摘要
Abstract
Objective:Elderly patients under emergency observation are at risk of frailty,which may lead to adverse outcomes.To enhance early identification and intervention efficiency,this study aims to develop and validate a risk prediction model for frailty in elderly patients under emergency observation.
Methods:A total of 336 elderly patients who underwent emergency observation at Huai'an Second People's Hospital from January 2023 to June 2024 were selected and randomly divided into a training set(n=168)and a validation set(n=168).Logistic regression analysis was used to identify independent risk factors for frailty,and a nomogram was constructed.Its discrimination and calibration were evaluated.
Results:In the training set,101(60.12%)patients were frail,while 96(57.14%)patients were frail in the validation set.Logistic regression analysis revealed that female sex(OR=4.431,P<0.001),comorbidities(OR=3.369,P=0.003),nutritional risk(OR=2.811,P=0.006),anemia(OR=2.258,P=0.031),and sarcopenia(OR=3.690,P=0.004)were independent risk factors for frailty.In the training set,the area under the receiver operating characteristic(ROC)curve(AUC)was 0.791(95%CI 0.716 to 0.866).The calibration curve showed good agreement between predicted and observed frailty,and the Hosmer-Lemeshow test yielded χ2=7.575,P=0.372.In the validation set,the AUC was 0.786(95%CI 0.714 to 0.857).The calibration curve also showed good agreement,with Hosmer-Lemeshow χ2=7.755,P=0.458.The decision curve analysis demonstrated that the nomogram provided greater net benefit in predicting frailty within threshold probabilities of 0.15-0.81(training set)and 0.13-0.85(validation set).
Conclusion:The nomogram based on female sex,comorbidities,nutritional risk,anemia,and sarcopenia can assist emergency healthcare providers in rapidly identifying elderly patients at high risk of frailty,thereby optimizing resource allocation and facilitating timely interventions.关键词
急诊留观/老年/衰弱/列线图/风险预测Key words
emergency observation/elderly/frailty/nomogram/risk prediction
