Early detection of chronic kidney disease: results of the PolNef study.

Background: Continuous increase in the number of patients with end-stage renal disease demands early detection of chronic kidney disease (CKD). The aim of the present study was to diagnose CKD in its earliest stages in a randomly selected population using a diagnostic algorithm developed by the working group.

Methods: An algorithm for the diagnostic procedure was created to identify patients with CKD requiring further nephrological care. Randomly chosen adult inhabitants of a city with a population of 60,000 were invited to participate in this study. Screening procedures included a microalbuminuria dipstick test accompanied by blood pressure measurement and medical questionnaire. In further diagnosis of CKD, estimated glomerular filtration rate (eGFR), albumin concentration in urine, urinalysis and ultrasound examination were used according to the algorithm. Multivariate logistic regression was performed to identify associations between participants' characteristics and albuminuria.

Results: Out of 9,700 invited subjects, 2,471 individuals participated in the PolNef study. Albuminuria was detected in 15.6% of the investigated population using the dipstick test and thereafter confirmed in 11.9% by the turbidimetric method. The modeling of multivariate logistic regression indicated the following independent predictors of albuminuria: male sex, diabetes, nocturia and hypertension. For people without diabetes and without hypertension, nocturia independently predicted detection of albuminuria. 481 people received a consultation with a nephrologist, and 96% of them were recognized as having CKD. At least 9% of patients with CKD had eGFR by MDRD <60 ml/min/1.73 m(2). Six persons were referred for further treatment because of newly diagnosed kidney tumor.

Conclusions: CKD in early stages occurs frequently in the studied population. The proposed diagnostic algorithm seems to be a powerful tool to identify subjects at risk of CKD. The role of nocturia as an independent predictor of albuminuria, both in the general population and in people without diabetes or hypertension, should be further examined.