Establishment and validation of a prediction model for geriatric frailty syndrome in elderly patients with AIS after treatment
10.3969/j.issn.1009-0126.2023.12.025
- VernacularTitle:老年急性缺血性脑卒中患者治疗后发生老年衰弱综合征预测模型的建立及验证
- Author:
Zhangjing CHEN
1
;
Xianbo KONG
;
Guopin WANG
;
Liqun ZHOU
;
Shanshan WANG
Author Information
1. 315040 宁波,解放军联勤保障部队第九○六医院干部病房
- Keywords:
stroke;
frailty;
retrospective studies;
logistic models;
forecasting
- From:Chinese Journal of Geriatric Heart Brain and Vessel Diseases
2023;25(12):1336-1339
- CountryChina
- Language:Chinese
-
Abstract:
Objective To establish a prediction model for geriatric frailty syndrome(GFS)in elder-ly patients with acute ischemic stroke(AIS)after treatment.Methods Clinical data of 156 elderly AIS patients admitted to our hospital from January 2020 to December 2022 were collected and ret-rospectively analyzed.According to occurrence of GFS or not,they were divided into GFS group(n=57)and control group(n=99).The differences of clinical features were recorded and com-pared between the two groups of elderly AIS patients.Multivariate logistic regression model was used to analyze the risk factors for GFS in the elderly AIS patients.And a prediction model for GFS was constructed.Results Larger proportions of aged ≥80 years,diabetes,massive cerebral infarction and dysphagia were observed in the GFS group than the control group(P＜0.05,P＜0.01).Multivariate logistic regression analysis showed that aged ≥80 years(OR=2.890,95％CI:1.306-6.395,P=0.009),diabetes(OR=4.892,95％CI:2.172-11.018,P=0.000),massive cere-bral infarction(OR=3.363,95％CI:1.418-7.977,P=0.006)and dysphagia(OR=2.772,95％CI:1.123-6.844,P=0.027)were independent risk factors for GFS in the elderly AIS patients after treatment.A nomogram prediction model was constructed.Then the dataset was randomly divided into a training set and a validation set in a ratio of 7∶3.The AUC value was 0.840(95％CI:0.754-0.927)in the training set,and 0.676(95％CI:0.518-0.833)in the validation set.Hos-mer-Lemeshow Goodness-of-Fit test indicated that when the model was subjected to the valida-tion set,a Chi-square value of 14.394 and a P value of 0.072 were obtained.Conclusion Our no-mogram prediction model has good value in predicting the occurrence of GFS in elderly AIS pa-tients after treatment.
