Accepted Manuscript Risk factors for falls in community stroke survivors: A systematic review and metaanalysis Tianma Xu, MOT, Lindy Clemson, PhD, Kate O’Loughlin, PhD, Natasha A. Lannin, PhD, Catherine Dean, PhD, Gerald Koh, MD, PhD PII:
S0003-9993(17)30528-2
DOI:
10.1016/j.apmr.2017.06.032
Reference:
YAPMR 56975
To appear in:
ARCHIVES OF PHYSICAL MEDICINE AND REHABILITATION
Received Date: 26 March 2017 Revised Date:
19 June 2017
Accepted Date: 25 June 2017
Please cite this article as: Xu T, Clemson L, O’Loughlin K, Lannin NA, Dean C, Koh G, Risk factors for falls in community stroke survivors: A systematic review and meta-analysis, ARCHIVES OF PHYSICAL MEDICINE AND REHABILITATION (2017), doi: 10.1016/j.apmr.2017.06.032. This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting proof before it is published in its final form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain.
Running head: Fall risk factors after stroke
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Risk factors for falls in community stroke survivors: A systematic review and metaanalysis Tianma Xu, MOT,
a,b
a
a
Lindy Clemson, PhD, Kate O’Loughlin, PhD, Natasha A. Lannin,
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d
e
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PhD, Catherine Dean, PhD, Gerald Koh, MD, PhD a
From the Ageing Work and Health Research Group, Faculty of Health Sciences, University of Sydney, Sydney, Australia;
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Health & Social Sciences Cluster, Singapore Institute of Technology, Singapore;
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Department of Community and Clinical Allied Health, La Trobe Clinical School La Trobe University, d
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Melbourne, Australia; Department of Health Professions, Faculty of Medicine and Health Sciences, Macquarie University, Sydney, Australia; Saw Swee Hock School of Public Health, National University of Singapore, Singapore;
Presented with preliminary results to the National Occupational Therapy Conference, 10
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October 2015, Singapore; and full findings to the 7th Biennial Australian and New Zealand Falls Prevention Conference, 29 November 2016, Melbourne, Australia.
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Acknowledgement
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Tianma Xu is supported by Singapore Institute of Technology for his Ph.D. study at the University of Sydney. We also would like to thank Professor Deborah Black from the University of Sydney for her statistical support in the meta-analysis.
Conflicts of interest We have no conflict of interest.
Corresponding author:
Running head: Fall risk factors after stroke
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Tianma Xu (MOT) Ageing Work & Health Research Unit Faculty of Health Sciences
75 East St, Lidcombe, NSW, 2141, Australia
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The University of Sydney,
Telephone: +61290367483 or +6565928673
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Systematic Review Registration No.: CRD42015023389
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Email address:
[email protected] or
[email protected]
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Abstract
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Objective: To identify the risk factors for falls in community stroke survivors.
Data Sources: A comprehensive search for articles indexed on MEDLINE, EMBASE,
CINAHL, PsychINFO, Cochrane Library, and Web of Science databases was conducted.
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Study Selection: Prospective studies investigating fall risk factors in community stroke survivors were included. Reviewers in pair independently screened the articles and
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determined inclusion through consensus. Studies meeting acceptable quality rating using the Q-Coh were included in the meta-analysis.
Data Extraction: Data extraction was done in duplicate by four reviewers using a standardized data extraction sheet, and confirmed by another independent reviewer for
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completeness and accuracy.
Data Synthesis: Twenty-one articles met the minimum criteria for inclusion; risk factors investigated by three or more studies (n=16) were included in a meta-analysis. The following
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risk factors had strong association with all fallers: impaired mobility (OR 4.36, CI 2.68-7.10);
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reduced balance (OR 3.87, CI 2.39-6.26); use of sedative / psychotropic medications (OR 3.19, CI 1.36-7.48); disability in self-care (OR 2.30, CI 1.51-3.49); depression (OR 2.11, CI 1.18-3.75); cognitive impairment (OR 1.75, CI 1.02-2.99); and history of fall (OR 1.67, CI 1.03-2.72). A history of falling (OR 4.19, CI 2.05-7.01) had a stronger association with recurrent fallers. Conclusions: This study confirms that balance and mobility problems, assisted self-care, taking sedative or psychotropic medications, cognitive impairment, depression, and history of falling are associated with falls in community stroke survivors. We recommend that any
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ACCEPTED MANUSCRIPT future research into falls prevention programs should consider addressing these modifiable risk factors. As the risk factors for falls in community stroke survivors are multifactorial,
Keywords: Community; Stroke; Accidental falls; Risk factors; Rehabilitation
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List of Abbreviations:
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interventions should be multi-dimensional.
