Construct validity and responsiveness of clinical upper limb measures and sensor-based arm use within the first year after stroke: a longitudinal cohort study
Abstract Background Construct 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 s...
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BMC
2025-01-01
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| Series: | Journal of NeuroEngineering and Rehabilitation |
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| Online Access: | https://doi.org/10.1186/s12984-024-01512-9 |
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| author | Johannes Pohl Geert Verheyden Jeremia Philipp Oskar Held Andreas Ruediger Luft Chris Easthope Awai Janne Marieke Veerbeek |
| author_facet | Johannes Pohl Geert Verheyden Jeremia Philipp Oskar Held Andreas Ruediger Luft Chris Easthope Awai Janne Marieke Veerbeek |
| author_sort | Johannes Pohl |
| collection | DOAJ |
| description | Abstract Background Construct 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. Methods In 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. Results Ninety-three individuals participated. At D3 and D10, correlations between clinical measures and AU metrics showed variability (range rs: 0.44–0.90). All following time points showed moderate-to-high positive correlations between clinical measures and affected AU metrics (range rs: 0.57–0.88). Unilateral nonaffected AU duration was negatively correlated with clinical measures (range rs: -0.48 to -0.77). Responsiveness across outcomes was highest between D10-D28 within moderate to strong relations between GRPC and clinical measures (rs: range 0.60–0.73), whereas relations were weaker for AU metrics (range rs: 0.28–0.43) Eight MIC values were estimated for clinical measures and nine for AU metrics, showing moderate to good accuracy (66–87%). Conclusions We 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 registration This trial was registered on clinicaltrials.gov; registration number NCT03522519. |
| format | Article |
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| institution | Kabale University |
| issn | 1743-0003 |
| language | English |
| publishDate | 2025-01-01 |
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| spelling | doaj-art-5630da693f2242c0acc1c3e675fdad8e2025-02-02T12:11:48ZengBMCJournal of NeuroEngineering and Rehabilitation1743-00032025-01-0122112110.1186/s12984-024-01512-9Construct validity and responsiveness of clinical upper limb measures and sensor-based arm use within the first year after stroke: a longitudinal cohort studyJohannes Pohl0Geert Verheyden1Jeremia Philipp Oskar Held2Andreas Ruediger Luft3Chris Easthope Awai4Janne Marieke Veerbeek5Lake Lucerne Institute, Data Analytics and Rehabilitation Technology (DART)Department of Rehabilitation Sciences, KU Leuven, Leuven Brain InstituteValens Clinics, Reha Center TriemliLake Lucerne Institute, Data Analytics and Rehabilitation Technology (DART)Lake Lucerne Institute, Data Analytics and Rehabilitation Technology (DART)Luzerner Kantonsspital, University, Teaching and Research Hospital, University of LucerneAbstract Background Construct 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. Methods In 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. Results Ninety-three individuals participated. At D3 and D10, correlations between clinical measures and AU metrics showed variability (range rs: 0.44–0.90). All following time points showed moderate-to-high positive correlations between clinical measures and affected AU metrics (range rs: 0.57–0.88). Unilateral nonaffected AU duration was negatively correlated with clinical measures (range rs: -0.48 to -0.77). Responsiveness across outcomes was highest between D10-D28 within moderate to strong relations between GRPC and clinical measures (rs: range 0.60–0.73), whereas relations were weaker for AU metrics (range rs: 0.28–0.43) Eight MIC values were estimated for clinical measures and nine for AU metrics, showing moderate to good accuracy (66–87%). Conclusions We 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 registration This trial was registered on clinicaltrials.gov; registration number NCT03522519.https://doi.org/10.1186/s12984-024-01512-9Upper limb measuresMovement sensorsMeasurement propertiesStrokeClinical rehabilitation |
| spellingShingle | Johannes Pohl Geert Verheyden Jeremia Philipp Oskar Held Andreas Ruediger Luft Chris Easthope Awai Janne Marieke Veerbeek Construct validity and responsiveness of clinical upper limb measures and sensor-based arm use within the first year after stroke: a longitudinal cohort study Journal of NeuroEngineering and Rehabilitation Upper limb measures Movement sensors Measurement properties Stroke Clinical rehabilitation |
| title | Construct validity and responsiveness of clinical upper limb measures and sensor-based arm use within the first year after stroke: a longitudinal cohort study |
| title_full | Construct validity and responsiveness of clinical upper limb measures and sensor-based arm use within the first year after stroke: a longitudinal cohort study |
| title_fullStr | Construct validity and responsiveness of clinical upper limb measures and sensor-based arm use within the first year after stroke: a longitudinal cohort study |
| title_full_unstemmed | Construct validity and responsiveness of clinical upper limb measures and sensor-based arm use within the first year after stroke: a longitudinal cohort study |
| title_short | Construct validity and responsiveness of clinical upper limb measures and sensor-based arm use within the first year after stroke: a longitudinal cohort study |
| title_sort | construct validity and responsiveness of clinical upper limb measures and sensor based arm use within the first year after stroke a longitudinal cohort study |
| topic | Upper limb measures Movement sensors Measurement properties Stroke Clinical rehabilitation |
| url | https://doi.org/10.1186/s12984-024-01512-9 |
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