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Morphometric Measurements and Muscle Atrophy Scoring as a Tool to Predict Body Weight and Condition of Horses

SIMPLE SUMMARY: Estimations of the body condition and body weight are important in horses to prevent disease and also to maintain the performance, fertility, and physical and mental stress tolerance of the animal. Yet, the estimation of body condition and body weight under practical circumstances is...

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Autores principales: Urbanek, Nadine, Zebeli, Qendrim
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10458044/
https://www.ncbi.nlm.nih.gov/pubmed/37624301
http://dx.doi.org/10.3390/vetsci10080515
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author Urbanek, Nadine
Zebeli, Qendrim
author_facet Urbanek, Nadine
Zebeli, Qendrim
author_sort Urbanek, Nadine
collection PubMed
description SIMPLE SUMMARY: Estimations of the body condition and body weight are important in horses to prevent disease and also to maintain the performance, fertility, and physical and mental stress tolerance of the animal. Yet, the estimation of body condition and body weight under practical circumstances is not easy. This research developed models that help in the prediction and estimation of body weight and body condition score of horses under practical conditions using common morphometric measurements of the body and evaluations of the Cresty Neck Score and Muscle Atrophy Scoring System; hence, these take into account the size of the animal, its abdominal extension and filling, regional fat adiposity, age, and degree of the muscularity. ABSTRACT: Accurate estimation of body weight (BW) and condition (BCS) is important in the equine practice. The main goal of this research was to develop models for the prediction of BW and BCS of horses in the practice using both common morphometric measurements and measurements of Cresty Neck Score (CNS) and Muscle Atrophy Scoring System (MASS) as a measure of muscularity. Our model showed that the BW of horses could be predicted with high reproducibility (concordance correlation coefficient = 0.97), accuracy (0.99), and precision (0.97) using the morphometric measurements of the height at withers, circumference of the chest, cane circumference, body length, and body circumference as well as the BCS, CNS, and muscle atrophy score of the hindlimbs. The stepwise multiple regression analysis revealed that the BCS of horses can be predicted with the data of parameters such as age, body length and an index consisting of measurements of the body circumference to height of withers, and the atrophy of the neck. Future research should use larger cohorts of animals to validate the findings of this study.
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spelling pubmed-104580442023-08-27 Morphometric Measurements and Muscle Atrophy Scoring as a Tool to Predict Body Weight and Condition of Horses Urbanek, Nadine Zebeli, Qendrim Vet Sci Article SIMPLE SUMMARY: Estimations of the body condition and body weight are important in horses to prevent disease and also to maintain the performance, fertility, and physical and mental stress tolerance of the animal. Yet, the estimation of body condition and body weight under practical circumstances is not easy. This research developed models that help in the prediction and estimation of body weight and body condition score of horses under practical conditions using common morphometric measurements of the body and evaluations of the Cresty Neck Score and Muscle Atrophy Scoring System; hence, these take into account the size of the animal, its abdominal extension and filling, regional fat adiposity, age, and degree of the muscularity. ABSTRACT: Accurate estimation of body weight (BW) and condition (BCS) is important in the equine practice. The main goal of this research was to develop models for the prediction of BW and BCS of horses in the practice using both common morphometric measurements and measurements of Cresty Neck Score (CNS) and Muscle Atrophy Scoring System (MASS) as a measure of muscularity. Our model showed that the BW of horses could be predicted with high reproducibility (concordance correlation coefficient = 0.97), accuracy (0.99), and precision (0.97) using the morphometric measurements of the height at withers, circumference of the chest, cane circumference, body length, and body circumference as well as the BCS, CNS, and muscle atrophy score of the hindlimbs. The stepwise multiple regression analysis revealed that the BCS of horses can be predicted with the data of parameters such as age, body length and an index consisting of measurements of the body circumference to height of withers, and the atrophy of the neck. Future research should use larger cohorts of animals to validate the findings of this study. MDPI 2023-08-09 /pmc/articles/PMC10458044/ /pubmed/37624301 http://dx.doi.org/10.3390/vetsci10080515 Text en © 2023 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Urbanek, Nadine
Zebeli, Qendrim
Morphometric Measurements and Muscle Atrophy Scoring as a Tool to Predict Body Weight and Condition of Horses
title Morphometric Measurements and Muscle Atrophy Scoring as a Tool to Predict Body Weight and Condition of Horses
title_full Morphometric Measurements and Muscle Atrophy Scoring as a Tool to Predict Body Weight and Condition of Horses
title_fullStr Morphometric Measurements and Muscle Atrophy Scoring as a Tool to Predict Body Weight and Condition of Horses
title_full_unstemmed Morphometric Measurements and Muscle Atrophy Scoring as a Tool to Predict Body Weight and Condition of Horses
title_short Morphometric Measurements and Muscle Atrophy Scoring as a Tool to Predict Body Weight and Condition of Horses
title_sort morphometric measurements and muscle atrophy scoring as a tool to predict body weight and condition of horses
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10458044/
https://www.ncbi.nlm.nih.gov/pubmed/37624301
http://dx.doi.org/10.3390/vetsci10080515
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