activities of daily living
OR
odds ratios
CI
confidence interval
RR
Relative Risk, Risk Ratio or Rate Ratio
MMSE
Mini-Mental State Examination
BBS
Berg Balance Scale
10MWT
10 metre walk test
TUG
timed up and go
FIM
Functional Independence Measure
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ADL
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ACCEPTED MANUSCRIPT Falls are one of the most frequent complications after stroke.1 Stroke survivors are more likely to
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fall than the general aging population and this could lead to greater deficits in activities of daily
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living (ADL) and mobility functions.2-4 The prevalence of falls among stroke survivors during the
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first six months after discharge from hospital is between 36% and 73%,5-7 and fall rates remain
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high between 40% and 58% among these individuals one year after stroke.8-11 More stroke
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survivors report falls in the first months post-stroke after discharge from the hospital and almost
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one out of three have a near-fall each month.12 Two-thirds of the stroke survivors fall indoors13-15
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and ambulatory stroke survivors are more likely to fall compared to those with higher dependency
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levels and reduced mobility.16 Among those who fall, walking and transfers are the most
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frequently mentioned activities at the time of fall.2
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The consequences of falls can cause further physical complications among stroke survivors in the
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community, such as soft tissue injuries,7 fractures,17 and restriction in functional activities.17 Once
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stroke survivors sustain a hip fracture, they are less likely to regain independent mobility than the
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general population.18 At the same time, stroke survivors often develop psychosocial issues from
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falling. The most common are depression19 and fear of falling,20 which can further reduce their
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level of activity leading to further physical deconditioning and loss of independence.21
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Understanding the risk factors for falls among community stroke survivors is crucial to
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developing an effective community falls prevention program. A number of cohort and case-
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control studies have reported that the risk of falls among community stroke survivors may
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increase with reduced balance,6 fear of falling,22, 23 depressive symptoms,24 a fall history during
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hospitalization,6, 7 motor and sensory impairment,23 and environmental safety hazards.24 However,
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there has been no systematic comprehensive review on fall predictors among stroke survivors
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after their discharge from hospital. A previous systematic review25 in 2009 published in the Dutch
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language included stroke participants from both hospital and community settings. However, it had 3
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broader inclusion criteria and did not include meta-analysis, presenting the results as a descriptive
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review. Furthermore, they did not distinguish between hospital and community settings.25 This
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systematic review and meta-analysis aims to identify the risk factors for falls in stroke survivors
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discharged from hospital and residing in the community, the setting where most falls occur.
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Methods
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A systematic review protocol was developed before the review commenced. The detail of the
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protocol was registered on the PROSPERO database under registration number
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CRD42015023389. Review methods followed the Preferred Reporting Items for Systematic
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Reviews and Meta-Analysis (PRISMA)26 and Meta-Analysis of Observational Studies in
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Epidemiology (MOOSE)27 guidelines.
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Search Strategy
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A broad search strategy was used; combinations included Medical Subject Headings, text words
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and word variants for three main themes: “stroke”, “falls”, and “study type”. As in similar
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reviews,25, 28, 29 title and abstract were searched (up to June 2015) in the following electronic
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databases: MEDLINE, EMBASE, PsycINFO, CINAHL, Cochrane Library (Cochrane Database of
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Systematic Review) and Web of sciences. For example, under “study type”, we included the
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following key words in our comprehensive search: prospective or cohort or case-control or
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follow-up or observational or cohort study or case-control study or observational study. Full
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search terms are available upon request. Additionally, bibliographies of identified publications
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and published reviews were hand searched for potentially relevant articles. An email alert function
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in electronic databases was created to keep track of any later published articles that may meet the
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selection criteria based on saved search history up to 31 May 2016.
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We included prospective cohort studies and case-control studies where all participants were 18
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years and above and clinically diagnosed with either first stroke or recurrent stroke. There was no
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restriction on the year of publication but was limited to English literature. Studies were included if
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at least 80% of the stroke participants in the study were being followed up in the community or
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non-institutionalized setting for a minimum period of three months. Clinical trials and
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retrospective studies were excluded. Studies conducted only during the hospitalization period or at
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residential care facilities were excluded. The primary outcomes were the risk factors for all fallers
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defined as community stroke survivors with at least one fall during follow-up. The secondary
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outcomes were the risk factors for recurrent fallers defined as community stroke survivors with
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two or more falls during follow-up.
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Data Extraction
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One reviewer (TX) screened titles and based on inclusion criteria, rated them as relevant, not
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relevant or maybe relevant. Abstracts for titles indicated with “yes” and “maybe” were
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independently scrutinized by a pair of reviewers (TX & LC). The selected articles were then
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reviewed independently in full text by two reviewers (TX, LC, KO, CD or NL). Any disagreement
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was discussed among at least three reviewers until consensus was reached. The following data
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was abstracted in duplicate by four reviewers (TX, LC, CD, and KO) using a standardized data
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extraction sheet. The data extraction sheet included year of publication, country of study, sample
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size, mean age of the participants, mean time since stroke at baseline assessment (duration of
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stroke), frequency of fall assessment, duration of follow-up, proportion of fallers, and risk factors
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for falls. The binary outcome variables reporting odds ratio (OR) with 95% Confidence Intervals
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(CI) for each risk factor were extracted. Results reported in non-ORs, such as Relative Risk, Risk
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Ratio or Rate Ratio (RR), were also extracted. When raw data is available to calculate the OR in
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another study,30 we calculated the OR with 95% confidence intervals using an online statistical
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ACCEPTED MANUSCRIPT OR calculator (Appendix A, Table 1).31 The different categories of frequency of fall assessment
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used in our data extraction were based on the Deandera et al’s systematic review.28 All extracted
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data on proportions of fallers and risk factors were categorized into all fallers and recurrent fallers.
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All findings from the selected studies were collated based on the common characteristics of
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participants, and the primary and secondary outcomes of this review. Another independent
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reviewer (NL) confirmed all data entries and checked for completeness and accuracy.
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Quality Assessment
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The evaluation of the methodological quality of primary studies is a key process in systematic
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review and meta-analysis. Strengthening the Reporting of Observational Studies in Epidemiology
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statement (STROBE)32 was used as a general guide for the reviewers to determine whether the
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selected observational studies were well reported. The quality assessment tool for cohort studies
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called “Q-Coh”33 has established its inter-rater reliability (kappa: 0.68 to 0.87) and acceptable
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validity, and it classifies methodological quality as either good, satisfactory or low.33 Hence, it
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was used to select studies with good or satisfactory methodological quality to be included in the
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meta-analysis. The Q-Coh tool was adapted by creating a standardized approach to decisions
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when reviewing components and determining rating scales relevant to falls. A list of confounders
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considered important to be controlled in fall studies was also defined before conducting the
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quality assessment and they were age, gender, falls before stroke, falls in the hospital, length of
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stay in the hospital, rehabilitation before and during the study.34 All selected studies were assessed
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for risk of bias using the adapted Q-Coh by two independent reviewers (TX, LC, KO, CD). All
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disagreements were solved in a consensus meeting. Any studies with good or satisfactory
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methodological quality were included in the meta-analysis.
