Construction of functional constipation risk prediction model for the elderly in nursing homes
10.3760/cma.j.cn211501-20240520-01271
- VernacularTitle:养老机构老年人功能性便秘风险预测模型的构建
- Author:
Guoao JIA
1
;
Qiqun TANG
1
;
Huiju HU
1
;
Liguo YANG
1
;
Jianmin LI
1
;
Jie YU
1
Author Information
1. 华北理工大学护理与康复学院，唐山 063200
- Publication Type:Journal Article
- Keywords:
Pension institutions;
Aged;
Constipation;
Influencing factors;
Prediction model
- From:
Chinese Journal of Practical Nursing
2025;41(2):111-118
- CountryChina
- Language:Chinese
-
Abstract:
Objective:To understand the current situation and influencing factors of functional constipation among elderly people in nursing homes, and construct a risk prediction model.Methods:Conveniently select 542 elderly people from 8 nursing homes in Tangshan urban area from July to November 2023 as the research subjects, use binary logistic regression analysis to construct a risk prediction model, and conduct internal validation of the model.Results:Among the 542 elderly people who were included in the study, there were 250 males and 292 females with an average age of 78.00 (70.00, 86.00) years. The incidence of functional constipation among elderly people in nursing homes was 54.06%(293/542). The predictive model includes six predictive factors: age, Barthel index, water intake, daily vegetable intake, insomnia, and perianal disease. The model AUC was 0.885 (95% CI 0.858-0.913), the Youden index was 0.628, the best critical value was 0.585, sensitivity was 0.819, specificity was 0.809. The Hosmer-Lemeshow test χ2=6.38, P=0.605. The internal validation results of the Bootstrap method showed that the AUC of the model was 0.876, the calibration curve was close to the standard line, and the Brier score was 0.135. The DCA results showed that the threshold was 0.1-0.9, and the model had good clinical net benefits. Conclusions:The incidence of functional constipation in elderly care institutions is relatively high. The functional constipation risk prediction model constructed in this study has good predictive efficacy and applicability, which can provide reference for nursing home staff.
