Nationwide estimates and risk factors of hospital readmission in patients with cirrhosis in the United States
Bibliographic record
Abstract
BACKGROUND: The burden of cirrhosis on the healthcare system is substantial and growing. Our objectives were to estimate the readmission rates and hospitalization costs as well as to identify risk factors for 90-day readmission in patients with cirrhosis. METHODS: We conducted a weighted analysis of the 2014 Nationwide Readmission Database to identify adult patients with cirrhosis-related complications in the United States and assessed readmission rates at 30, 60 and 90 days post-index hospitalization. Predictors of 90-day readmissions were identified using weighted regression models adjusting for patient and hospital characteristics; the national estimate of hospitalization costs was also calculated. RESULTS: Of the 58 954 patients admitted with cirrhosis-related complications in 2014, 14 910 (25%) were readmitted within 90 days because of cirrhosis-related complications. The main causes of readmission were ascites (56%), hepatic encephalopathy (47%) and bleeding oesophageal varices (9%). Independent predictors of 90-day readmissions were male sex (adjusted OR [aOR]: 1.08, 95% CI, 1.04-1.13), age <60 (aOR: 1.27, 95% CI, 1.22-1.32), privately insured (aOR: 0.74, 95% CI, 0.70-0.77), having ≥3 comorbid conditions (aOR: 1.27, 95% CI, 1.14-1.42) and being discharged against medical advice (aOR: 1.41, 95% CI, 1.25-1.59). The weighted cumulative national cost estimate of the index admission was $1.8 billion, compared to $0.5 billion for readmission. CONCLUSIONS: A quarter of patients admitted with cirrhosis-related complications were readmitted within 90 days, representing a significant economic burden related to readmission of this population. Interventions and resource allocations to reduce readmission rates among cirrhotic patients is critical.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".