Evidence map›Paper›PMID 31839979›Full record

ArticleJFMS open reports

Prevalence of feline immunodeficiency virus and feline leukaemia virus in domestic cats in Hungary.

Anna Szilasi, Lilla Dénes, Eszter Krikó, Kristin Heenemann, Reinhard Ertl, Míra Mándoki, Thomas W Vahlenkamp, Gyula Balka

Abstract read
In one paragraph

Article in JFMS open reports. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.

0numbers the graph read from it
0cells of the map it votes in
12citing 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

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

12 citing papers in PubMed.

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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.

Anna SzilasiDepartment of Pathology, University of Veterinary Medicine, Budapest, Pest, Hungary.ORCID https://orcid.org/0000-0002-1634-6730
Lilla DénesDepartment of Pathology, University of Veterinary Medicine, Budapest, Pest, Hungary.
Eszter KrikóCentre for Bioinformatics, University of Veterinary Medicine, Budapest, Pest, Hungary.
Kristin HeenemannInstitute of Virology, Faculty of Veterinary Medicine, Leipzig University, Leipzig, Sachsen, Germany.
Reinhard ErtlVetCore Facility for Research, University of Veterinary Medicine, Vienna, Austria.ORCID https://orcid.org/0000-0001-7485-3661
Míra MándokiDepartment of Pathology, University of Veterinary Medicine, Budapest, Pest, Hungary.
Thomas W VahlenkampInstitute of Virology, Faculty of Veterinary Medicine, Leipzig University, Leipzig, Sachsen, Germany.
Gyula BalkaDepartment of Pathology, University of Veterinary Medicine, Budapest, Pest, Hungary.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectivesFeline immunodeficiency virus (FIV) and feline leukaemia virus (FeLV) are retroviruses affecting cats worldwide. The objectives of the study were to estimate the prevalence of these retroviruses in domestic cats in Hungary and to characterise the phylogenetic relationships of FIV strains.

methodsA total of 335 anticoagulated whole-blood samples obtained from both a healthy and ill cat population were examined for the presence of FIV and FeLV with two methods: ELISA and PCR. Statistical analysis was carried out to analyse the data obtained. Sequencing and phylogenetic analysis of partial polymerase (

resultsStatistical analysis showed 11.8% and 9.9% true prevalence of FeLV and FIV, respectively, with ELISA. The apparent prevalence calculated from the PCR results were 17.3% for FeLV and 13.1% for FIV. Phylogenetic analysis of partial CONCLUSIONS AND RELEVANCE: We report the first thorough overview of the prevalence of FeLV and FIV in Hungary, which is relatively high, and give insight into the genetic diversity of Hungarian strains of FIV.

Indexed as

HungaryImmunodeficiency virusleukaemia virusphylogenyprevalence

Identifiers

PMID31839979
PMCPMC6904780

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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.