Instability on Hospital Discharge and the Risk of Adverse Outcomes in Patients With Pneumonia
Bibliographic record
Abstract
BACKGROUND: Investigating claims that patients are being sent home from the hospital "quicker and sicker" requires a way of objectively measuring appropriateness of hospital discharge. OBJECTIVE: To define and validate a simple, usable measure of clinical stability on discharge for patients with community-acquired pneumonia. METHODS: Information on daily vital signs and clinical status was collected in a prospective, multicenter, observational cohort study. Unstable factors in the 24 hours prior to discharge were temperature greater than 37.8 degrees C, heart rate greater than 100/min, respiratory rate greater than 24/min, systolic blood pressure lower than 90 mm Hg, oxygen saturation lower than 90%, inability to maintain oral intake, and abnormal mental status. Outcomes were deaths, readmissions, and failure to return to usual activities within 30 days of discharge. RESULTS: Of the 680 patients, 19.1% left the hospital with 1 or more instabilities. Overall, 10.5% of patients with no instabilities on discharge died or were readmitted compared with 13.7% of those with 1 instability and 46.2% of those with 2 or more instabilities (P<.003). Instability on discharge (> or =1 unstable factor) was associated with higher risk-adjusted rates of death or readmission (odds ratio [OR], 1.6; 95% confidence interval [CI], 1.0-2.8) and failure to return to usual activities (OR, 1.5; 95% CI, 1.0-2.4). Patients with 2 or more instabilities had a 5-fold greater risk-adjusted odds of death or readmission (OR, 5.4; 95% CI, 1.6-18.4). CONCLUSIONS: Instability on discharge is associated with adverse clinical outcomes. Pneumonia guidelines and pathways should include objective criteria for judging stability on discharge to ensure that efforts to shorten length of stay do not jeopardize patient safety.
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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 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 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".