Intensive, time-series measurement of upper limb recovery in the subacute phase following stroke

Goodwin, Nicola; Sunderland, Alan

doi:10.1191/0269215503cr571oa

Cited by 20 publications

(7 citation statements)

References 26 publications

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“…Additionally, the recovery of upper extremity function in the control group as measured by the B&B and the light object lift subtest of the J-T test battery lends support to the previous observation that some patients with a first ischemic stroke in various subcortical loci can expect to recover upper extremity function when enrolled in an intensive task-specific exercise program. 3,8,9,33,34 The main hypothesis that FES combined with task-specific exercises significantly enhances such recovery when compared to task-specific exercise alone was clearly demonstrated in this study.…”

Section: Discussionsupporting

confidence: 63%

Functional Electrical Stimulation Enhancement of Upper Extremity Functional Recovery During Stroke Rehabilitation: A Pilot Study

Alon

Levitt

McCarthy

2007

Neurorehabil Neural Repair

202

109

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Objective. To test if functional electrical stimulation (FES) can enhance the recovery of upper extremity function during early stroke rehabilitation. Methods. Open-label block-randomized trial, begun during inpatient rehabilitation and continued at the patients' home. Patients were assigned to either FES combined with task-specific upper extremity rehabilitation (n = 7) or a control group that received task-specific therapy alone (n = 8) over 12 weeks. Outcome measures. Hand function (Box & Blocks, B&B; Jebsen-Taylor light object lift, J-T) and motor control (modified Fugl-Meyer, mF-M) were video-recorded for both upper extremities at baseline, 4, 8, and 12 weeks. Results. B&B mean score at 12 weeks favored (P = .049) the FES group (42.3 ± 16.6 blocks) over the control group (26.3 ± 11.0 blocks). The FES group J-T task was 6.7 ± 2.9 seconds and faster (P = .049) than the 11.8 ± 5.4 seconds of the control group. Mean mF-M score of the FES group at 12 weeks was 49.3 ± 5.1 points out of 54, compared to the control group that scored 40.6 ± 8.2 points (P = .042). All patients regained hand function. Conclusion. Upper extremity task-oriented training that begins soon after stroke that incorporates FES may improve upper extremity functional use in patients with mild/moderate paresis more than task-oriented training without FES.

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Section: Discussionsupporting

confidence: 63%

Functional Electrical Stimulation Enhancement of Upper Extremity Functional Recovery During Stroke Rehabilitation: A Pilot Study

Alon

Levitt

McCarthy

2007

Neurorehabil Neural Repair

202

109

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“…Previous studies suggested that baseline functional status is a stronger predictor for the recovery of functions than are multidimensional risk factors because the initial patterns of recovery could be affected by any of a number of multiple factors [16], [17]. Longitudinal studies on stroke recovery have traditionally focused on correlational analysis using linear regression modeling [18]–[25]. Moreover, single-subject research has assessed the slope of a trend or the rate of change within the individual's data so that individual recovery could be deduced from the correlation of the group data [16], [17], [26]–[28].…”

Section: Introductionmentioning

confidence: 99%

“…However, stroke patients typically show nonlinear recovery patterns [29]. In general, cognitive and motor dysfunction and activity limitation show rapid recovery during the acute phase and reach a plateau or level off after several months following onset [15]–[17], [25]. Koyama et al [16] and Suzuki et al [17] examined the validity and the applicability of logarithmic modeling for predicting the functional recovery of stroke patients with hemiplegia.…”

Section: Introductionmentioning

confidence: 99%

Predicting Recovery of Cognitive Function Soon after Stroke: Differential Modeling of Logarithmic and Linear Regression

