Balance Measures for Fall Risk Screening in Community-Dwelling Older Adults with COPD: A Longitudinal Analysis
RESPIRATORY MEDICINE(2024)
McMaster Univ | West Pk Healthcare Ctr | Univ Sydney | Dalhousie Univ | Teesside Univ | Alfred Hlth | Inst Breathing & Sleep | Univ Aveiro | Univ Alberta | Univ Melbourne | McMaster Innovat Pk
Abstract
BackgroundChronic obstructive pulmonary disease (COPD) increases fall risk, but consensus is lacking on suitable balance measures for fall risk screening in this group. We aimed to evaluate the reliability and validity of balance measures for fall risk screening in community-dwelling older adults with COPD.MethodsIn a secondary analysis of two studies, participants, aged ≥60 with COPD and 12-month fall history or balance issues were tracked for 12-month prospective falls. Baseline balance measures – Brief Balance Evaluation Systems Test (Brief BESTest), single leg stance (SLS), Timed Up and Go (TUG), and TUG Dual-Task (TUG-DT) test – were assessed using intra-class correlation (ICC2,1) for reliability, Pearson/Spearman correlation with balance-related factors for convergent validity, t-tests/Wilcoxon rank-sum tests with fall-related and disease-related factors for known-groups validity, and area under the receiver operator characteristic curve (AUC) for predictive validity.ResultsAmong 174 participants (73±8 years; 86 females) with COPD, all balance measures showed excellent inter-rater and test-retest reliability (ICC2,1=0.88-0.97) and moderate convergent validity (r=0.34-0.77) with related measures. Brief BESTest and SLS test had acceptable known-groups validity (p<0.05) for 12-month fall history, self-reported balance problems, and gait aid use. TUG test and TUG-DT test discriminated between groups based on COPD severity, supplemental oxygen use, and gait aid use. All measures displayed insufficient predictive validity (AUC<0.70) for 12-month prospective falls.ConclusionThough all four balance measures demonstrated excellent reliability, they lack accuracy in prospectively predicting falls in community-dwelling older adults with COPD. These measures are best utilized within multi-factorial fall risk assessments for this population.
MoreTranslated text
Key words
COPD,Balance,Mobility,Falls,Prospective study
求助PDF
上传PDF
View via Publisher
AI Read Science
AI Summary
AI Summary is the key point extracted automatically understanding the full text of the paper, including the background, methods, results, conclusions, icons and other key content, so that you can get the outline of the paper at a glance.
Example
Background
Key content
Introduction
Methods
Results
Related work
Fund
Key content
- Pretraining has recently greatly promoted the development of natural language processing (NLP)
- We show that M6 outperforms the baselines in multimodal downstream tasks, and the large M6 with 10 parameters can reach a better performance
- We propose a method called M6 that is able to process information of multiple modalities and perform both single-modal and cross-modal understanding and generation
- The model is scaled to large model with 10 billion parameters with sophisticated deployment, and the 10 -parameter M6-large is the largest pretrained model in Chinese
- Experimental results show that our proposed M6 outperforms the baseline in a number of downstream tasks concerning both single modality and multiple modalities We will continue the pretraining of extremely large models by increasing data to explore the limit of its performance
Upload PDF to Generate Summary
Must-Reading Tree
Example

Generate MRT to find the research sequence of this paper
Related Papers
2010
被引用168 | 浏览
2010
被引用127 | 浏览
1999
被引用1936 | 浏览
2013
被引用91 | 浏览
2004
被引用140 | 浏览
2015
被引用53 | 浏览
2015
被引用36 | 浏览
2018
被引用32 | 浏览
2015
被引用37 | 浏览
2010
被引用246 | 浏览
2021
被引用13 | 浏览
2021
被引用58 | 浏览
2022
被引用337 | 浏览
Data Disclaimer
The page data are from open Internet sources, cooperative publishers and automatic analysis results through AI technology. We do not make any commitments and guarantees for the validity, accuracy, correctness, reliability, completeness and timeliness of the page data. If you have any questions, please contact us by email: report@aminer.cn
Chat Paper
GPU is busy, summary generation fails
Rerequest