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A nomogram using ocular hemodynamics and clinical factors accurately predicts ischemic stroke risk, offering a novel tool for early cerebrovascular assessment.

“Stroke constitutes a severe cerebrovascular condition and is the second leading cause of death and disability globally,” researchers wrote in the American Journal of Ophthalmology. “It is categorized into two types: ischemic and hemorrhagic, with ischemic stroke comprising approximately 80% of cases. …With the aging population worldwide, the prevalence of ischemic stroke is expected to increase gradually.”

Ocular vascular characteristics can be used to monitor cerebrovascular diseases due to similar physiologic characteristics, the researchers continued. They conducted a retrospective clinical cohort study to develop a nomogram prediction model for ischemic stroke using ocular hemodynamic characteristics.

The study included 337 patients aged 50 years and older. General data were collected, and ultrasonography was used to assess the hemodynamic parameters of the ophthalmic artery, central retinal artery, and posterior ciliary artery. Retinal vessel diameters were measured from color fundus images, and relevant laboratory indicators  were obtained for all patients. Logistic regression analysis was performed to identify risk factors for ischemic stroke.

The nomogram model combined traditional factors such as hypertension and hyperlipidemia with the ophthalmic artery resistance index (OA-RI) to comprehensively evaluate the risk of ischemic stroke, offering a novel perspective for studying the correlation between ocular blood flow and cerebrovascular diseases.

Nomogram Model Predictive for Ischemic Stroke

Among the 337 patients enrolled, the researchers identified 176 cases of ischemic stroke (mean age, 71.55 years; 67.05% men) and 161 control cases. The incidence of diabetes, hypertension, and hyperlipidemia was higher in the ischemic stroke group compared with the control group (all P<0.001). The researchers found no significant difference in ocular vascular parameters between groups.

Independent risk factors for ischemic stroke such as hypertension (OR, 2.17; 95% CI, 1.16-4.08; P=0.016), hyperlipidemia (OR, 2.21; 95% CI, 1.18-4.14; P=0.013), and OA-RI (OR, 5.98; 95% CI, 3.27-10.93; P<0.001) were identified by multivariate regression analysis.

The area under the receiving operator curve of the training cohort (n=235) was 0.790 (95% CI, 0.733-0.847) and 0.773 (95% CI, 0.679-0.866) for the validation cohort (n=102), revealing a consistent predictive capability of the nomogram model for ischemic stroke. Sensitivity and specificity were 0.776 and 0.672 in the training cohort and 0.822 and 0.491 in the validation cohort, respectively. Mean absolute errors for the training and validation cohorts were 0.020 and 0.013, respectively. In addition, decision curve analysis used to assess the clinical utility of the nomogram demonstrated good clinical benefit.

“Compared to traditional risk prediction models, the nomogram prediction model, when combined with ocular vascular hemodynamics, more effectively evaluates the risk of ischemic stroke,” the researchers wrote.