Early hospital readmission and survival in patients with cirrhosis: A population-based study
Bibliographic record
Abstract
Background: Readmission in patients with cirrhosis is common. We aimed to determine the association between early hospital readmission and survival in the general population of patients with cirrhosis. Methods: This retrospective cohort study used routinely collected health care data from Ontario. We identified adults with cirrhosis using a validated case definition, and included those with at least one hospital admission between 1992 and 2016 resulting in discharge. Patients were classified into two groups based on timing of readmission after index admission: 1) ≤90 days, or 2) >90 days or no readmission. We described overall survival (OS) 90 days after the index hospitalization by readmission status using Kaplan–Meier curves and the log-rank test. The association between readmission and OS was evaluated using a multivariate Cox proportional hazards regression model. Results: Our study included 115,081 patients. The median OS was shorter in patients readmitted in ≤90 days (4.1 years, IQR 0.9, 13.1) compared with those readmitted in >90 days or not readmitted during the study period (9.6 years, IQR 3.2, 21.9, p <0.001). Adjusting for potential confounders, those readmitted in ≤90 days had a higher hazard of death than those not readmitted (hazard ratio [HR] 1.56, 95% CI 1.53 to 1.59, p <0.001). Conclusions: Early readmission in patients with cirrhosis is a strong predictor of decreased OS. Our results suggest that patients with cirrhosis who have an early readmission should be further studied to determine whether this risk is modifiable. They can also be used to discuss long-term prognosis with patients and family members.
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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 | 0.002 |
| 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 | 0.000 | 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".