A Novel Nomogram to Predict Early Neurological Deterioration in Patients with Acute Ischemic Stroke.

BACKGROUND: Acute ischemic stroke (AIS) is a vital cause of mortality and morbidity in China. Many AIS patients develop early neurological deterioration (END). This study was aimed to construct a nomogram to predict END in AIS patients. METHODS: AIS patients in Nanjing First Hospital were recruited as the training cohort. Additional patients in Nantong Third People's Hospital were enrolled as the validation cohort. Multivariate logistic regression was utilized to establish the nomogram. Discrimination and calibration performance of the nomogram was tested by concordance index (c-index) and calibration plots. Decision curve analysis (DCA) was employed to assess the utility of the nomogram. RESULTS: We recruited 1889 and 818 patients in the training and validation cohorts, respectively. Age (odds ratio [OR], 1.075; 95% confidence interval [CI], 1.059-1.091), diabetes mellitus (OR, 1.673; 95% CI, 1.181-2.370), atrial fibrillation (OR, 3.297; 95% CI, 2.005-5.421), previous antiplatelet (OR, 0.473; 95% CI, 0.301-0.744), hyper-sensitive C-reactive protein (Hs-CRP) (OR, 1.049; 95% CI, 1.036-1.063) and baseline National Institutes of Health Stroke Scale (NIHSS) (OR, 1.071; 95% CI, 1.045-1.098) were associated with END and incorporated in the nomogram. C-index was 0.826 (95% CI, 0.785-0.885) and 0.798 (95% CI, 0.749-0.847) in the training and validation cohorts. By DCA, the model was relevant between thresholds of 0.06 and 0.90 in the training cohort, as well as 0.08 and 0.77 in the validation cohort. CONCLUSIONS: The nomogram comprised of Hs-CRP, age, diabetes mellitus, atrial fibrillation, previous antiplatelet and baseline NIHSS may predict the risk of END in AIS patients.