F Ge1, M Liu, S Tang, Y Lu, S L Szanton. 1. Minhui Liu and Siyuan Tang, Central South University Xiangya Nursing School, Changsha, Hunan, China, mliu62@jhu.edu.
Abstract
OBJECTIVE: (1) To establish appropriate FRAIL-NH cutoff points in nursing homes in Mainland China; (2) To compare the FRAIL-NH scale and Frailty Index in assessing frailty prevalence and associated factors in nursing homes. DESIGN: A cross-sectional study. SETTING: Six nursing homes in Changsha, China. PARTICIPANTS: A total of 302 residents aged 60 years or older (mean aged 82.71±8.49, 71.2% female). MEASUREMENTS: Frailty was assessed using the 34-item Frailty Index and the FRAIL-NH scale. RESULTS: The appropriate FRAIL-NH cutoff points to classify frail status and frailest status were 1.5 (87.6% sensitivity, 63.3% specificity) and 7.5 (94.1% sensitivity, 73.4% specificity), respectively. Based on the FRAIL-NH and Frailty Index, 69.5% (48% for frail and 21.5% for frailest), and 66.5% (60.9% for frail and 5.6% for frailest) of residents were at risk of frailty, respectively. There was no statistically significant difference in the total frailty prevalence assessed by FRAIL-NH and Frailty Index (χ2=0.617, P=0.432). The FRAIL-NH Scale is significantly associated with the Frailty Index (correlation coefficient (r) = 0.74, P < 0.001), but there was a Kappa agreement of 0.39 for frailty classification between the FRAIL-NH and Frailty Index, with the Frailty Index classifying a larger number of individuals as frail. When using FRAIL-NH scale, disease and self-reported health status were associated with frail and frailest status while age was just associated with frailest status. regarding the Frailty Index, age, diseases, medications and self-reported health status were associated with frail and frailest status. CONCLUSION: The FRAIL-NH is a simple and effective tool to assess the overall frailty rate in nursing homes, and the Frailty Index may be more suitable capturing the multidimensionality of frailty at an individual level. Careful consideration in the selection of a frailty instrument, based on the intended purpose, is necessary.
OBJECTIVE: (1) To establish appropriate FRAIL-NH cutoff points in nursing homes in Mainland China; (2) To compare the FRAIL-NH scale and Frailty Index in assessing frailty prevalence and associated factors in nursing homes. DESIGN: A cross-sectional study. SETTING: Six nursing homes in Changsha, China. PARTICIPANTS: A total of 302 residents aged 60 years or older (mean aged 82.71±8.49, 71.2% female). MEASUREMENTS: Frailty was assessed using the 34-item Frailty Index and the FRAIL-NH scale. RESULTS: The appropriate FRAIL-NH cutoff points to classify frail status and frailest status were 1.5 (87.6% sensitivity, 63.3% specificity) and 7.5 (94.1% sensitivity, 73.4% specificity), respectively. Based on the FRAIL-NH and Frailty Index, 69.5% (48% for frail and 21.5% for frailest), and 66.5% (60.9% for frail and 5.6% for frailest) of residents were at risk of frailty, respectively. There was no statistically significant difference in the total frailty prevalence assessed by FRAIL-NH and Frailty Index (χ2=0.617, P=0.432). The FRAIL-NH Scale is significantly associated with the Frailty Index (correlation coefficient (r) = 0.74, P < 0.001), but there was a Kappa agreement of 0.39 for frailty classification between the FRAIL-NH and Frailty Index, with the Frailty Index classifying a larger number of individuals as frail. When using FRAIL-NH scale, disease and self-reported health status were associated with frail and frailest status while age was just associated with frailest status. regarding the Frailty Index, age, diseases, medications and self-reported health status were associated with frail and frailest status. CONCLUSION: The FRAIL-NH is a simple and effective tool to assess the overall frailty rate in nursing homes, and the Frailty Index may be more suitable capturing the multidimensionality of frailty at an individual level. Careful consideration in the selection of a frailty instrument, based on the intended purpose, is necessary.
Authors: Kenneth Rockwood; Xiaowei Song; Chris MacKnight; Howard Bergman; David B Hogan; Ian McDowell; Arnold Mitnitski Journal: CMAJ Date: 2005-08-30 Impact factor: 8.262
Authors: Samuel D Searle; Arnold Mitnitski; Evelyne A Gahbauer; Thomas M Gill; Kenneth Rockwood Journal: BMC Geriatr Date: 2008-09-30 Impact factor: 3.921