CKD-EPI creatinine equation (2009)
The CKD-EPI creatinine equation is based on the same four variables as the MDRD Study equation, but uses a 2-slope spline to model the relationship between estimated GFR and serum creatinine, and a different relationship for age, sex and race. The equation was reported to perform better and with less bias than the MDRD Study equation, especially in patients with higher GFR. This results in reduced misclassification of CKD.
Autori výskumu: Levey AS, Stevens LA, Schmid CH, Zhang YL, Castro AF, Feldman HI, Kusek JW, Eggers P, Van Lente F, Greene T, and Coresh J.
Verzia: 1.16
  • Verejnosť
  • Nefrológia
  • {{ modelType }}
  • Podrobnosti na
  • Overenie modelu
  • Uložiť vstup
  • Vstupné zaťaženie

Vypočítajte výsledok

Nastavenie ďalších parametrov na vykonanie výpočtu

Estimated GFR: ml/min/1.73m2

{{ resultSubheader }}
{{ chart.title }}
Interval výsledkov {{ additionalResult.min }} na {{ additionalResult.max }}

Podmienené informácie

The CKD-EPI (Chronic Kidney Disease Epidemiology Collaboration) equation was developed in an effort to create a more precise formula to estimate glomerular filtrate rate (GFR) from serum creatinine and other readily available clinical parameters, especially at when actual GFR is >60 mL/min per 1.73m2.

Researchers pooled data from multiple studies to develop and validate this new equation. They randomly divided 10 studies which included 8254 participants, into separate data sets for development and internal validation. 16 additional studies, which included 3896 participants, were used for external validation.

The CKD-EPI equation performed better than the MDRD (Modification of Diet in Renal Disease Study) equation, especially at higher GFR, with less bias and greater accuracy. When looking at NHANES (National Health and Nutrition Examination Survey) data, the median estimated GFR was 94.5 mL/min per 1.73 m2 vs. 85.0 mL/min per 1.73 m2, and the prevalence of chronic kidney disease was 11.5% versus 13.1%.

{{ file.classification }}
PRO
Poznámka
Poznámky sú viditeľné len pri sťahovaní výsledkov a Evidencio ich neukladá.

Tento model sa poskytuje na vzdelávacie, školiace a informačné účely. Nesmie sa používať na podporu lekárskeho rozhodovania ani na poskytovanie lekárskych alebo diagnostických služieb. Prečítajte si náš úplný text disclaimer.

Základné modely Časť
Komentáre
Komentár
Prosím, zadajte komentár
Komentáre sú viditeľné pre každého

Spätná väzba modelu

Zatiaľ žiadna spätná väzba 1 komentár {{ model.comments.length }} Komentáre
Na stránke {{ comment.created_at }} {{ comment.user.username }} už neregistrovaný autor napísal:
{{ comment.content }}
logo

Prihláste sa, aby ste povolili funkcie tlače Evidencio

Aby ste mohli používať funkcie tlače Evidencio, musíte byť prihlásení.
Ak nemáte konto Evidencio Community, môžete si vytvoriť bezplatné osobné konto na:

https://www.evidencio.com/registration

Vytlačené výsledky - príklady {{ new Date().toLocaleString() }}


Výhody komunitného účtu Evidencio


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.


Upozornenie: Samotné výpočty by nikdy nemali určovať starostlivosť o pacienta a nenahrádzajú odborný úsudok.
Evidencio v3.25 © 2015 - 2024 Evidencio. All Rights Reserved