Predictive Models for Non-Alcoholic Fatty Liver Disease Diagnosis in Mexican Patients with Gallstone Disease: Sex-Specific Insights

• Published in: Diagnostics (Basel) 2024-07, Vol.14 (14), p.1487
• Main Authors: Rodríguez-Hernández, Nemry, Lazo-de-la-Vega-Monroy, María-Luisa, Ruiz-Noa, Yeniley, Preciado-Puga, Monica-Del-Carmen, Garcia-Ramirez, Juana-Rosalba, Jordan-Perez, Benjamin, Garnelo-Cabañas, Serafin, Ibarra-Reynoso, Lorena-Del-Rocío
• Format: Article
• Language: English
• Subjects: Biopsy; Body mass index; Cholecystectomy; Decision-making; Diseases; Fatty liver; Gallbladder; gallstone disease; Gallstones; Glucose; Health care industry; High density lipoprotein; Hospitals; Inflammation; Laparoscopy; Liver cirrhosis; Liver diseases; Medical diagnosis; Metabolic syndrome; Mexico; NAFLD diagnosis; Obesity; Patients; predictive models; sex-specific variations; Type 2 diabetes; Ultrasonic imaging; Weight control; Womens health
• ISSN: 2075-4418; 2075-4418
• DOI: 10.3390/diagnostics14141487

(1) Background: Evidence regarding Non-Alcoholic Fatty Liver Disease (NAFLD) diagnosis is limited in the context of patients with gallstone disease (GD). This study aimed to assess the predictive potential of conventional clinical and biochemical variables as combined models for diagnosing NAFLD in patients with GD. (2) Methods: A cross-sectional study including 239 patients with GD and NAFLD diagnosed by ultrasonography who underwent laparoscopic cholecystectomy and liver biopsy was conducted. Previous clinical indices were also determined. Predictive models for the presence of NAFLD stratified by biological sex were obtained through binary logistic regression and sensitivity analyses were performed. (3) Results: For women, the model included total cholesterol (TC), age and alanine aminotransferase (ALT) and showed an area under receiver operating characteristic curve (AUC) of 0.727 ( < 0.001), sensitivity of 0.831 and a specificity of 0.517. For men, the model included TC, body mass index (BMI) and aspartate aminotransferase (AST), had an AUC of 0.898 ( < 0.001), sensitivity of 0.917 and specificity of 0.818. In both sexes, the diagnostic performance of the designed equations was superior to the previous indices. (4) Conclusions: These models have the potential to offer valuable guidance to healthcare providers in clinical decision-making, enabling them to achieve optimal outcomes for each patient.