Comparison of Three Tools to Measure Improvements in Upper-Limb Function With Poststroke Therapy

Thompson-Butel, Angelica G.; Lin, Gaven; Shiner, Christine T.; McNulty, Penelope A.

doi:10.1177/1545968314547766

Cited by 34 publications

(40 citation statements)

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“…However the Fugl-Meyer Scale was constructed on the assumptions that recovery proceeds in a proximal-to-distal fashion and from synergistic-to-isolated movements (Fugl-Meyer, Jaasko et al 1975; Gladstone, Danells et al 2002); however, both these assumptions have been contested recently (Woodbury, Velozo et al 2007; Beebe and Lang 2008; Crow and Harmeling-van der Wel 2008). Furthermore, the Fugl-Meyer scale may show ceiling effects for fine motor skills in higher functioning patients (Thompson-Butel, Lin et al 2014). …”

Section: Clinical Outcomesmentioning

confidence: 99%

Upper Limb Motor Impairment After Stroke

Raghavan

2015

Physical Medicine and Rehabilitation Clinics of North America

282

198

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Synopsis Understanding upper limb impairment after stroke is essential to planning therapeutic efforts to restore function. However determining which upper limb impairment to treat and how is complex for two reasons: 1) the impairments are not static, i.e. as motor recovery proceeds, the type and nature of the impairments may change; therefore the treatment needs to evolve to target the impairment contributing to dysfunction at a given point in time. 2) multiple impairments may be present simultaneously, i.e., a patient may present with weakness of the arm and hand immediately after a stroke, which may not have resolved when spasticity sets in a few weeks or months later; hence there may be a layering of impairments over time making it difficult to decide what to treat first. The most useful way to understand how impairments contribute to upper limb dysfunction may be to examine them from the perspective of their functional consequences. There are three main functional consequences of impairments on upper limb function are: (1) learned nonuse, (2) learned bad-use, and (3) forgetting as determined by behavioral analysis of tasks. The impairments that contribute to each of these functional limitations are described.

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Section: Clinical Outcomesmentioning

confidence: 99%

Upper Limb Motor Impairment After Stroke

Raghavan

2015

Physical Medicine and Rehabilitation Clinics of North America

282

198

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“…This analysis was designed to minimise the floor and/or ceiling effects of individual assessments, given the heterogeneous distribution of motor-function within this cohort (ThompsonButel et al, 2014;2015). The first principle component was extracted to generate a PCA motorfunction score for each patient, whereby lower scores correspond to lower motor-function.…”

Section: Motor Functional Assessment Analysismentioning

confidence: 99%

Cortical beta oscillations and motor thresholds differ across the spectrum of post-stroke motor impairment, a preliminary MEG and TMS study

et al. 2015

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“…8 To determine the optimal method to evaluate post-stroke impairment, recent studies have compared assessment tools, including the use of the FM-UE. 9–11 …”

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confidence: 99%

“…10,11,16 For example, to avoid ceiling effects common to the FM-UE, it has been suggested that the test should be used for measuring baseline and changes in impairment only among patients with lower motor function. 10,11,17 Furthermore, the utility of the FM-UE used alone to assess function has been questioned. Thompson-Butel and colleagues hold that a single instrument is not able to distinguish levels of post stroke impairment.…”

mentioning

confidence: 99%

Determining Levels of Upper Extremity Movement Impairment by Applying a Cluster Analysis to the Fugl-Meyer Assessment of the Upper Extremity in Chronic Stroke

Woytowicz

Rietschel²,

Goodman³

et al. 2017

Archives of Physical Medicine and Rehabilitation

257

172

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Objective To quantitatively define levels of upper extremity movement impairment using cluster analysis of Fugl-Meyer upper extremity (FM-UE) with and without reflex items. Design Secondary analysis of FM-UE individual item scores compiled from baseline testing of 5 studies with consistent testing procedures. Setting University and VA research centers. Participants: Individuals (N=−247) with chronic stroke (>6 months post-stroke). Interventions Not applicable. Main Outcome Measures Cut-off scores defined by total FM-UE scores of clusters identified by two hierarchical cluster analyses run on full sample of FM-UE individual item scores (with/without reflexes). Patterns of motor function defined by aggregate item scores of clusters. Results FM-UE scores ranged from 2–63 (mean=26.9±15.7) with reflex items and 0–57 (mean=22.1 ±15.3) without reflex items. Three clusters were identified. The distributions of the FM-UE scores revealed considerable overlap between the clusters, therefore four distinct stroke impairment levels were also derived. Conclusions For chronic stroke, the cluster analyses of the upper extremity FM support either a three or a four impairment level classification scheme.

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Comparison of Three Tools to Measure Improvements in Upper-Limb Function With Poststroke Therapy

Abstract: These results suggest that no single test is suitable for measuring function and improvement across the spectrum of poststroke upper-limb dysfunction and that assessment tool selection should be based on the level of residual motor-function of individual patients.

Cited by 34 publications

References 50 publications

Upper Limb Motor Impairment After Stroke

Upper Limb Motor Impairment After Stroke

Cortical beta oscillations and motor thresholds differ across the spectrum of post-stroke motor impairment, a preliminary MEG and TMS study

Determining Levels of Upper Extremity Movement Impairment by Applying a Cluster Analysis to the Fugl-Meyer Assessment of the Upper Extremity in Chronic Stroke

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