Development of a Prediction Model for Combined Assessment of SII, Albumin, and Fibrinogen to Evaluate Frailty Risk in Patients with Inflammatory Bowel Disease.

Background: Frailty is frequently observed in patients with inflammatory bowel disease (IBD) and is strongly associated with adverse clinical outcomes. This study aimed to develop a risk prediction model for frailty in IBD patients by integrating three key indicators: systemic immune-inflammation index (SII), albumin (Alb), and fibrinogen (FIB). The objective was to establish an early identification approach for frailty and contribute to reducing the disease burden. Methods: Among the 344 patients diagnosed with IBD, 61 were identified as frail. Factors that exhibited significant differences in univariate analysis were incorporated into a multivariable binary logistic regression model to identify independent predictors of frailty in IBD patients. Receiver operating characteristic (ROC) curves were generated to evaluate the predictive efficacy of SII, Alb, and FIB in the occurrence of frailty. A nomogram prediction model was developed, and its performance was assessed using the concordance index (C-index) and calibration curves. Results: The incidence of frailty in the training and validation sets was 17.8% and 17.6%, respectively. Multivariable binary logistic regression analysis indicated that a high Pittsburgh Sleep Quality Index (PSQI) score, elevated SII, increased FIB levels, and reduced Alb levels were significant risk factors for frailty in IBD patients. ROC analysis for both the training and validation sets demonstrated that the predictive ability of the combined serological and demographic indicators was superior to that of any single indicator, with area under the curve (AUC) values of 0.906 and 0.904, respectively. The C-index of the nomogram model in the training set was 0.917, confirming its strong predictive performance in both datasets. Conclusion: Preoperative serological testing provides an effective method for predicting frailty in IBD patients. The frailty risk prediction model developed in this study demonstrated high predictive accuracy and serve as a valuable tool for the clinical assessment of frailty risk in IBD patients.