Evidence map›Paper›PMID 30652056›Full record

ReviewJournal of clinical imaging science2018

Amyotrophic Lateral Sclerosis and its Mimics/Variants: A Comprehensive Review.

Vivek S Yedavalli, Abhijit Patil, Parinda Shah

Abstract readReview
In one paragraph

Review in Journal of clinical imaging science, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 20 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
20citing papers in PubMed, 2 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

20 citing papers in PubMed, 2 syntheses or guidelines pooled it.

  1. Pooled it
  2. Bibrachial amyotrophy as a rare manifestation of intraspinal fluid collection: a case report and systematic review.Neurological sciences : official journal of the Italian Neurological Society and of the Italian Society of Clinical Neurophysiology · 2024
    Pooled it
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  9. Identification of a mutation inClinical case reports · 2024
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  16. Role of EphA4 in Mediating Motor Neuron Death in MND.International journal of molecular sciences · 2021
    Review
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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

3 authors.

Vivek S YedavalliDepartment of Neuroradiology and Neurointervention, Stanford University, Palo Alto, California, USA.
Abhijit PatilDepartment of Radiology, Advocate Illinois Masonic Medical Center, Chicago, Illinois, USA.
Parinda ShahDepartment of Radiology, Advocate Illinois Masonic Medical Center, Chicago, Illinois, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Motor neuron diseases (MNDs) are a debilitating subset of diseases, which result in progressive neuronal destruction and eventual loss of voluntary muscular function. These entities are often challenging to distinguish and accurately diagnose given overlapping clinical pictures and overall rarity. This group of diseases has a high morbidity and mortality rate overall and delineating each type of disease can help guide appropriate clinical management and improve quality of life for patients. Of all MNDs, amyotrophic lateral sclerosis (ALS) is by far the most common comprising 80%-90% of cases. However, other mimics and variants of ALS can appear similar both clinically and radiographically. In this review, we delve into the epidemiological, physiological, neuroimaging, and prognostic characteristics and management of ALS and its most common MND mimics/variants. In doing so, we hope to improve accuracy in diagnosis and potential management for this rare group of diseases.

Indexed as

Amyotrophic lateral sclerosispostpolio syndromeprimary lateral sclerosisprogressive bulbar palsyprogressive muscular atrophyspinal and bulbar muscular atrophy

Identifiers

PMID30652056
PMCPMC6302559

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.