Abstract: Objective To explore the changes in frailty symptoms and cognitive function in the elderly patients with chronic diseases and polypharmacy, and to analyze the correlation between them. Methods The clinical data of 110 elderly patients with polypharmacy and chronic diseases who were treated in Zunyi First People’s Hospital from August 2023 to February 2024 were collected. On the day of the visit (T1), 6 months after the visit (T2), and 12 months after the visit (T3), Fried Frailty Phenotype (FFP) scale and Mini-Mental State Examination (MMSE) were used to assess the frailty symptoms and cognitive function in the patients. The Pearson correlation coefficient was used to analyze the correlation of frailty symptoms between the different time points. Mplus 8.3 software was used to construct a latent variable growth curve model (LGCM) to explore the development trajectory of frailty symptoms. According to the trajectory characteristics, 110 patients were divided into stable frailty group (n=58), slow frailty group (n=32) and rapid frailty group (n=20). The general characteristics of different trajectory categories were compared, and the score of MMSE among different trajectory groups at each time point was analyzed by repeated measures ANOVA. The correlations between frailty development trajectories and cognitive function were analyzed by multiple linear regression. Results The correlations of FFP scores between different time points in enrolled patients were all statistically significant (P<0.001), and FFP score at T3 was higher than that at T2 and T1 (P<0.05); The initial mean level of FFP was 1.543, and the differences among individuals were statistically significant (P<0.001). Frailty symptoms showed an overall increasing trend from T1 to T3, and the differences in rates of change among individuals were statistically significant (P<0.001). There were significant differences among the three trajectories in terms of age, body mass index, types of medication used, and types of diseases (P<0.01). Repeated measures ANOVA revealed that MMSE scores in the stable frailty group showed no significant changes from T1 to T3 (P>0.05). However, the slow frailty group and the rapid frailty group had significantly lower MMSE scores than the stable frailty group at all time points (P<0.01). Furthermore, the rate of decline in MMSE scores was significantly faster in the rapid frailty group compared to the slow frailty group (P<0.01). Multiple linear regression analysis showed that, adjusting for variables or not, the risk of cognitive decline was higher in the slow frailty group and the rapid frailty group compared to the stable frailty group. Conclusions The frailty symptoms of elderly patients with chronic diseases and polypharmacy showed an increasing trend over time, and the frailty trajectory is heterogeneous, which is obviously related to cognitive function. Clinically, it is necessary to formulate personalized intervention strategies for patients with different frailty trajectories and strengthen the monitoring and management of frailty and cognitive function in elderly patients with chronic diseases and polypharmacy.    

Key words: geriatric chronic diseases, polypharmacy, frailty, developmental trajectory, cognitive function