Currently, there are no robust models for predicting the outcome of acute-on-chronic hepatitis B liver failure (ACHBLF). We aimed to establish and validate a new prognostic scoring system, named ALPH-Q, that integrates electrocardiography parameters that may be used to predict short-term mortality of patients with ACHBLF.
Two hundred fourteen patients were included in this study. The APLH-Q score was constructed by Cox proportional hazard regression analysis and was validated in an independent patient cohort. The area under the receiver-operating characteristic curve was used to compare the performance of different models, including APLH-Q, Child–Pugh score (CPS), model of end-stage liver disease (MELD), and a previously reported logistic regression model (LRM).
The APLH-Q score was constructed with 5 independent risk factors, including age (HR = 1.034, 95% CI: 1.007–1.061), liver cirrhosis (HR = 2.753, 95% CI: 1.366–5.548), prothrombin time (HR = 1.031, 95% CI: 1.002–1.062), hepatic encephalopathy (HR = 2.703, 95% CI: 1.630–4.480), and QTc (HR = 1.008, 95% CI: 1.001–1.016). The performance of the ALPH-Q score was significantly better than that of MELD and CPS in both the training (0.896 vs 0.712, 0.896 vs 0.738, respectively, both P < 0.05) and validation cohorts (0.837 vs 0.689, 0.837 vs 0.585, respectively, both P < 0.05). Compared with LRM, APLH-Q also showed a better performance (0.896 vs 0.825, 0.837 vs 0.818, respectively).
We have developed a novel APLH-Q score with greater performance than CPS, MELD, and LRM for predicting short-term mortality of patients with ACHBLF.