Lower household income is associated with an increased risk of hospital readmission in patients with decompensated cirrhosis
Bibliographic record
Abstract
BACKGROUND AND AIM: The impact of household income, a surrogate of socioeconomic status, on hospital readmission rates for patients with decompensated cirrhosis has not been well characterized. METHODS: The Nationwide Readmission Database from 2012 to 2014 was used to study the association of lower median household income on 30-, 90-, and 180-day hospital readmission rates for patients with decompensated cirrhosis. RESULTS: From the 42 679 001 hospital admissions contained in the sample, there were 82 598 patients with decompensated cirrhosis who survived a hospital admission in the first 6 months of the year. During a uniform 6-month follow-up period, 25 914 (31.4%), 39 928 (48.3%), and 47 496 (57.5%) patients were readmitted at 30, 90, and 180 days, respectively. After controlling for demographic and clinical confounders, patients residing in the three lowest income quartiles were significantly more likely to be readmitted at 30 days than those in the fourth quartile (first quartile, odds ratio [OR] 1.32 [95% confidence interval, CI, 1.17-1.47, P < 0.01]; second quartile, OR 1.25 [95% CI 1.13-1.38, P < 0.01]; and third quartile, OR 1.08 [95% CI 0.97-1.20, P = 0.07]). The association between lower socioeconomic status and the higher risk of readmissions persisted at 90 days (first quartile, OR 1.21 [95% CI 1.14-1.30, P < 0.01]) and 180 days (first quartile, OR 1.32 [95% CI 1.20-1.44, P < 0.01]). CONCLUSION: Patients with decompensated cirrhosis residing in the lowest income quartile had a 32% higher odds of hospital readmissions at 30, 90, and 180 days compared with those in the highest income quartile.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".