Evidence map›Paper›PMID 31299928›Full record

ArticleBMC nephrology2019

Kidney and cystic volume imaging for disease presentation and progression in the cat autosomal dominant polycystic kidney disease large animal model.

Yoshihiko Yu, Kate L Shumway, Jodi S Matheson, Marie E Edwards, Timothy L Kline, Leslie A Lyons

Open access · goldAbstract read
In one paragraph

Article in BMC nephrology, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing papers in PubMed
1.8field-weighted citation impact, top 14% 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

8 citing papers in PubMed, 15 citations in OpenAlex.

  1. Contribution of polycystic kidney disease to the development of chronic renal dysfunction in cats.Veterinary research forum : an international quarterly journal · 2026
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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

6 authors at 3 institutions in 2 countries.

Yoshihiko YuDepartment of Veterinary Medicine and Surgery, College of Veterinary Medicine, University of Missouri, Columbia, MO, USA.
Kate L ShumwayDepartment of Veterinary Medicine and Surgery, College of Veterinary Medicine, University of Missouri, Columbia, MO, USA.
Jodi S MathesonDepartment of Veterinary Medicine and Surgery, College of Veterinary Medicine, University of Missouri, Columbia, MO, USA.
Marie E EdwardsDivision of Nephrology and Hypertension, Mayo Clinic, Rochester, MN, USA.
Timothy L KlineDivision of Nephrology and Hypertension, Mayo Clinic, Rochester, MN, USA.
Leslie A LyonsDepartment of Veterinary Medicine and Surgery, College of Veterinary Medicine, University of Missouri, Columbia, MO, USA. lyonsla@missouri.edu.ORCID 0000-0002-1628-7726
Missouri College · USMayo Clinic · USNippon Veterinary and Life Science University · JP

Funding

Pilot and FeasibilityP30DK090728 · NIDDK · MAYO CLINIC ROCHESTER · PI TORRES, VICENTE E · 2010 to 2019
$11.8M
Advanced MR Imaging and Image Analytics as a Precision Medicine Tool to Manage ADPKDK01DK110136 · NIDDK · MAYO CLINIC ROCHESTER · PI KLINE, TIMOTHY LEE · 2017 to 2021
$732k
NIDDK NIH HHS K01 DK110136NIDDK NIH HHS P30 DK090728NIDDK NIH HHS P30DK090728
6 · The paper itself

Abstract

backgroundApproximately 30% of Persian cats have a c.10063C > A variant in polycystin 1 (PKD1) homolog causing autosomal dominant polycystic kidney disease (ADPKD). The variant is lethal in utero when in the homozygous state and is the only ADPKD variant known in cats. Affected cats have a wide range of progression and disease severity. However, cats are an overlooked biomedical model and have not been used to test therapeutics and diets that may support human clinical trials. To reinvigorate the cat as a large animal model for ADPKD, the efficacy of imaging modalities was evaluated and estimates of kidney and fractional cystic volumes (FCV) determined.

methodsThree imaging modalities, ultrasonography, computed tomography (CT), and magnetic resonance imaging examined variation in disease presentation and disease progression in 11 felines with ADPKD. Imaging data was compared to well-known biomarkers for chronic kidney disease and glomerular filtration rate. Total kidney volume, total cystic volume, and FCV were determined for the first time in ADPKD cats. Two cats had follow-up examinations to evaluate progression.

resultsFCV measurements were feasible in cats. CT was a rapid and an efficient modality for evaluating therapeutic effects that cause alterations in kidney volume and/or FCV. Biomarkers, including glomerular filtration rate and creatinine, were not predictive for disease progression in feline ADPKD. The wide variation in cystic presentation suggested genetic modifiers likely influence disease progression in cats. All imaging modalities had comparable resolutions to those acquired for humans, and software used for kidney and cystic volume estimates in humans proved useful for cats.

conclusionsRoutine imaging protocols used in veterinary medicine are as robust and efficient for evaluating ADPKD in cats as those used in human medicine. Cats can be identified as fast and slow progressors, thus, could assist with genetic modifier discovery. Software to measure kidney and cystic volume in human ADPKD kidney studies is applicable and efficient in cats. The longer life and larger kidney size span than rodents, similar genetics, disease presentation and progression as humans suggest cats are an efficient biomedical model for evaluation of ADPKD therapeutics.

Indexed as

Disease Models, AnimalAnimalsCatsDisease ProgressionFemaleKidneyKidney Function TestsMagnetic Resonance ImagingMaleOrgan SizePolycystic Kidney, Autosomal DominantTomography, X-Ray ComputedUltrasonographyADPKDESRDFelinePKD1

Identifiers

PMID31299928
PMCPMC6625046
OpenAlexW2958925635

What OpenQuestion holds

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LicenceCC BY
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Registered trials

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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.