Evidence map›Paper›PMID 39096327›Full record

ArticleEuropean geriatric medicine2024

Assessing muscle quality as a key predictor to differentiate fallers from non-fallers in older adults.

Emeline Michel, Raphael Zory, Olivier Guerin, Frederic Prate, Guillaume Sacco, Fréderic Chorin

Abstract read
In one paragraph

Article in European geriatric medicine, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.

0numbers the graph read from it
0cells of the map it votes in
11citing papers in PubMed
–field-weighted citation impact
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

11 citing papers in PubMed.

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  8. Reduced phase angle as a potential indicator of mild cognitive impairment.Journal of clinical biochemistry and nutrition · 2025
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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

6 authors.

Emeline MichelDepartment of Geriatric Medicine, Université Côte d'Azur, Centre Hospitalier Universitaire de Nice, Clinique Gériatrique de Soins Ambulatoires, 06003, Nice, France. michel.e2@chu-nice.fr.ORCID 0000-0001-5082-1817
Raphael ZoryUniversité Côte d'Azur, LAMHESS, Nice, France.
Olivier GuerinDepartment of Geriatric Medicine, Université Côte d'Azur, Centre Hospitalier Universitaire de Nice, Clinique Gériatrique de Soins Ambulatoires, 06003, Nice, France.
Frederic PrateDepartment of Geriatric Medicine, Université Côte d'Azur, Centre Hospitalier Universitaire de Nice, Clinique Gériatrique de Soins Ambulatoires, 06003, Nice, France.
Guillaume SaccoDepartment of Geriatric Medicine, Université Côte d'Azur, Centre Hospitalier Universitaire de Nice, Clinique Gériatrique de Soins Ambulatoires, 06003, Nice, France.
Fréderic ChorinDepartment of Geriatric Medicine, Université Côte d'Azur, Centre Hospitalier Universitaire de Nice, Clinique Gériatrique de Soins Ambulatoires, 06003, Nice, France.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundFalling is an important public health issue because of its prevalence and severe consequences. Evaluating muscle performance is important when assessing fall risk. The study aimed to identify factors [namely muscle capacity (strength, quality, and power) and spatio-temporal gait attributes] that best discriminate between fallers and non-fallers in older adults. The hypothesis is that muscle quality, defined as the ratio of muscle strength to muscle mass, is the best predictor of fall risk.

methods184 patients were included, 81% (n = 150) were women and the mean age was 73.6 ± 6.83 years. We compared body composition, mean grip strength, spatio-temporal parameters, and muscle capacity of fallers and non-fallers. Muscle quality was calculated as the ratio of maximum strength to fat-free mass. Mean handgrip and power were also controlled by fat-free mass. We performed univariate analysis, logistic regression, and ROC curves.

resultsThe falling patients had lower muscle quality, muscle mass-controlled power, and mean weighted handgrip than the non-faller. Results showing that lower muscle quality increases fall risk (effect size = 0.891). Logistic regression confirmed muscle quality as a significant predictor (p < .001, OR = 0.82, CI [0.74; 0.89]). ROC curves demonstrated muscle quality as the most predictive factor of falling (AUC = 0.794).

conclusionThis retrospective study showed that muscle quality is the best predictor of fall risk, above spatial and temporal gait parameters. Our results underscore muscle quality as a clinically meaningful assessment and may be a useful complement to other assessments for fall prevention in the aging population.

Indexed as

Accidental FallsHand StrengthMuscle, SkeletalMuscle StrengthAgedAged, 80 and overBody CompositionFemaleGaitGeriatric AssessmentHumansMaleRisk AssessmentRisk FactorsROC CurveAgingFallMuscle powerMuscle qualityOlder adults

Identifiers

PMID39096327
PMCPMC11615084

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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.