital admission score validated to predict 1-year mortality. MAIN OUTCOMES AND MEASURES: The primary outcome was inhospital mortality. Secondary outcomes included adverse events, resource utilization, and costs. RESULTS: < 0.001). For low-risk patients, multivariable logistic regression showed mortality was independently associated with older age (odds ratio, 1.02 per 1 yr; 95% CI, 1.00-1.03 per 1 yr), Multiple Organ Dysfunction Score (odds ratio, 1.42 per 1 point; 95% CI, 1.31-1.54 per 1 point), fluid management adverse events (odds ratio, 2.84; 95% CI, 1.29-6.25), hospital-acquired infections (odds ratio, 1.60; 95% CI, 1.02-2.51), and mechanical ventilation (odds ratio, 1.98; 95% CI, 1.20-3.26). CONCLUSIONS AND RELEVANCE: Despite their robust premorbid status, low-risk patients admitted to the ICU had significant inhospital mortality. Fluid management adverse events, hospital-associated infections, multiple organ dysfunction, and mechanical ventilation are important prognostic factors for low-risk 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 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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 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".