http://stroke.ahajournals.org/content/early/2017/03/09/STROKEAHA.116.015790.short
Abstract
Background and Purpose
Several clinical measures and biomarkers are associated with motor
recovery after stroke, but none are used to guide rehabilitation for
individual patients. The objective of this study was to evaluate the
implementation of upper limb predictions in stroke rehabilitation, by
combining clinical measures and biomarkers using the Predict Recovery
Potential (PREP) algorithm.
Methods—Predictions
were provided for patients in the implementation group (n=110) and
withheld from the comparison group (n=82). Predictions guided
rehabilitation therapy focus for patients in the implementation group.
The effects of predictive information on clinical practice (length of
stay, therapist confidence, therapy content, and dose) were evaluated.
Clinical outcomes (upper limb function, impairment and use,
independence, and quality of life) were measured 3 and 6 months
poststroke. The primary clinical practice outcome was inpatient length
of stay. The primary clinical outcome was Action Research Arm Test score
3 months poststroke.
Results—Length
of stay was 1 week shorter for the implementation group (11 days; 95%
confidence interval, 9–13 days) than the comparison group (17 days; 95%
confidence interval, 14–21 days; P=0.001), controlling for upper limb impairment, age, sex, and comorbidities. Therapists were more confident (P=0.004) and modified therapy content according to predictions for the implementation group (P<0.05).
The algorithm correctly predicted the primary clinical outcome for 80%
of patients in both groups. There were no adverse effects of algorithm
implementation on patient outcomes at 3 or 6 months poststroke.
Conclusions—PREP
algorithm predictions modify therapy content and increase
rehabilitation efficiency after stroke without compromising clinical
outcome.
Clinical Trial Registration—URL: http://anzctr.org.au. Unique identifier: ACTRN12611000755932.
No comments:
Post a Comment