Analysis of Risk Factors and Establishment of a Prediction Model for Acute Cholecystitis in Asymptomatic Gallbladder...

To identify the risk factors for acute cholecystitis (AC) in patients with asymptomatic gallbladder stone (AGS) and to establish a clinical prediction model.

A descriptive study. Place and Duration of the Study: Department of Hepatobiliary and Pancreatic Surgery, Shaoxing Central Hospital, Shaoxing, China, from January 2023 to January 2025.

A total of 43 AGS patients and 86 AC patients were enrolled. Univariate analysis identified clinically significant indicators, which were incorporated into a multivariate binary logistic regression model to construct a nomogram. The receiver operating characteristic (ROC) curve, calibration curve, concordance index (C-index), and decision curve analysis (DCA) were used to evaluate model performance.

Univariate analysis showed higher blood glucose, gallbladder length/width, gallbladder wall thickness, gallbladder neck stones, sludge-like stones, and positive bile culture in the AC group (all p <0.05). Independent risk factors were identified by multivariate analysis, which included blood glucose ≥6.75 mmol/L, gallbladder width ≥30.5 mm, wall thickness ≥3.15 mm, gallbladder neck stones, and sludge-like stones (p <0.05). The calibration curve exhibited excellent consistency between the predictive model and actual clinical reality. The C-index was 0.905 (95% CI: 0.876-0.934), and the area under the curve (AUC) was 0.924 (95% CI: 0.880-0.967), confirming the model's excellent discriminative ability.

Blood glucose ≥6.75 mmol/L, gallbladder width ≥30.5 mm, wall thickness ≥3.15 mm, gallbladder neck stone, and sludge-like stones serve as independent risk factors for AC in the AGS patients. This model exhibits good predictive performance and high clinical utility.

Asymptomatic gallstone, Acute cholecystitis, Risk factors, Prediction model, AGS.