Prevalence of cognitive impairment in liver transplant recipients
Bibliographic record
Abstract
Liver transplant (LT) recipients have a high burden of cognitive impairment risk factors identified in other populations, yet little work has explored cognition in the United States LT population. We characterized prevalence of cognitive impairment (CI) in LT recipients pre-LT and ≥3 months post-LT. Adult LT recipients with cirrhosis but without active pre-LT hepatic encephalopathy (HE) were screened for CI using the Montreal Cognitive Assessment (MoCA) for CI (MoCA <24) both pre-LT and ≥3 months post-LT. The association between cognitive performance and recipient characteristics was assessed using logistic regression. Of 107 LT recipients, 36% had pre-LT CI and 27% had post-LT CI [median (Q1-Q3) MoCA 26 (23-28)]. Each 1-point increase in pre-LT MoCA was associated with 26% lower odds of post-LT cognitive impairment (aOR .74, 95% CI .63-.87, p < .001), after adjusting for recipient age, history of HE, and time since LT. In this study of cirrhosis recipients without active pre-LT HE, cognitive impairment was prevalent before LT and remained prevalent ≥3 months after LT (27%), long after effects of portal hypertension on cognition would be expected to have resolved. Our data expose an urgent need for more comprehensive neurologic examination of LT recipients to better identify, characterize, and address predictors of post-LT cognitive impairment.
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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 | 0.002 |
| 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 | 0.000 |
| 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".