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Statistical analysis
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outcome variables with 95% CI investigated by at least three studies in a comparable manner were
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included in the meta-analysis. Decisions regarding inclusion of studies that can be meaningfully
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compared were based on the validity of the outcome measures for measuring the domain of
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interest. When different statistical analysis (e.g. both univariate analysis and multivariate analysis)
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was used for the same risk factor in the study, the unadjusted results from the univariate statistical
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analysis were pooled in the meta-analysis. However, when only adjusted results or results from
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multivariate statistical analysis were presented in the study, these were included in the meta-
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analysis.
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Since falls are more common in the studied population, the OR will considerably overestimate the
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relative risk, or in other words, the relative risk will underestimate the OR if we combine both in
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the meta-analysis.35, 36 Hence, we analysed all outcome variables reported in ORs and non-ORs
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separately using the Comprehensive Meta-Analysis software (version 2.0)37 to generate pooled
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estimates of effect sizes for each risk factor. We used the random-effects model with 95% CI for
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all analyses in consideration of the diverse effect sizes of the included studies. The random-effects
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model allowed us to estimate the mean of a distribution of effects from the selected studies in
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meta-analysis.38 The i²-test was used to test the level of heterogeneity among the included studies.
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The i²-test has been recommended as one of the most preferred and reliable tests for
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heterogeneity,39 which represents the degree of variation in estimated effects across studies. It has
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proposed that low heterogeneity is if the i² value falls lower than 50%, moderate for 50-75%, and
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high for above 75%.40 All binary outcome variables or the risk factors reported in ORs were
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pooled together for analyses and the respective risk factors reported in non-ORs were analysed
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separately to support the findings from pooled ORs.
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Results 7
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Figure 1 summarises the flow of searches, inclusions, and exclusions. It included one eligible
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study41 that was found from the database email alert system. Twenty-one studies including 19
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cohort studies and two case-control studies met the selection criteria and were assessed for risk of
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bias using the adapted Q-Coh tool.33
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Methodological quality
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The summary of quality assessment is presented in appendix A, table 2. A study was considered
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as “good” quality if at least six domain items in Q-Coh were given positive ratings and
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“acceptable” quality if four or five domain items were rated as positive. Anything below was
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considered as “low” quality. Out of the 21 papers, seven papers4, 5, 8, 24, 41-43 were rated as “good”
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quality and nine papers6, 10, 11, 16, 30, 44-47 were rated as “acceptable” quality. The remaining five
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papers7, 12, 48-50 were rated as “low” quality and excluded in the meta-analysis.
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Characteristics of included studies
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Study characteristics of the 16 included studies are displayed in table 1. Studies were conducted
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in the community settings across different continents (Asia Pacific, Europe, and North America)
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with a mean cohort age of sixty-nine years old, mean sample size less than 300 (range: 3011 –
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117445), and published between 200224 and 2015.41 The range of follow-up period was from four
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months24 to two years.44, 45 Out of the 16 studies, 11 studies5, 11, 16, 24, 30, 41-43, 45-47 identified risk
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factors for all fallers, three studies4, 6, 8 identified risk factors for recurrent fallers, and two
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studies10, 44 reported risk factors for both all fallers and recurrent fallers. A total number of 4,160
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stroke participants from 16 studies and 1,116 (27%) stroke participants were classified as fallers.
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The proportion of all fallers across studies ranged from 23%24 to 55%,8 and recurrent fallers from
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5%44 to 42%.8 Summary characteristics of the included studies are shown in appendix A, table 3.
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Meta-analysis
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The meta-analysis revealed evidence on the risk factors for falling in people with stroke after
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discharge from hospital. Based on previous literature on falls in older adults28, 51 and stroke
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population,52 we proposed a classification dividing risk factors into the following domains:
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sociodemographic, sensorimotor, cognitive, psychosocial, medical, balance and mobility, and self-
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care risk factors. A total of 14 risk factors for both all fallers and recurrent fallers were
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investigated by at least three studies, and at least one risk factor was represented under each fall
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risk category (table 2).
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< Table 2>
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Many of the risk factors examined across studies have used different scales and this is likely to
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impact on heterogeneity. For four risk factors, cognitive impairment, balance and mobility, and
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disability in self-care, we made post-priori decisions to exclude studies given lack of validity for
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the measures used. For instance, under the cognitive domain, we pooled all Mini-Mental State
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Examination (MMSE)5, 10, 30 together in the analysis and excluded the single item - Functional
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Independence Measure (FIM) (memory score). We pooled all balance measures using Berg
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Balance Scale (BBS) in the analysis,30, 46, 47 whereas studies using non-validated or single
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performance test, such as Fugl Meyer Assessment postural stability score,5 “unable to semitandem
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stand”,10 and “inability to recover by stepping”41 were excluded. Similarly, the mobility status
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assessed using the 10 metre walk test (10MWT)53 and timed up and go (TUG)54 test were pooled
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together, and “Unable to walk for ≤0.25ms”10 was deselected for analysis. Under the disability in
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self-care domain, the FIM score5 is a broader measure of disability compared to the other scales,
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such as the Modified Rakin Scale,44 ADL difficulties (bath/shower),10 and Barthel Index scores,42,
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which measure a range of discrete self-care activities and can be meaningfully grouped together
for meta-analysis.
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Table 2 shows the overall pooled results in ORs for each risk factor for 2 outcomes: all fallers and
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recurrent fallers. Additional studies are listed where results were not available as an OR. Pooled
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results for studies that contributed to significant risk factors for all fallers are shown in figure 2
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and for recurrent fallers in figure 3.
