Evidence map›Paper›PMID 34409974›Full record

ArticleThe journal of nutrition, health & aging2021

An Assessment of the Toulouse Saint Louis University Mini Falls Assessment Tool to Predict Incident Falls among Older Adults Residing in Nursing Homes: A 6-Month Prospective Study.

M Locquet, F Bonnard, C Beaudart, C Coendo, S Gillain, J-Y Reginster, O Bruyère

Open access · greenAbstract read
In one paragraph

Article in The journal of nutrition, health & aging, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
0.8field-weighted citation impact, top 26% 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

3 citing papers in PubMed, 4 citations in OpenAlex.

  1. Fall Risk Management in Nursing Homes: A Scoping Review.Healthcare (Basel, Switzerland) · 2025
    Review
  2. Review
  3. Validation of F3ALLS Assessment in Older Adults.The journal of nutrition, health & aging · 2022
    Article
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 2 institutions in 2 countries.

M LocquetOlivier Bruyère, University of Liège, Liège, Belgium, olivier.bruyere@uliege.be.
F Bonnard
C Beaudart
C Coendo
S Gillain
J-Y Reginster
O Bruyère
University of Liège · BEKing Saud University · SA

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectivesToulouse Saint Louis University Mini Falls Assessment (TSLUMFA) tool has been designed to predict falls. It was initially validated in a geriatric clinic in 2018. The primary objective was to evaluate the predictive capacity of the TSLUMFA for incident falls in older adults residing in nursing homes. The secondary objective was to determine the TSLUMFA optimal cut-off value identifying those older adults with a high-risk of falling. SETTINGS: A longitudinal study was carried out over a period of six months.

participants93 older adults residing in nursing homes were evaluated for the present study. MEASUREMENTS: The TSLUMFA (made up of 7 criteria) was administered at baseline, and incident falls were recorded based on a registry of falls. Comparisons of TSLUMFA scores between fallers and non-fallers were performed using the U Mann-Whitney test or Chi². Correlation between the total TSLUMFA score (/30 points) and incident fall(s) was explored using the Cox proportional hazard model. ROC analysis enabled an optimal cut-off value to be established to identify those adults at the highest-risk of falling.

resultsIn the study, 93 older adults (61.3% women) with a median age of 80 (69-87) years were included. The median total TSLUMFA score was 21 (19-24.5) points. During the 6-month study period, 38 subjects (40.9%) experienced at least one fall. The total TSLUMFA score in older adults with incident fall(s) was significantly lower than in those who did not fall (20 (15.75-22.25) points versus 23 (20-25) points and a p-value of <0.001). For each 1-point higher score at the total TSLUMFA a 9% less chance of falling was observed during the study period (p-value = 0.006). The AUC was 0.736 (95%CI: 0.617-0.822) and p-value <0.001, clearly demonstrating its interesting performance as a screening tool. A score of ≤ 21 points was identified as the optimal cut-off to identify those older adults at a higher-risk of falling.

conclusionThe TSLUMFA performed well and successfully identified older adults with a high risk of falling in a nursing home setting. Further comparisons with existing tools are warranted.

Indexed as

Accidental FallsHealth Status IndicatorsAgedAged, 80 and overFemaleGeriatric AssessmentHumansIncidenceLongitudinal StudiesMaleNursing HomesProspective StudiesRisk Assessmentfallsolder adultspublic healthScreening toolTSLUMFA

Identifiers

PMID34409974
PMCPMC12280582
OpenAlexW3179612853

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
Read underepoch 390

Registered trials

None linked

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.