Chronic Kidney Disease Prediction Model Includes Periodontal Status

Objectives: To identify high-risk subgroups for chronic kidney disease by applying a multivariable model of traditional and non-traditional risk factors to estimate an individual's probability of chronic kidney disease. Chronic kidney disease is a public health problem that is undiagnosed in a significant number of those affected. Methods: We identified 11,955 adults ≥18 years-old with information on kidney function and chronic kidney disease risk factors in the Third National Health and Nutrition Examination Survey. The main outcome, chronic kidney disease was estimated glomerular filtration rate 15-59ml/min/1.73m². The main exposure was periodontal status, based on a clinical examination, and categorized as no periodontal disease, periodontal disease, or edentulous. Other traditional and non-traditional risk factors for chronic kidney disease included in the multivariable logistic regression model were socioeconomic status (age, race/ethnicity, gender, income), health status/behavior (hypertension, smoking), biomarkers (macroalbuminuria, high cholesterol, low high-density lipoprotein), and health care utilization (annual physician visit and hospitalized in the past year). We identified high-risk subgroups for chronic kidney disease by estimating individual probability using beta coefficients from the logistic regression model. Results: The estimated probability that an individual with specific risk factors will have chronic kidney disease ranged from virtually no probability/no-risk (0%) for an individual with none of the 12 risk factors, to very high probability/high-risk (91%) for an older, non-Hispanic white edentulous female former smoker, with hypertension, macroalbuminuria, high cholesterol, low high-density lipoprotein, an annual physician visit, lower income and who was hospitalized in the past year. Conclusions: The findings from this national population-based study suggest the importance of simultaneously taking into account multiple risk factors, including periodontal status to identify high-risk subgroups for chronic kidney disease. This model could contribute to identifying individuals at risk for chronic kidney disease and ultimately reduce its burden through early intervention.

Research Support: NIH/NIDCR 5K08DE016031-04