Assessment of associations between transition diseases and reproductive performance of dairy cows using survival analysis and decision tree algorithms.


Journal

Preventive veterinary medicine
ISSN: 1873-1716
Titre abrégé: Prev Vet Med
Pays: Netherlands
ID NLM: 8217463

Informations de publication

Date de publication:
Mar 2020
Historique:
received: 26 09 2019
revised: 10 01 2020
accepted: 27 01 2020
pubmed: 10 2 2020
medline: 21 10 2020
entrez: 10 2 2020
Statut: ppublish

Résumé

This study aimed to evaluate the associations between transition cow conditions and diseases TD with fertility in Holstein cows, and to compare analytic methods for doing so. Kaplan-Meier, Cox proportional hazard, and decision tree models were used to analyze the associations of TD with the pregnancy risk at 120 and 210 DIM from a 1-year cohort with 1946 calvings from one farm. The association between TD and fertility was evaluated as follows: 1 cows with TD whether complicated with another TD or not TD-all, versus healthy cows, and 2 cows with uncomplicated TD TD-single, versus cows with multiple TD TD+; complicated cases, versus healthy cows. The occurrence of twins, milk fever, retained placenta, metritis, ketosis, displaced abomasum, and clinical mastitis were recorded. Using Kaplan-Meier models, in primiparous cows the 120 DIM pregnancy risk was 62% (95% CI: 57-67 %) for healthy animals. This was not significantly different for TD-single (58%; 95% CI: 51-66 %) but was reduced for TD+ (45%; 95% CI: 33-60 %). Among healthy primiparous cows, 80% (95% CI: 75-84 %) were pregnant by 210 DIM, but pregnancy risk at that time was reduced for primiparous cows with TD-single (72%; 95% CI: 65-79 %) and TD+ (62%; 95% CI: 49-75 %). In healthy multiparous cows, the 120 DIM pregnancy risk was 53% (95% CI: 49-56 %), which was reduced for TD-single (36%; 95% CI: 31-42 %) and TD+ (30%; 95% CI: 24-38 %). The 210 DIM pregnancy risk for healthy multiparous cows was 70% (95% CI: 67-72 %), being higher than the 210 DIM pregnancy risk for multiparous cows with TD-single (47%; 95% CI: 42-53 %) or TD+ (46%; 95% CI: 38-54 %). Cows with TD-all presented similar pregnancy risk estimates as for TD + . Cox proportional hazards regressions provided similar magnitudes of effects as the Kaplan-Meier estimates. Survival analysis and decision tree models identified parity as the most influential variable affecting fertility. Both modeling techniques concurred that TD + had a greater effect than TD-single on the probability of pregnancy at 120 and 210 DIM. Decision trees for individual TD identified that displaced abomasum affected fertility at 120 DIM in primiparous while metritis was the most influential TD at 120 and 210 DIM for multiparous cows. The data were too sparse to assess multiple interactions in multivariable Cox proportional hazard models for individual TD. Machine learning helped to explore interactions between individual TD to study their hierarchical effect on fertility, identifying conditional relationships that merit further investigation.

Identifiants

pubmed: 32036304
pii: S0167-5877(19)30675-0
doi: 10.1016/j.prevetmed.2020.104908
pii:
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

104908

Informations de copyright

Copyright © 2020 Elsevier B.V. All rights reserved.

Auteurs

O Bogado Pascottini (O)

Population Medicine, Ontario Veterinary College, University of Guelph, ON, N1G 2W1, Canada. Electronic address: osvaldo.bogado@ugent.be.

M Probo (M)

Veterinary Teaching Hospital, Department of Veterinary Medicine, University of Milan, via Dell'Università 6, 26900 Lodi, Italy.

S J LeBlanc (SJ)

Population Medicine, Ontario Veterinary College, University of Guelph, ON, N1G 2W1, Canada.

G Opsomer (G)

Department of Reproduction, Obstetrics and Herd Health, Faculty of Veterinary Medicine, Ghent. University, Salisburylaan 133, 9820 Merelbeke, Belgium.

M Hostens (M)

Department of Reproduction, Obstetrics and Herd Health, Faculty of Veterinary Medicine, Ghent. University, Salisburylaan 133, 9820 Merelbeke, Belgium.

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Classifications MeSH