Hernaez, Ruben; Karvellas, Constantine J; Liu, Yan; Sacleux, Sophie-Caroline; Khemichian, Saro; Stein, Lance L; Shetty, Kirti; ... Multi-Organ Dysfunction and Evaluation for Liver Transplantation; + view all Hernaez, Ruben; Karvellas, Constantine J; Liu, Yan; Sacleux, Sophie-Caroline; Khemichian, Saro; Stein, Lance L; Shetty, Kirti; Lindenmeyer, Christina C; Boike, Justin R; Simonetto, Douglas A; Rahimi, Robert S; Jalal, Prasun K; Izzy, Manhal; Kriss, Michael S; Im, Gene Y; Lin, Ming V; Jou, Janice H; Fortune, Brett E; Cholankeril, George; Kuo, Alexander; Mahmud, Nadim; Kanwal, Fasiha; Saliba, Faouzi; Sundaram, Vinay; Artzner, Thierry; Jalan, Rajiv; Multi-Organ Dysfunction and Evaluation for Liver Transplantation; - view fewer (2023) The novel SALT-M score predicts 1-year post-transplant mortality in patients with severe acute-on-chronic liver failure. Journal of Hepatology , 79 (3) pp. 717-727. 10.1016/j.jhep.2023.05.028.

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Abstract

BACKGROUND & AIMS: Patients with acute-on-chronic liver failure grades 2/3 (severe ACLF) have 28-day mortality ranging from 30-90%. Though liver transplantation (LT) has demonstrated a survival benefit, the scarcity of donor organs and uncertainty regarding post-LT mortality among patients with severe ACLF may cause provider hesitation to proceed with LT. We developed and externally validated a model to predict 1-year post-LT mortality in severe ACLF, called the Sundaram ACLF-LT-M probability score, and estimated the median length of stay (LoS) after LT (ACLF-LT-LoS). METHODS: In 15 LT centers in the USA, we retrospectively identified a cohort of severe ACLF patients transplanted between 2014-2019, followed up to Jan'2022. Candidate predictors included demographics, clinical, laboratory values, and organ failures. We selected predictors in the final model using clinical criteria and externally validated them in two French cohorts. We provided measures of overall performance, discrimination, and calibration. We used multivariable median regression to estimate LoS after adjusting for clinically relevant factors. RESULTS: We included 735 patients, of whom 521 (70.8%) had severe ACLF (120 ACLF3,external cohort). The median age was 55 years, and 104 with severe ACLF (19.9%) died within 1-year post-LT. Our final model included age > 50 years, use of 1/2+ inotropes, presence of respiratory failure, diabetes mellitus, and body mass index (BMI, continuous). The c-statistic was 0.72 (derivation) and 0.80 (validation), indicating adequate discrimination and calibration based on the observed/expected probability plots. Age, respiratory failure, BMI, and presence of infection independently predicted median LoS. CONCLUSIONS: The ACLF-LT-M score predicts mortality within 1-year after LT in patients with ACLF.The ACLF-LT-LoS score predicted median post-LT stay. Future studies using the ACLF-LT scores could assist in determining transplant benefits. IMPACT AND IMPLICATIONS: Acute-on-chronic liver failure (ACLF) is a common syndrome, characterized by multi-organ failure in patients with cirrhosis associated with high-short term mortality. Liver transplantation (LT) may be the only life-saving procedure available to these patients but clinically unstability can augment the perceived risk of post-transplant mortality at one year. We provided a parsinominous score with clinically, and readily available parameters to objectively assess 1-year post LT survival and predict median length of stay after LT. Using modern estimation techniques, we developed and externally validated a clinical score model called the Sundaram ACLF-LT-Mortality score in 521 U.S. patients with ACLF with 2 or 3+ organ failure (s) and 120 French patients with grade ACLF-3. The area under the receiver operating characteristics curve was 0.72 in the development cohort and 0.80 in the validation cohort. We also provided an estimation of the median length of stay after LT in these patients. Our models can be incorporated in the discussion of risks/benefits in patients with severe ACLF listed for LT. Nevertheless, the score is far from perfect and other factors, such as patient's preference and center-specific factors, need to be considered whe using these tools.

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