Portal Vein Thrombosis in Cirrhosis: Incidence, Outcomes and Anticoagulation

Overview

Portal vein thrombosis (PVT) is a blood-clot complication that occurs in some people with liver cirrhosis and can worsen bleeding, ascites, encephalopathy and survival. However, doctors still lack reliable tools to predict who will develop PVT, how much it really shortens life, and whether anticoagulation (blood-thinner) treatment clearly improves outcomes and is safe.This multicentre, bidirectional cohort study will follow about 2,500 adults with cirrhosis cared for at seven major hospitals in China. The team will first review 1,682 historical cases recorded since 2010 and then prospectively enrol another 840 patients from June 2025 onward. Participants may or may not already have PVT when they enter the study. All will undergo routine blood tests and abdominal imaging, and will be followed at roughly 6 months, 1 year and 2 years after discharge, through clinic visits, hospital records or telephone calls. The study has three goals : 1. Identify risk factors for new PVT and build an easy-to-use prediction model. 2. Clarify the impact of PVT on prognosis, especially all-cause death and decompensation of cirrhosis. 3. Evaluate real-world anticoagulation: patients who receive blood-thinners will be compared with those who do not, looking at survival, clot progression or resolution, and major bleeding events. Because no experimental drug or random assignment is involved, participation does not change a patient's routine care. All personal information will be de-identified and protected according to Chinese data-security laws. Results from this study are expected to help doctors recognise high-risk patients earlier and choose safer, more effective anticoagulation strategies to improve quality of life and survival in cirrhosis.

Background and rationale Portal vein thrombosis (PVT) complicates ≈10-25 % of cirrhosis cases and is linked to variceal bleeding, ascites, hepatic encephalopathy and inferior transplant-free survival. Existing data are fragmented, largely single-centre, and often exclude patients managed without anticoagulation. Consequently, clinicians still lack robust, generalisable tools for (a) predicting incident PVT, (b) quantifying its true prognostic impact, and (c) balancing the benefits and risks of real-world anticoagulant therapy. Study design This is a seven-centre, bidirectional cohort comprising a retrospective arm (chart review of 1 682 cirrhotic adults hospitalised) and a prospective arm that will enrol ≈ 840 additional patients, yielding a total target size of ≈ 2 500 subjects. Eligible participants are aged ≥18 years, have imaging-confirmed cirrhosis (any aetiology), and can be stratified into three baseline states: (1) no PVT, (2) focal or partial PVT, or (3) occlusive/complete PVT. Key exclusions are hepatocellular carcinoma invading the portal vein, Budd-Chiari syndrome, current pregnancy, or life expectancy \< 3 months. Data collection and follow-up At index admission (or first study visit) the team records demographics, liver disease aetiology, Child-Pugh/MELD scores, thrombophilia panel, abdominal Doppler/CT, and treatment decisions (including anticoagulant class, dose and duration). Follow-up contacts are scheduled at 6 ± 1 months, 12 ± 2 months and 24 ± 3 months via clinic visit, electronic health record extraction or structured telephone interview . End-points captured at each contact include incident PVT, progression/regression of an existing thrombosis, major bleeding (ISTH criteria), liver-related decompensation, transplantation and all-cause mortality. Statistical plan Predictors of incident PVT will be screened with univariable Fine-Gray competing-risk models (death/transplant as competing events); independent factors will enter a multivariable model to derive a PVT-Risk Score. Model performance will be quantified by Harrell's C-index, time-dependent AUROC and calibration plots, with bootstrap internal validation and external temporal validation using the prospective sub-cohort. Propensity-score overlap weighting will compare anticoagulation versus no-anticoagulation for key outcomes, while multi-state Markov models will characterise transitions between "no PVT", "partial PVT", "complete PVT" and "death/transplant". Pre-specified subgroup analyses include Child-Pugh class, non-selective β-blocker use and thrombophilia status.