Add like
Add dislike
Add to saved papers

Prediction Model and Risk Stratification Tool for Survival in Patients With CKD.

KI Reports 2018 March
Introduction: Because chronic kidney disease (CKD) adversely affects survival, prediction of mortality risk should help to identify individuals requiring therapeutic intervention. The goal of this project was to construct and to validate a risk scoring system and prediction model of the probability of 2-year mortality in a CKD population.

Methods: We applied the Woodpecker approach to develop prediction equations using linear, exponential, and combined models. A risk indicator R on a scale of 0 to 10 was calculated as follows: starting with 0, add 0.048 for each year of age above 20, 0.45 for male sex, 0.49 for each stage of CKD over stage 2, 1.04 for proteinuria, 0.72 for smoking history, and 0.49 for each significant comorbidity up to 5.

Results: Using R to predict 2-year mortality, the model yielded an area under the receiver operating characterisic curve of 0.83 (95% confidence interval = 0.81-0.86) with 5062 subjects with CKD ≥stage 2 from a National Health and Nutrition Examination Survey cohort (1999-2004) having a 3.2% 2-year mortality. The combined expression offered results closest to most actual outcomes for the entire population and for each CKD stage. For those patients with higher risk ( R  ≥ 4-5, >5-6, and >6), the predicted 2-year mortality rates were 3.8%, 6.4%, and 13.0%, respectively, compared to observed mortality rates of 2.7%, 4.5%, and 13.3%.

Conclusion: The risk stratification tool and prediction model of 2-year mortality demonstrated good performance and may be used in clinical practice to quantify the risk of death for individual patients with CKD.

Full text links

We have located links that may give you full text access.
Can't access the paper?
Try logging in through your university/institutional subscription. For a smoother one-click institutional access experience, please use our mobile app.

For the best experience, use the Read mobile app

Mobile app image

Get seemless 1-tap access through your institution/university

For the best experience, use the Read mobile app

All material on this website is protected by copyright, Copyright © 1994-2024 by WebMD LLC.
This website also contains material copyrighted by 3rd parties.

By using this service, you agree to our terms of use and privacy policy.

Your Privacy Choices Toggle icon

You can now claim free CME credits for this literature searchClaim now

Get seemless 1-tap access through your institution/university

For the best experience, use the Read mobile app