Nomogram Model for Predicting the Functional Outcomes in Patients With Minor Ischemic Stroke Based on Clinical Characteristics and Small Vessel Disease Burden.

Abstract

Objectives: Our purpose is to assess the role of total small vessel disease (SVD) burden affecting the clinical outcome and develop and validate a prognostic nomogram for minor ischemic stroke (MIS) patients.

Methods: Between January 2018 and April 2023, 454 MIS patients were enrolled. The functional outcome was the modified Rankin scale (mRS) score at 90 days. The least absolute shrinkage and selection operator (LASSO) regression and multivariate logistic regression model were used to identify prognostic predictors, and then a nomogram was drawn.

Results: Our nomogram comprising of systolic blood pressure (SBP), baseline National Institutes of Health Stroke Scale score (NIHSS), total SVD burden scores, coronary heart disease, disabling stroke, progressive stroke, alteplase treatment, and infarction location demonstrated a good discriminative power in both the training set (AUC=0.870; 95% CI: 0.827-0.912) and the internal validation set (AUC=0.876; 95% CI: 0.817-0.935). The calibration curve and DCA in our result showed the model's high degree of calibration and clinical value. The DeLong test was used to compare the AUCs between the nomogram and non-SVD burden score model in the training (P=0.028) and internal validation sets (P=0.013), indicating that our nomogram performs significantly better than the non-SVD burden score model.

Conclusions: The SVD burden is an important prognosis factor. Furthermore, the proposed nomogram has good discrimination, calibration, and clinical benefits and is better than the non-SVD burden score model in predicting the outcomes for MIS patients.