Evidence map›Paper›PMID 40041720›Full record

ArticleTranslational animal science2025

Urinary chemistry in healthy cross-bred pet rabbits (

Yeh Sze-Yu, Sung Chi-Hsuan, Liu Pin-Chen, Wu Ching-Fen, Lin Tsai-Lu, Cheng Tsung-Li, Chi-Chung Chou

Abstract read
In one paragraph

Article in Translational animal science, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Review
  2. Article
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

7 authors.

Yeh Sze-YuDepartment of Veterinary Medicine, College of Veterinary Medicine, National Chung-Hsing University, Taichung 40227, Taiwan.
Sung Chi-HsuanDepartment of Veterinary Medicine, College of Veterinary Medicine, National Chung-Hsing University, Taichung 40227, Taiwan.
Liu Pin-ChenDepartment of Veterinary Medicine, College of Veterinary Medicine, National Chung-Hsing University, Taichung 40227, Taiwan.
Wu Ching-FenDepartment of Veterinary Medicine, College of Veterinary Medicine, National Chiayi University, Chiayi City, Taiwan.
Lin Tsai-LuDepartment of Veterinary Medicine, College of Veterinary Medicine, National Chung-Hsing University, Taichung 40227, Taiwan.
Cheng Tsung-LiVeterinary Medical Teaching Hospital, College of Veterinary Medicine, National Chung-Hsing University, Taichung 40227, Taiwan.
Chi-Chung ChouDepartment of Veterinary Medicine, College of Veterinary Medicine, National Chung-Hsing University, Taichung 40227, Taiwan.ORCID https://orcid.org/0000-0002-4622-2552

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Renal biomarkers for early detection of decreased kidney function have been extensively studied in dogs and cats, but there is limited research for pet rabbits. Specifically, studies on urinary indices for cross-bred rabbits are scarce. Therefore, this study aimed to assess the potential use of urinalysis in cross-bred pet rabbits. Urine samples from 30 healthy crossbred pet rabbits and 11 rabbits with suspected kidney disease (KD) from three clinics were collected. RIs of urinary indices, including urinary protein, creatinine (uCRE), urinary protein-to-creatinine (UPC) ratio, gamma-glutamyl transferase (uGGT), and uGGT ratio, were established and compared to two published reference intervals (RIs). The results showed that healthy rabbits consistently had low urine protein levels and abnormal UPC ratios, compared to a published study involving only pure-bred rabbits. Rabbits with KD had higher urine protein levels and a significantly higher UPC ratio (

Indexed as

kidney diseaseOryctolagus cuniculusrabbitreference intervalsurinary biomarkers

Identifiers

PMID40041720
PMCPMC11879030

What OpenQuestion holds

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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.