Abstract
Objective: A proportion of acute ischemic stroke (AIS) patients suffer from early neurological deterioration (END) within 24 hours following intravenous thrombolysis (IVT), which greatly increases the risk of poor prognosis of these patients. Therefore, we aimed to explore the predictors of early neurological deterioration of ischemic origin (END i ) in AIS patients after IVT and develop a nomogram prediction model. Methods: This study collected 244 AIS patients with post-thrombolysis END i as the derivation cohort and 155 patients as the validation cohort. In the derivation cohort, multivariable logistic regression analysis was used to identify the independent risk factors for END i , which were subsequently used to establish the nomogram predictive model. Furthermore, the validation cohort data were used for external validation of the nomogram. Results: The results of multivariable logistic regression analysis showed that neutrophil to lymphocyte ratio (NLR) (OR 2.616, 95% CI 1.640-4.175, P<0.001), mean platelet volume (MPV) (OR 3.334, 95% CI 1.351-8.299, P=0.009), body mass index (BMI) (OR 1.979, 95% CI 1.285-3.048, P=0.002) and atrial fibrillation (AF) (OR 8.012, 95% CI 1.341-47.873, P=0.023) were significantly associated with END i . The area under the curve of the prediction model constructed from the above four factors was 0.981 (95% CI 0.961-1.000) and the calibration curve was close to the ideal diagonal line. Furthermore, decision curve analysis showed a significantly greater net benefit of the nomogram. These results were successfully validated internally and externally. Conclusions: NLR, MPV, BMI and AF were independent risk factors and predictors of END i . The nomogram prediction model based on these four factors exhibited good discrimination and calibration power. It might be a reliable and easy-to-use tool to predict post-thrombolysis END i in AIS patients. Keywords: Acute ischemic stroke; early neurological deterioration; intravenous thrombolysis; nomogram; prediction model
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