Estimated creatinine excretion per day (CKD epidemiology collaboration)
This model estimates an individual's expected daily creatinine excretion. Knowledge of the normal rate of creatinine excretion can be applied to assess completeness of the 24 hr urine collection.
Research authors: Ix JH, Wassel CL, Stevens LA, Beck GJ, Froissart M, Navis G, Rodby R, Torres VE, Zang YL, Greene T, Levey AS.
Version: 1.21
  • Public
  • Clinical pharmacology
  • {{ modelType }}
  • Details
  • Validate model
  • Save input
  • Load input

Calculate the result

Set more parameters to perform the calculation

Estimated creatinine excretion (ECR): mg/day

{{ resultSubheader }}
{{ chart.title }}
Result interval {{ additionalResult.min }} to {{ additionalResult.max }}

Conditional information

How this model should be used: 
Creatinine excretion rate (CER) indicates timed urine collection accuracy. Although equations to estimate CER exist, their bias and precision are untested and none simultaneously include age, sex, race, and weight.

Model limitations: 
Caution should be used in using the equations in patients without kidney disease and in persons with muscle mass outside of population norms.

Model performance upon internal validation: 
Performance of the newly developed equation was assessed in internal (N=822) and external (N=987) validation data sets. Little bias (<1%) was observed in the internal validation data set. Precision was moderate (interquartile range around the percent difference was 26%). For accuracy, the measured CER was within 15% of the expected CER (P15) among 59% of individuals, and within 30% of  expected CER (P30) among 85% of individuals. 

Source: 
Ix JH, Wassel CL, Stevens LA, et al. Equations to estimate creatinine excretion rate: the CKD epidemiology collaboration. Clin J Am Soc Nephrol. 2011;6(1):184-91.

{{ file.classification }}
PRO
Note
Notes are only visible in the result download and will not be saved by Evidencio

This model is provided for educational, training and information purposes. It must not be used to support medical decision making, or to provide medical or diagnostic services. Read our full disclaimer.

Underlying models Part of
Comments
Comment
Please enter a comment
Comments are visible to anyone

Model feedback

No feedback yet 1 Comment {{ model.comments.length }} Comments
On {{ comment.created_at }} {{ comment.user.username }} a no longer registered author wrote:
{{ comment.content }}
logo

Please sign in to enable Evidencio print features

In order to use the Evidencio print features, you need to be logged in.
If you don't have an Evidencio Community Account you can create your free personal account at:

https://www.evidencio.com/registration

Printed results - Examples {{ new Date().toLocaleString() }}

Evidencio Community Account Benefits

With an Evidencio Community account you can:

  • Create and publish your own prediction models.
  • Share your prediction models with your colleagues, research group, organization or the world.
  • Review and provide feedback on models that have been shared with you.
  • Validate your models and validate models from other users.
  • Find models based on Title, Keyword, Author, Institute, or MeSH classification.
  • Use and save prediction models and their data.
  • Use patient specific protocols and guidelines based on sequential models and decision trees.
  • Stay up-to-date with new models in your field as they are published.
  • Create your own lists of favorite models and topics.

A personal Evidencio account is free, with no strings attached!
Join us and help create clarity, transparency, and efficiency in the creation, validation, and use of medical prediction models.

Disclaimer: Calculations alone should never dictate patient care, and are no substitute for professional judgement.
Terms & Conditions | Privacy Policy | Disclaimer | Contact | Refuse cookies |
Evidencio v3.25 © 2015 - 2024 Evidencio. All Rights Reserved