Evidence map›Paper›PMID 34556721›Full record

Observational studyScientific reports2021

Real-world gait speed estimation, frailty and handgrip strength: a cohort-based study.

Abolfazl Soltani, Nazanin Abolhassani, Pedro Marques-Vidal, Kamiar Aminian, Peter Vollenweider, Anisoara Paraschiv-Ionescu

Abstract readObservational Study
In one paragraph

Observational study in Scientific reports, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 28 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
28citing papers in PubMed, 1 pooled it
–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

28 citing papers in PubMed, 1 synthesis or guideline pooled it.

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  3. Real-world walking and activity patterns in community-dwelling older adults: a cross-sectional analysis of baseline data from the SMART-AGE trial.European review of aging and physical activity : official journal of the European Group for Research into Elderly and Physical Activity · 2026
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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.

Abolfazl Soltani *Laboratory of Movement Analysis and Measurement (LMAM) , Ecole Polytechnique Federale de Lausanne (EPFL), Lausanne, Switzerland.
Nazanin Abolhassani *Department of Medicine, Internal Medicine, Lausanne University Hospital (CHUV) and University of Lausanne (UNIL), Lausanne, Switzerland.
Pedro Marques-VidalDepartment of Medicine, Internal Medicine, Lausanne University Hospital (CHUV) and University of Lausanne (UNIL), Lausanne, Switzerland.
Kamiar AminianLaboratory of Movement Analysis and Measurement (LMAM) , Ecole Polytechnique Federale de Lausanne (EPFL), Lausanne, Switzerland.
Peter VollenweiderDepartment of Medicine, Internal Medicine, Lausanne University Hospital (CHUV) and University of Lausanne (UNIL), Lausanne, Switzerland.
Anisoara Paraschiv-IonescuLaboratory of Movement Analysis and Measurement (LMAM) , Ecole Polytechnique Federale de Lausanne (EPFL), Lausanne, Switzerland. anisoara.ionescu@epfl.ch.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Gait speed is a reliable outcome measure across multiple diagnoses, recognized as the 6th vital sign. The focus of the present study was on assessment of gait speed in long-term real-life settings with the aim to: (1) demonstrate feasibility in large cohort studies, using data recorded with a wrist-worn accelerometer device; (2) investigate whether the walking speed assessed in the real-world is consistent with expected trends, and associated with clinical scores such as frailty/handgrip strength. This cross-sectional study included n = 2809 participants (1508 women, 1301 men, [45-75] years old), monitored with a wrist-worn device for 13 consecutive days. Validated algorithms were used to detect the gait bouts and estimate speed. A set of metrics were derived from the statistical distribution of speed of gait bouts categorized by duration (short, medium, long). The estimated usual gait speed (1-1.6 m/s) appears consistent with normative values and expected trends with age, gender, BMI and physical activity levels. Speed metrics significantly improved detection of frailty: AUC increase from 0.763 (no speed metrics) to 0.798, 0.800 and 0.793 for the 95th percentile of individual's gait speed for bout durations < 30, 30-120 and > 120 s, respectively (all p < 0.001). Similarly, speed metrics also improved the prediction of handgrip strength: AUC increase from 0.669 (no speed metrics) to 0.696, 0.696 and 0.691 for the 95th percentile of individual's gait speed for bout durations < 30, 30-120 and > 120 s, respectively (all p < 0.001). Forward stepwise regression showed that the 95th percentile speed of gait bouts with medium duration (30-120 s) to be the best predictor for both conditions. The study provides evidence that real-world gait speed can be estimated using a wrist-worn wearable system, and can be used as reliable indicator of age-related functional decline.

Indexed as

AccelerometryAgedAgingCross-Sectional StudiesFeasibility StudiesFemaleFollow-Up StudiesFrailtyGeriatric AssessmentHand StrengthHumansMaleMiddle AgedProspective StudiesWalking SpeedWearable Electronic Devices

Identifiers

PMID34556721
PMCPMC8460744

What OpenQuestion holds

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LicenceCC BY
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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.