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Risk factors for all fallers
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The overall pooled results based on comparable risk factors identified the following risk factors
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for all fallers (figure 2) in declining magnitude of OR: impaired mobility (OR 4.36, 2.68 to 7.10);
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reduced balance (OR 3.87, 2.39 to 6.26); use of sedative / psychotropic medications (OR 3.19,
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1.36 to 7.48); disability in self-care (OR 2.30, 1.51 to 3.49); depression (OR 2.11, 1.18 to 3.75);
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cognitive impairment (OR 1.75, 1.02 to 2.99); and history of fall (OR 1.67, 1.03 to 2.72). In
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addition to the pooled ORs, individual studies reported in non-ORs for history of fall (rate ratio
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1.30), depression (relative risk 1.60), reduced balance (risk ratio 2.10) and impaired mobility (risk
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ratio 3.50) further supporting the above findings (table 2).
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Table 2 also shows that the pooled results for the following variables were shown relatively low
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relationship to all fallers and statistically non-significant: age (OR 1.02); gender (OR 1.01);
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duration of stroke (OR 1.11); visual impairment (OR 1.39); and multiple strokes (OR 1.39). The
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pooled results for the following variables were statistically non-significant with moderate to high
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level of heterogeneity: motor impairment (OR 1.75); urinary incontinence (OR 1.54). The forest
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plots of the above risk factors that were statistically non-significant can be found in appendix B,
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figure 1. 10
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Risk factors for recurrent fallers
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Table 2 also shows the 4 risk factors for recurrent fallers which were investigated by three or
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more studies. The pooled OR for history of fall (OR 4.19, 2.50 to 7.01) indicates that people with
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stroke who had a history of fall post-stroke are strongly associated with risk of recurrent falling
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(figure 3). It is difficult to draw conclusions for use of sedative and psychotropic medications,
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reduced balance and motor impairment in relationship to recurrent falling because of the high
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heterogeneity. Forest plots of risk factors for recurrent fallers with high levels of heterogeneity or
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non-significance can be found in appendix B, figure 2-3.
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Discussion
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This meta-analysis showed that impaired balance and mobility, the use of sedative/psychotropic
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medications, and disability in self-care were strongly associated with falling among stroke
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survivors living in the community, while depression, cognitive impairment, and history of fall
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were moderately associated with falling among this population.
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Pooling results from a total of 16 studies reveal that there are common risk factors for falls
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between community stroke survivors and community-dwelling older adults. Both our study
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findings and another systematic review study on fall risk factors in community older adults28
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support that history of fall and mobility problem are associated with falls. We found impaired
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mobility and depression lead to a higher risk of falls in community stroke survivors (OR 4.36; OR
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2.11) compared to community older adults (OR 2.1; OR 1.63).28 Our findings also highlight that
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having a history of a fall including a near-fall in the home, community or hospital setting predicts
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a higher risk of recurrent falling in the stroke group (OR 4.19) than found in community older
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community older adults.28 A history of falling was also highly associated with recurrent falls (OR
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>4), again similar to the findings of the Deandera et al’s study.28 Given that falls are common in
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this group, our study confirms that clinical attention to fall prevention is needed for any stroke
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survivor with a history of near-fall8 or fall in the hospital or rehabilitation setting6 or a fall in the
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past twelve months.10, 44 Clinicians should thus screen for falls as one component of their routine
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clinical care for stroke patients.
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While the risk of falls is associated with increasing age in community older adults28 our meta-
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analysis shows no relationship between age, gender and all fallers among community stroke
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survivors, despite participants in included studies generally being older with an average age of
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sixty-nine. This lack of relationship may, however, be a factor of the design of included studies.
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There were only a small number of studies that presented OR for both age and gender, as some
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studies included age and/or gender as potential confounding factors and therefore did not
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individually analyse them.10, 11, 24, 41, 46, 47 Furthermore, we were unable to include the variables of
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age and gender in logistic regression analysis due to the different statistical methodologies used in
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some selected studies. For instance, one study set the statistical power to 15% in order for the
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variables to be selected for further analysis.8
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Motor impairment, while clinically thought to increase risk of falls, was not found to be associated
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with falling in our study. Motor impairment, a sensorimotor risk factor, can be understood as a
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limitation of function in terms of muscle control, movement or mobility55 and can affect the
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movement control of the affected side of the body. However, the lack of consistency in the use of
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terminology that describes motor impairment after stroke55 and the variability in the use of motor
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impairment measures across studies led to high heterogeneity and likely the statistically non-
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significance. Thus, it is difficult to conclude whether motor impairment is a risk factor for falling 12
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and/or recurrent falls. The methodological limitations of the included studies thus make further
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research necessary.
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The results of our meta-analysis support that cognitive impairment is associated with falling in
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community stroke survivors. This is worthy of further investigation, given the limitations inherent
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with the use of different cognitive screening tools used in the included studies. Cognitive
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impairment after stroke is common; almost one out of four stroke survivors have some form of
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cognitive impairment in the first three months after a stroke.56 Additionally, stroke survivors with
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cognitive impairment may experience reduced safety awareness and require more attention from
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their family members or other caregivers. Future studies should use cognitive tests that are more
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sensitive in identifying stroke survivors with cognitive impairment. For example, the Montreal
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Cognitive Assessment57 is a validated screening tool in detecting people with mild cognitive
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impairment and more sensitive in identifying cognitive abnormalities after stroke than MMSE.57,
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Depression too is common after stroke; almost one third of all stroke survivors experience
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depressive symptoms at some time after the onset of stroke.19 The included studies used different
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cut-off points for the same scale to define severe depression10 making interpretation of data
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difficult. Nevertheless study findings do suggest screening stroke survivors for depressive
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symptoms and being aware of the need for appropriate psychosocial interventions for stroke
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survivors with depressive symptoms.
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Our analysis showed a three-fold increased risk of falls associated with the use of
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sedative/psychotropic medications as a risk factor of falling among community stroke survivors.
