Background/purpose: Overt hepatic encephalopathy (HE) risk should be preoperatively predicted to identify patients suitable for curative transjugular intrahepatic portosystemic shunt (TIPS) instead of palliative treatments.
Methods: A total of 185 patients who underwent TIPS procedure were randomised (130 in the training dataset and 55 in the validation dataset). Clinical factors and imaging characteristics were assessed. Three different models were established by logistic regression analyses based on clinical factors (ModelC), imaging characteristics (ModelI), and a combination of both (ModelCI). Their discrimination, calibration, and decision curves were compared, to identify the best model. Subgroup analysis was performed for the best model.
Results: ModelCI, which contained two clinical factors and two imaging characteristics, was identified as the best model. The areas under the curve of ModelC, ModelI, and ModelCI were 0.870, 0.963, and 0.978 for the training dataset and 0.831, 0.971, and 0.969 for the validation dataset. The combined model outperformed the clinical and imaging models in terms of calibration and decision curves. The performance of ModelCI was not influenced by total bilirubin, Child-Pugh stages, model of end-stage liver disease score, or ammonia. The subgroup with a risk score ≥ 0.88 exhibited a higher proportion of overt HE (training dataset: 13.3% vs. 97.4%, p < 0.001; validation dataset: 0.0% vs. 87.5%, p < 0.001).
Conclusion: Our combination model can successfully predict the risk of overt HE post-TIPS. For the low-risk subgroup, TIPS can be performed safely; however, for the high-risk subgroup, it should be considered more carefully.
Keywords: Calibration; Clinical factor; Combined model; Decision curve; Discrimination; Imaging characteristics; Nervous system toxicity; Preoperative prediction; Risk stratification; TIPS.
© 2021. The Author(s).