Objective To explore the influencing factors of delayed medical treatment in patients with stroke warning syndrome(SWS),and construct and validate the risk prediction model.Methods A total of 192 patients with SWS treated in our hospital from October 2021 to April 2023 were selected and divided into a modeling set and a validation set by the random number method at a ratio of 7:3.Patients in the modeling set were divided into a delayed group and a non-delayed group according to whether there was a delay in their medical treatment.Through the multi-factor Logistic regression analysis of influencing factors,a prediction model was established based on the regression method.The prediction efficacy was tested by using the work characteristic curve,calibration curve and clinical decision curve.Results Age,NIHSS score,distance from the place of onset to the hospital,family history of stroke,SHKS score,SSS score,and SSRS score were all influential factors in the delay in medical treatment for patients with SWS(p<0.05),and the model had good predictive performance and clinical benefit.Conclusion The predictive efficacy of the risk prediction model for delayed medical treatment for patients with SWS is good and may provide a basis for healthcare professionals to improve patients'medical visits behavior.
Stroke warning syndrome(SWS)Delays for medical treatmentPrediction model
NETL
NSTL
万方数据
