Quick chronic liver failure-sequential organ failure assessment: an easy-to-use scoring model for predicting mortality risk in critically ill cirrhosis patients.

Background And Aim: Critically ill cirrhosis patients have an increased risk of morbidity and mortality, even after admission to the ICU. Our objectives were to compare the predictive accuracy of model for end-stage liver disease (MELD), MELD-Na, UK model for end-stage liver disease, and chronic liver failure-sequential organ failure assessment (CLIF-SOFA) by the development and validation of an easy-to-use prognostic model [named quick CLIF-SOFA (qCLIF-SOFA)] for early risk prediction in critically ill patients with cirrhosis.

Patients And Methods: Overall, 1460 patients were extracted from the MIMIC-III database and enrolled in this study at 30-day and 90-day follow-up. qCLIF-SOFA was developed in the established cohort (n=730) and a performance analysis was completed in the validation cohort (n=730) using area under the receiver operating characteristic curve. Results were compared with CLIF-SOFA.

Results: The performance of CLIF-SOFA was significantly better than that of MELD, MELD-Na, and UK model for end-stage liver disease for predicting both 30-day and 90-day mortality (all P<0.05). qCLIF-SOFA consisted of five independent factors (bilirubin, creatinine, international normalized ratio, mean arterial pressure, and vasopressin) associated with mortality. In the established cohort, CLIF-SOFA and qCLIF-SOFA predicted mortality with area under the receiver operating characteristic curve values of 0.768 versus 0.743 at 30-day, 0.747 versus 0.744 at 90-day, and 0.699 versus 0.706 at 1 year, respectively (all P>0.05). A similar result was observed in the validation cohort (0.735 vs. 0.734 at 30 days, 0.723 vs. 0.737 at 90 days, and 0.682 vs. 0.700 at 1 year, respectively, all P>0.05).

Conclusion: The utility of CLIF-SOFA was further shown to predict mortality for critically ill cirrhosis patients. The novel and simpler qCLIF-SOFA model showed comparable accuracy compared with existing CLIF-SOFA for prognostic prediction.