Study improves prediction of movement recovery
Wednesday, 22 March 2017
Study improves prediction of movement recovery to better target rehab after stroke
Kiwi researchers have developed a new and
simple process that is helping therapists accurately predict
how well their patients will regain the use of their hands
and arms after a stroke.
Associate Professor Cathy Stinear and her team at the University of Auckland have created and tested a unique algorithm with therapists treating stroke patients at Auckland Hospital as part of a Health Research Council of New Zealand (HRC)-funded study to better target stroke rehabilitation and improve patients’ outcomes.
The PREP algorithm (Predicting REcovery Potential) can be used in the initial days after a person has had a stroke to predict if they will have an ‘excellent’, ‘good’, ‘limited’ or ‘poor’ recovery of their hand and arm.
The findings from the study, which have been published online this month in the top international journal Stroke, showed the algorithm could correctly predict how well stroke patients’ hands and arms recovered in about 80 per cent of cases, something which is notoriously difficult to do otherwise.
“Your ability to live independently six months after a stroke depends on three main things: your age, the severity of the initial stroke, and how well your hand and arm recover movement. We can’t do anything about your age or how bad your stroke was, but we can do something about how we rehabilitate your hand and arm,” says Dr Stinear.
Research done overseas shows that therapists aren’t very good at predicting how well someone who has had a stroke will be using their hand and arm in three or six months’ time, regardless of how much clinical experience they have. Dr Stinear says there have been particular difficulties predicting recovery in the middle group – that’s people whose movement is not terrible, but not great either.
In this study, recovery predictions were provided for 110 stroke patients and withheld from 82 stroke patients in a comparison group.
Dr Stinear and her team found that therapists who used PREP were more confident that they knew what to expect for their patients’ recovery. This knowledge helped them to tailor their rehabilitation therapy to better meet each patients’ individual needs. In turn, this helped their patients to leave hospital and get back to their homes a week earlier on average than patients who didn’t receive the prediction information.
“What we’ve done is develop a simple algorithm that can make accurate predictions for individual patients, help therapists confidently tailor their therapy, and help patients leave hospital a week earlier with no negative effects on their recovery or satisfaction with care,” says Dr Stinear.
Using the PREP algorithm, the prognosis for close to two-thirds of stroke patients can be made with a simple two-minute clinical assessment of strength in a person’s upper limb. If patients score less than 5 out of 10 on this test (about a third of patients), therapists then use a safe and non-invasive method called transcranial stimulation (TMS) to test how well messages are getting from the stroke side of the brain down to the muscles of the weak hand and arm.
“We’ve had patients who can’t move their hand and arm at all, but when we use the TMS test and stimulate that movement area of their brain, we can see a response in those muscles. This tells us that even though things are looking pretty grim for that person at that point in time, they actually have great potential for recovery because the system still works,” says Dr Stinear.
“This information helps us identify patients whose potential for recovery with intense therapeutic input might otherwise go unrecognised and unrealised. It’s also really important for the patient and their family because it gives them hope and makes them more optimistic about recovery.”
For patients who don’t reach the required threshold in the TMS test, an MRI scan is used to see how much structural damage has been done to the key connections in their brain responsible for movement. This can be used to predict if there are enough residual connections to get at least some movement back to help with basic things like dressing and bathing.
One possible concern was that people with a worse outlook might not be given as much rehabilitation, however, Dr Stinear says this wasn’t the case. The predictions didn’t affect the amount of therapy that patients completed, only the goals and content of the therapy. Patients who received the prediction information recovered just as well those who didn’t.
Dr Stinear’s HRC funding also supported neurological physiotherapist and doctoral student Marie-Claire Smith to run a parallel study for patients with walking difficulties after a stroke. Ms Smith has created another algorithm that can predict when stroke patients will be able to walk independently again with more than 90 per cent accuracy and using just two simple clinical assessments.
HRC Chief Executive Professor Kath McPherson says this research will help therapists and the families of stroke patients get a much more accurate picture of both the level and duration of support that the stroke patient is going to need.
“This is a great example of translational research in action. Cathy and her team have trained therapists at Auckland Hospital to use this tool and they are currently busy helping other hospitals in New Zealand and the US and UK to use it too. They’ve also committed to making all of the resources developed freely available to download online through their wikispace site to give back to the community and maximise New Zealanders’ return on investment,” says Professor McPherson.
View the publication in Stroke: http://stroke.ahajournals.org/content/early/2017/03/09/STROKEAHA.116.015790?ijkey=dYpqSi2hJIroQz1&keytype=ref
More information on PREP is available at http://prepforstrokerehab.wikispaces.com/