Arguments for the biological and predictive relevance of the proportional recovery rule

The proportional recovery rule (PRR) posits that most stroke survivors can expect to reduce a fixed proportion of their motor impairment. As a statistical model, the PRR explicitly relates change scores to baseline values - an approach that arises in many scientific domains but has the potential to introduce artifacts and flawed conclusions. We describe approaches that can assess associations between baseline and changes from baseline while avoiding artifacts due either to mathematical coupling or to regression to the mean. We also describe methods that can compare different biological models of recovery. Across several real datasets in stroke recovery, we find evidence for non-artifactual associations between baseline and change, and support for the PRR compared to alternative models. We also introduce a statistical perspective that can be used to assess future models. We conclude that the PRR remains a biologically relevant model of stroke recovery

Improving Inpatient Stroke Rehabilitation: Proportional Recovery, Neural Coupling and Performance Feedback

The goal of stroke rehabilitation is to enable and improve recovery of lost function of patients suffering from a stroke. The recovery after stroke is split up into three phases. The rst phase, the acute phase, lasts for hours and days after a stroke. Patients are usually hospitalized with the goal to stabilize the condition of the patients. After the acute phase patients enter the sub-acute phase. In this phase patients recover much of the lost function due to spontaneous neurological recovery aided by training. Rehabilitation at the beginning of the sub-acute phase, which lasts up to six to nine months, is often carried out in an inpatient setting. Six to nine months after stroke, patients enter the chronic phase. In this phase further recovery is possible, but usually slower than in the sub-acute phase. In the chronic phase, recovery is mostly driven by training. The work in this thesis is focused on rehabilitation in the sub-acute phase. The aim of this thesis was to develop and test paradigms to improve stroke recovery during inpatient rehabilitation with a focus on motivation in the sub acute phase. It is generally diffcult to prove superiority of interventions in the sub acute phase due to the variance in recovery caused by spontaneous neurological recovery. This dffculty to prove superiority is reflected in the lack of evidenced based therapies for sub acute stroke rehabilitation. To battle the dffculties of developing and proving evidence based therapies, a conceptual framework containing three steps has been proposed: First, identify a promising neural mechanism to restore or to take advantage of. Second, test the mechanics of your hypothesis in a small scale clinical trial and third, show the effcacy of your intervention in a multi center trial. The work in this thesis focuses on the second step: Testing the mechanics of promising interventions. The potential of interventions to improve recovery in the sub acute phase is controversially discussed in literature as there are doubts that recovery beyond spontaneous recovery is even possible. These doubts are largely a manifestation of a speci c interpretation of the renowned Proportional Recovery Rule. The rule states that patients suffering a stroke recover a set proportional of their lost function. One interpretation of the rule assumes that the proportion of recovery is unaffected by rehabilitation interventions and that this set proportion poses an upper bound on potential recovery. The fi rst research question of this thesis was to evaluate, whether doubts that recovery in the sub acute phase has an upper bound and is unaffected by rehabilitation are founded. To clarify these doubts, the literature and the reported data leading to the formation of the Proportional Recovery Rule was reevaluated. To analyze the data leading to the formulation of the Proportional Recovery Rule, data and analyses of the most influential publications on the topic were collected and standardized. The standardized data sets were then compared to simulated data sets exaggerating speci c features of stroke recovery to discuss whether the reported data exhibits these features. Through this process it is shown that the rule holds true as a description of a population-level mechanism, where patients recover a proportion of their initial impairment. But we also showed that there is signi cant variance between different data sets and prediction of recovery on a subject level is not recommend based on the rule. As there is high variance in the recovery of patients we dismiss the notion that the Proportional Recovery Rule posses an upper bound on recovery. We argue that the variance between the analyzed data sets might have been caused by differences in rehabilitation interventions. Several suggestions on how to avoid controversy caused by diverse interpretations of the same data sets through the application of statistical rigor were formulated. The second research question emerged within the work of colleagues investigating a promising neural coupling mechanism caused by specifi c bi-manual movements. These so called cooperative movements are characterized by two hands of an operator moving relative toeach other against the resistance of a clutch. A good example of such a movement is the opening of a bottle. It is hypothesized that by targeting cooperative movements in stroke rehabilitation, treatment effcacy can be increased. To further examine the neural coupling mechanism caused by these movements, a novel device was needed to enable the training of test subjects. To enable training with cooperative movements, the novel device needed to be able to provide an interface with the described properties which are needed to elicit the neural coupling effect. Further, the device needed to be rearrangeable such that a variety of movements could be performed with it. These requirements could best be ful lled by a device consisting of two independent actuator modules which are connected by haptically rendering the properties of a clutch connecting the two modules. The resulting research question was whether manipulating the simulated clutch would cause the same neural coupling response as operating a real clutch. In a test setup with the new device and healthy participants it was shown that the same speci c neural responses were recorded with the simulated clutch as were with a real clutch. The developed device was then replicated and used by colleagues for further studies. The third research question was whether performance feedback is able to increase motivation in stroke patients in an inpatient setting during the sub acute phase. Motivation is a predictor of recovery and it is hypothesized that by increasing motivation of patients for therapy, therapy effciency can be increased. We showed that by providing patients with daily, printed performance feedback containing information about the patients progress, patient activity measured by activity tracker increased but subjective enjoyment of therapy decreased. The reason for the decrease in enjoyment is likely because the feedback was perceived as controlling. Controlling feedback can have detrimental effects on intrinsic motivation which is often equated with the enjoyment of a task. Our results show the potential of providing performance feedback but also highlight that care in the design of the feedback is warranted. In conclusion, the reevaluation of the Proportional Recovery Rule reignited a productive discussion of recovery in the sub acute phase and will lead to more rigor in interpretation and analysis moving forward. Further, the investigation of a neural coupling mechanism was enabled by providing a suitable training device for cooperative hand movements. Finally, the effect of performance feedback on patient motivation was investigated and the findings can be used to create and refine future motivational interventions

