An observational study on the effect of hypercholesterolemia developed after living donor liver transplantation on cardiac event and graft failure
Bibliographic record
Abstract
This study sought to evaluate the association between newly-developed significant hypercholesterolemia within one year following living donor liver transplantation (LDLT) and long term outcomes in light of cardiovascular events and graft failure. From October 2003 to July 2017, 877 LDLT recipients were stratified according to development of significant hypercholesterolemia within one year following LDLT. The primary outcome was occurrence of a major adverse cardiac event (MACE), defined as a composite of cardiac death, myocardial infarction, and coronary revascularization after LDLT. The incidence of graft failure, defined as all-cause death or retransplantation, was also compared. A total of 113 (12.9%) recipients developed significant hypercholesterolemia within one year. The differences in incidences of cardiac related events and graft related events began emerging significantly higher in the hypercholesterolemia group after 24 months and 60 months since the LDLT, respectively. After adjustment using the inverse probability of weighting, the hazard ratio (HR) for MACE was 2.77 (95% confidence interval (CI) 1.16-6.61; p = 0.02), while that for graft failure was 3.76 (95% CI 1.97-7.17, p < 0.001). A significant hypercholesterolemia after LDLT may be associated with cardiac and graft-related outcome; therefore, a further study and close monitoring of cholesterol level after LDLT is needed.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".