Objective:To analyze the influencing factors of post-stroke fatigue(PSF)in the acute phase of elderly patients with ischemic stroke(IS),to construct a risk predictive model for PSF in the acute phase of elderly IS patients,and to evaluate the prediction effect of the model by internal and external verification.Methods:A total of 438 elderly IS patients(330 in the training set and 108 in the validation set)were selected from October 2022 to October 2023 in two tertiary hospitals in Nanning.Lasso regression was used to screen the predictive variables,and a multivariate Logistic regression model was constructed based on the screened predictive variables,and the Nomogram of the model was drawn.The validation and evaluation of the model were mainly based on the area under curve(AUC)of the receiver operating characteristic curve,the Hosmer-Lemeshow test(H-L test),and the actual clinical net benefit of the model was evaluated according to the decision curve analysis(DCA).Results:Based on the Lasso regression penalty contraction method,four predictors of age,diabetes history,previous stroke history,and regular exercise were selected.Further construction of the Logistic regression model showed that higher age,diabetes history,and previous stroke history were risk factors for PSF,and regular exercise was a protective factor for PSF(P<0.05).The internal and external validation showed that the model had better predictive performance.The AUC of the training set was 0.836(95%CI 0.792-0.880),the sensitivity was 73.0%,the specificity was 83.6%,and the Youden index was 0.566.The AUC of the validation set was 0.798(95%CI 0.712-0.884),the sensitivity was 82.0%,the specificity was 68.1%,and the Youden index was 0.501.The H-L test(training set χ2 =10.452,P =0.235,validation set χ2 =7.042,P =0.425,)showed that the model had good consistency and goodness of fit.The DCA results showed that when the threshold probabilities of training set and validation set were 0.10～0.94 and 0.18～0.99,respectively,the clinical effectiveness of the model was higher.Conclusion:The model constructed in this study has a good prediction effect,which can provide reference for clinical nurses to identify PSF in the acute phase of elderly IS patients and implement preventive nursing.
elderly patientsischemic strokepost-stroke fatiguepredictive model
NETL
NSTL
维普
万方数据