What the Proportional Recovery Rule Is (and Is Not): Methodological and Statistical Considerations

In 2008, it was proposed that the magnitude of recovery from nonsevere upper limb motor impairment over the first 3 to 6 months after stroke, measured with the Fugl-Meyer Assessment (FMA), is approximately 0.7 times the initial impairment ("proportional recovery"). In contrast to patients with nonsevere hemiparesis, about 30% of patients with an initial severe paresis do not show such recovery ("nonrecoverers"). Hence it was suggested that the proportional recovery rule (PRR) was a manifestation of a spontaneous mechanism that is present in all patients with mild-to-moderate paresis but only in some with severe paresis. Since the introduction of the PRR, it has subsequently been applied to other motor and nonmotor impairments. This more general investigation of the PRR has led to inconsistencies in its formulation and application, making it difficult to draw conclusions across studies and precipitating some cogent criticism. Here, we conduct a detailed comparison of the different studies reporting proportional recovery and, where appropriate, critique statistical methodology. On balance, we conclude that existing data in aggregate are largely consistent with the PRR as a population-level model for upper limb motor recovery; recent reports of its demise are exaggerated, as these excessively focus on the less conclusive issue of individual subject-level predictions. Moving forward, we suggest that methodological caution and new analytical approaches will be needed to confirm (or refute) a systematic character to spontaneous recovery from motor and other poststroke impairments, which can be captured by a mathematical rule either at the population or at the subject level

Arguments for the biological and predictive relevance of the proportional recovery rule

The proportional recovery rule (PRR) posits that most stroke survivors can expect to reduce a fixed proportion of their motor impairment. As a statistical model, the PRR explic-itly relates change scores to baseline values – an approach that arises in many scientific domains but has the potential to introduce artifacts and flawed conclusions. We describe approaches that can assess associations between baseline and changes from baseline while avoiding artifacts due either to mathematical coupling or to regression to the mean. We also describe methods that can compare different biological models of recovery. Across several real datasets in stroke recovery, we find evidence for non-artifactual associations between baseline and change, and support for the PRR compared to alternative models. We also introduce a statistical perspective that can be used to assess future models. We conclude that the PRR remains a biologically relevant model of stroke recovery