Evidence map›Paper›PMID 36009621›Full record

ReviewAnimals : an open access journal from MDPI2022

Using Pregnancy-Associated Glycoproteins (PAGs) to Improve Reproductive Management: From Dairy Cows to Other Dairy Livestock.

Olimpia Barbato, Laura Menchetti, Gabriele Brecchia, Vittoria Lucia Barile

Abstract readReview
In one paragraph

Review in Animals : an open access journal from MDPI, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers.

0numbers the graph read from it
0cells of the map it votes in
19citing 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

19 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Review
  5. Early pregnancy detection in ruminants: challenges and innovations.The Journal of reproduction and development · 2025
    Review
  6. Article
  7. Article
  8. Article
  9. Article
  10. Advances in Dairy Cattle Reproduction-A Foreword.Animals : an open access journal from MDPI · 2024
    Article
  11. Article
  12. Article
  13. Article
  14. Article
  15. Article
  16. Review
  17. Article
  18. Article
  19. 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

4 authors.

Olimpia BarbatoDepartment of Veterinary Medicine, University of Perugia, Via San Costanzo 4, 06126 Perugia, Italy.ORCID 0000-0003-0828-4610
Laura MenchettiDepartment of Veterinary Medicine, University of Milano, Via dell'Università 6, 26900 Lodi, Italy.ORCID 0000-0001-8500-7970
Gabriele BrecchiaDepartment of Veterinary Medicine, University of Milano, Via dell'Università 6, 26900 Lodi, Italy.ORCID 0000-0003-4750-2801
Vittoria Lucia BarileResearch Centre for Animal Production and Aquaculture, Consiglio per la Ricerca in Agricoltura e l'Analisi dell'Economia Agraria (CREA), Via Salaria 31, 00015 Monterotondo, Italy.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Pregnancy success represents a major issue for the economic income of cattle breeders. Early detection of pregnant and non-pregnant animals, as well as the prediction of early pregnancy failure, can influence farm management decisions. Several diagnostic tools for pregnancy are currently available. Among these, pregnancy-associated glycoproteins (PAGs) have been shown to be useful for identifying the presence of vital embryos and for pregnancy follow-up monitoring. This review presents an overview of the PAGs' functions, their pregnancy trends, and their use as a tool to improve reproductive management in bovine and other dairy livestock, such as small ruminants and buffalos.

Indexed as

bovinebuffalodairy livestockgoatpregnancypregnancy-associated glycoproteinsreproductive managementsheep

Identifiers

PMID36009621
PMCPMC9404451

What OpenQuestion holds

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LicenceCC BY
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Registered trials

None linked

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.