Alexander Gieswinkel

Background: Early diagnosis of chronic kidney disease (CKD) is essential to slow progression and delay or prevent dialysis. However, in the absence of specific symptoms, patients and physicians may remain unaware of the disease for a long period. Here we present an analysis from the Gutenberg Health Study, a prospective longitudinal cohort study, to estimate the prevalence of CKD indicators in the population. Methods: A representative sample of 10 125 individuals underwent extensive medical testing at baseline; 9331 were tested again after 5 years. The estimated glomerular filtration rate (eGFR) was calculated using the Chronic Kidney Disease Epidemiology Collaboration formula with serum creatinine. Urinary albumin:creatinine ratios (UACRs) were determined from spot urine samples. Results: At baseline, 2.5% of subjects had decreased eGFR (30 mg/g) and 1.0% had both. Within 5 years, the incidence of new-onset decreased eGFR was 3.4%, the incidence of new-onset increased albuminuria was 6.9% and 1.4% had both new-onset decreased eGFR and increased albuminuria. Most importantly, 6.8% of all subjects and 3.2% of subjects without hypertension, diabetes or known kidney disease had chronic increased albuminuria, consistent with the presence of CKD. Conclusions: This is the first study to report the longitudinal prevalence of CKD in the population. Chronic increased albuminuria, a sensitive marker of CKD, is highly prevalent in the German population even in the absence of risk factors for kidney disease.

Obesity and cardiometabolic disease often, but not always, coincide. Distinguishing subpopulations within which cardiometabolic risk diverges from the risk expected for a given body mass index (BMI) may facilitate precision prevention of cardiometabolic diseases. Accordingly, we performed unsupervised clustering in four European population-based cohorts (N ≈ 173,000). We detected five discordant profiles consisting of individuals with cardiometabolic biomarkers higher or lower than expected given their BMI, which generally increases disease risk, in total representing ~20% of the total population. Persons with discordant profiles differed from concordant individuals in prevalence and future risk of major adverse cardiovascular events (MACE) and type 2 diabetes. Subtle BMI-discordances in biomarkers affected disease risk. For instance, a 10% higher probability of having a discordant lipid profile was associated with a 5% higher risk of MACE (hazard ratio in women 1.05, 95% confidence interval 1.03, 1.06, P = 4.19 × 10⁻¹⁰; hazard ratio in men 1.05, 95% confidence interval 1.04, 1.06, P = 9.33 × 10⁻¹⁴). Multivariate prediction models for MACE and type 2 diabetes performed better when incorporating discordant profile information (likelihood ratio test P < 0.001). This enhancement represents an additional net benefit of 4−15 additional correct interventions and 37−135 additional unnecessary interventions correctly avoided for every 10,000 individuals tested.

Gaukhar Baidildinova, Vincent ten Cate, Marina Panova-Noeva, Bianca Dahlen, Alexander Gieswinkel, Saskia von Ungern-Sternberg, Steffen Rapp, Konstantin Str Gaukhar Baidildinova, Vincent ten Cate, Marina Panova-Noeva, Bianca Dahlen, Alexander Gieswinkel, Saskia von Ungern-Sternberg, Steffen Rapp, Konstantin Str