A nomogram to predict the risk of falling down from bed in semi-disabled elderly stroke patients
Objective To investigate the influencing factors for falling down from bed in semi-disabled elderly stroke patients,and to create a nomogram and formulate targeted prevention and treatment measures to reduce the risk of falling down from bed.Methods Clinical data of 374 semi-disabled elderly stroke patients from January 2020 to December 2022 were retrospectively collected and randomly divided into modeling group and verification group at a ratio of 7∶3.Univariate and multivariate Logistic regression analyses were performed to screen the risk factors for falling down from bed in semi-disabled elderly stroke patients.Stepwise Logistic regression and Lasso-Logistic regression models were established for parameter estimation.Based on the Lasso-Logistic regression equation,the risk factors falling down from bed in semi-disabled elderly stroke patients were screened to construct a nomogram,and internal verification was carried out to evaluate its prediction efficiency and clinical effectiveness.Results Among 374 cases,totally 369 questionnaires were effectively collected.A total of 369 semi-disabled elderly stroke patients were randomly divided into modeling group(n=258)and verification group(n= 111)at a ratio of 7∶3.History of falling,sleep disorder,depression,frailty,nocturia≥3 times/night and Morse Fall Scale(MFS)score were the risk factors for falling down from bed in semi-disabled elderly stroke patients,which were verified with good goodness-of-fit and prediction effect by stepwise Logistic regression(P<0.05).The C-index of the nomogram in the modeling group and the verification group was 0.813 and 0.842,respectively,and the area under the curve(AUC)was 0.813 and 0.842,respectively.The calibration curve and decision curve analysis(DCA)confirmed that the model had high calibration ability and net benefit value.Conclusion History of falling,sleep disorder,depression,frailty,nocturia≥3 times/night,and MFS score are risk factors for falling down from bed in semi-disabled elderly stroke patients.A nomogram based on these risk factors is of clinical significance to predict the risk of falling down from bed in semi-disabled elderly stroke patients,thus providing predictable intervention measures for clinical workers to reduce the occurrence of falling down from bed.
elderlystrokesemi-disabledfalling down from bednomogramprediction modelLasso-Logistic regression model
万方数据
维普
