Evidence map›Paper›PMID 29691904›Full record

ReviewJournal of veterinary internal medicine2018

Pathological classification of equine recurrent laryngeal neuropathy.

Alexandra C E Draper, Richard J Piercy

Open access · goldAbstract readReview
In one paragraph

Review in Journal of veterinary internal medicine, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.

0numbers the graph read from it
0cells of the map it votes in
13citing papers in PubMed
5.2field-weighted citation impact, top 4% of its field
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

13 citing papers in PubMed, 34 citations in OpenAlex.

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  13. Pathological classification of equine recurrent laryngeal neuropathy.Journal of veterinary internal medicine · 2018
    Review
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

2 authors at 1 institution in 1 country.

Alexandra C E DraperComparative Neuromuscular Disease Laboratory, Department is Clinical Science and Services, Royal Veterinary College, London, United Kingdom.ORCID http://orcid.org/0000-0003-3766-919X
Richard J PiercyComparative Neuromuscular Disease Laboratory, Department is Clinical Science and Services, Royal Veterinary College, London, United Kingdom.
Royal Veterinary College · GB

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Recurrent Laryngeal Neuropathy (RLN) is a highly prevalent and predominantly left-sided, degenerative disorder of the recurrent laryngeal nerves (RLn) of tall horses, that causes inspiratory stridor at exercise because of intrinsic laryngeal muscle paresis. The associated laryngeal dysfunction and exercise intolerance in athletic horses commonly leads to surgical intervention, retirement or euthanasia with associated financial and welfare implications. Despite speculation, there is a lack of consensus and conflicting evidence supporting the primary classification of RLN, as either a distal ("dying back") axonopathy or as a primary myelinopathy and as either a (bilateral) mononeuropathy or a polyneuropathy; this uncertainty hinders etiological and pathophysiological research. In this review, we discuss the neuropathological changes and electrophysiological deficits reported in the RLn of affected horses, and the evidence for correct classification of the disorder. In so doing, we summarize and reveal the limitations of much historical research on RLN and propose future directions that might best help identify the etiology and pathophysiology of this enigmatic disorder.

Indexed as

AnimalsCranial Nerve DiseasesHorse DiseasesHorsesRecurrent Laryngeal Nerveaxonopathybilateral mononeuropathyhorselarynxmyelinopathypolyneuropathyrecurrent laryngeal neuropathy

Identifiers

PMID29691904
PMCPMC6060325
OpenAlexW2800202506

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
Read underepoch 390

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.