Abstract

Background The most widely used frailty phenotype and frailty indexes are either time-consuming or complicated, thus restricting their generalization in clinical practice; and therefore, an easier and faster screening tool is needed to be developed. Objective To select sensitive symptoms in traditional Chinese medicine (TCM) and study whether they can improve the risk prediction of frailty. Methods This is a cross-sectional study enrolling 2249 Chinese elderly community dwellers. Data were collected via face-to-face inquiries, anthropometric measurements, laboratory tests, and community health files. Frailty was the main outcome measure, and it was evaluated by Fried's frailty phenotype (FP). The ordinal logistic regression model was used to identify the factors associated with frailty. The risk assessment plot was used to compare the discriminative ability for frailty among models with and without TCM symptoms. Results The identified sensitive influential factors for frailty included age, education level, dietary habits, chronic obstructive pulmonary disease, diabetes, cerebral infarction, osteoporosis, cold limbs, lethargy and laziness in speaking and moving, weakness of lower limbs, slow movement, dry mouth and throat, and glazed expression. The risk prediction for “frailty cumulative components ≥1” was not significantly increased, while for “frailty cumulative components ≥2”, a new model developed with the above selected TCM symptoms had a higher AUC than the baseline model without it (0.79 VS 0.81, P=0.002). And the NRI and IDI for the new model were 41.4% (P=0.016) and 0.024% (P=0.041), respectively. Conclusion This research might provide an easier and faster way for early identification and risk prediction of frailty in elderly community dwellers.

Highlights

  • Frailty, characterized by an increased vulnerability to stressors due to a reduction in function across multiple physiological systems [1], is an emerging global health burden and gaining more and more international attention [2]

  • For the limitation of funding of this project, eventually, by using a simple random sampling method, we randomly selected 2500 subjects from the annual physical examination population of eight community centers in Shanghai during September 2018 to December 2019. en, 2249 subjects were enrolled according to the following inclusion criteria: 1) age more than 65 according to the 2019 ICFSR international clinical practice guidelines for identification and management of frailty [12] and 2) complete data on Fried’s frailty phenotype (FP) evaluation, general information, history of chronic disease and medication, cognitive function, and the traditional Chinese medicine (TCM) symptoms based on deficiency syndrome

  • All participating community physicians were asked to receive 1–2 days of intensive training of research-related skills and techniques until they are qualified. en, face-to-face inquiries between them and patients were conducted through electronic small programs on mobile phones we developed previously and the paper version of the form of questionnaire. e cognition of subjects was evaluated by clock drawing task (CDT) [13] and Mini-Mental State Examination (MMSE) [14]

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Summary

Introduction

Frailty, characterized by an increased vulnerability to stressors due to a reduction in function across multiple physiological systems [1], is an emerging global health burden and gaining more and more international attention [2]. Frailty can lead to various adverse outcomes such as increased mortality, disability, falls, fractures, hospitalization and nursing home admission [4, 5]. The main challenges for these two tools are that they are too complicated and time-consuming for use in clinical settings, which preclude their application to large-scale screens and routine physical examinations. They are applied for only a subset of patients, with most of the older people in a community or hospital not having their frailty assessed at all

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