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

• Published in: Clinical interventions in aging Vol. 14; pp. 2249 - 2259
• Main Authors: Liang, Yao-Dan, Zhang, Yao-Nan, Li, Yan-Ming, Chen, Yu-Hui, Xu, Jing-Yong, Liu, Ming, Li, Jing, Ma, Zhao, Qiao, Lin-Lin, Wang, Zi, Yang, Jie-Fu, Wang, Hua
• Format: Journal Article
• Language: English
• Published: New Zealand Dove Medical Press Limited 01.12.2019; Taylor & Francis Ltd; Dove; Dove Medical Press
• Subjects: Activities of daily living; Aged; Albumin; Anxiety; Cardiology; Cardiovascular disease; china; China - epidemiology; Chronic fatigue syndrome; Chronic illnesses; Cognition & reasoning; Comorbidity; Cross-Sectional Studies; elderly hospitalized patients; Elderly patients; Electronic health records; Emergency Service, Hospital - statistics & numerical data; Female; Frail Elderly - statistics & numerical data; Frailty; Frailty - epidemiology; Genotype & phenotype; Geriatric Assessment - methods; Geriatrics; Heart rate; Hospital patients; Hospitalization; Humans; Inpatient care; Inpatients; Insomnia; Male; Older people; Original Research; Patient assessment; Prevalence; risk factor; Risk Factors; Surveys and Questionnaires; Walking; wards; China; Alberta; frailty; risk factor; wards; China; elderly hospitalized patients
• DOI: 10.2147/CIA.S225149
• ISSN: 1178-1998; 1176-9092

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. 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. 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. 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.