Objective Based on single center data,to investigate the predictive factors of motor dysfunction in stroke patients,and the nomogram prediction model was established and verified.Methods The patients with stroke who were treated in Affiliated Hospital of Yangzhou University hospital from January 2021 to November 2022 were selected as the research objects,and the patients were taken as the occurrence group and the non occurrence group according to whether there was motor dysfunction;The risk factors of motor dysfunction were screened by multi-factor Logistic regression analysis,and the nomogram prediction model was constructed by R 4.0.3 software;ROC curve and calibration graph were applied to verify the discrimination and consistency of the model.Results In this study,198 of 267 stroke patients had motor dysfunction,with an incidence of 74.16％;Multivariate Logistic regression analysis showed that female(OR=7.143),education level of junior high school or below(OR=3.462),age ≥65 years(OR=3.923),course of disease(OR=6.622),diabetes(OR=3.551),atrial fibrillation(OR=6.138),recurrence(OR=2.962),admission NIHSS score(OR=1.745)were all risk factors affecting the occurrence of motor dysfunction(P＜0.05);based on the above risk factors,an nomograph model was established to predict the risk of motor dysfunction in stroke patients,the ROC curve showed that the AUC of this model for predicting the risk of stroke was 0.961(95％CI:0.942-0.981).H-L goodness of fit test showed that the deviation between the actual observation value and the risk prediction value in the nomogram model was not statistically obvious(x2=6.154,P=0.630).Conclusion There are many independent risk factors affecting the occurrence of motor dysfunction in stroke patients.The constructed nomogram prediction model can effectively predict the occurrence risk of motor dysfunction and provide reference for individual clinical diagnosis and treatment.
StrokeMotor dysfunctionRisk factorsNomograph model
维普
万方数据
