Association between balance ability and the tendency of geriatric syndromes in elderly inpatients based on the "Edge Intelligent System"
10.3760/cma.j.issn.0254-9026.2025.02.011
- VernacularTitle:基于"边缘智能系统"研究老年住院患者平衡与老年综合征罹患倾向的关联性
- Author:
Minzheng XU
1
;
Qiang XUE
1
;
Yunxia FAN
1
;
Yu SHEN
1
;
Ying LIU
1
Author Information
1. 南京医科大学第一附属医院 江苏省人民医院老年医学科，南京 210029
- Publication Type:Journal Article
- Keywords:
Postural balance;
Geriatric assessment;
Artificial intelligence
- From:
Chinese Journal of Geriatrics
2025;44(2):173-179
- CountryChina
- Language:Chinese
-
Abstract:
Objective:To analyze the current status and influencing factors of balance ability in elderly inpatients, and to explore the correlation between balance function and the tendency to suffer from geriatric syndromes.Methods:A total of 262 elderly patients hospitalized from April to August 2023 were selected as the research objects by convenience sampling method.A systematic health assessment was performed by professional evaluators using the "Edge Intelligent Geriatric Assessment System" software of the Jiangsu Province Hospital within one week after admission.According to the results of Performance Oriented Mobility Assessment(POMA), the subjects were divided into normal balance group(n=188), POMA score 19 to 24 group(n=36)and less than 19 score group(n=38), the differences in the tendency of the three groups of patients to develop geriatric syndromes were compared.Logistic regression analysis was used to screen the related factors and construct the regression equation.Receiver operating characteristic(ROC)curve was drawn to evaluate the predictive value of regression equation.Results:A total of 262 patients, of which 156(59.54%)were males, with an age range of 60 to 100 years(mean age 74.11±8.77 years)were included in the study.The total POMA score of 262 patients was 23.69±6.00, of which 74 cases(28.24%)had balance dysfunction.Univariate analysis showed that there were significant differences in age( t=20.356, P<0.001), serum albumin( t=3.999, P=0.019), proportions of people suffering from depression, frailty, sarcopenia, sleep disorders, nutrition risk and high fall risk between patients with different balance ability( χ2=10.250, 76.763, 101.728, 37.805, 22.472, 75.095, all P<0.05).Binary logistic regression model showed that age, sarcopenia, suspected insomnia, insomnia, and nutritional risk were independent predictors of balance ability in elderly patients(OR=1.071, 12.424, 6.719, 8.321, 3.440, all P<0.05).The above related variables were included in the regression equation: Logit(P)=-8.792+ 0.069×age+ 2.520×sarcopenia+ 1.905×suspected insomnia+ 2.119×insomnia+ 1.236×nutritional risk.ROC curve analysis showed that the area under the curve(AUC)was 0.902(95% CI: 0.857-0.946, P<0.001), the predictive specificity was 86.17% and the sensitivity was 85.14%. Conclusions:Age≥75.5 years, sarcopenia, sleep disorders, and nutritional risk could be used as predictors of balance disorders in elderly inpatients.The regression model constructed based on these indicators has a good predictive value.The establishment of the edge intelligent geriatric assessment system promotes the improvement of medical information level.
