Identification of Frailty and Its Risk Factors in Elderly Hospitalized Patients from Different Wards: A Cross-Sectional Study in China

Yao-Dan Liang; Yao-Nan Zhang; Yan-Ming Li; Yu-Hui Chen; Jing-Yong Xu; Ming Liu; Jing Li; Zhao Ma; Lin-Lin Qiao; Zi Wang; Jie-Fu Yang; Hua Wang

doi:10.2147/CIA.S225149

Identification of Frailty and Its Risk Factors in Elderly Hospitalized Patients from Different Wards: A Cross-Sectional Study in China

Clin Interv Aging. 2019 Dec 19:14:2249-2259. doi: 10.2147/CIA.S225149. eCollection 2019.

Authors

Yao-Dan Liang^{1

2}, Yao-Nan Zhang³, Yan-Ming Li⁴, Yu-Hui Chen⁵, Jing-Yong Xu⁶, Ming Liu⁷, Jing Li⁸, Zhao Ma⁹, Lin-Lin Qiao¹⁰, Zi Wang¹¹, Jie-Fu Yang¹, Hua Wang¹

Affiliations

¹ Department of Cardiology, Beijing Hospital, National Center of Gerontology, Beijing, People's Republic of China.
² Chinese Academy of Medical Sciences, Peking Union Medical College, Beijing, People's Republic of China.
³ Department of Orthopedics.
⁴ Department of Pulmonary and Critical Care Medicine.
⁵ Department of Neurology.
⁶ Department of General Surgery.
⁷ Department of Urology.
⁸ Department of Geriatrics.
⁹ Department of Rehabilitation.
¹⁰ Department of Traditional Chinese Medicine.
¹¹ Department of Cardiac Surgery, Beijing Hospital, National Center of Gerontology, Beijing, People's Republic of China.

Abstract

Objectives: To survey the difference of frailty prevalence in elderly inpatients amongdifferent wards; to compare the diagnostic performance of five frailty measurements (Clinical Frailty Scale [CFS], FRAIL, Fried, Edmonton, Frailty Index [FI]) in identifying frailty; and to explore the risk factors of frailty in elderly inpatients.

Participants and methods: This was a cross-sectional study including 1000 inpatients (mean age 75.2±6.7 years, 51.5% male; 542, 229, and 229 patients from cardiology, non-surgical, and surgical wards, respectively) in a tertiary hospital from September 2018 to February 2019. We applied the combined index to integrate the five frailty measurements mentioned above as the gold standard of frailty diagnosis. Multivariate logistic regression models were used to determine the independent risk factors of frailty.

Results: Frailty prevalence was 32.3% (Fried), 36.2% (CFS), 19.2% (FRAIL), 25.2% (Edmonton), 35.1% (FI) in all patients. The frailty was more common in non-surgical wards, regardless of the frailty assessment tools used (non-surgical wards: 27.5% to 51.5%; cardiology ward: 14.9% to 29.3%; surgical wards: 18.8% to 41.9%). CFS≥5 showed a sensitivity of 94.1% and a specificity of 85.2% for all patients. FI≥0.25 showed a sensitivity of 94.8% and a specificity of 87.0% for all patients. Age [odds ratio (OR) = 1.089, P<0.001], education level (OR = 0.782, P=0.001), heart rate (OR = 1.025, P<0.001), albumin (OR = 0.911, P=0.002), log D-dimer (OR = 2.940, P<0.001), ≥5 comorbidities (OR = 2.164, P=0.002), and ≥5 medications (OR = 2.819, P<0.001) were independently associated with frailty in all participants.

Conclusion: Frailty is common among elderly inpatients, especially in non-surgical wards. CFS is a preferred screening tool and FI may be an optimal assessment tool. Old age, low educational level, fast heart rate, low albumin, high D-dimer, ≥5 comorbidities, and polypharmacy are independent risk factors of frailty in elderly hospitalized patients.

Keywords: China; elderly hospitalized patients; frailty; risk factor; wards.

MeSH terms

Aged
China / epidemiology
Comorbidity
Cross-Sectional Studies
Emergency Service, Hospital / statistics & numerical data*
Female
Frail Elderly / statistics & numerical data*
Frailty / epidemiology*
Geriatric Assessment / methods*
Humans
Inpatients*
Male
Prevalence
Risk Factors
Surveys and Questionnaires

Grants and funding

This work was supported by Beijing Municipal Science & Technology Commission (D181100000218003), CAMS Innovation Fund for Medical Sciences (No. 2018-I2M-1-002), and Chinese Academy of Medical Sciences (No. 2019PT320013).