Evidence map›Paper›PMID 35442522›Full record

ArticleVeterinary medicine and science2022

Questionnaire survey on the usage of antiseizure drugs for dogs and cats in Japanese veterinary hospitals (2020).

Satoshi Mizuno, Rikako Asada, Daisuke Hasegawa

Open access · goldAbstract readLetter
In one paragraph

Article in Veterinary medicine and science, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
0.7field-weighted citation impact, top 32% 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

5 citing papers in PubMed, 6 citations in OpenAlex.

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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 at 1 institution in 1 country.

Satoshi MizunoLaboratory of Veterinary Radiology, Nippon Veterinary and Life Science University, Tokyo, Japan.ORCID 0000-0002-2595-5482
Rikako AsadaLaboratory of Veterinary Radiology, Nippon Veterinary and Life Science University, Tokyo, Japan.ORCID 0000-0002-5080-2998
Daisuke HasegawaLaboratory of Veterinary Radiology, Nippon Veterinary and Life Science University, Tokyo, Japan.ORCID 0000-0002-7554-9108
Nippon Veterinary and Life Science University · JP

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Epilepsy is the most common neurological disorder in veterinary medicine. Recently, evidence-based recommendations or systematic reviews for using antiseizure drugs (ASDs) in dogs and cats have been published, but there are many differences in economic, geographical, and historical backgrounds and/or the availability of each ASD between countries. In the present study, we conducted a questionnaire survey on the usage of ASDs in 511 veterinary hospitals in Japan in 2020. As a result, zonisamide (ZNS) was the most commonly prescribed drug for idiopathic (83%) and structural epilepsy (76%) in dogs. In cats, phenobarbital was the most frequently prescribed drug for idiopathic (48%) and structural epilepsy (51%), but ZNS was also commonly prescribed (41% and 36%, respectively). Additionally, ZNS was the most frequently used ASD in combination therapy for canine idiopathic epilepsy. We also surveyed the frequency of measuring ASD blood levels; however, a relatively high percentage of hospitals (22%) did not perform such measurements. Although the evidence level for ZNS is still poor for both species, it is generally used as the first-line ASD in Japan. A large-scale and higher evidential study for ZNS and the education of practitioners for adequate antiseizure medication are required.

Indexed as

Cat DiseasesDog DiseasesEpilepsyAnimalsCatsDogsHospitals, AnimalJapanSurveys and Questionnaires

Identifiers

PMID35442522
PMCPMC9297804
OpenAlexW4224280868

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.