Evidence map›Paper›PMID 21745124›Full record

ArticleAmyotrophic lateral sclerosis : official publication of the World Federation of Neurology Research Group on Motor Neuron Diseases2011

Progression of white matter degeneration in amyotrophic lateral sclerosis: A diffusion tensor imaging study.

Yu Zhang, Norbert Schuff, Susan C Woolley, Gloria C Chiang, Lauren Boreta, Joel Laxamana, Jonathan S Katz, Michael W Weiner

Abstract read
In one paragraph

Article in Amyotrophic lateral sclerosis : official publication of the World Federation of Neurology Research Group on Motor Neuron Diseases, 2011. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 36 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
36citing papers in PubMed, 1 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

36 citing papers in PubMed, 1 synthesis or guideline pooled it.

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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

8 authors.

Yu ZhangCenter for Imaging of Neurodegenerative Diseases, Veterans Affairs Medical Center, San Francisco, CA, USA. Yu.Zhang@ucsf.edu
Norbert Schuff
Susan C Woolley
Gloria C Chiang
Lauren Boreta
Joel Laxamana
Jonathan S Katz
Michael W Weiner

Funding

TRAINING AND DISSEMINATIONP41RR023953 · NCRR · NORTHERN CALIFORNIA INSTITUTE/RES/EDU · PI WEINER, MICHAEL W · 2008 to 2011
$6.0M
NCRR NIH HHS P41 RR023953
6 · The paper itself

Abstract

Whether longitudinal diffusion tensor MRI imaging (DTI) can capture disease progression in patients with amyotrophic lateral sclerosis (ALS) is unclear. The primary goal of this study was to determine if DTI detects progression of the corticospinal tracts (CST) degeneration in ALS. Seventeen ALS patients and 19 age- and gender-matched healthy controls were scanned with DTI at baseline for cross-sectional analyses. For longitudinal analyses, the ALS patients had repeat DTI scans after eight months. Tractography of the CST was used to guide regions-of-interest (ROI) analysis and complemented by a voxelwise analysis. Cross-sectional study found that baseline FA of the right superior CST was markedly reduced in ALS patients compared to controls. The FA reductions in this region correlated with the disease severity in ALS patients. Longitudinal study found that FA change rate of the right superior CST significantly declined over time. In conclusion, longitudinal DTI study captures progression of upper motor fiber degeneration in ALS. DTI can be useful for monitoring ALS progression and efficacy of treatment interventions.

Indexed as

AgedAmyotrophic Lateral SclerosisCross-Sectional StudiesDiffusion Tensor ImagingDisease ProgressionFemaleHumansLongitudinal StudiesMaleMiddle AgedNerve DegenerationNerve Fibers, MyelinatedPyramidal Tracts

Identifiers

PMID21745124
PMCPMC3804304

What OpenQuestion holds

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Registered trials

None linked

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.