Naimon Nattakarn, Jarudecha Thitichai, Sussadee Metita, Muikaew Rattana, Charoensin Supochana
Department of Veterinary Nursing, Faculty of Veterinary Technology, Kasetsart University, 50 Ngam Wong Wan Road, Ladyaow, Chatuchak, Bangkok, Thailand.
Department of Veterinary Technology, Faculty of Veterinary Technology, Kasetsart University, 50 Ngam Wong Wan Road, Ladyaow, Chatuchak, Bangkok, Thailand.
Vet World. 2024 Oct;17(10):2193-2203. doi: 10.14202/vetworld.2024.2193-2203. Epub 2024 Oct 4.
Body temperature is the most useful clinical parameter for evaluating animal health. In clinical practice, rectal temperature is the gold standard for assessing body temperature, but rectal temperature measurement is not convenient and can cause stress in animals. The non-contact infrared thermometer is considered an alternative method for skin temperature measurements in animals. Many biological factors may influence the response of body regions to thermal challenges; thus, the identification of these variables is essential for accurate infrared temperature measurements. This study aimed to estimate the relationship between the physiological factors of cats and their body temperature measured across various body positions, as well as to propose a model for predicting rectal temperature using an infrared thermometer.
A total of 184 client-owned cats were included in this study. The infrared temperature (°F) was measured using a non-contact infrared thermometer at five body positions: maxillary canine gingival margin (GCT), anal skin (ANS), inguinal canal (ING), ear canal (EC), and palmar pad. The five biological factors (age, body condition score [BCS], gender, hair type, and hair color) were recorded and analyzed to adjust predictive factors for rectal temperature prediction. All statistical analyses were performed using multivariable linear regression. The rectal temperature prediction model was then designed using the forward stepwise selection method.
Based on multivariable linear regression analysis of infrared temperature results, the pre-prediction model showed significant correlations with rectal temperature for ANS, GCT, and EC (p = 0.0074, 0.0042, and 0.0118, respectively). Moreover, the combination of infrared temperatures on ANS and ING was the most appropriate parameter for predicting rectal temperature (p = 0.0008). All models were adjusted according to the baseline characteristics of the cats. However, the adjusted R-squared values of the pre-prediction model of the infrared temperature on the ANS, GCT, and EC and the final prediction model by the infrared temperature on the ANS combined with the ING were low (8.7%, 8.9%, 7.3%, and 12.8%, respectively).
The prediction model of rectal temperature of cats by infrared temperature from a non-contact infrared thermometer in ANS combined with ING and adjusted by age, BCS, hair type, and hair color may be applicable for use in clinical practice. This study found that the adjusted R-squared values of all models were low; the predictive model will need to be developed and used to test validity and reliability with an external study group for assessing their practical usefulness.
体温是评估动物健康状况最有用的临床参数。在临床实践中，直肠温度是评估体温的金标准，但测量直肠温度不方便，且会给动物带来应激。非接触式红外温度计被认为是测量动物皮肤温度的一种替代方法。许多生物学因素可能会影响身体各部位对热刺激的反应；因此，识别这些变量对于准确的红外温度测量至关重要。本研究旨在评估猫的生理因素与在不同身体部位测量的体温之间的关系，并提出一种使用红外温度计预测直肠温度的模型。
本研究共纳入184只客户拥有的猫。使用非接触式红外温度计在五个身体部位测量红外温度（华氏度）：上颌犬牙龈边缘（GCT）、肛门皮肤（ANS）、腹股沟管（ING）、耳道（EC）和掌垫。记录并分析五个生物学因素（年龄、身体状况评分[BCS]、性别、毛发类型和毛色），以调整直肠温度预测的预测因素。所有统计分析均使用多变量线性回归进行。然后使用向前逐步选择法设计直肠温度预测模型。
基于对红外温度结果的多变量线性回归分析，预测前模型显示ANS、GCT和EC的红外温度与直肠温度具有显著相关性（p分别为0.0074、0.0042和0.0118）。此外，ANS和ING的红外温度组合是预测直肠温度的最合适参数（p = 0.0008）。所有模型均根据猫的基线特征进行了调整。然而，ANS、GCT和EC的红外温度预测前模型以及ANS与ING的红外温度最终预测模型的调整后R平方值较低（分别为8.7%、8.9%、7.3%和12.8%）。
由非接触式红外温度计测量的ANS与ING的红外温度结合年龄、BCS、毛发类型和毛色调整后的猫直肠温度预测模型可能适用于临床实践。本研究发现所有模型的调整后R平方值都很低；需要开发预测模型并与外部研究组一起用于测试其有效性和可靠性，以评估它们的实际实用性。
