Liver Transplantation in the Time of a Pandemic
Bibliographic record
Abstract
OBJECTIVE: During the initial wave of the COVID-19 pandemic, organ transplantation was classified a CMS Tier 3b procedure which should not be postponed. The differential impact of the pandemic on access to liver transplantation was assessed. SUMMARY BACKGROUND DATA: Disparities in organ access and transplant outcomes among vulnerable populations have served as obstacles in liver transplantation. METHODS: Using UNOS STARfile data, adult waitlisted candidates were identified from March 1, 2020 to November 30, 2020 (n = 21,702 pandemic) and March 1, 2019 to November 30, 2019 (n = 22,797 pre-pandemic), and further categorized and analyzed by time periods: March to May (Period 1), June to August (Period 2), and September to November (Period 3). Comparisons between pandemic and pre-pandemic groups included: Minority status, demographics, diagnosis, MELD, insurance type, and transplant center characteristics. Liver transplant centers (n = 113) were divided into tertiles by volume (small, medium, large) for further analyses. Multivariable logistic regression was fitted to assess odds of transplant. Competing risk regression was used to predict probability of removal from the waitlist due to transplantation or death and sickness. Additional temporal analyses were performed to assess changes in outcomes over the course of the pandemic. RESULTS: During Period 1 of the pandemic, Minorities showed greater reduction in both listing (-14% vs -12% Whites), and transplant (-15% vs -7% Whites), despite a higher median MELD at transplant (23 vs 20 Whites, P < 0.001). Of candidates with public insurance, Minorities demonstrated an 18.5% decrease in transplants during Period 1 (vs -8% Whites). Although large programs increased transplants during Period 1, accounting for 61.5% of liver transplants versus 53.4% pre-pandemic (P < 0.001), Minorities constituted significantly fewer transplants at these programs during this time period (27.7% pandemic vs 31.7% pre-pandemic, P = 0.04). Although improvements in disparities in candidate listings, removals, and transplants were observed during Periods 2 and 3, the adjusted odds ratio of transplant for Minorities was 0.89 (95% CI 0.83-0.96, P = 0.001) over the entire pandemic period. CONCLUSIONS: COVID-19's effect on access to liver transplantation has been ubiquitous. However, Minorities, especially those with public insurance, have been disproportionately affected. Importantly, despite the uncertainty and challenges, our systems have remarkable resiliency, as demonstrated by the temporal improvements observed during Periods 2 and 3. As the pandemic persists, and the aftermath ensues, health care systems must consciously strive to identify and equitably serve vulnerable populations.
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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 | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".