Sex is a major effect modifier between body composition and mortality in patients with cirrhosis assessed for liver transplantation
Bibliographic record
Abstract
Abstract Background and Aims Body composition predicts mortality in patients with cirrhosis. The impact of sex on this association is unknown. We investigated the impact of sex on this association in patients with cirrhosis assessed for liver transplantation. Methods This single‐centre retrospective cohort study included adults assessed for liver transplantation. Nutritional status was assessed using the Royal Free Hospital‐Global Assessment (RFH‐GA). Body composition at the third lumbar vertebrae was determined. Sarcopenia SMI was defined as Skeletal Muscle Index <50 cm 2 /m 2 in males and <39 cm 2 /m 2 in females. Sarcopenia PMI was defined as the sex‐specific 25th percentile of the Psoas Muscle Index. Patients were assessed for the occurrence of liver transplantation and death. Analyses were stratified by sex. Results The cohort comprised 628 patients, including 199 females and 429 males. Both groups were similar in terms of baseline liver disease severity by Model for End‐stage Liver Disease (MELD) ( p = .98) and nutritional status ( p = .24). Sarcopenia SMI was present in 41% of males compared to 27% of females ( p < .001). In the male cohort, when adjusted for age and MELD, sarcopenia PMI (aHR 1.74, 95% CI 1.08–2.80) and RFH‐GA (aHR 1.40, 95% CI 1.03–1.90) remained independent predictors of mortality. Adipose tissue had no impact on outcomes in males. In female patients, adipose tissue (TATI or VATI depending on the multivariable model) was independently associated with mortality, whereas sarcopenia and malnutrition were not. Conclusions This study demonstrates that male patients were susceptible to low muscle mass, whereas female patients were not. Future research in this patient population should minimize sex‐related bias and present data for both groups separately.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".