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Comparative Study
. 2021 Jun;15(3):753-765.
doi: 10.1007/s12072-021-10175-w. Epub 2021 Jun 25.

Comparative accuracy of prognostic models for short-term mortality in acute-on-chronic liver failure patients: CAP-ACLF

Nipun Verma  1 , Radha Krishan Dhiman  2 , Virendra Singh  1 , Ajay Duseja  1 , Sunil Taneja  1 , Ashok Choudhury  3 , Manoj Kumar Sharma  3 , C E Eapen  4 , Harshad Devarbhavi  5 , Mamun Al Mahtab  6 , Akash Shukla  7 , Saeed Sadiq Hamid  8 , Wasim Jafri  8 , Amna Shubhan Butt  8 , Qin Ning  9 , Tao Chen  9 , Soek Siam Tan  10 , Laurentius A Lesmana  11 , Cosmas Rinaldi A Lesmana  11 , Manoj K Sahu  12 , Jinhua Hu  13 , Guan Huei Lee  14 , Ajit Sood  15 , Vandana Midha  15 , Omesh Goyal  15 , Hasmik Ghazinian  16 , Dong Joon Kim  17 , Sombat Treeprasertsuk  18 , V G Mohan Prasad  19 , Abdul Kadir Dokmeci  20 , Jose D Sollano  21 , Samir Shah  22 , Diana Alcantara Payawal  23 , P N Rao  24 , Anand Kulkarni  24 , George K Lau  25 , Zhongping Duan  26 , Yu Chen  26 , Osamu Yokosuka  27 , Zaigham Abbas  28 , Fazal Karim  29 , Debashish Chowdhury  30 , Ananta Shrestha Prasad  31 , Shiv Kumar Sarin  3 ; APASL ACLF Working Party
Affiliations
Comparative Study

Comparative accuracy of prognostic models for short-term mortality in acute-on-chronic liver failure patients: CAP-ACLF

Nipun Verma et al. Hepatol Int. 2021 Jun.

Abstract

Background: Multiple predictive models of mortality exist for acute-on-chronic liver failure (ACLF) patients that often create confusion during decision-making. We studied the natural history and evaluated the performance of prognostic models in ACLF patients.

Methods: Prospectively collected data of ACLF patients from APASL-ACLF Research Consortium (AARC) was analyzed for 30-day outcomes. The models evaluated at days 0, 4, and 7 of presentation for 30-day mortality were: AARC (model and score), CLIF-C (ACLF score, and OF score), NACSELD-ACLF (model and binary), SOFA, APACHE-II, MELD, MELD-Lactate, and CTP. Evaluation parameters were discrimination (c-indices), calibration [accuracy, sensitivity, specificity, and positive/negative predictive values (PPV/NPV)], Akaike/Bayesian Information Criteria (AIC/BIC), Nagelkerke-R2, relative prediction errors, and odds ratios.

Results: Thirty-day survival of the cohort (n = 2864) was 64.9% and was lowest for final-AARC-grade-III (32.8%) ACLF. Performance parameters of all models were best at day 7 than at day 4 or day 0 (p < 0.05 for C-indices of all models except NACSELD-ACLF). On comparison, day-7 AARC model had the numerically highest c-index 0.872, best accuracy 84.0%, PPV 87.8%, R2 0.609 and lower prediction errors by 10-50%. Day-7 NACSELD-ACLF-binary was the simple model (minimum AIC/BIC 12/17) with the highest odds (8.859) and sensitivity (100%) but with a lower PPV (70%) for mortality. Patients with day-7 AARC score > 12 had the lowest 30-day survival (5.7%).

Conclusions: APASL-ACLF is often a progressive disease, and models assessed up to day 7 of presentation reliably predict 30-day mortality. Day-7 AARC model is a statistically robust tool for classifying risk of death and accurately predicting 30-day outcomes with relatively lower prediction errors. Day-7 AARC score > 12 may be used as a futility criterion in APASL-ACLF patients.

Keywords: AARC; APASL; CILF-C ACLF; Deaths; EASL; Liver failure; MELD; NACSELD; Natural history; Prediction.

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