[A new equation to predict urine creatinine values using data from Chilean population]

Area of Science:

• Clinical Chemistry
• Biomarker Analysis
• Population Health

Background:

• Accurate 24-hour urinary creatinine excretion (UCr) assessment is crucial for evaluating kidney function.
• Current UCr estimation often relies on broad weight-indexed ranges or predictive equations.

Purpose of the Study:

• To develop a novel equation for estimating 24-hour UCr specifically for the Chilean population.
• To compare the performance of the new equation against established UCr prediction formulas.

Main Methods:

• Utilized 464 24-hour urine collections from Chilean outpatients (aged 15-88).
• Developed a multiple linear regression model linking UCr to sex, age, height, and weight.
• Validated the new equation against existing formulas using a separate subset of collections.

Main Results:

• Age, sex, and weight were significant predictors of 24-hour UCr.
• The newly developed Chilean equation demonstrated comparable accuracy to CKD-EPI and Walser equations.
• The new formula outperformed several other existing UCr prediction models.

Conclusions:

• A population-specific equation derived from Chilean data provides accurate 24-hour UCr estimation.
• This new tool enhances the reliability of UCr assessments in the Chilean context.