Evidence map›Paper›PMID 31925838›Full record

ArticleAnnals of neurology2020

Predicting Upper Limb Motor Impairment Recovery after Stroke: A Mixture Model.

Rick van der Vliet, Ruud W Selles, Eleni-Rosalina Andrinopoulou, Rinske Nijland, Gerard M Ribbers, Maarten A Frens, Carel Meskers, Gert Kwakkel

Abstract read
In one paragraph

Article in Annals of neurology, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 117 papers, 7 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
117citing papers in PubMed, 7 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.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

117 citing papers in PubMed, 7 syntheses or guidelines pooled it.

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57 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

8 authors.

Rick van der VlietDepartment of Neuroscience, Erasmus University Medical Center, Rotterdam, the Netherlands.
Ruud W SellesDepartment of Rehabilitation Medicine, Erasmus University Medical Center, Rotterdam, the Netherlands.ORCID 0000-0002-2432-6756
Eleni-Rosalina AndrinopoulouDepartment of Biostatistics, Erasmus University Medical Center, Rotterdam, the Netherlands.
Rinske NijlandDepartment of Rehabilitation Medicine, Amsterdam University Medical Centre, VU University Medical Center, Amsterdam Neurosciences and Amsterdam Movement Sciences, Amsterdam, the Netherlands.
Gerard M RibbersDepartment of Rehabilitation Medicine, Erasmus University Medical Center, Rotterdam, the Netherlands.
Maarten A FrensDepartment of Neuroscience, Erasmus University Medical Center, Rotterdam, the Netherlands.
Carel MeskersDepartment of Rehabilitation Medicine, Amsterdam University Medical Centre, VU University Medical Center, Amsterdam Neurosciences and Amsterdam Movement Sciences, Amsterdam, the Netherlands.
Gert KwakkelDepartment of Rehabilitation Medicine, Amsterdam University Medical Centre, VU University Medical Center, Amsterdam Neurosciences and Amsterdam Movement Sciences, Amsterdam, the Netherlands.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectiveSpontaneous recovery is an important determinant of upper extremity recovery after stroke and has been described by the 70% proportional recovery rule for the Fugl-Meyer motor upper extremity (FM-UE) scale. However, this rule is criticized for overestimating the predictability of FM-UE recovery. Our objectives were to develop a longitudinal mixture model of FM-UE recovery, identify FM-UE recovery subgroups, and internally validate the model predictions.

methodsWe developed an exponential recovery function with the following parameters: subgroup assignment probability, proportional recovery coefficient r

resultsThe model distinguished 5 subgroups with different recovery parameters ( r

interpretationFM-UE recovery reflects different subgroups, each with its own recovery profile. Cross-validation indicates that FM-UE endpoints and FM-UE recovery clusters can be well predicted. Results will contribute to the understanding of upper limb recovery patterns in the first 6 months after stroke. ANN NEUROL 2020;87:383-393 Ann Neurol 2020;87:383-393.

Indexed as

Models, NeurologicalPredictive Value of TestsRecovery of FunctionAdultAgedAged, 80 and overDisability EvaluationFemaleHumansLongitudinal StudiesMaleMiddle AgedMotor DisordersPrognosisStrokeStroke Rehabilitation

Identifiers

PMID31925838
PMCPMC7065018

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Registered trials

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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.