Association between social determinants of health and rates of liver transplantation in individuals with cirrhosis
Bibliographic record
Abstract
BACKGROUND AND AIMS: This study evaluated the association between neighborhood-level social determinants of health (SDOH) and liver transplantation (LT) among patients with cirrhosis who have universal access to health care. APPROACH AND RESULTS: This was a retrospective population-based cohort study from 2000-2019 using administrative health care data from Ontario, Canada. Adults aged 18-70 years with newly decompensated cirrhosis and/or HCC were identified using validated coding. The associations between five neighborhood level SDOH quintiles and LT were assessed with multivariate Fine-Gray competing risks regression to generate subdistribution HRs (sHRs) where death competes with LT. Overall, n = 38,719 individuals formed the cohort (median age 57 years, 67% male), and n = 2788 (7%) received LT after a median of 23 months (interquartile range 3-68). Due to an interaction, results were stratified by sex. After multivariable regression and comparing those in the lowest versus highest quintiles, individuals living in the most materially resource-deprived areas (female sHR, 0.61; 95% CI, 0.49-0.76; male sHR, 0.55; 95% CI, 0.48-0.64), most residentially unstable neighborhoods (female sHR, 0.61; 95% CI, 0.49-0.75; male sHR, 0.56; 95% CI, 0.49-0.65), and lowest-income neighborhoods (female sHR, 0.57; 95% CI, 0.46-0.7; male sHR, 0.58; 95% CI, 0.50-0.67) had ~40% reduced subhazard for LT (p < 0.01 for all). No associations were found between neighborhoods with the most diverse immigrant or racial minority populations or age and labor force quintiles and LT. CONCLUSIONS: This information highlights an urgent need to evaluate how SDOH influence rates of LT, with the overarching goal to develop strategies to overcome inequalities.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".