Construction of a nomogram model for fall influencing factors and risk in elderly inpatients
Objective To evaluate the risk of falls and construct a risk prediction model,and provide a basis for the fall management of hospitalized elderly patients.Methods A cross-sectional survey was conducted among 614 elderly inpatients in a tertiary hospital in Wuhu City from February 2022 to August 2022,using a general information question-naire,frailty assessment scale,and sarcopenia screening scale.Trained research team members administered the Morse Fall Risk Assessment Scale to the participants,and those scoring above 45 points were classified as high-risk for falls.Based on this,the elderly inpatients were divided into a high-risk group(n=210)and a non-high-risk group(n=404).Binary Logistic regression was employed to analyze the statistically significant variables from the univariate analysis and identify the factors influencing patients' risk of falling.The model was evaluated using calibration curves,Hosmer-Leme-show goodness-of-fit test,ROC curves,and DCA curves.Results Among 614 elderly hospitalized patients with falls scores(42.42±24.51),210 cases were in the group at high risk of falling,and the rate of high risk of falling was 34.2%.The results of the binary Logistic regression analysis showed that,Advanced age,the frequency of exercise was≤2 times per week,combined with sarcopenia(OR=2.682,95%CI:1.785～4.031),combined(OR=2.103,95%CI:1.433～3.085)were all independent factors affecting the high risk of falls in elderly inpatients(P＜0.05).A nomogram prediction model of fall risk in elderly inpatients was established based on the above independent influencing factors.The area under the ROC curve of this risk prediction model was 0.717(95%CI:0.675～0.758),and the Homster-Lemeshow fit test(χ2=13.332,P=0.101)showed that the model has good discrimination and fit,and the clinical decision curve threshold probability was 0.22 to 0.52,suggesting that the model has good clinical utility.Conclusion Based on the risk factors of falls in elderly inpatients,this study constructed a nomogram model so which clinical staff can screen people at high risk of falling,implement personalized fall interventions to reduce the occurrence of fall events and improve their quality of life in their later years.
Elderly hospitalized patientsFallsInfluencing factorPrediction model
万方数据
维普
