Evidence map›Paper›PMID 40104847›Full record

ArticleVeterinary medicine and science2025

Construction of a Diagnostic Prediction Model for Feline Nasal and Nasopharyngeal Diseases in Japan Using Noninvasive Examinations.

Aki Fujiwara-Igarashi, Yuta Nakazawa, Takafumi Ohshima, Sho Goto, Masatoshi Ino, Yuji Hamamoto, Yoshinori Takeuchi, Hideyuki Kanemoto

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Article in Veterinary medicine and science, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

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2 · The registry

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3 · Its place in the literature

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4 · The record

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5 · Who and what money

Authors and funding

8 authors.

Aki Fujiwara-IgarashiLaboratory of Veterinary Radiology, School of Veterinary Medicine, Nippon Veterinary and Life Science University, Musashino, Tokyo, Japan.ORCID 0000-0003-0386-3728
Yuta NakazawaLaboratory of Veterinary Radiology, School of Veterinary Medicine, Nippon Veterinary and Life Science University, Musashino, Tokyo, Japan.
Takafumi OhshimaLaboratory of Veterinary Radiology, School of Veterinary Medicine, Nippon Veterinary and Life Science University, Musashino, Tokyo, Japan.
Sho GotoLaboratory of Veterinary Radiology, School of Veterinary Medicine, Nippon Veterinary and Life Science University, Musashino, Tokyo, Japan.
Masatoshi InoLaboratory of Veterinary Radiology, School of Veterinary Medicine, Nippon Veterinary and Life Science University, Musashino, Tokyo, Japan.
Yuji HamamotoLaboratory of Veterinary Radiology, School of Veterinary Medicine, Nippon Veterinary and Life Science University, Musashino, Tokyo, Japan.
Yoshinori TakeuchiDivision of Medical Statistics, Department of Social Medicine, Faculty of Medicine, Toho University, Ota-ku, Tokyo, Japan.
Hideyuki KanemotoDVMs Animal Medical Center Yokohama, Yokohama, Kanagawa, Japan.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundAlthough feline nasal and nasopharyngeal diseases (NNDs) often require advanced tests under general anaesthesia for definitive diagnosis, not all patients can undergo them.

objectivesThis study aimed to construct diagnostic prediction models for feline NNDs in Japan using noninvasive examinations, signalment and history.

methodsSeventy-nine cats diagnosed with NNDs, including representative diseases in Japan-nasal and nasopharyngeal tumours (NNT), rhinitis (RS) and nasopharyngeal stenosis (NPS)-were retrospectively investigated to construct prediction models (model group, GM). Thirty-nine cats diagnosed were prospectively investigated to validate their efficacy (validation group, GV). Three predictive models were developed: Models 1 and 2 were manually constructed, with Model 1 designed to predict NNT, RS and NPS individually and Model 2 distinguishing between these diseases. Model 3 was constructed using least absolute shrinkage and selection operator logistic regression. Sensitivity, indicating the ability to identify cases of each disease, and specificity, reflecting the ability to exclude other diseases, were used to assess performance.

resultsIn Model 1 of the GV, the sensitivity and specificity for NNT, RS and NPS were 1.00 and 0.73, 0.62 and 0.96 and 0.78 and 0.97, respectively. In Model 2 of the GV, the values were 0.94 and 0.86 for NNT, 0.77 and 0.92 for RS and 0.75 and 0.94 for NPS. In Model 3 of the GV, they were 0.94 and 0.05 for NNT, 0.25 and 1.00 for RS and 0.13 and 0.84 for NPS.

conclusionsThe diagnostic prediction models, particularly Models 1 and 2, could help estimate whether advanced tests are necessary.

Indexed as

Cat DiseasesNasopharyngeal DiseasesNose DiseasesRhinitisAnimalsCatsFemaleJapanMaleRetrospective StudiesSensitivity and Specificitydiagnostic prediction modelnasal and nasopharyngeal diseasesnasal and nasopharyngeal tumournasopharyngeal stenosisrhinitis

Identifiers

PMID40104847
PMCPMC11920745

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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.