Evidence map›Paper›PMID 42225604›Full record

ArticleJournal of veterinary science2026

Risk factors for early and mid-to-late pregnancy loss and their effects on reproductive performance in dairy cows.

Hyun-Gu Kang, Jae-Kwan Jeong, Ill-Hwa Kim

Abstract read
In one paragraph

Article in Journal of veterinary science, 2026. 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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0citing papers in PubMed
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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

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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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

3 authors.

Hyun-Gu Kang *College of Veterinary Medicine, Chungbuk National University, Cheongju 28644, Korea.ORCID https://orcid.org/0000-0002-3827-6112
Jae-Kwan Jeong *College of Veterinary Medicine, Chungbuk National University, Cheongju 28644, Korea.ORCID https://orcid.org/0000-0002-8379-3194
Ill-Hwa KimCollege of Veterinary Medicine, Chungbuk National University, Cheongju 28644, Korea.ORCID https://orcid.org/0000-0002-2092-0264

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

importanceThe risk factors and reproductive consequences of pregnancy loss may differ by gestational stage, but stage-specific patterns before and after placentation is firmly established have not been adequately characterized.

objectiveTo identify the risk factors for pregnancy loss at different gestational stages, before and after 60 days of gestation when the placentation is firmly established and quantify the subsequent reproductive performance.

methodsThis study analyzed the records from 6,444 pregnancies confirmed by transrectal ultrasonography 31 days after artificial insemination. Pregnancy loss between 31-61 days was categorized as late embryonic or early fetal loss (LEL-EFL), and losses between 62-260 days were categorized as mid-to-late fetal loss (M-LFL). Multivariable logistic regression was used to assess the risk factors. Survival analysis was performed to assess the probability of becoming pregnant again by 400 days postpartum.

resultsThe cumulative incidence of pregnancy loss was 5.8% for LEL-EFL and 7.7% for M-LFL; LEL-EFL accounted for 43.2% of all losses. A higher body condition score at calving tended to reduce the risk of early loss ( CONCLUSIONS AND RELEVANCE: The patterns of pregnancy loss were stage-specific, and early and later losses had distinct and progressively more adverse effects on reproductive performance. Optimizing the body condition at calving, refining breeding management, and improving peripartum health may reduce pregnancy loss and improve reproductive outcomes.

Indexed as

Abortion, VeterinaryCattle DiseasesReproductionAnimalsCattleFemaleGestational AgeInsemination, ArtificialPregnancyRisk Factorsbody condition scoreEmbryonic mortalityfetal mortalityheat stressperiparturient disease

Identifiers

PMID42225604
PMCPMC13236467

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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.