Sugimura¹,

Yamada

Omori

et al. 2013

PLoS ONE

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Cognitive disorders in the acute stage of stroke are common and are important independent predictors of adverse outcome in the long term. Despite the impact of cognitive disorders on both patients and their families, it is still difficult to predict the extent or duration of cognitive impairments. The objective of the present study was, therefore, to provide data on predicting the recovery of cognitive function soon after stroke by differential modeling with logarithmic and linear regression. This study included two rounds of data collection comprising 57 stroke patients enrolled in the first round for the purpose of identifying the time course of cognitive recovery in the early-phase group data, and 43 stroke patients in the second round for the purpose of ensuring that the correlation of the early-phase group data applied to the prediction of each individual's degree of cognitive recovery. In the first round, Mini-Mental State Examination (MMSE) scores were assessed 3 times during hospitalization, and the scores were regressed on the logarithm and linear of time. In the second round, calculations of MMSE scores were made for the first two scoring times after admission to tailor the structures of logarithmic and linear regression formulae to fit an individual's degree of functional recovery. The time course of early-phase recovery for cognitive functions resembled both logarithmic and linear functions. However, MMSE scores sampled at two baseline points based on logarithmic regression modeling could estimate prediction of cognitive recovery more accurately than could linear regression modeling (logarithmic modeling, R2 = 0.676, P<0.0001; linear regression modeling, R2 = 0.598, P<0.0001). Logarithmic modeling based on MMSE scores could accurately predict the recovery of cognitive function soon after the occurrence of stroke. This logarithmic modeling with mathematical procedures is simple enough to be adopted in daily clinical practice.

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“…10 This is likely to occur in particular when the time periods between repeated measurements are relatively short and the within-subject correlation high, which is often the case in stroke. 4,11 Because of this limitation, we elected to use a model in which the crosssectional component is more or less "removed" from the analysis by modeling only change scores. By modeling longitudinal change scores, one can develop a rationale for the impact of improvements of underlying functions, such as strength, synergism, and balance control on changes in walking ability (ie, quasi-causal relationships).…”

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confidence: 99%

Predicting Improvement in Gait After Stroke

Kollen

Port

Lindeman

et al. 2005

Stroke

235

179

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Background and Purpose-To study the longitudinal relationship of functional change in walking ability and change in time-dependent covariates and to develop a multivariate regression model to predict longitudinal change of walking ability. Methods-A total of 101 acute stroke patients with first-ever ischemic middle cerebral artery strokes was used as the population. Prospective cohort study based on 18 repeated measurements over time during the first poststroke year. Baseline characteristics as well as longitudinal information from functional ambulation categories (FAC), Fugl-Meyer leg score (FM-leg), Motricity index leg score (MI-leg), letter cancellation task (LCT), Fugl-Meyer balance (FMbalance), and timed balance test (TBT) were obtained. Intervention consisted of a basic rehabilitation program with additional arm, leg, or air splint therapy. Main outcome measure constituted change scores on FAC over time. Results-In total, 1532 of the 1717 change scores were available for regression analysis. The regression model showed that TBT change scores were the most important factor in predicting improvement on FAC (␤ϭ0.094; PϽ0.001) followed by changes scores on FM-leg (␤ϭ0.014; PϽ0.001) and reduction in LCT omissions (␤ϭϪ0.010; PϽ0.001) and MI leg test (␤ϭ0.001; PϽ0.001). In addition, time itself was significantly negatively associated with improvement (␤ϭϪ0.002; PϽ0.001). Conclusion-Improvement in standing balance control is more important than improvement in leg strength or synergism to achieve improvement in walking ability, whereas reduction in visuospatial inattention is independently related to improvement of gait. Finally, time itself is an independent covariate that is negatively associated with change on FAC, suggesting that most pronounced improvements occur earlier after stroke.

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Intensive, time-series measurement of upper limb recovery in the subacute phase following stroke

Cited by 20 publications

References 26 publications

Functional Electrical Stimulation Enhancement of Upper Extremity Functional Recovery During Stroke Rehabilitation: A Pilot Study

Functional Electrical Stimulation Enhancement of Upper Extremity Functional Recovery During Stroke Rehabilitation: A Pilot Study

Predicting Recovery of Cognitive Function Soon after Stroke: Differential Modeling of Logarithmic and Linear Regression

Predicting Improvement in Gait After Stroke

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