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The high level of heterogeneity (i²=94%) present when we calculated the effect size of fall risk for
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recurrent fallers may be due to the differences in measures, such as types10, 44 and number of 13
ACCEPTED MANUSCRIPT medications.6 In view of the small number of studies included in the analysis, there is also a need
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to explore the influence of different types of medications commonly prescribed post-stroke that
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may cause giddiness, such as antiepileptic drugs which are often prescribed for seizure control59
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and pain60 in the stroke population. Since post-stroke central pain is common,61 clinicians should
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consider the possible adverse events (such as falls) when prescribing medications for pain
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management post stroke. In addition, other non-pharmacological interventions for pain
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management, such as neurostimulation therapy and cognitive behavioral therapy could be
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explored as alternative options.61
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Our meta-analysis shows that community stroke survivors with impaired balance and mobility
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have a four-fold increased risk of falls. Using the standardized and validated functional screening
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tools, such as BBS, 10MWT and TUG test can help identify stroke survivors at risk of falls.
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Previous structured exercise-based interventions with stroke survivors targeting strength, balance
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and mobility were found to have no significant effect on fall reduction,23,62 whereas a recent 12-
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week simplified Tai Chi is the first study to show a better effect in reducing falls in community
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stroke survivors than exercise-based intervention using post hoc test (x²=5.6; p=.06).63 However,
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this result should be interpreted with cautions as no fall rate or fall risk analysis was conducted,
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and no further follow-up was done after the intervention. Dean et al.62 demonstrated a differential
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effect in a group based exercise program between the stroke participants who had slower mobility
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compared to those who had a faster gait, however, these effects did not reach statistical
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significance within the subgroups. In view of the neurological deficits presented in people after
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stroke, such as muscle weakness, sensory impairment and spasticity, we suggest future research to
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find out if stroke-specific exercises for improving strength, balance and mobility in this
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population reduce the risk of falls.
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ACCEPTED MANUSCRIPT Our analysis revealed that disability in self-care (OR>2) was a risk factor for falls in community
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stroke survivors. Unlike most other risk factors for falls in community stroke survivors, disability
310
in self-care as a risk factor is unique to the stroke population. Many people after stroke experience
311
some form of difficulty in performing self-care activities. This may help identify any stroke
312
survivors at a high risk of falls and likely to benefit from self-care retraining as part of a fall
313
prevention program.
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314
Identification of major risk factors is key to better understanding how falls may be prevented
316
among stroke survivors. Several falls risk assessment tools have been used in predicting falls in
317
the general population. For example, the Falls Risk for Older People – Community Setting
318
(FROP-Com)64 is one the comprehensive fall risk screening tool for general population. Our key
319
risk factors that we identified for the community stroke survivors are included in the FROP-Com
320
with the exception of depression. If using the FROP-Com for community stroke survivors, we
321
would recommend the addition of a depression screening tool. The Downtown index65 was
322
another risk screening tool purported to predict falls. It reported excellent sensitivity (91%) but
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with very poor specificity (27%) when it was used to predict elderly stroke survivors at risk of
324
falls66 and would not be recommended.
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In the general population, the Cochrane review67 has recommended both single interventions (e.g.
327
exercises, home safety) and multifactorial interventions as being effective. It seems people with
328
stroke are at high risk of falling, and that the risk of falls is multifactorial. It is clear that we need
329
to address each of these risk factors, such as reduced balance and mobility, taking
330
sedative/psychotropic medications, disability in self-care, as well as cognitive and psychosocial
331
factors of depression and cognitive impairment. As the risk factors for falls in the general
332
population are very similar, it does suggest that we could use the falls prevention programs that
333
work for the general population. However, further research is needed to understand the underlying
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15
ACCEPTED MANUSCRIPT reasons for risk specific to stroke. For example, which components of the balance and mobility or
335
which aspects of the self-care disabilities could lead to falls in people with stroke? Observational
336
studies and interviews with stroke survivors, caregivers and healthcare professionals could
337
elucidate how current general multifactorial programs could potentially be refined and translated
338
for stroke.
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339
In summary, the findings of this review have several implications. Firstly, since community stroke
341
survivors with reduced balance and mobility have four-fold increased risk of falls, falls prevention
342
programs should focus on improving balance and mobility using evidence-based interventions
343
(e.g. programs targeting muscle strength and balance deficits). Secondly, stroke survivors who are
344
taking sedative or psychotropic medications should take extra precautions especially when there
345
are other risk factors present at the same time. Thirdly, falls prevention programs tend to include
346
home safety,69 but do not specifically look at self-care activities or participation at home or in the
347
community. In order to address the disability in self-care after stroke, we suggest occupational
348
therapy interventions should include both home safety and setting of occupational goals to
349
maximize their level of independence in self-care activities and activity participation post-
350
stroke.68 More importantly, proper patient and caregiver education on the cognitive and
351
psychosocial risk factors for falls is highly recommended to prevent people with stroke from
352
falling, especially before discharge from the hospital settings. Lastly, early screening of these risk
353
factors upon discharge from the hospitals is crucial in identifying potential fallers.
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340
355
Study limitations
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There were some limitations in this meta-analysis. First, as discussed above, the number of
357
observational studies reporting fall risk factors in community stroke survivors was small. Testing
358
for heterogeneity among the selected studies and excluding those with high heterogeneity further
359
reduced the number of potential studies that could be included in our meta-analysis. Second, 16
ACCEPTED MANUSCRIPT results were interpreted based on the 16 studies that we could pool and potential selection bias
361
may exist as we excluded non-English and abstract-only publications. Third, the lack of
362
standardization in fall data collection methods and statistical analysis methods are likely to affect
363
the homogeneity across all studies. Hence, only data from the studies with ‘good’ and ‘acceptable’
364
quality ratings were included in this review. Fourth, we could not pool all data from each paper in
365
view of such divergent outcome measures used. The calculation of pooled ORs for some of the
366
included risk factors did not include non-validated measures reporting OR and the data reporting
367
non-OR. In order to have at least three studies for each risk factor in the meta-analysis, we had to
368
pool the estimates derived from the selected studies with different levels of possibility of residual
369
confounding or bias, which may have affected the overall effect size computation and result
370
interpretation. This factor was carefully considered when we looked into the comparable risk
371
factors that could be meaningfully grouped together to minimize the level of heterogeneity. In
372
view of the above shortfalls, the study results should be interpreted with caution.
