Liver Transplant Wait-list Trends in Young American Adults
Bibliographic record
Abstract
Background: Cirrhosis refers to end stage liver disease and it is the final common pathway for all chronic liver diseases (CLDs). Recent data illustrates that mortality secondary to cirrhosis is increasing in the United States (US) and is highest among young adults. Whether these trends are also occurring in Liver Transplant (LT) wait-list candidates however has not been well established. This study aimed to describe the epidemiology of LT wait-listing trends in the US over the past two decades stratified by age at listing, cirrhosis etiology, and sex. Methods: We conducted a retrospective population-based study from 2002 – 2018, examining all adult LT wait-listed patients in the US. Patients >= 20 years at the time of LT listing were identified from the Scientific Registry of Transplant Recipients (SRTR) database. Annual standardized incidence proportions were calculated from US census data. Poisson regression was used to assess changes in the annual incidence of LT wait-listing stratified by age, sex, and cirrhosis etiology and described by incidence rate ratios (IRR). Results: A total of 216,936 unique individuals were included. The median age at LT wait-listing was 57 years (Range: 20-83; IQR: 51 - 62), with 68% being male, and 11,312 individuals (5.2%) were < 40 years at listing. The most common etiologies of cirrhosis were HCV, alcohol-related liver disease (ALD), and non-alcoholic fatty liver disease (NAFLD). The age and sex standardized incidence proportion of LT wait-listing more than doubled in both young and older adults over the study period (<40: 0.16/100,000 in 2002 to 0.28/ 100,000 in 2018; >=40: 2.2/100,000 in 2002 to 4.34/100,000 in 2018). Using poisson regression, the etiologies with the highest annual IRR were ALD (<40: IRR 1.11, 95% CI 1.10 – 1.12, p<.001; >=40 IRR 1.06, 95% CI 1.06 – 1.07, p<.001) and NAFLD (<40: IRR 1.13, 95% CI 1.10 – 1.15, p<.001; >=40: IRR 1.16, 95% CI 1.15 – 1.16, p<.001). The rate of waitlisting for ALD in young females was higher than males (IRR 1.11, 95% CI 1.10 – 1.12, p< .001) Conversely, the listing rate for NAFLD was lower in young females compared to young males (IRR 0.97, 95% CI 0.97 – 0.98, p< .001). Conclusion: The incidence of LT wait-listing is increasing in both young and older adults in the US driven primarily by ALD and NAFLD. In young adults, rates of listing are increasing most in young women with ALD and men with NAFLD. These data support ongoing efforts to identify young adults with ALD and NAFLD where public health interventions can prevent the development of cirrhosis and liver-related complications.
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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 | 0.000 | 0.001 |
| 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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".