Integrating serum globulin into the ICF framework: a novel multidimensional predictive model for 1-year mRS outcomes...

The long-term functional prognosis after ischemic stroke (IS) plays a crucial role in rehabilitation planning, yet it remains challenging to predict in clinical practice. Existing prognostic models primarily focus on short-term outcomes and lack integration of multidimensional determinants. Although elevated serum globulin levels have been associated with acute neuroinflammation and short-term disability, their prognostic significance for 1-year functional outcomes within a comprehensive biopsychosocial framework has not yet been established. To address these gaps, this study aimed to develop and validate a multidimensional prognostic model that integrates serum globulin as a key inflammatory biomarker into the International Classification of Functioning, Disability and Health (ICF) framework of the World Health Organization (WHO), with the objective of predicting 1-year functional outcome in patients with acute ischemic stroke (AIS).

This prospective study consecutively enrolled 1,562 AIS patients at a Grade A tertiary hospital from 2021 to 2023; after data cleaning and screening, 1,356 cases were included for analysis. Baseline data were collected within 1 week of hospital admission. The study cohort was randomly divided into a training set (70%, n = 949) for model development and a validation set (30%, n = 407) for internal validation. The primary outcome was the patients' functional status assessed using the modified Rankin Scale (mRS), 1-year post-admission. Predictors significant (p < 0.05) in univariate analysis within the training set were entered into backward stepwise multivariable logistic regression. The performance of the model was comprehensively evaluated using the area under the curve (AUC), Hosmer-Lemeshow test, calibration curve, and decision curve analysis (DCA).

Multivariable analysis identified six independent predictors (all p < 0.05): age, occupational status, BI, serum globulin, number of stroke episodes and NIHSS. A nomogram incorporating these predictors demonstrated excellent discrimination in both training (AUC = 0.90, 95% CI 0.88-0.93) and validation sets (AUC = 0.85, 95% CI 0.80-0.89). Calibration was good, with predicted probabilities (training: 22.23%; validation: 21.72%) closely matching the observed incidence of 22.20%, nonsignificant Hosmer-Lemeshow test results (p > 0.05), and well-aligned calibration curves. DCA confirmed the model's superior net benefit over "treat-all" and "treat-none" strategies across clinically relevant high-risk thresholds (20-80%) in both training and validation cohorts.

This study successfully integrated serum globulin into the ICF framework and constructed a prognostic model for the 1-year prognosis after AIS. It enables early identification of high-risk individuals and personalized rehabilitation strategies to improve long-term recovery.