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Conclusions
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Stroke survivors with balance and mobility problems, assisted self-care, taking sedative or
376
psychotropic medications, cognitive impairment, depression, and history of falling are at risk of
377
falls. All the above risk factors except history of falling are amenable through interventions. We
378
recommend that any future research into falls prevention programs for community stroke
379
survivors should consider addressing these modifiable risk factors. As the risk factors for falls in
380
community stroke survivors are multifactorial and few single interventions has been shown
381
effective in this population, interventions should be multi-dimensional.
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Figure Legends Figure 1: Flowchart of study selection
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significant with low level of heterogeneity.
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Figure 3: The overall pooled results for risk factor for recurrent fallers which were statistically
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Table 1: Summary characteristic of 16 prospective observational studies investigating fall risk factors in community stroke survivors Mean time since stroke at baseline assessment 4 months
Frequency of fall assessment* Intermediate
Duration of follow up (months) 6
Outcome (fallers) ˆ All
First/ Recurrent stroke Both
Proportion of all fallers % (n) 36.0% (24)
Proportion of recurrent fallers % (n) 15% (10)
Year 2012
Country of Study Turkey
Sample size 66
Male 32
Andersson et al
2008
Sweden
140
78
75
NA
Low
12
All
NA
41.4% (58)
NA
Ashburn et al
2008
UK
115
77
70.2
80 days
Low
12
Rec
Both
55.0% (63)
42% (48)
Blennerhassett et al
2012
Australia
30
20
66
>1 year
Low
14.5
All
NA
40.0% (12)
Callaly et al
2015
Ireland
522
262
70.6
3 days
Low
24
All/ Rec
Both
23.5% (124)
33% (10) 5% (27)
Divani et al
2009
USA
1174
550
74
3.5 years
Low
24
All
Both
46.0% (540)
NA
Jalayondeja et al
2014
Thailand
97
59
61.9
1 month
High
6
All
1st stroke
25.8% (25)
13% (13)
Jorgensen et al
2002
Norway
111
63
68
>10 years
High
4
All
Both
23.0% (25)
12% (13)
Kerse et al
2008
1104
546
70.7
1 day
Intermediate
6
All
Both
37.0% (407)
19% (211)
Lamb et al
2003
New Zealand UK
94
0
76
48 months
Intermediate
12
All/ Rec
Both
48.0% (45)
29% (27)
Mackintosh et al
2006
Australia
55
25
68.1
2.3 months
High
6
Rec
Both
45.0% (25)
22% (12)
Mansfield et al
2015
Canada
95
60
62.5
51.2 days
High
6
All
NA
36.8% (35)
15% (14)
Persson et al
2011
Norway
96
56
73
2 days
Intermediate
12
All
1st stroke
48.0% (46)
NA
Simpson et al
2011
Canada
80
58
67.6
NA
High
12
Rec
1st stroke
50.0% (40)
31% (26)
Wada et al
2007
Japan
101
62
67.2
6.1 year
High
12
All
NA
44.6% (45)
20% (20)
Yates et al
2002
USA
280
140
69.3
3-14 days
High
6
All
NA
50.7% (142)
NA
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ˆ Rec: Recurrent.
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Authors Alemdaroglu et al
Mean or median age (yrs) 64
*High: fall information was obtained at least every 3 months; intermediate: participants were interviewed less frequently than for “high” but at least every 6 months; low: when the participants were interviewed only once a year.
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Table 2: Meta-analysis results from 16 studies.
Risk factors for recurrent fallers Sociodemographic risk factors History of fall Sensorimotor risk factor Motor impairment Medical risk factors Use of sedative / psychotropic medications Mobility & self-care risk factors Reduced balance Note:
0.07 0.94 0.04
Mixed Mixed Mixed
5
1.75 (0.98-3.12)
81%
0.06
Mixed
3
1.75 (1.02-2.99)
0%
0.04
Mixed
3
2.11 (1.18-3.75)
59%
0.01
3 3 2 2
1.39 (0.86-2.25) 1.11 (0.90-1.35) 1.39 (0.79-2.46) 1.54 (0.59-4.04)
0% 74% 43% 44%
3
3.19 (1.36-7.48)
3 3 4
3.87 (2.39-6.26) 4.36 (2.68-7.10) 2.30 (1.51-3.49)
No. of studies reporting OR
OR (95% CI)
Statistical methods
Rate ratio Rate ratio Rate ratio
1 1 1
1.10 (1.01-1.20) 1.10 (0.93-1.30) 1.30 (1.13-1.50)
0% 0% 0%
0.03 0.26 <.01
Multivariate Multivariate Multivariate
Rate ratio Relative risk
1 1
1.10 (1.01-1.20) 0.80 (0.64-1.00)
0% 0%
0.03 0.05
Multivariate Multivariate
Rate ratio
1
1.10 (0.86-1.40)
0%
0.44
Multivariate
Mixed
Relative risk
1
1.60 (1.11-2.30)
0%
0.01
Multivariate
0.18 0.33 0.15 0.38
Mixed Mixed Multivariate Mixed
Rate ratio Rate ratio Rate ratio Rate ratio
1 1 1 1
0.97 (0.86-1.10) 1.10 (1.01-1.20) 0.91 (0.75-1.10) 1.30 (1.21-1.40)
0% 0% 0% 0%
0.64 0.03 0.33 <.01
Multivariate Multivariate Multivariate Multivariate
22%
0.01
Mixed
0% 0% 46%
0.01 <.01 <.01
Mixed Mixed Mixed
Risk Ratio Risk Ratio
1 1
2.10 (1.16-3.80) 3.50 (1.00-12.23)
0% 0%
0.01 0.05
Univariate Univariate
IRR (95% CI)
Heterogeneity i²
p
Statistical methods*
0.91 (0.85-0.98)
0%
0.01
Heterogeneity i²
p
Statistical methods*
3
0.88 (0.30-2.53)
72%
0.81
Mixed
3
2.23 (1.18-4.23)
94%
0.01
Mixed
3
2.40 (0.68-8.49)
81%
0.17
Mixed
4.19 (2.50-7.01)
13%
<.01
Mixed
i² value= 50-75%: moderate heterogeneity; i² value >75%: high heterogeneity *Mixed statistical methods include univariate and multivariate analyses.
