Background: Early detection of chronic kidney disease (CKD) might help physicians prevent further renal deterioration and the related long-term sequelae; however, to date there are no readily available tools to help predict this situation. Kshirsagar and colleagues derived and validated a simple risk score to predict incident kidney disease using clinical information that is readily available for most patients.
The Study: Data from two community-based, prospective cohort studies, the Atherosclerosis Risk In Communities Study and the Cardiovascular Health Study, were analyzed. Participants were at least 45 years of age initially and were followed for up to nine years. Renal function was assessed at baseline and then periodically over time. Participants were randomly divided into a development data set to investigate potential risk factors for CKD, and a validation group was used to confirm the results of the development data set. The primary outcome was the development of CKD, defined as a glomerular filtration rate lower than 60 mL per minute per 1.73 m2.
Results: Data from 14,155 participants were reviewed. Based on the data development set, a simplified model was constructed that allowed for risk scoring based on common patient risk factors for CKD (see accompanying table). Validation models showed that a total score of 3 or greater successfully screened for future CKD, with 69 percent sensitivity, 58 percent specificity, a positive predictive value of 17 percent, and a negative predictive value of 94 percent.
Conclusion: To the authors' knowledge, this is the first tool that can identify patients at risk of developing CKD among middle-aged and older adults up to nine years later. They recommend that scores of 3 or higher warrant surveillance for CKD, lifestyle modifications, and intensive management of risk factors such as diabetes and hypertension.