Proportional Recovery From Lower Limb Motor Impairment After Stroke

Smith, Marie-Claire; Byblow, Winston D.; Barber, P. Alan; Stinear, Cathy M.

doi:10.1161/strokeaha.116.016478

Cited by 93 publications

(119 citation statements)

References 13 publications

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“…When predicting behavioural performance in humans, these effect sizes are unprecedented. Like many of its counterparts 5,10,12 , this study also reported a group of 'non-fitters', who did not make the predicted recovery. But if non-fitters can be distinguished from fitters at the acute stage, as the authors' results also suggest, the implication is that we can predict most patients' recovery near-perfectly, at least during the first few months after stroke onset.…”

Section: Introductionmentioning

confidence: 53%

“…Taken together, these studies report analyses involving over 500 patients, spread across different countries with different approaches to rehabilitation, regardless of the patients' ages at stroke onset, stroke type, sex, or therapy dose 2 . And there is increasing evidence that the proportional recovery rule also captures recovery from other post-stroke impairments, including impairments of lower limb function 10 , attention 11,12 , and language 12,13 : one recent study suggests that proportional recovery applies quite generally across cognitive domains 14 . Indeed, even rats appear to recover proportionally after stroke 15 .…”

Section: Introductionmentioning

confidence: 99%

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Recovery after stroke: not so proportional after all?

Hope

Friston

Price

et al. 2018

Preprint

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27Background 28The proportional recovery rule asserts that most stroke survivors recover a fixed proportion of lost 29 function. Reports that the rule can be used to predict recovery, extraordinarily accurately, are 30 rapidly accumulating. Here, we show that the rule may not be as powerful as it seems. 31 Methods 32We provide a formal analysis of the relationship between baseline scores (X), outcomes (Y) and 33 recovery (Y-X), to highlight the shortcomings of the proportional recovery rule, and illustrate those 34 problems with simulations in which synthetic recovery data are derived from different types of 35 recovery processes. 36 Findings 37When the correlation between baseline scores and recovery is stronger than that between baselines 38 scores and outcomes, the former can create an inflated impression of how predictable outcomes 39 really are given baseline scores. This often happens when outcomes are less variable than baseline 40 scores, as is common in empirical studies of recovery after stroke. Moreover, we cannot use the 41 results of these correlations to distinguish proportional recovery from recovery which is either not 42 consistently proportional, or not proportional at all. 43 Interpretation 44Analyses relating baseline scores to subsequent change are a minefield: our formal analysis applies 45 as consistently outside the area of stroke as it does within it. One implication of our analysis is that 46 the proportional recovery rule is not as predictive of real recovery after stroke as recent empirical 47 studies suggest. Another is that different analytical methods will be required to ascertain whether 48 recovery is even proportional at all. 49 50 All rights reserved. No reuse allowed without permission.

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Section: Introductionmentioning

confidence: 53%

Section: Introductionmentioning

confidence: 99%

Recovery after stroke: not so proportional after all?

Hope

Friston

Price

et al. 2018

Preprint

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“…As recently emphasized, the next step is to start an international collaboration for building data sets large enough to address these questions and move recovery and rehabilitation studies forward . These databases could also be used to model recovery of lower limb impairment as well as other nonmotor modalities such as speech and visuo‐spatial neglect after stroke …”

Section: Discussionmentioning

confidence: 99%

“…Longitudinal studies have repeatedly demonstrated the time‐dependency of neurological recovery after stroke, including upper and lower limb motor function, visuo‐spatial neglect, and speech . This suggests that recovery follows a predictable pattern, which is often described as spontaneous neurological recovery .…”