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0% 6% 37%
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1.02 (1.00-1.03) 1.01 (0.76-1.34) 1.67 (1.03-2.72)
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4
Fall risk factors in non-Odds Ratio (non-OR) Heterogeneity No. of studies RR** (95% CI) p reporting non-OR i²
Statistical methods
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Cognitive risk factor Cognitive impairment Psychosocial risk factor Depression Medical risk factors Visual impairment Duration of stroke Multiple strokes Urinary incontinence Use of sedative / psychotropic medications Mobility & self-care risk factors Reduced balance Impaired mobility Disability in self-care
p
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Sociodemographic risk factors Age Gender (female) History of fall Sensorimotor risk factor Motor impairment (lower Extremities)
Heterogeneity i²
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Risk factors for all fallers
Fall risk factors in Odds Ratio (OR) No. of studies OR (95% CI) reporting OR
No. of studies reporting non-OR
Incidence rate ratio 1
RR** includes: Rate Ratio, Relative Risk or Risk Ratio; IRR: Incidence Rate Ratio
Multivariate
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Appendix A
Table 1: Calculating Odds Ratio for Andersson et al.’s study
Andersson et al 2008 (n=140)
42
16
Age Female Visual impairment Cognitive impairment (MMSE<=23) Low mood (GDS>=6) Motor impairment (UE, BL<=56) Motor impairment (LE, BL<=35) Impaired functional mobility (TUG>14s) Impaired balance (BBS<45)
23 18 23 19 26 29 30 28 27
7 6 3 2 5 3 1 1 2
58 Yes 30 24 26 21 31 32 31 29 29
No 28 34 32 37 27 26 27 29 29
Odds
28
54
1.071 0.706 0.813 0.568 1.148 1.231 1.148 1.000 1.000
20 20 16 7 14 21 16 13 12
21 18 14 9 14 15 12 3 3
82 Yes 41 38 30 16 28 36 28 16 15
95% CI Lower limit
Upper limit p value
RI PT
Total
Non-faller Low SE high SE Total Odds
No 41 44 52 66 54 46 54 66 67
1.0000 0.864 0.577 0.242 0.519 0.783 0.519 0.242 0.224
OR
1.071 0.547 2.100 0.82 0.414 1.612 1.41 0.710 2.795 1.090 5.031 2.34 2.21 1.112 4.410 1.57 0.799 3.094 1.112 4.410 2.21 1.948 8.737 4.13 4.47 2.088 9.556
SC
Faller Low SE high SE Total
0.841 0.561 0.328 0.029 0.024 0.190 0.024 0.000 0.000
M AN U
OR and 95% CI were calculated in https://www.medcalc.org/calc/odds_ratio.php
Table 2: Q-Coh Quality Assessment for prospective observational studies SN
Representativeness
Ax Domain
Comparability of Maintenance of Exposure measure Outcome measure the groups the comparability
Statistical analyses
Attrition
Overall Rating
Quality
Studies 1 Alemdaroglu et al, 2012
3+
1
4+
1
4+
1
2+
1
8+2-
1
2+
1
1+
1
7
Good
2 Ashburn et al., 2008
2+1-
1
4+
1
4+
1
2+
1
10+
1
2+
1
1+
1
7
Good
3 Mansfield et al., 2015
2+1-
4 Wada et al., 2007
1+2-
5 Kerse et al., 2008
3+
6 Jogensen et al., 2002
2+1-
7 Simpson etal., 2011
2+1-
8 Andersson et al., 2008
2+1-
9 Blennerhassett et al., 2012 11 Divani et al., 2009 12 Jalayondeja et al., 2014
Items
Rating
Items
Rating
Items
TE D
Rating
Rating
Items
Rating
Items
Rating
Items
Rating
1
4+
1
4+
1
2+
1
10+
1
2+
1
1+
1
7
Good
0
4+
1
4+
1
2+
1
8+2-
1
2+
1
1+
1
6
Good
1
4+
1
4+
1
2+
1
7+3-
0
2+
1
1+
1
6
Good
1
4+
1
4+
1
2+
1
10+
1
2-
0
1+
1
6
Good
1
4+
1
4+
1
2+
1
10+
1
2-
0
1+
1
6
Good
1
4+
1
4+
1
2+
1
5+5-
0
1+1-
0
1+
1
5
Acceptable
2+1-
1
4+
1
4+
1
1+1-
0
6+4-
0
1+1-
0
1+
1
4
Acceptable
2+1-
1
4+
1
4+
1
2+
1
7+3-
0
1+1-
0
1+
1
5
Acceptable
2+1-
1
4+
1
4+
1
2+
1
7+3-
0
2-
0
1+
1
5
Acceptable
1+2-
EP
10 Callaly et al., 2015
Items
4+
1
4+
1
2+
1
10+
1
2-
0
1+
1
5
13 Lamb et al., 2003
3+
1
4+
1
4+
1
2+
1
7+3-
0
1+1-
0
1+
1
5
Acceptable
14 Mackintosh et al., 2006
1+2-
0
4+
1
4+
1
2+
1
10+
1
2-
0
1+
1
5
Acceptable
15 Persson et al., 2011
2+1-
1
4+
1
4+
1
2+
1
7+3-
0
2-
0
1+
1
5
Acceptable
16 Yates et al., 2002
1+2-
0
4+
1
4+
1
1+1-
0
7+3-
0
2+
1
1+
1
4
Acceptable
1 Andersson et al., 2006
3+
1
4+
1
4+
1
2-
0
5+5-
0
2-
0
1-
0
3
Low
2 Forster & Young, 1995
2+1-
1
3+1-
0
4+
1
1+1-
0
7+3-
0
2-
0
1+
1
3
Low
3 Hyndman & Ashburn, 2004
1+2-
0
3+1-
0
4+
1
1+1-
0
10+
1
1+1-
0
1-
0
2
Low
4 Said et al., 2013
1+2-
0
4+
1
4+
1
1+1-
0
6+4-
0
2-
0
1+
1
3
Low
5 Wagner et al., 2009
3-
0
3+1-
0
3+1-
0
2-
0
8+2-
1
2-
0
1-
0
1
Low
AC C
0
Acceptable
"+" indicates positive rating and "-" indicates negative rating for the assessed item in each category For rating under each Category, "1" indicates positive rating and "0" indicates "negative" rating.
