Predictive Ability of Preoperative PT-INR and Postoperative MCP1 for Post-hepatectomy Liver Failure

The rate of change in clinical indicators can predict the progression of hepatitis B virus-related acute-on-chronic preliver failure

The objective of this study was to investigate the predictors and predictive model construction of the progression of HBV-Pre.Acute-on-chronic liver failure (ACLF), a total of 133 patients with HBV-Pre.ACLF was divided into the progressive group (52 patients) and the recovery group (81 patients) according to whether they progressed to ACLF or not. The clinical parameters N%, L%, PLT, ALT, TBiL, ALB, Cre, Na, NH3, CRP, AFP, prothrombin time (PT), international normalized ratio (INR), FIB, and their rate of change at baseline were analyzed in the 2 groups. The independent risk factors for HBV-Pre.ACLF progression was found by univariate and multivariate analyses, and a predictive model was constructed. The clinical parameters ALB, FIB, Na, combined alprostadil treatment and MELD, and MELD-Na scores at baseline were significantly different between the 2 groups (P <.05), while ALT, TBiL, Cre, CHE, NH3, N%, L%, PLT, INR, and PT were not significantly different (P >.05). The change rates of Na, CHE, PT, FIB, CRP, Cre, PLT, and the ratio after to before of N% were significantly different between the 2 groups (P <.05), while the change rates of ALT, TBIL, NH3, AFP, L%, and the ratio after to before of INR were not significantly different between the 2 groups (P >.05). Univariate and multivariate analyses showed that baseline ALB, Na, FIB, combined alprostadil therapy and the rate of change of Na and PLT were protective factors for disease progression, and the rate of change of PT, CRP, and the ratio after to before of N% were independent risk factors for disease progression. The novel model was LogitP = -6.051 + 4.049×ΔPT + 0.626×ΔCRP + 4.527×the ratio after to before N% and its area under the curve was 0.944 (95% confidence interval: 0.900-0.988) predicting progression of HBV-Pre.ACLF, and the best cutoff value was -0.22. The patients with a higher logitP score (> -0.22) had an increased risk for progression to ACLF (P <.05). The novel model logitP shows good predictive value for the disease progression of HBV-Pre.ACLF.

Effect of early peri-operative arterial lactate concentration level ratios on post-hepatectomy liver failure

BACKGROUND

Post-hepatectomy liver failure (PHLF) is a serious complication after hepatectomy and a major cause of death. The current criteria for PHLF diagnosis (ISGLS consensus) require laboratory data of elevated INR level and hyperbilirubinemia on or after postoperative day 5. This study aims to propose a new indicator for the early clinical prediction of PHLF.

METHODS

The peri-operative arterial lactate concentration level ratios were derived from time points within the 3 days before surgery and within POD1, the patients were divided into two groups: high lactate ratio group (≥ 1) and low lactate ratio group (< 1). We compared the differences in morbidity rates between the two groups. Utilized logistic regression analysis to identify the risk factors associated with PHLF development and ROC curves to compare the predictive value of lactate ratio and other liver function indicators for PHLF.

RESULTS

A total of 203 patients were enrolled in the study. Overall morbidity and severe morbidity occurred in 64.5 and 12.8 per cent of patients respectively. 39 patients (19.2%) met the criteria for PHLF, including 15 patients (7.4%) with clinically relevant Post-hepatectomy liver failure (CR-PHLF). With a significantly higher incidence of PHLF observed in the lactate ratio ≥ 1 group compared to the lactate ratio < 1 group (n = 34, 26.8% vs. n = 5, 6.6%, P < 0.001). Multivariable logistic regression analysis revealed that a lactate ratio ≥ 1 was an independent predictor for PHLF (OR: 3.239, 95% CI 1.097-9.565, P = 0.033). Additionally, lactate ratio demonstrated good predictive efficacy for PHLF (AUC = 0.792).

CONCLUSIONS

Early assessment of peri-operative arterial lactate concentration level ratios may provide experience in early intervention of complications in patients with hepatocellular carcinoma, which can reduce the likelihood of PHLF occurrence and improve patient prognosis.

A Nomogram Based on Preoperative Inflammatory Indices and ICG-R15 for Prediction of Liver Failure After Hepatectomy in HCC Patients

Objective

To establish a nomogram based on inflammatory indices and ICG-R15 for predicting post-hepatectomy liver failure (PHLF) among patients with resectable hepatocellular carcinoma (HCC).

Methods

A retrospective cohort of 407 patients with HCC hospitalized at Xiangya Hospital of Central South University between January 2015 and December 2020, and 81 patients with HCC hospitalized at the Second Xiangya Hospital of Central South University between January 2019 and January 2020 were included in the study. Totally 488 HCC patients were divided into the training cohort (n=378) and the validation cohort (n=110) by random sampling. Univariate and multivariate analysis was performed to identify the independent risk factors. Through combining these independent risk factors, a nomogram was established for the prediction of PHLF. The accuracy of the nomogram was evaluated and compared with traditional models, like CP score (Child-Pugh), MELD score (Model of End-Stage Liver Disease), and ALBI score (albumin-bilirubin) by using receiver operating characteristic (ROC) curve, calibration curve, and decision curve analysis (DCA).

Results

Cirrhosis (OR=2.203, 95%CI:1.070-3.824, P=0.030), prothrombin time (PT) (OR=1.886, 95%CI: 1.107-3.211, P=0.020), tumor size (OR=1.107, 95%CI: 1.022-1.200, P=0.013), ICG-R15% (OR=1.141, 95%CI: 1.070-1.216, P<0.001), blood loss (OR=2.415, 95%CI: 1.306-4.468, P=0.005) and AST-to-platelet ratio index (APRI) (OR=4.652, 95%CI: 1.432-15.112, P=0.011) were independent risk factors of PHLF. Nomogram was built with well-fitted calibration curves on the of these 6 factors. Comparing with CP score (C-index=0.582, 95%CI, 0.523-0.640), ALBI score (C-index=0.670, 95%CI, 0.615-0.725) and MELD score (C-ibasedndex=0.661, 95%CI, 0.606-0.716), the nomogram showed a better predictive value, with a C-index of 0.845 (95%CI, 0.806-0.884). The results were consistent in the validation cohort. DCA confirmed the conclusion as well.

Conclusion

A novel nomogram was established to predict PHLF in HCC patients. The nomogram showed a strong predictive efficiency and would be a convenient tool for us to facilitate clinical decisions.