Development and validation of a prediction model to estimate the probability of frailty in older emergency patients
10.3760/cma.j.issn.1671-0282.2025.02.015
- VernacularTitle:急诊老年患者衰弱预测模型的建立与验证
- Author:
Junyu LI
1
;
Guodong WANG
;
Na SHANG
;
Na WANG
;
Shubin GUO
;
Huizhen LIU
Author Information
1. 首都医科大学康复医学院，中国康复研究中心北京博爱医院急诊科，北京 100068
- Keywords:
Frailty;
Prediction model;
Nomogram;
Internal validation;
Emergency department;
Elderly;
Clinical data;
Biomarkers
- From:
Chinese Journal of Emergency Medicine
2025;34(2):226-232
- CountryChina
- Language:Chinese
-
Abstract:
Objective:To develop and validate a prediction model by combining clinical data and biomarkers to evaluate the probability of frailty among older emergency patients.Methods:A cross-sectional study was conducted. From January 2021 to December 2021, patients aged 60 years and older admitted to the emergency department of China Rehabilitation Research Center were enrolled. Data of patient's clinical information were collected. The patients were divided into frail group and non-frail group according to the Fried's frailty phenotype and clinical data were compared between the two groups. LASSO regression was used to deal with dimension reduction and multivariate logistic regression was employed to construct a prediction model based on variables selected by the LASSO regression. Nomogram was used to visualize the prediction model. The area under the receiver operating characteristic curve, calibration curve, decision curve analysis and bootstrap were used to evaluate the discrimination, calibration, clinical applicability, and internal validity of the model respectively.Results:A total of 348 patients were enrolled, and the incidence of frailty was 53.74% (187/348). Education, coronary heart disease, chronic obstructive pulmonary disease, albumin, fibrinogen, N-terminal pro-brain natriuretic peptide, decreased creatinine, and underweight were independent predictors for frailty in older emergency patients ( P < 0.05). A nomogram model was built based on the above predictors and the model showed good discrimination, calibration and clinical applicability. Conclusions:The study utilized objective clinical data and biomarkers to establish a predictive model for the occurrence of frailty in elderly emergency department patients. This model aids in risk stratification and targeted intervention for elderly emergency patients, thereby improving patient outcomes.
