1. Development and Validation of a General Population Renal Risk Score
- Author
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Halbesma, N., Jansen, D.F., Heymans, M.W., Stolk, R.P., Jong, P.E. de, Gansevoort, R.T., PREVEND Study Grp, Life Course Epidemiology (LCE), Cardiovascular Centre (CVC), Lifestyle Medicine (LM), Groningen Kidney Center (GKC), Methodology and Applied Biostatistics, EMGO+ - Musculoskeletal Health, Epidemiology and Data Science, and EMGO - Musculoskeletal health
- Subjects
Male ,CHRONIC KIDNEY-DISEASE ,Time Factors ,Epidemiology ,Blood Pressure ,PROGRESSION ,Kidney ,urologic and male genital diseases ,Critical Care and Intensive Care Medicine ,Logistic regression ,Risk Factors ,Statistics ,Odds Ratio ,Health Status Indicators ,Prospective Studies ,PREDICTORS ,Prospective cohort study ,Netherlands ,education.field_of_study ,Framingham Risk Score ,Age Factors ,Middle Aged ,PREVALENCE ,C-Reactive Protein ,Nephrology ,Hypertension ,Disease Progression ,Female ,Kidney Diseases ,Glomerular Filtration Rate ,Cohort study ,Adult ,NATIONAL-HEALTH ,medicine.medical_specialty ,NEPHROPATHY ,MODELS ,Population ,UNITED-STATES ,Risk Assessment ,SDG 17 - Partnerships for the Goals ,Predictive Value of Tests ,Internal medicine ,medicine ,Albuminuria ,Humans ,education ,Aged ,Transplantation ,Receiver operating characteristic ,business.industry ,Reproducibility of Results ,Odds ratio ,medicine.disease ,Logistic Models ,ROC Curve ,Chronic Disease ,business ,Biomarkers ,Kidney disease - Abstract
There is a need for prediction scores that identify individuals at increased risk for developing progressive chronic kidney disease (CKD). Therefore, this study was performed to develop and validate a "renal risk score" for the general population. Design, setting, participants,measurements For this study we used data from the PREVEND (Prevention of Renal and Vascular ENdstage Disease) study, a prospective population-based cohort study with a median follow-up of 6.4 years. Participants with two or three consecutive estimated GFR (eGFR) measurements during follow-up were included. Participants within the group who had the most renal function decline (top 20% of the total population) and had an eGFR value60 ml/min per 1.73 m² during follow-up were defined as having progressive CKD. Possible predictors for progressive CKD were selected on the basis of univariable logistic regression analyses.A final prediction model was built using backward logistic regression analysis. Besides baseline eGFR, the model contained age, urinary albumin excretion, systolic BP, C-reactive protein, and known hypertension. The area under the receiver operating characteristic (ROC) curve was 0.84. We performed internal validation by using a bootstrapping procedure. As expected, after the regression coefficients were corrected for optimism, the area under the ROC curve was still 0.84. For clinical use we divided all predictors in meaningful clinical categories to develop a score chart. The area under the ROC curve was 0.83, indicating the high discriminative value of this model.Given the high internal validity of this renal risk score, this score can be helpful to identify individuals at increased risk for progressive CKD.
- Published
- 2011
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