Supplemental Data Content to 'Data from 81 cases of subtotal cholecystectomy used to generate a multiple logistic regression model to predict postoperative bile leak'

This is the supplemental data content for the original paper titled “Multiple logistic regression model to predict bile leak associated with subtotal cholecystectomy” (Surg Endosc 2023 Apr 4:1–9. DOI: 10.1007/s00464-023-10049-2. Epub ahead of print. PMID: 37016083; PMCID: PMC10072799), and data article titled “Data from 81 cases of subtotal cholecystectomy used to generate a multiple logistic regression model to predict postoperative bile leak”. The study was reported according to the preferred reporting of case series in surgery (PROCESS) and transparent reporting of a multivariable prediction model for individual prognosis or diagnosis (TRIPOD) guidelines. The data are presented by FAIR (Findable, Accessible, Interoperable, Reusable) principles.

Multivariable logistic regression revealed two independent predictors of bile leak associated with subtotal cholecystectomy: open-tract STC (odds ratio [OR], 7.07; 95% confidence interval [CI], 2.191–25.89; P = 0.0170) and acute cholecystitis (OR, 5.449; 95% CI, 1.584–23.48; P = 0.0121). The area under the receiver-operating characteristic curve was 82.11% (95% CI, 72.87–91.34; P < 0.0001). Tjur’s pseudo-R2 was 0.3189, and the Hosmer–Lemeshow goodness-of-fit statistic was 4.916 (P = 0.7665).

This supplement for the Mendeley repository provides further details to reproduce the study results. It is organised into sections that follow the structure of the articles. It contains nine tables.