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ACCEPTED MANUSCRIPT
Table 3: Summary characteristics of the included studies
No. of Studies*
3 7 3
2 3 1
M AN U
3 9 1
2 3 1
SC
6 3 4
RI PT
All Fallers
EP
TE D
Characteristics Location Asia Pacific Europe North America No. of subjects included in the study <100 100-200 >200 Mean or median age of study poulation (years) <65 65-75 >75 Duration of follow-up (months) 3-6 7-12 >12 Year of publication 2000-2005 2006-2010 2011-2015 Frequency of fall assessment High Intermediate low
Recurrent Fallers
0 5 1
6 4 3
1 4 1
0 6 7
2 1 3
5 6 2
3 2 1
AC C
*The sum does not add up to the total because two papers presented both outcomes
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ACCEPTED MANUSCRIPT
Appendix B
Risk factors (for all fallers) Author, year
Weight %
Odds ratio and 95% CI
OR (95% CI)
Age 12.53 0.07 77.89 9.51
1.02 (0.97 to 1.07) 1.07 (0.55 to 2.10) 1.01 (0.99 to 1.03) 1.06 (1.00 to 1.12) 1.02 (1.00 to 1.03); p=0.07 Heterogeneity i² = 0%;
RI PT
Alemdaroglu et al 2012 Andersson et al 2008 Callaly et al 2015 Kerse et al 2008
Gender (Female) 2.02 (0.72 to 5.63) 0.82 (0.42 to 1.62) 0.99 (0.75 to 1.31) 1.01 (0.76 to 1.34); p=0.94 Heterogeneity i² = 6%;
SC
Alemdaroglu et al 2012 Andersson et al 2008 Kerse et al 2008
Motor impairment 0.97 (0.91 to 1.04) 2.21 (1.11 to 4.40) 1.20 (0.51 to 2.83) 3.71 (1.67 to 8.25) 2.20 (1.04 to 4.66) 1.75 (0.98 to 3.12); p=0.06 Heterogeneity i² = 81%;
M AN U
Alemdaroglu et al 2012 Andersson et al 2008 Lamb et al 2003 Persson et al 2011 Yates et al 2002
Visual impairment
1.47 (0.54 to 4.04) 1.41 (0.71 to 2.80) 1.30 (0.53 to 3.19) 1.39 (0.86 to 2.25); p=0.18
26.98 19.56 16.99 17.86 18.62
22.54 48.94 28.51
TE D
Alemdaroglu et al 2012 Andersson et al 2008 Lamb et al 2003
7.39 16.36 76.26
Heterogeneity i² = 0%; Duration of stroke
Multiple strokes
Heterogeneity i² = 74%; 71.32 28.68
1.16 (0.83 to 1.62) 2.20 (0.91 to 5.32) 1.39 (0.79 to 2.46); p=0.25
AC C
Kerse et al 2008 Lamb et al 2003
55.16 3.84 41.01
1.00 (0.99 to 1.02) 1.10 (0.41 to 2,99) 1.26 (1.07 to 1.48) 1.11 (0.90 to 1.35); p=0.33
EP
Alemdaroglu et al 2012 Lamb et al 2003 Wada et al 2007
Heterogeneity i² = 43%;
Urinary incontinence
Alemdaroglu et al 2012 Lamb et al 2003
0.84 (0.25 to 2.84) 2.30 (1.00 to 5.30) 1.54 (0.59 to 4.04); p=0.38 Heterogeneity i² = 44%; 0.1 0.2
39.99 60.01 0.5
Decrease odds in falling
1
2
5
10
Increase odds in falling
Figure 1 The overall pooled results for risk factors for all fallers which were statistically non-significant.
3
ACCEPTED MANUSCRIPT Risk factors (for recurrent fallers)
Author, Year
OR (95% CI)
OR (Random) and 95% CI
Use of Sedative and Psychotropic Medications 3.84 (1.45-10.18) 2.80 (2.66-2.95) 1.30 (1.00-1.70) 2.23 (1.18-4.23); p=0.014 Heterogeneity i²=94%
20.99 40.79 38.22
0.1 0.2
0.5
Decrease odds of falling
1
2
RI PT
Callaly et al 2015 Lamb et al 2003 Mackintosh et al 2006
Weight %
5
10
Increase odds of falling
Figure 2 The overall pooled results for risk factors for recurrent fallers which were statistically
SC
significant with high level of heterogeneity.
EP
TE D
M AN U
Risk factors (for recurrent fallers)
AC C
Figure 3 The overall pooled results for risk factors for recurrent fallers which were statistically non-significant with high level of heterogeneity.
4