ArticleLiver transplantation : official publication of the American Association for the Study of Liver Diseases and the International Liver Transplantation Society2026
Machine learning-derived clinical phenotypes of ascites in cirrhosis: A multi-center latent class analysis with external validation.
Article in Liver transplantation : official publication of the American Association for the Study of Liver Diseases and the International Liver Transplantation Society, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
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.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
0 citing papers in PubMed.
No citing paper in PubMed yet.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
11 authors.
Funding
Abstract
Ascites development in cirrhosis reduces 5-year survival from 80% to 30%, yet substantial heterogeneity exists among patients with comparable ascites severity. This multicenter retrospective cohort study included adult liver transplant candidates with ascites at 4 United States centers (2015-2024). Latent class analysis was performed using 7 clinical variables: ascites grade, bilirubin, albumin, platelet count, estimated glomerular filtration rate, systolic blood pressure, and portal vein thrombosis. The derivation cohort (n=625) from the University of California San Francisco and Columbia University was randomly split 80/20 for model development and internal validation. External validation was performed at the University of Southern California (n=59) and Mayo Clinic (n=93). Primary outcomes were acute kidney injury (AKI) and waitlist mortality over 365 days. Three phenotypes emerged: "CKD-Metabolic" (30.4%, lowest eGFR 76.5 mL/min/1.73 m 2 ), "Vasodilatory-Synthetic Dysfunction" (38.9%, highest bilirubin 7.03 mg/dL, lowest blood pressure 117.5 mmHg), and "PVT-Intermediate" (30.7%, severe thrombocytopenia 68.1×10 3 /μL, 24.0% PVT). In validation cohorts (n=305), phenotypes demonstrated robust classification (mean posterior probability 0.823-0.855). Vasodilatory-Synthetic Dysfunction showed increased AKI risk versus CKD-Metabolic in derivation (MELD 3.0-adjusted HR 2.95, 95% CI 2.07-4.22, p <0.001) and validation cohorts (HR 3.39, 95% CI 1.93-5.94, p <0.001). Competing risk analysis revealed no mortality differences, but Vasodilatory-Synthetic Dysfunction was associated with higher transplantation rates (validation: HR 1.63, 95% CI 1.19-2.22, p =0.002). Three reproducible clinical phenotypes of ascites were identified with distinct risk profiles. The Vasodilatory-Synthetic Dysfunction phenotype was associated with a 3-fold increase in the risk of AKI that persisted after adjustment for MELD 3.0. No differences in waitlist mortality were observed, likely reflecting effective MELD-based transplant allocation that preferentially removes the highest-acuity patients from the waitlist.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.