Evidence map›Paper›PMID 29159193›Full record

ArticleAnnals of clinical and translational neurology2017

PREP2: A biomarker-based algorithm for predicting upper limb function after stroke.

Cathy M Stinear, Winston D Byblow, Suzanne J Ackerley, Marie-Claire Smith, Victor M Borges, P Alan Barber

Registry-linked trialAbstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Annals of clinical and translational neurology, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT04688970 (Personalized Neurorehabilitative Precision Medicine - From Data to Therapies), which is not on this map. Cited by 157 papers, 6 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
157citing papers in PubMed, 6 pooled it
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

NCT04688970 unknown statusnot on this mapstarted 2020, after this paper: background citation

Personalized Neurorehabilitative Precision Medicine - From Data to Therapies

TypeobservationalSponsorUniversity Hospital TuebingenRan2020 to 2022Enrolled500ConditionsStroke, Acute, Outcome, Improvement, Rehabilitation, Upper Extremity ParesisArmsno intervention
3 · Its place in the literature

Who cites it

157 citing papers in PubMed, 6 syntheses or guidelines pooled it.

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  3. Quantitative measures of the resting EEG in stroke: a systematic review on clinical correlation and prognostic value.Neurological sciences : official journal of the Italian Neurological Society and of the Italian Society of Clinical Neurophysiology · 2023
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97 more citing papers are in PubMed but not listed here.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors.

Cathy M StinearDepartment of Medicine University of Auckland Private Bag 92019 Auckland 1142 New Zealand.ORCID 0000-0002-9404-1959
Winston D ByblowCentre for Brain Research University of Auckland Private Bag 92019 Auckland 1142 New Zealand.
Suzanne J AckerleyDepartment of Medicine University of Auckland Private Bag 92019 Auckland 1142 New Zealand.
Marie-Claire SmithDepartment of Medicine University of Auckland Private Bag 92019 Auckland 1142 New Zealand.
Victor M BorgesDepartment of Medicine University of Auckland Private Bag 92019 Auckland 1142 New Zealand.
P Alan BarberDepartment of Medicine University of Auckland Private Bag 92019 Auckland 1142 New Zealand.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Objective: Recovery of motor function is important for regaining independence after stroke, but difficult to predict for individual patients. Our aim was to develop an efficient, accurate, and accessible algorithm for use in clinical settings. Clinical, neurophysiological, and neuroimaging biomarkers of corticospinal integrity obtained within days of stroke were combined to predict likely upper limb motor outcomes 3 months after stroke. Methods: Data from 207 patients recruited within 3 days of stroke [103 females (50%), median age 72 (range 18-98) years] were included in a Classification and Regression Tree analysis to predict upper limb function 3 months poststroke. Results: The analysis produced an algorithm that sequentially combined a measure of upper limb impairment; age; the presence or absence of upper limb motor evoked potentials elicited with transcranial magnetic stimulation; and stroke lesion load obtained from MRI or stroke severity assessed with the NIHSS score. The algorithm makes correct predictions for 75% of patients. A key biomarker obtained with transcranial magnetic stimulation is required for one third of patients. This biomarker combined with NIHSS score can be used in place of more costly magnetic resonance imaging, with no loss of prediction accuracy. Interpretation: The new algorithm is more accurate, efficient, and accessible than its predecessors, which may support its use in clinical practice. While further work is needed to potentially incorporate sensory and cognitive factors, the algorithm can be used within days of stroke to provide accurate predictions of upper limb functional outcomes at 3 months after stroke. www.presto.auckland.ac.nz.

Identifiers

PMID29159193
PMCPMC5682112

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Registered trials

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.