Evidence map›Paper›PMID 31172226›Full record

ArticleNeuroradiology2019

Predictive value of the combination of lesion location and volume of ischemic infarction with rehabilitation outcomes.

Chen Lin, Neil Chatterjee, Jungwha Lee, Richard Harvey, Shyam Prabhakaran

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Article in Neuroradiology, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

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

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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

7 citing papers in PubMed.

  1. Small Strokes, Big Impact: Excessive Mortality After Acute Ischemic Stroke in Parkinson's Disease.Movement disorders : official journal of the Movement Disorder Society · 2026
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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

5 authors.

Chen LinUniversity of Alabama Birmingham, 1813 6th Avenue South, Birmingham, AL, 35294, USA. clin@uabmc.edu.ORCID http://orcid.org/0000-0001-5291-9674
Neil ChatterjeeNorthwestern University, Chicago, IL, USA.
Jungwha LeeNorthwestern University, Chicago, IL, USA.
Richard HarveyNorthwestern University, Chicago, IL, USA.
Shyam PrabhakaranNorthwestern University, Chicago, IL, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

purposeIn acute ischemic stroke, infarct location and volume have, separately, been used to determine long-term outcomes after stroke. Little information exists on the combination of these imaging characteristics on rehabilitation outcomes. We evaluated the association between infarct lesion location volume with the Functional Independence Measure (FIM) measure during inpatient rehabilitation facility (IRF) in ischemic stroke patients.

methodsBetween 2012 and 2014, we prospectively enrolled consecutive acute ischemic stroke patients admitted from a Comprehensive Stroke Center and followed to an IRF in Chicago, Illinois. We adjudicated infarct volumes in specific lesion locations using a validated brain atlas. Volumes were calculated using an automated pipeline. FIM measure was extracted from IRF charts. We analyzed the association between acute infarct characteristics and functional measures using adjusted Spearman's correlation.

resultsAmong 162 stroke patients (mean age 67.6 years, 48.1% male, 58.6% Caucasian), the median FIM at IRF was 52 (IQR 36-62). In an adjusted analysis, infarct volumes in the left basal ganglia (r

conclusionsThere is an association between specific infarct lesion location volume and subsequent FIM scores assessed at IRF. Our findings suggest that imaging during index stroke hospitalization could be used to predict outcomes assessed during IRF.

Indexed as

Brain MappingMagnetic Resonance ImagingActivities of Daily LivingAcute DiseaseAgedBasal Ganglia Cerebrovascular DiseaseCerebral InfarctionCorrelation of DataDiffusion Magnetic Resonance ImagingFemaleFrontal LobeHumansMaleMiddle AgedPrognosisProspective StudiesCerebrovascular imagingInfarct locationInfarct sizePatient outcomesStroke rehabilitationVolumetry

Identifiers

PMID31172226

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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.