Clinical Prediction Model for Screening Acute Ischemic Stroke Patients With More Than 10 Cerebral Microbleeds

BackgroundHemorrhagic transformation is one of the most serious complications in intravenous thrombolysis. Studies show that the existence of more than 10 cerebral microbleeds is strongly associated with hemorrhagic transformation. The current study attempts to develop and validate a clinical prediction model of more than 10 cerebral microbleeds. MethodsWe reviewed the computed tomography markers of cerebral small vessel diseases and the basic clinical information of acute ischemic stroke patients who were investigated using susceptibility weighted imaging from 2018 to 2021. A clinical prediction model of more than 10 cerebral microbleeds was established. Discrimination, calibration, and the net benefit of the model were assessed. Finally, a validation was conducted to evaluate the accuracy and stability of the model. ResultsThe multivariate logistic regression model showed hypertension, and some computed tomography markers (leukoaraiosis, lacunar infarctions, brain atrophy) were independent risk factors of more than 10 cerebral microbleeds. These risk factors were used for establishing the clinical prediction model. The area under the receiver operating characteristic curve (AUC) was 0.894 (95% CI: 0.870-0.919); Hosmer-Lemeshow chi-squared test yielded chi(2) = 3.946 (P = 0.862). The clinical decision cure of the model was higher than the two extreme lines. The simplified score of the model ranged from 0 to 12. The model in the internal and external validation cohort also had good discrimination (AUC 0.902, 95% CI: 0.868-0.937; AUC 0.914, 95% CI: 0.882-0.945) and calibration (P = 0.157, 0.247), and patients gained a net benefit from the model. ConclusionsWe developed and validated a simple scoring tool for acute ischemic stroke patients with more than 10 cerebral microbleeds; this tool may be beneficial for paradigm decision regarding intravenous recombinant tissue plasminogen activator therapy of acute ischemic stroke.