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

## TL;DR

Researchers tested a creatinine-based formula to estimate urine volume in nonpregnant, nonlactating cows, finding it was reasonably accurate but had some biases.

## Contribution

The study evaluates and identifies limitations of a creatinine-based urine volume estimation method in nonlactating cows.

## Key findings

- 76.4% of observations fell within a ±10% deviation range between estimated and observed urine volume.
- There was a bias estimate across body weight quartiles when using the creatinine-based equation.
- Including factors like body condition score and metabolic state may improve model accuracy.

## Abstract

Summary: Urine analysis helps evaluate how cows use nutrients and excrete excess minerals and nitrogenous metabolites. Accurately estimating nutrient excretion requires both the concentration of urinary components and the total volume excreted. However, direct measurement of urine volume is labor-intensive and often impractical on commercial farms. This study evaluated a creatinine-based method to estimate urine output in nonpregnant, nonlactating Holstein cows (12 cows, 6 time points per cow, 72 observations). The estimated urine volume (EUV) was calculated using the following equation: EUV = [29 × BW (kg)]/[urinary creatinine concentration (mg/L)], where BW is body weight. There was a bias estimate across BW quartiles. Overall, 76.4% of the observations fell within a ±10% deviation range between estimated and observed urinary volume.

Summary: Urine analysis helps evaluate how cows use nutrients and excrete excess minerals and nitrogenous metabolites. Accurately estimating nutrient excretion requires both the concentration of urinary components and the total volume excreted. However, direct measurement of urine volume is labor-intensive and often impractical on commercial farms. This study evaluated a creatinine-based method to estimate urine output in nonpregnant, nonlactating Holstein cows (12 cows, 6 time points per cow, 72 observations). The estimated urine volume (EUV) was calculated using the following equation: EUV = [29 × BW (kg)]/[urinary creatinine concentration (mg/L)], where BW is body weight. There was a bias estimate across BW quartiles. Overall, 76.4% of the observations fell within a ±10% deviation range between estimated and observed urinary volume.

•A fixed 29 mg/kg of BW creatinine rate estimated urine output within ±10% for 76.4% of the observations in nonpregnant, nonlactating Holstein cows.•There was a bias estimate across BW quartiles.•Model accuracy may improve by including factors such as body condition score and metabolic state.

A fixed 29 mg/kg of BW creatinine rate estimated urine output within ±10% for 76.4% of the observations in nonpregnant, nonlactating Holstein cows.

There was a bias estimate across BW quartiles.

Model accuracy may improve by including factors such as body condition score and metabolic state.

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.