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DOI 10.1097/lvt.0000000000000942

Медицинская библиотека · Liver transplantation : official publication of the American Association for the Study of Liver Diseases and the International Liver Transplantation Society · 2026

Machine learning-derived clinical phenotypes of ascites in cirrhosis: A multi-center latent class analysis with external validation.

Cullaro Giuseppe, Lai Jennifer C, Liu Taryn, Gomez Miguel E, Simonetto Douglas A, Lee Sean, Lee Brian P, Allegretti Andrew S, Mazumder Nikhilesh R, Patidar Kavish R, Verna Elizabeth C

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Аннотация

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.

Для цитирования: Cullaro Giuseppe, Lai Jennifer C, Liu Taryn, Gomez Miguel E, Simonetto Douglas A, Lee Sean, Lee Brian P, Allegretti Andrew S, Mazumder Nikhilesh R, Patidar Kavish R, Verna Elizabeth C. Machine learning-derived clinical phenotypes of ascites in cirrhosis: A multi-center latent class analysis with external validation.. Liver transplantation : official publication of the American Association for the Study of Liver Diseases and the International Liver Transplantation Society. 2026. DOI: 10.1097/lvt.0000000000000942.
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