Evidence map›Paper›PMID 42528684›Full record

ArticleFrontiers in veterinary science2026

Risk assessment of subclinical mastitis in Holstein cows in Jiangsu Province of China.

Yan Liang, Zhaozheng Zhang, Shuang Gu, Niel A Karrow, Jinling Hua, Yongjiang Mao

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Article in Frontiers in 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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0cells of the map it votes in
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

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

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

6 authors.

Yan LiangCollege of Animal Science, Anhui Science and Technology University, Chuzhou, China.
Zhaozheng ZhangCollege of Animal Science, Anhui Science and Technology University, Chuzhou, China.
Shuang GuCollege of Animal Science, Anhui Science and Technology University, Chuzhou, China.
Niel A KarrowDepartment of Animal Biosciences, Center for Genetic Improvement of Livestock, University of Guelph, Guelph, ON, Canada.
Jinling HuaCollege of Animal Science, Anhui Science and Technology University, Chuzhou, China.
Yongjiang MaoCollege of Animal Science and Technology, Yangzhou University, Yangzhou, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Introduction: Milk somatic cell count (SCC) and somatic cell score (SCS) are good indicators of the occurrence of subclinical mastitis (SCM) in dairy cows. Methods: In this study, multi-factor ANOVA model was used to analyze the fixed effects of 6 factors, including farm size, management, parity, calving season, lactation stage, and previous SCS (PSCS), on the current month SCS in milk of dairy cows in a training dataset containing 858,546 dairy herd improvement (DHI) records from 12 dairy farms in Jiangsu Province of China. The Logistic regression models of SCS or SCM were established for each factor and and then valiated with a separate dataset containing 27,575 DHI records from 6 other dairy farms. Results: The results showed that the six factors had significant effects on SCS and SCM incidence in dairy cows ( Conclusion: The model may be useful for risk stratification (e.g., identifying high-risk subgroups), but prospective validation is needed before field application.

Indexed as

Chinese Holstein cowfixed effectsmulti-factor logistic regressionnongenetic factorssubclinical mastitis (SCM)

Identifiers

PMID42528684
PMCPMC13414748

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