Preoperative predictors of liver decompensation after mini-invasive liver resection

Carlo Sposito, Michela Monteleone, Luca Aldrighetti, Umberto Cillo, Raffaele Dalla Valle, Alfredo Guglielmi, Giuseppe Maria Ettorre, Alessandro Ferrero, Fabrizio Di Benedetto, Giorgio Ettore Rossi, Luciano De Carlis, Felice Giuliante, Vincenzo Mazzaferro

Research output: Contribution to journalArticlepeer-review

Abstract

BACKGROUND: Post-hepatectomy liver failure (PHLF) represents the most frequent complication after liver surgery, and the most common cause of morbidity and mortality. Aim of the study is to identify the predictors of PHLF after mini-invasive liver surgery in cirrhosis and chronic liver disease, and to develop a model for risk prediction.

METHODS: The present study is a multicentric prospective cohort study on 490 consecutive patients who underwent mini-invasive liver resection from the Italian Registry of Mini-invasive Liver Surgery (I go MILS). Retrospective additional biochemical and clinical data were collected.

RESULTS: On 490 patients (26.5% females), PHLF occurred in 89 patients (18.2%). The only independent predictors of PHLF were Albumin-Bilirubin (ALBI) score (OR 3.213; 95% CI 1.661-6.215; p < .0.0001) and presence of ascites (OR 3.320; 95% CI 1.468-7.508; p = 0.004). Classification and regression tree (CART) modeling led to the identification of three risk groups: PHLF occurred in 23/217 patients with ALBI grade 1 (10.6%, low risk group), in 54/254 patients with ALBI score 2 or 3 and absence of ascites (21.3%, intermediate risk group) and in 12/19 patients with ALBI score 2 or 3 and evidence of ascites (63.2%, high risk group), p < 0.0001. The three groups showed a corresponding increase in postoperative complications (20.0%, 27.5% and 66.7%), Comprehensive Complication Index (5.1 ± 11.1, 6.0 ± 10.9 and 18.8 ± 18.9) and hospital stay (6.0 ± 4.0, 6.0 ± 6.0 and 8.0 ± 5.0 days).

CONCLUSION: The risk of PHLF can be stratified by determining two easily available preoperative factors: ALBI and ascites. This model of risk prediction offers an objective instrument for a correct clinical decision-making.

Original languageEnglish
Pages (from-to)718-727
Number of pages10
JournalSurgical Endoscopy
Volume35
Issue number2
DOIs
Publication statusPublished - Feb 2021

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