What the fuck, the goal is 100% recovery for ALL survivors. Cherry picking will not be tolerated. So the stroke medical world expects strokes to be consistent, ignoring the real world stroke out there.
Biomarkers for Patient Selection Improve Stroke Rehabilitation Trial Efficiency
Abstract
There
is high inter-individual variability in recovery after stroke, which
reduces statistical power in rehabilitation trials. This could be
addressed by using biomarkers for patient selection. Corticospinal tract
function assessed with transcranial magnetic stimulation (TMS) is a
candidate biomarker for trials aiming to improve upper-limb motor
recovery. Patients in whom TMS can elicit motor evoked potentials (MEPs)
have a functionally intact lateral corticospinal tract and better motor
recovery. We used an existing data set to estimate the sample sizes
required to detect rehabilitation benefits on upper-limb motor
performance 90 days after stroke. Baseline clinical assessments were
made and MEP status of the paretic upper-limb determined within 7 days
post-stroke. Upper-limb Fugl-Meyer (UE-FM) and Action Research Arm Test
(ARAT) scores were obtained 90 days after stroke. Analyses were carried
out for the full sample, and repeated for the MEP+ subset. Population
estimates of the UE-FM and ARAT scores 90 days post-stroke were used to
calculate the sample sizes required to detect clinically meaningful
treatment effects of 7 points on the UE-FM and ARAT scores. Baseline and
90-day assessments were completed by 207 patients (103 women, mean 70.6
SD 15.1 years). The full sample and MEP+ subset (n=177) had similar
demographic and baseline clinical characteristics. The estimated
required sample sizes to detect treatment effects for MEP+ patients were
only 27-29% of those for the full sample of patients. The estimated
percentage of patients who are MEP+ was 85.5% (95%CI 81.2%-89.9%).
Biomarkers could be used to enrich samples for stroke rehabilitation
trials. Selecting patients on the basis of MEP status reduces variance,
thereby reducing required sample size by around 75% without
significantly limiting the pool of participants. Using biomarkers for
patient selection could markedly increase rehabilitation trial
sensitivity and efficiency, with associated decreases in costs and time
required for completion.
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