Prevalence of chronic kidney disease in the community in the United Kingdom in OxRen, a population-based cohort study

Background: Chronic kidney disease (CKD) is a largely asymptomatic condition of diminished renal function, which may not be detected until advanced stages without screening. Aim: To establish undiagnosed and overall CKD prevalence using a cross-sectional analysis. Design and Setting: Longitudinal cohort study in UK primary care. Method: Participants aged ≥60 years were invited to attend CKD screening visits to determine whether they had reduced renal function (estimated glomerular filtration rate [eGFR] Results: A total of 3207 participants were recruited and 861 attended the baseline assessment. The CKD cohort consisted of 327 people with existing CKD, 257 people with CKD diagnosed through screening (CKD prevalence of 18.2%, 95% confidence interval [CI] = 16.9 to 19.6), and 277 with borderline/transient decreased renal function. In the CKD cohort, 54.4% were female, mean standard deviation (SD) age was 74.0 (SD 6.9) years, and mean eGFR was 58.0 (SD 18.4) ml/min/1.73 m2. Of the 584 with confirmed CKD, 44.0% were diagnosed through screening. Over half of the CKD cohort (51.9%, 447/861) fell into CKD stages 3–5 at their baseline assessment, giving an overall prevalence of CKD stages 3–5 of 13.9% (95% CI = 12.8 to 15.1). More people had reduced eGFR using the Modification of Diet in Renal Disease (MDRD) equation than with CKD Epidemiology Collaboration (CKD-EPI) equation in the 60–75-year age group and more had reduced eGFR using CKD-EPI in the ≥80-year age group. Conclusion: This study found that around 44.0% of people living with CKD are undiagnosed without screening, and prevalence of CKD stages 1–5 was 18.2% in participants aged >60 years. Follow-up will provide data on annual incidence, rate of CKD progression, determinants of rapid progression, and predictors of cardiovascular events.</p

Impact of a single eGFR and eGFR-estimating equation on chronic kidney disease reclassification:A cohort study in primary care

Background Chronic kidney disease (CKD) is diagnosed using the estimated glomerular filtration rate (eGFR) and the urinary albumin:creatinine ratio (ACR). The eGFR is calculated from serum creatinine levels using the Modification of Diet in Renal Disease (MDRD) or Chronic Kidney Disease Epidemiology Collaboration (CKD-EPI) equations. Aim To compare the performance of one versus two eGFR/ACR measurements, and the impact of equation choice, on CKD diagnosis and classification. Design and setting Cohort study in primary care in the Thames Valley region of the UK. Method Data were from 485 participants aged &gt;60 years in the Oxford Renal Cohort Study with at least two eGFR tests. The proportion of study participants diagnosed and classified into different CKD stages using one and two positive tests were compared. Prevalence of CKD diagnosis and classification by CKD stage were compared when eGFR was calculated using MDRD and CKD-EPI equations. Results Participants included in the analysis had a mean age of 72.1 (±6.8) years and 57.0% were female. Use of a single screening test overestimated the proportion of people with CKD by around 25% no matter which equation was used, compared with the use of two tests. The mean eGFR was 1.4 ml/min/1.73 m2 (95% CI = 1.1 to 1.6) higher using the CKD-EPI equation compared with the MDRD equation. More patients were diagnosed with CKD when using the MDRD equation, compared with the CKD-EPI equation, once (64% versus 63%, respectively) and twice (39% versus 38%, respectively), and 16 individuals, all of who had CKD stages 2 or 3A with MDRD, were reclassified as having a normal urinary ACR when using the CKD-EPI equation. Conclusion Current guidance to use two eGFR measures to diagnose CKD remains appropriate in an older primary care population to avoid overdiagnosis. A change from MDRD to CKD-EPI equation could result in one in 12 patients with a CKD diagnosis with MDRD no longer having a diagnosis of CKD.</p

Impact of a single eGFR and eGFR-estimating equation on chronic kidney disease reclassification:A cohort study in primary care

Background Chronic kidney disease (CKD) is diagnosed using the estimated glomerular filtration rate (eGFR) and the urinary albumin:creatinine ratio (ACR). The eGFR is calculated from serum creatinine levels using the Modification of Diet in Renal Disease (MDRD) or Chronic Kidney Disease Epidemiology Collaboration (CKD-EPI) equations. Aim To compare the performance of one versus two eGFR/ACR measurements, and the impact of equation choice, on CKD diagnosis and classification. Design and setting Cohort study in primary care in the Thames Valley region of the UK. Method Data were from 485 participants aged &gt;60 years in the Oxford Renal Cohort Study with at least two eGFR tests. The proportion of study participants diagnosed and classified into different CKD stages using one and two positive tests were compared. Prevalence of CKD diagnosis and classification by CKD stage were compared when eGFR was calculated using MDRD and CKD-EPI equations. Results Participants included in the analysis had a mean age of 72.1 (±6.8) years and 57.0% were female. Use of a single screening test overestimated the proportion of people with CKD by around 25% no matter which equation was used, compared with the use of two tests. The mean eGFR was 1.4 ml/min/1.73 m2 (95% CI = 1.1 to 1.6) higher using the CKD-EPI equation compared with the MDRD equation. More patients were diagnosed with CKD when using the MDRD equation, compared with the CKD-EPI equation, once (64% versus 63%, respectively) and twice (39% versus 38%, respectively), and 16 individuals, all of who had CKD stages 2 or 3A with MDRD, were reclassified as having a normal urinary ACR when using the CKD-EPI equation. Conclusion Current guidance to use two eGFR measures to diagnose CKD remains appropriate in an older primary care population to avoid overdiagnosis. A change from MDRD to CKD-EPI equation could result in one in 12 patients with a CKD diagnosis with MDRD no longer having a diagnosis of CKD.</p