Optimizing the Dose of Rehabilitation After Stroke

University Of Southern California, Los Angeles CA

Investigators

Linked publications & trials

Abstract

DESCRIPTION (provided by applicant): Because each patient post stroke has unique impairments and function, it is important to depart from a one size fits all approach to rehabilitation. Although there is now evidence that motor therapy can improve function and use of the more affected limb for patients with moderate to mild impairments, change in use in the months following therapy is variable: for some patients there is an increase in use, but for others a decrease in use. Our long-term goal is to determine prospectively the dose of therapy that leads to further improvements of use after therapy for individual patients while keeping cost at reasonable levels - we call this dose critical dose. Our objective here is to investigate long-term predictions of use as a function of the dose of therapy and of the patient's neurological and behavioral characteristics. Our general hypothesis is that, for a subset of patients, there is a threshold level for arm and hand function to be achieved after therapy, such that if therapy brings function above this threshold, spontaneous use and function will reinforce each other in a virtuous circle. We formulated our hypothesis based on computational models that demonstrate such a threshold and account for existing data. We will address our general hypothesis and accomplish our objective with two aims. Aim 1. Determine the effect of a distributed dose of therapy on immediate and long-term gains in upper extremity use. Aim 2: Develop a means to compute the critical dose for individual patients. With the first aim, we will test our general hypothesis and generate relevant clinical data of function and use. The data will then be used in the second aim to develop a predictive model, based on the Extended Kalman Filter, of long-term arm and hand use as a function of the dose of therapy as well as behavioral and neurological data. Our proposed work is significant because such a predictive model of stroke recovery, once subjected under future funding to clinical trials, can be used to influence policy regarding the necessary dosage of effective treatments at a reasonable cost for the growing number of persons who have survived stroke. This work will also make an important neuro- scientific contribution as we will model, and test behaviorally, the causal and adaptive linkages between the decisions to use the affected arm and recovery of motor function.