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confidence: 99%

Predicting Upper Limb Motor Impairment Recovery after Stroke: A Mixture Model

Vliet

Selles

Andrinopoulou

et al. 2020

Annals of Neurology

140

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Objective Spontaneous recovery is an important determinant of upper extremity recovery after stroke and has been described by the 70% proportional recovery rule for the Fugl–Meyer motor upper extremity (FM‐UE) scale. However, this rule is criticized for overestimating the predictability of FM‐UE recovery. Our objectives were to develop a longitudinal mixture model of FM‐UE recovery, identify FM‐UE recovery subgroups, and internally validate the model predictions. Methods We developed an exponential recovery function with the following parameters: subgroup assignment probability, proportional recovery coefficient r k, time constant in weeks τ k, and distribution of the initial FM‐UE scores. We fitted the model to FM‐UE measurements of 412 first‐ever ischemic stroke patients and cross‐validated endpoint predictions and FM‐UE recovery cluster assignment. Results The model distinguished 5 subgroups with different recovery parameters ( r1 = 0.09, τ1 = 5.3, r2 = 0.46, τ2 = 10.1, r3 = 0.86, τ3 = 9.8, r4 = 0.89, τ4 = 2.7, r5 = 0.93, τ5 = 1.2). Endpoint FM‐UE was predicted with a median absolute error of 4.8 (interquartile range [IQR] = 1.3–12.8) at 1 week poststroke and 4.2 (IQR = 1.3–9.8) at 2 weeks. Overall accuracy of assignment to the poor (subgroup 1), moderate (subgroups 2 and 3), and good (subgroups 4 and 5) FM‐UE recovery clusters was 0.79 (95% equal‐tailed interval [ETI] = 0.78–0.80) at 1 week poststroke and 0.81 (95% ETI = 0.80–0.82) at 2 weeks. Interpretation FM‐UE recovery reflects different subgroups, each with its own recovery profile. Cross‐validation indicates that FM‐UE endpoints and FM‐UE recovery clusters can be well predicted. Results will contribute to the understanding of upper limb recovery patterns in the first 6 months after stroke. ANN NEUROL 2020;87:383–393 Ann Neurol 2020;87:383–393

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“…35 Based on the congruency of these findings with the human literature, it is plausible that common biological stroke recovery processes that are engaged by these variables might exist across mammalian species. 36 In humans, it has been demonstrated that this proportional recovery rule can be used to predict recovery of impairments within a variety of functional domains, including both upper 32,33,37 and lower limbs, 38 aphasia, 39 and visual neglect. 40 To address this secondary objective, we assessed whether our model of initial poststroke impairment, cortical infarct volume, and rehabilitation intensity 35 could be generalized as predictors of recovery on an additional forelimb motor task (single-pellet reaching).…”

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confidence: 99%

Synergistic Effects of Enriched Environment and Task-Specific Reach Training on Poststroke Recovery of Motor Function

Jeffers

Corbett

2018

Stroke

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Background and Purpose-Reach training in concert with environmental enrichment provides functional benefits after experimental stroke in rats. The present study extended these findings by assessing whether intensive task-specific reach training or enrichment initiated alone would provide similar functional benefit. Additionally, we investigated whether the 70% recovery rule, or a combined model of initial poststroke impairment, cortical infarct volume, and rehabilitation intensity, could predict recovery in the single-pellet task, as previously found for the Montoya staircase. Methods-Rats were trained on single-pellet reaching before middle cerebral artery occlusion via intracerebral injection of ET-1 (endothelin-1). There were 4 experimental groups: stroke+enrichment, stroke+reaching, stroke+enrichment+reaching, and sham+enrichment+reaching. Reaching rehabilitation utilized a modified Whishaw box that encouraged impaired forelimb reaching for 6 hours per day, 5 days per week, for 4 weeks. All treatment paradigms began 7 days after ischemia with weekly assessment on the single-pellet task during rehabilitation and again 4 weeks after rehabilitation concluded. Results-Rats exposed to the combination of enrichment and reaching showed the greatest improvement in pellet retrieval and comparable performance to shams after 3 weeks of treatment, whereas those groups that received a monotherapy remained significantly impaired at all time points. Initial impairment alone did not significantly predict recovery in single-pellet as the 70% rule would suggest; however, a combined model of cortical infarct volume and rehabilitation intensity predicted change in pellet retrieval on the single-pellet task with the same accuracy as previously shown with the staircase, demonstrating the generalizability of this model across reaching tasks. Conclusions-Task-specific reach training and environmental enrichment have synergistic effects in rats that persist long after rehabilitation ends, and this recovery is predicted by infarct volume and rehabilitation intensity.

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Proportional Recovery From Lower Limb Motor Impairment After Stroke

Cited by 93 publications

References 13 publications

Recovery after stroke: not so proportional after all?

Recovery after stroke: not so proportional after all?

Predicting Upper Limb Motor Impairment Recovery after Stroke: A Mixture Model

Synergistic Effects of Enriched Environment and Task-Specific Reach Training on Poststroke Recovery of Motor Function

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