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. 2023 Aug 9;10(8):515.
doi: 10.3390/vetsci10080515.

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

Affiliations

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

Nadine Urbanek et al. Vet Sci. .

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.

Keywords: body condition score; body weight; crest neck score; morphometric measurements; muscle atrophy score; over-condition.

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Conflict of interest statement

The authors declare no conflict of interest.

Figures

Figure 1
Figure 1
Depiction of morphometric measurements (except the body circumference) shown on the horse.
Figure 2
Figure 2
The line of best fit and the quality parameters of the model developed in this study for the prediction of body weight (BW) of horses (CCC = concordance correlation coefficient; CI = confidence intervals).
Figure 3
Figure 3
The line of best fit and the quality parameters of the model for the prediction of BW of horses using the model of Catalano et al. [20].
Figure 4
Figure 4
The line of best fit and the quality parameter of the model for the estimation of BW of horses using the model of Schramme and Kienzle [24].

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