Kidney Function

Background: Urinary markers were tested as predictors of macroalbuminuria or microalbuminuria in patients with type 1 diabetes.Study Design: Nested case-control of participants in the Diabetes Control and Complications Trial (DCCT).Setting & Participants: 87 cases of microalbuminuria were matched to 174 controls in a 1:2 ratio, while 4 cases were matched to 4 controls in a 1:1 ratio, resulting in 91 cases and 178 controls for microalbuminuria. 55 cases of macroalbuminuria were matched to 110 controls in a 1:2 ratio. Controls were free of micro-/macroalbuminuria when their matching case first developed micro-/macroalbuminuria.Predictors: Urinary N-acetyl-β-d-glucosaminidase (NAG), pentosidine, advanced glycation end product (AGE) fluorescence, and albumin excretion rate (AER).Outcomes: Incident microalbuminuria (2 consecutive annual AERs > 40 but ≤ 300 mg/d) or macroalbuminuria (AER > 300 mg/d).Measurements: Stored urine samples from DCCT entry and 1-9 years later when macro- or microalbuminuria occurred were measured for the lysosomal enzyme NAG and the AGE pentosidine and AGE fluorescence. AER and adjustor variables were obtained from the DCCT.Results: Submicroalbuminuric AER levels at baseline independently predicted microalbuminuria (adjusted OR, 1.83; P < 0.001) and macroalbuminuria (adjusted OR, 1.82; P < 0.001). Baseline NAG excretion independently predicted macroalbuminuria (adjusted OR, 2.26; P < 0.001) and microalbuminuria (adjusted OR, 1.86; P < 0.001). Baseline pentosidine excretion predicted macroalbuminuria (adjusted OR, 6.89; P = 0.002). Baseline AGE fluorescence predicted microalbuminuria (adjusted OR, 1.68; P = 0.02). However, adjusted for NAG excretion, pentosidine excretion and AGE fluorescence lost the predictive association with macroalbuminuria and microalbuminuria, respectively.Limitations: Use of angiotensin-converting enzyme inhibitors was not directly ascertained, although their use was proscribed during the DCCT.Conclusions: Early in type 1 diabetes, repeated measurements of AER and urinary NAG excretion may identify individuals susceptible to future diabetic nephropathy. Combining the 2 markers may yield a better predictive model than either one alone. Renal tubule stress may be more severe, reflecting abnormal renal tubule processing of AGE-modified proteins, in individuals susceptible to diabetic nephropathy.

Background: The Chronic Kidney Disease Epidemiology Collaboration (CKD-EPI) is more accurate than the Modification of Diet in Renal Disease (MDRD) Study equation. We applied both equations in a cohort representative of the Australian adult population.Study Design: Population-based cohort study.Setting & Participants: 11,247 randomly selected noninstitutionalized Australians aged ≥ 25 years who attended a physical examination during the baseline AusDiab (Australian Diabetes, Obesity and Lifestyle) Study survey.Predictors & Outcomes: Glomerular filtration rate (GFR) was estimated using the MDRD Study and CKD-EPI equations. Kidney damage was defined as urine albumin-creatinine ratio ≥ 2.5 mg/mmol in men and ≥ 3.5 mg/mmol in women or urine protein-creatinine ratio ≥ 0.20 mg/mg. Chronic kidney disease (CKD) was defined as estimated GFR (eGFR) ≥ 60 mL/min/1.73 m2 or kidney damage. Participants were classified into 3 mutually exclusive subgroups: CKD according to both equations; CKD according to the MDRD Study equation, but no CKD according to the CKD-EPI equation; and no CKD according to both equations. All-cause mortality was examined in subgroups with and without CKD.Measurements: Serum creatinine and urinary albumin, protein, and creatinine measured on a random spot morning urine sample.Results: 266 participants identified as having CKD according to the MDRD Study equation were reclassified to no CKD according to the CKD-EPI equation (estimated prevalence, 1.9%; 95% CI, 1.4-2.6). All had an eGFR ≥ 45 mL/min/1.73 m2 using the MDRD Study equation. Reclassified individuals were predominantly women with a favorable cardiovascular risk profile. The proportion of reclassified individuals with a Framingham-predicted 10-year cardiovascular risk ≥ 30% was 7.2% compared with 7.9% of the group with no CKD according to both equations and 45.3% of individuals retained in stage 3a using both equations. There was no evidence of increased all-cause mortality in the reclassified group (age- and sex-adjusted hazard ratio vs no CKD, 1.01; 95% CI, 0.62-1.97). Using the MDRD Study equation, the prevalence of CKD in the Australian population aged ≥ 25 years was 13.4% (95% CI, 11.1-16.1). Using the CKD-EPI equation, the prevalence was 11.5% (95% CI, 9.42-14.1).Limitations: Single measurements of serum creatinine and urinary markers.Conclusions: The lower estimated prevalence of CKD using the CKD-EPI equation is caused by reclassification of low-risk individuals. Am J Kidney Dis 00:00-00

The American Journal of Kidney Diseases Acid-Base and Electrolyte Teaching Case from Saito et al, which appeared in a recent issue of the journal, presents a teaching opportunity about research designs and in particular the use of single-subject (N-of-1 or N=1) trials. Saito et al observed instability in a patient with congenital methylmalonic acidemia during hemodialysis (HD) using an acetate-containing dialysate. Based on biochemistry, they assumed that this response likely was caused by the acetate. They tested an acetate-free citrate HD dialysate in the same patient and did not find this response. Their study looked to more rigorously compare the effectiveness of these 2 buffers and also to verify the connection between the observed adverse reactions (hypotension) and the acetate-based dialysate in this individual.