Nomogram to predict risk for early ischemic stroke by non-invasive method.

Abstract

Stroke is the acute onset of neurological deficits and is associated with high morbidity, mortality, and disease burden. In the present study, we aimed to develop a scientific, nomogram for non-invasive predicting risk for early ischemic stroke, in order to improve stroke prevention efforts among high-risk groups. Data were obtained from a total of 2151 patients with early ischemic stroke from October 2017 to September 2018 and from 1527 healthy controls. Risk factors were examined using logistic regression analyses. Nomogram and receiver operating characteristic (ROC) curves were drawn, cutoff values were established. Significant risk factors for early ischemic stroke included age, sex, blood pressure, history of diabetes, history of genetic, history of coronary heart disease, history of smoking. A nomogram predicting ischemic stroke for all patients had an internally validated concordance index of 0.911. The area under the ROC curve for the logistic regression model was 0.782 (95% confidence interval [CI]: 0.766–0.799, P < .001), with a cutoff value of 2.5. The nomogram developed in this study can be used as a primary non-invasive prevention tool for early ischemic stroke and is expected to provide data support for the revision of current guidelines.