Identification of Frailty and Its Risk Factors in Elderly Hospitalized Patients from Different Wards: A Cross-Sectional Study in China
Received 29 July 2019
Accepted for publication 1 December 2019
Published 19 December 2019 Volume 2019:14 Pages 2249—2259
Checked for plagiarism Yes
Review by Single anonymous peer review
Peer reviewer comments 4
Editor who approved publication: Dr Zhi-Ying Wu
Yao-Dan Liang,1,2 Yao-Nan Zhang,3 Yan-Ming Li,4 Yu-Hui Chen,5 Jing-Yong Xu,6 Ming Liu,7 Jing Li,8 Zhao Ma,9 Lin-Lin Qiao,10 Zi Wang,11 Jie-Fu Yang,1 Hua Wang1
1Department of Cardiology, Beijing Hospital, National Center of Gerontology, Beijing, People’s Republic of China; 2Chinese Academy of Medical Sciences, Peking Union Medical College, Beijing, People’s Republic of China; 3Department of Orthopedics; 4Department of Pulmonary and Critical Care Medicine; 5Department of Neurology; 6Department of General Surgery; 7Department of Urology; 8Department of Geriatrics; 9Department of Rehabilitation; 10Department of Traditional Chinese Medicine; 11Department of Cardiac Surgery, Beijing Hospital, National Center of Gerontology, Beijing, People’s Republic of China
Correspondence: Hua Wang; Jie-Fu Yang
Department of Cardiology, Beijing Hospital, National Center of Gerontology, No. 1, Dahua Road, Dongcheng District, Beijing 100730, People’s Republic of China
Tel +86 13911680467; +86 13601292259
Email firstname.lastname@example.org; email@example.com
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: frailty, elderly hospitalized patients, wards, risk factor, China
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