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

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...

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Autores principales: 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
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Dove 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6927496/
https://www.ncbi.nlm.nih.gov/pubmed/31908435
http://dx.doi.org/10.2147/CIA.S225149
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author 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
author_facet 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
author_sort Liang, Yao-Dan
collection PubMed
description 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.
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spelling pubmed-69274962020-01-06 Identification of Frailty and Its Risk Factors in Elderly Hospitalized Patients from Different Wards: A Cross-Sectional Study in China 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 Clin Interv Aging Original Research 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. Dove 2019-12-19 /pmc/articles/PMC6927496/ /pubmed/31908435 http://dx.doi.org/10.2147/CIA.S225149 Text en © 2019 Liang et al. http://creativecommons.org/licenses/by-nc/3.0/ This work is published and licensed by Dove Medical Press Limited. The full terms of this license are available at https://www.dovepress.com/terms.php and incorporate the Creative Commons Attribution – Non Commercial (unported, v3.0) License (http://creativecommons.org/licenses/by-nc/3.0/). By accessing the work you hereby accept the Terms. Non-commercial uses of the work are permitted without any further permission from Dove Medical Press Limited, provided the work is properly attributed. For permission for commercial use of this work, please see paragraphs 4.2 and 5 of our Terms (https://www.dovepress.com/terms.php).
spellingShingle Original Research
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
Identification of Frailty and Its Risk Factors in Elderly Hospitalized Patients from Different Wards: A Cross-Sectional Study in China
title Identification of Frailty and Its Risk Factors in Elderly Hospitalized Patients from Different Wards: A Cross-Sectional Study in China
title_full Identification of Frailty and Its Risk Factors in Elderly Hospitalized Patients from Different Wards: A Cross-Sectional Study in China
title_fullStr Identification of Frailty and Its Risk Factors in Elderly Hospitalized Patients from Different Wards: A Cross-Sectional Study in China
title_full_unstemmed Identification of Frailty and Its Risk Factors in Elderly Hospitalized Patients from Different Wards: A Cross-Sectional Study in China
title_short Identification of Frailty and Its Risk Factors in Elderly Hospitalized Patients from Different Wards: A Cross-Sectional Study in China
title_sort identification of frailty and its risk factors in elderly hospitalized patients from different wards: a cross-sectional study in china
topic Original Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6927496/
https://www.ncbi.nlm.nih.gov/pubmed/31908435
http://dx.doi.org/10.2147/CIA.S225149
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