Are Elderly Patients with Obstructive Airway Disease Being Prematurely Discharged?
Bibliographic record
Abstract
Despite the temporal trend toward decreasing length of hospital stay for all medical conditions in North America, the effect of different lengths of hospitalization on short-term outcomes such as readmission or mortality has not been well studied. However, there is growing concern that very short stays in hospital may result in premature discharges, which may lead to worse outcomes for patients. We conducted a population-based study of elderly patients with obstructive airway disease in Ontario, Canada to test the hypothesis that very short initial hospital stays increase the short-term risk for readmission and mortality. Using a cohort of 32,384 elderly patients 65 yr of age or older, we compared 15-d rates of readmission and mortality among patients with different lengths of stay. Although patients with hospital stays of less than 4 d were younger and had fewer comorbidities, they were 39% (95% confidence interval [CI], 20% to 61%) more likely to be readmitted and 45% (95% CI, 9% to 92%) more likely to die within 15 d postdischarge compared with those who stayed 4 to 6 d. The risk was highest among patients whose stay was less than or equal to 1 hospital day; they had a 69% (95% CI, 32% to 117%) excess risk of readmission and a 2.08 (95% CI, 1.23 to 3.45) -fold increase in mortality compared with those who stayed in hospital for 2 d. This suggests that some elderly patients with obstructive airway disease may be being prematurely discharged.
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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 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 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".