Evidence map›Paper›PMID 25887660›Full record

Trial reportBMC geriatrics2015

Does the timed up and go test predict future falls among British community-dwelling older people? Prospective cohort study nested within a randomised controlled trial.

Gotaro Kojima, Tahir Masud, Denise Kendrick, Richard Morris, Sheena Gawler, Jonathan Treml, Steve Iliffe

Open access · goldAbstract readRandomized Controlled Trial
PubMed Full text at PMC Publisher
In one paragraph

Trial report in BMC geriatrics, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 73 papers, 4 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
73citing papers in PubMed, 4 pooled it
25.0field-weighted citation impact, top 1% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

73 citing papers in PubMed, 4 syntheses or guidelines pooled it, 164 citations in OpenAlex.

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13 more citing papers are in PubMed but not listed here.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

7 authors at 3 institutions in 1 country.

Gotaro KojimaDepartment of Primary Care & Population Health, University College London, London, UK. gotarokojima@yahoo.co.jp.
Tahir MasudDepartment of Health Care for Older People, Nottingham University Hospitals NHS Trust, Nottingham, UK. Tahir.Masud@nuh.nhs.uk.
Denise KendrickSchool of Medicine, Division of Primary Care, University of Nottingham, Nottingham, UK. Denise.Kendrick@nottingham.ac.uk.
Richard MorrisDepartment of Primary Care & Population Health, University College London, London, UK. richard.morris@bristol.ac.uk.
Sheena GawlerDepartment of Primary Care & Population Health, University College London, London, UK. s.gawler@ucl.ac.uk.
Jonathan TremlUniversity Hospitals Birmingham NHS Trust, Birmingham, UK. Jonathan.Treml@uhb.nhs.uk.
Steve IliffeDepartment of Primary Care & Population Health, University College London, London, UK. s.iliffe@ucl.ac.uk.
Nottingham University Hospitals NHS Trust · GBUniversity Hospitals Birmingham NHS Foundation Trust · GBUniversity of Nottingham · GB

Funding

Department of Health 06/36/04Medical Research Council MR/K00414X/1
6 · The paper itself

Abstract

backgroundFalling is common among older people. The Timed-Up-and-Go Test (TUG) is recommended as a screening tool for falls but its predictive value has been challenged. The objectives of this study were to examine the ability of TUG to predict future falls and to estimate the optimal cut-off point to identify those with higher risk for future falls.

methodsThis is a prospective cohort study nested within a randomised controlled trial including 259 British community-dwelling older people ≥65 years undergoing usual care. TUG was measured at baseline. Prospective diaries captured falls over 24 weeks. A Receiver Operating Characteristic curve analysis determined the optimal cut-off point to classify future falls risk with sensitivity, specificity, and predictive values of TUG times. Logistic regression models examined future falls risk by TUG time.

resultsSixty participants (23%) fell during the 24 weeks. The area under the curve was 0.58 (95% confidence interval (95% CI) = 0.49-0.67, p = 0.06), suggesting limited predictive value. The optimal cut-off point was 12.6 seconds and the corresponding sensitivity, specificity, and positive and negative predictive values were 30.5%, 89.5%, 46.2%, and 81.4%. Logistic regression models showed each second increase in TUG time (adjusted for age, gender, comorbidities, medications and past history of two falls) was significantly associated with future falls (adjusted odds ratio (OR) = 1.09, 95% CI = 1.00-1.19, p = 0.05). A TUG time ≥12.6 seconds (adjusted OR = 3.94, 95% CI = 1.69-9.21, p = 0.002) was significantly associated with future falls, after the same adjustments.

conclusionsTUG times were significantly and independently associated with future falls. The ability of TUG to predict future falls was limited but with high specificity and negative predictive value. TUG may be most useful in ruling in those with a high risk of falling rather than as a primary measure in the ascertainment of risk.

Indexed as

Physical Therapy ModalitiesAccidental FallsAgedAged, 80 and overCohort StudiesFemaleGeriatric AssessmentHumansMaleOdds RatioProspective StudiesRisk FactorsROC CurveTime FactorsUnited Kingdom

Identifiers

PMID25887660
PMCPMC4403843
OpenAlexW2090635370

What OpenQuestion holds

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LicenceCC BY
Read underepoch 390

Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.