Evidence map›Paper›PMID 39881332›Full record

Observational studyJournal of neuroengineering and rehabilitation2025

Construct validity and responsiveness of clinical upper limb measures and sensor-based arm use within the first year after stroke: a longitudinal cohort study.

Johannes Pohl, Geert Verheyden, Jeremia Philipp Oskar Held, Andreas Ruediger Luft, Chris Easthope Awai, Janne Marieke Veerbeek

Registry-linked trialAbstract readObservational Study
In one paragraph

Observational study in Journal of neuroengineering and rehabilitation, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT03522519 (Profiling and Predicting the Natural Course of Real World Physical Activity and Upper Limb Use After Stroke), which is not on this map. Cited by 7 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
7citing 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.

NCT03522519 completednot on this map

Profiling and Predicting the Natural Course of Real World Physical Activity and Upper Limb Use After Stroke

TypeobservationalSponsorUniversity of ZurichRan2018 to 2021Enrolled98ConditionsStrokeArmsReal world performance of physical activity and arm use
3 · Its place in the literature

Who cites it

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

  1. Pooled it
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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.

Johannes PohlLake Lucerne Institute, Data Analytics and Rehabilitation Technology (DART), Vitznau, Switzerland. Johannes.Pohl@llui.org.
Geert VerheydenDepartment of Rehabilitation Sciences, KU Leuven, Leuven Brain Institute, Leuven, Belgium.
Jeremia Philipp Oskar HeldValens Clinics, Reha Center Triemli, Zurich, Switzerland.
Andreas Ruediger LuftLake Lucerne Institute, Data Analytics and Rehabilitation Technology (DART), Vitznau, Switzerland.
Chris Easthope Awai *Lake Lucerne Institute, Data Analytics and Rehabilitation Technology (DART), Vitznau, Switzerland.
Janne Marieke Veerbeek *Luzerner Kantonsspital, University, Teaching and Research Hospital, University of Lucerne, Lucerne, Switzerland.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundConstruct validity and responsiveness of upper limb outcome measures are essential to interpret motor recovery poststroke. Evaluating the associations between clinical upper limb measures and sensor-based arm use (AU) fosters a coherent understanding of motor recovery. Defining sensor-based AU metrics for intentional upper limb movements could be crucial in mitigating bias from walking-related activities. Here, we investigate the measurement properties of a comprehensive set of clinical measures and sensor-based AU metrics when gait and non-functional upper limb movements are excluded.

methodsIn this prospective, longitudinal cohort study, individuals with motor impairment were measured at days 3 ± 2 (D3), 10 ± 2 (D10), 28 ± 4 (D28), 90 ± 7 (D90), and 365 ± 14 (D365) after their first stroke. Using clinical measures, upper limb motor function (Fugl-Meyer Assessment), capacity (Action Research Arm Test, Box & Block Test), and perceived performance (14-item Motor Activity Log) were assessed. Additionally, individuals wore five movement sensors (trunk, wrists, and ankles) for three days. Thirteen AU metrics were computed based on functional movements during non-walking periods. Construct validity across clinical measures and AU metrics was determined by Spearman's rank correlations for each time point. Criterion responsiveness was examined by correlating patient-reported Global Rating of Perceived Change (GRPC) scores and observed change in upper limb measures and AU metrics. Optimal cut-off values for minimal important change (MIC) were estimated by ROC curve analysis.

resultsNinety-three individuals participated. At D3 and D10, correlations between clinical measures and AU metrics showed variability (range r

conclusionsWe present reference data on the construct validity and responsiveness of clinical upper limb measures and specified sensor-based AU metrics within the first year after stroke. The MIC values can be used as a benchmark for clinical stroke rehabilitation.

trial registrationThis trial was registered on clinicaltrials.gov; registration number NCT03522519.

Indexed as

ArmStrokeStroke RehabilitationUpper ExtremityAdultAgedCohort StudiesFemaleHumansLongitudinal StudiesMaleMiddle AgedProspective StudiesRecovery of FunctionReproducibility of ResultsClinical rehabilitationMeasurement propertiesMovement sensorsStrokeUpper limb measures

Identifiers

PMID39881332
PMCPMC11776245

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Registered trials

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.