Evaluation of a creatinine-based equation to predict urine volume in nonpregnant, nonlactating Holstein cows

IF 2.2
JDS communications Pub Date : 2026-03-01 Epub Date: 2026-01-16 DOI:10.3168/jdsc.2025-0846
J.L. Bermeo , L.C. Solórzano , A. Rico , N. Silva-del-Río
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Abstract

Accurate estimation of urine output is essential for assessing nutrient utilization, particularly for nutrients predominantly excreted through urine, such as minerals and protein-derived metabolites. An equation utilizing creatinine concentration and BW has been previously developed to estimate urinary volume (EUV) in lactating Holstein dairy cows, defined as EUV = [29 × BW (kg)]/[urinary creatinine (mg/L)]. Our objective was to evaluate whether this equation introduces bias when used for estimating urinary output in nonpregnant, nonlactating Holstein cows and to identify factors influencing its accuracy. For our study, we used 72 paired observations that included observed urinary volume (OUV) and urinary creatinine concentration. These observations were obtained from a prior research study that assessed the relative availability of various magnesium (Mg) sources using a duplicated 6 × 6 Latin square design, with cows (n = 12) grouped into squares based on lower (square 1) or higher (square 2) BW across 6 periods. Enrolled cows were of second parity (n = 8) and third or greater parity (n = 4), with BW ranging from 590 to 831 kg. To determine the agreement between EUV and OUV, we constructed 2 mixed-effects models. The first model evaluated slope bias (testing if the slope was significantly different from 1), whereas the second assessed mean bias (testing if the intercept was significantly different from 0) between EUV and mean-centered OUV. In our dataset, creatinine excretion per kilogram of BW ranged from 15.0 to 35.6 mg/kg BW with an average of 27.6 mg/kg BW. When assessing the agreement between OUV and EUV, we observed both slope and mean biases when applying the creatinine-based equation. Furthermore, there was a bias estimate across BW quartiles. Overall, 76.4% of observations fell within ±10% deviation range between EUV and OUV. These findings suggest that further research is needed to identify factors that can refine the creatinine and BW-based predictive equation specifically for nonpregnant, nonlactating Holstein dairy cows.

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以肌酸酐为基础的公式预测非怀孕、非哺乳期荷斯坦奶牛尿量的评价。
准确估计尿量对于评估营养利用至关重要,特别是对于主要通过尿液排出的营养物质,如矿物质和蛋白质衍生代谢物。以前已经建立了一个利用肌酸酐浓度和体重来估计泌乳荷斯坦奶牛尿量(EUV)的方程,定义为EUV = [29 ×体重(kg)]/[尿肌酐(mg/L)]。我们的目的是评估该方程在用于估计非怀孕、非哺乳期荷斯坦奶牛的尿量时是否会引入偏差,并确定影响其准确性的因素。在我们的研究中,我们使用了72对观察数据,包括观察尿量(OUV)和尿肌酐浓度。这些观察结果来自先前的一项研究,该研究使用重复的6 × 6拉丁方阵设计评估了各种镁(Mg)来源的相对有效性,奶牛(n = 12)在6个时期内根据较低(方阵1)或较高(方阵2)的体重分组。入组奶牛为2胎次(n = 8)和3胎次以上(n = 4),体重为590 ~ 831 kg。为了确定EUV和OUV之间的一致性,我们构建了两个混合效应模型。第一个模型评估斜率偏差(检验斜率是否显著不同于1),而第二个模型评估EUV和均值中心OUV之间的平均偏差(检验截距是否显著不同于0)。在我们的数据集中,每公斤体重的肌酐排泄量从15.0到35.6 mg/kg BW不等,平均为27.6 mg/kg BW。在评估OUV和EUV之间的一致性时,我们在应用基于肌酐的方程时观察到斜率和平均值偏差。此外,在体重四分位数之间存在偏倚估计。总体而言,76.4%的观测值在EUV和OUV之间±10%的偏差范围内。这些发现表明,需要进一步的研究来确定能够细化肌酸酐和体重预测方程的因素,特别是对于未怀孕、未泌乳的荷斯坦奶牛。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
JDS communications
JDS communications Animal Science and Zoology
CiteScore
2.00
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