Evidence map›Paper›PMID 35369603›Full record

ArticleVeterinary world2022

Comparison of three progesterone quantification methods using blood samples drawn from bitches during the periovulatory phase.

Hassan A Hussein, Gerhard Schuler, Theresa Conze, Axel Wehrend

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Article in Veterinary world, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing 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

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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

7 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

4 authors.

Hassan A HusseinDepartment of Theriogenology, Faculty of Veterinary Medicine, Assiut University, Assiut, Egypt.
Gerhard SchulerClinic for Obstetrics, Gynaecology and Andrology of Large and Small Animals with Veterinary Ambulance, Justus Liebig University, Giessen, Germany.
Theresa ConzeClinic for Obstetrics, Gynaecology and Andrology of Large and Small Animals with Veterinary Ambulance, Justus Liebig University, Giessen, Germany.
Axel WehrendClinic for Obstetrics, Gynaecology and Andrology of Large and Small Animals with Veterinary Ambulance, Justus Liebig University, Giessen, Germany.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background and Aim: Measuring blood progesterone (P4) concentration has become an essential diagnostic tool in small animal reproductive medicine. Methods enabling precise and rapid on-site measurements are in high demand, especially for the optimization of breeding management in bitches. This study aimed to compare two commercial on-site methods (Speed™ P4, Virbac [M1] and mini VIDAS®, bioMérieux [M2]) and a well-established radioimmunoassay (RIA), which was used as a reference method. Materials and Methods: Comparative measurements were performed on 52 blood serum samples collected from 45 clinically healthy bitches of different breeds. The dogs had been presented to determine the estrus cycle stage and predict the time of ovulation. Each sample was divided into three aliquots. In aliquot 1, P4 was measured immediately applying M2. Aliquots 2 and 3 were stored at -20°C until analysis was performed using RIA and M1. The consistency of the three methods was investigated by pairwise linear regression analyses. Results: In RIA, the P4 concentrations ranged between 1.1 and 25.4 ng/mL. Regression analyses revealed highly significant (p<0.0001) positive correlations between the three methods applied (M1 vs. RIA: R=0.94; M2 vs. RIA: R=0.98; and M1 vs. M2: R=0.91). Conclusion: The results show that the two commercial on-site methods tested exhibit approximately equal, high consistency with the radioimmunological reference method and can, therefore, be used beneficially in a clinical setting. However, biological interpretation of data must be performed in a method-specific manner.

Indexed as

dogenzyme-linked immunofluorescenceimmunochromatographyprogesteroneradioimmunoassay

Identifiers

PMID35369603
PMCPMC8924395

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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.