PP160 - A MULTIMODAL MODEL INTEGRATING NUTRITIONAL, HEPATIC, INFLAMMATORY AND SURGICAL FACTORS ACCURATELY PREDICTS POSTOPERATIVE MORBIDITY AFTER LIVER RESECTION

PP160

A MULTIMODAL MODEL INTEGRATING NUTRITIONAL, HEPATIC, INFLAMMATORY AND SURGICAL FACTORS ACCURATELY PREDICTS POSTOPERATIVE MORBIDITY AFTER LIVER RESECTION

L. PEREZ SANTIAGO^1,*, S. Amores Alandi², E. Muñoz-Forner^3,4, B. Alabadí-Pardiñes², P. Melgar-Requena⁵, Á. Abad-González⁶, J. M. Ramia⁵, R. Amrani⁷, I. Mora-Oliver³, M. Garcés-Albir ^3,4, J. Salinas Gómez⁸, S. Palma Milla⁹, M. Bellver¹⁰, I. Castro De la Vega¹¹, M. Serradilla-Martín¹², F. Losfablos Callau¹³, P. Sánchez-Velázquez¹⁴, M. D. Muns¹⁵, M. Civera Andrés², L. Sabater-Ortí^3,16, D. Dorcaratto³

¹Department of General and Digestive Surgery, Hospital Clinico Universitario. INCLIVA Biomedical Research Institute, Colorectal Surgery Unit, ²Department of Endocrinology and Nutrition. Hospital Clinico Universitario. INCLIVA Biomedical Research Institute, Body Composition Unit, ³Department of General and Digestive Surgery, Hospital Clinico Universitario. INCLIVA Biomedical Research Institute, Liver-Biliary and Pancreatic Surgery Unit, ⁴Department of Anatomy, University of Valencia, Valencia, ⁵Hepatobiliary and Pancreatic Surgery Unit, Department of General and Digestive Surgery, Hospital General Universitario de Alicante, Liver-Biliary and Pancreatic Surgery Unit, ⁶Hepatobiliary and Pancreatic Surgery Unit, Department of General and Digestive Surgery, Hospital General Universitario de Alicante, ⁷Department of Endocrinology and Nutrition. Hospital Clinico Universitario. INCLIVA Biomedical Research Institute, Endocrinology and Nutrition Department, Alicante, ⁸Department of General and Digestive Surgery, Hospital La Paz, Liver-Biliary and Pancreatic Surgery Unit, ⁹Department of Endocrinology and Nutrition. Hospital La Paz, Endocrinology and Nutrition Department, Madrid, ¹⁰Department of General and Digestive Surgery, Hospital General Universitario de Castellón, Liver-Biliary and Pancreatic Surgery Unit, ¹¹Department of Endocrinology and Nutrition. Hospital General Universitario de Castellón, Endocrinology and Nutrition Department, Castellón, ¹²Department of General and Digestive Surgery, Hospital Miguel Servert, Liver-Biliary and Pancreatic Surgery Unit, ¹³Department of Endocrinology and Nutrition. Hospital Miguel Servet, Endocrinology and Nutrition Department, Zaragoza, ¹⁴Department of General and Digestive Surgery, Hospital del Mar, Liver-Biliary and Pancreatic Surgery Unit, ¹⁵Department of Endocrinology and Nutrition. Hospital del Mar, Endocrinology and Nutrition Department, Barcelona, ¹⁶Departmen of Surgery, University of Valencia, Valencia, Spain

Rationale: Accurate perioperative risk stratification in liver surgery requires integration of multiple domains, including nutritional status, liver function, systemic inflammation and surgical factors. This study aimed to develop a multimodal model to predict postoperative complications.

Methods: Prospective observational study including 99 consecutive adult patients undergoing elective liver resection. Preoperative assessment included GLIM-defined malnutrition and Albumin–Bilirubin (ALBI) grade. Surgical approach (laparoscopic vs open) and postoperative inflammatory response (C-reactive protein, PCR) were recorded. Postoperative complications were graded using the Clavien–Dindo classification and the Comprehensive Complication Index (CCI). Multivariable logistic regression was used to identify independent predictors and build a predictive model. Model discrimination was assessed using the area under the receiver operating characteristic curve (AUC).

Results: ALBI grade 2 (OR 9.87, 95% CI 1.24–78.71; p=0.03), GLIM-defined moderate/severe malnutrition (OR 8.35, 95% CI 1.31–53.05; p=0.02), and postoperative PCR ≥89.5 mg/L (OR 6.51, 95% CI 1.43–29.63; p=0.01) were independently associated with postoperative complications, whereas laparoscopic approach was protective (OR 0.22, 95% CI 0.05–0.99; p=0.04). The model showed excellent discrimination, with an AUC of 0.88 (95% CI 0.80–0.96; p<0.001).

Conclusion: A multimodal model integrating nutritional, hepatic, inflammatory and surgical factors provides accurate prediction of postoperative morbidity after liver resection. This approach may improve perioperative risk stratification and support individualized patient management.

Disclosure of Interest: None declared