Surgical endoscopy · 2026
Derivation and internal validation of the enhanced liver fibrosis (ELF)-based prediction score for advanced liver fibrosis in obese patients undergoing bariatric surgery.
СтатьяВалидационное исследованиеНазвание и аннотация: Перевод пока не подготовлен
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Gagal Saksham, Rath Brahma Kumar, Khan Washim Firoz, Baksi Aditya, Arumugaswamy Prasanna, Singh Archna, Yadav Rajni, Shalimar, Aggarwal Sandeep, Bhattacharjee Hemanga Kumar
Аннотация
BACKGROUND: Liver fibrosis in obese patients with Metabolic Dysfunction-Associated Steatotic Liver Disease (MASLD) is associated with liver-related complications and mortality. While liver biopsy is the gold standard for assessing fibrosis, it is unsuitable for follow-up. Contemporary non-invasive alternatives for detecting fibrosis are insufficient for accurate surgical risk stratification in bariatric patients. We aimed to develop and internally validate a multivariable prediction score using the Enhanced Liver Fibrosis (ELF) test, liver stiffness measurement (LSM), and routine preoperative laboratory tests and compare its performance against established non-invasive tests (NITs).
METHODS: This prospective study was conducted at AIIMS, New Delhi, from January 2022 to August 2025. All patients underwent standard preoperative evaluation and investigations, followed by intraoperative liver biopsy for histological assessment. The best multivariable logistic regression model was derived for advanced fibrosis (≥ F3) and internally validated with 2000 bootstrap resamples.
RESULTS: In a complete-case analysis of 189 patients, with a mean BMI of 46.3 ± 8.2 kg/m2, liver biopsy revealed advanced fibrosis in 33 patients (17.5%). The final advanced fibrosis severity in obesity (AFSO) score retained LSM (OR 4.83, 95% CI 2.35-9.93), ELF score (OR 2.92, 95% CI 1.64-5.20), and platelet count (OR 0.99, 95% CI 0.983-0.997) as independent predictors of advanced fibrosis. Discrimination was excellent [AUROC (95CI) 0.91; (0.86-0.96)]. Calibration accuracy was good (Optimism: 0.015; Brier score: 0.093). Rule-out and rule-in cutoffs were 0.15 for sensitivity ≥ 0.91 (negative predictive value, 0.98) and 0.31 for specificity ≥ 0.90 (positive predictive value, 0.59), respectively. Compared with existing NITs, the new model demonstrated superior diagnostic accuracy and clinical utility (p < 0.001).
CONCLUSION: This score provides an accurate, non-invasive alternative to liver biopsy for ruling out advanced fibrosis in patients with obesity undergoing bariatric surgery, with potential utility for longitudinal follow-up. External validation is warranted before clinical implementation.
METHODS: This prospective study was conducted at AIIMS, New Delhi, from January 2022 to August 2025. All patients underwent standard preoperative evaluation and investigations, followed by intraoperative liver biopsy for histological assessment. The best multivariable logistic regression model was derived for advanced fibrosis (≥ F3) and internally validated with 2000 bootstrap resamples.
RESULTS: In a complete-case analysis of 189 patients, with a mean BMI of 46.3 ± 8.2 kg/m2, liver biopsy revealed advanced fibrosis in 33 patients (17.5%). The final advanced fibrosis severity in obesity (AFSO) score retained LSM (OR 4.83, 95% CI 2.35-9.93), ELF score (OR 2.92, 95% CI 1.64-5.20), and platelet count (OR 0.99, 95% CI 0.983-0.997) as independent predictors of advanced fibrosis. Discrimination was excellent [AUROC (95CI) 0.91; (0.86-0.96)]. Calibration accuracy was good (Optimism: 0.015; Brier score: 0.093). Rule-out and rule-in cutoffs were 0.15 for sensitivity ≥ 0.91 (negative predictive value, 0.98) and 0.31 for specificity ≥ 0.90 (positive predictive value, 0.59), respectively. Compared with existing NITs, the new model demonstrated superior diagnostic accuracy and clinical utility (p < 0.001).
CONCLUSION: This score provides an accurate, non-invasive alternative to liver biopsy for ruling out advanced fibrosis in patients with obesity undergoing bariatric surgery, with potential utility for longitudinal follow-up. External validation is warranted before clinical implementation.