ArticleBMC gastroenterology2025
Frailty and liver transplant eligibility beyond MELD scores: integrating functional status into candidate selection.
Article in BMC gastroenterology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
1 citing paper in PubMed.
- Prognostic Value of Exercise Testing in Patients with Liver Cirrhosis.Diagnostics (Basel, Switzerland) · 2026Article
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4 authors.
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Abstract
backgroundThe MELD score, while central to liver transplant prioritization, fails to capture frailty, an important predictor of transplant eligibility and outcomes.
aimTo assess the impact of frailty on transplant eligibility and compare its predictive accuracy to MELD-Na.
methodsWe prospectively studied adults with cirrhosis referred to for transplant evaluation. Frailty was assessed using the Clinical Frailty Scale (CFS) by a multidisciplinary team, with adjudication for disagreements. Laboratory data were collected, MELD scores calculated, and transplant eligibility determined using our institutional framework. Correlation, logistic regression, and ROC analyses compared MELD and CFS in predicting eligibility.
resultsAmong 672 patients evaluated, 76 (11.3%) met the primary endpoint of transplant eligibility. Eligible patients had significantly lower MELD scores, but better frailty status compared with ineligible patients (mean CFS 3.2 vs. 5.8, p < 0.001). CFS correlated moderately with MELD (r = 0.62) and showed superior predictive accuracy for eligibility (AUC 0.84 vs. 0.72).
conclusionFrailty, assessed by the Clinical Frailty Scale, outperformed MELD-Na in predicting transplant eligibility and proved relevant even in low-MELD populations. These findings highlight frailty as a practical determinant of eligibility and a step toward standardized, evidence-based equitable selection frameworks.
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