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/