Estimated Pulse Wave Velocity and All-Cause and Cardiovascular Mortality in the General Population.

Background: Carotid-femoral pulse wave velocity (cfPWV), acknowledged as a reliable proxy of arterial stiffness, is an independent predictor of cardiovascular (CV) events. Carotid-femoral PWV is considered the gold standard for the estimation of arterial stiffness. cfPWV is a demanding, time consuming and expensive method, and an estimated PWV (ePWV) has been suggested as an alternative method when cfPWV is not available. Our aim was to analyze the predictive role of ePWV for CV and all-cause mortality in the general population. Methods: In a stratified random sample of 1086 subjects from the general Croatian adult population (EH-UH study) (men 42.4%, average age 53 ± 16), subjects were followed for 17 years. ePWV was calculated using the following formula: ePWV = 9.587 - 0.402 × age + 4.560 × 10-3 × age2 - 2.621 × 10-5 × age2 × MBP + 3.176 × 10-3 × age × MBP - 1.832 × 10-2 × MBP. MBP= (DBP) + 0.4(SBP - DBP). Results: At the end of the follow-up period, there were 228 deaths (CV, stroke, cancer, dementia and degenerative diseases, COLD, and others 43.4%, 10.5%, 28.5%, 5.2%, 3.1%, 9.3%, respectively). In the third ePWV tercile, we observed more deaths due to CV disease than to cancer (20.5% vs. 51.04%). In a Cox regression analysis, for each increase in ePWV of 1 m/s, there was a 14% increase risk for CV death. In the subgroup of subjects with higher CV risk, we found ePWV to be a significant predictor of CV deaths (ePWV (m/s) CI 1.108; p < 0.029; HR 3.03, 95% CI 1.118-8.211). Conclusions: In subjects with high CV risk, ePWV was a significant and independent predictor of CV mortality.

Should the CKD EPI Equation Be Used for Estimation of the Glomerular Filtration Rate in Obese Subjects?

INTRODUCTION: The pandemic of obesity is strongly related to increase of chronic kidney disease (CKD) prevalence. The currently recommended CKD epidemiology collaboration (CKD EPI) equation has several serious limitations, particularly in obese subjects who have high body surface area (BSA). The aim of our study was to analyze differences in the prevalence of CKD between CKD EPI and de-indexed equations where individual BSA was used. METHODS: In a total of 2,058 subjects (random sample from a general rural population, 29.65% obese), BSA was estimated using DuBois and DuBois and Moesteller equations and included into the de-indexed equations (CKD DBi, CKD Mi). CKD was classified according to the KDIGO guidelines, and glomerular hyperfiltration (GHF) was defined as 95th percentile, according to the gender and age decade. RESULTS: In obese subjects, prevalence of CKD was significantly higher with CKD EPI than with CKD DBi and CKD Mi equations (9.5%, 6.1%, 5.3%, respectively; p < 0.001), while prevalence of GHF was significantly lower (3.8%, 12.3%, 12.8%, respectively; p < 0.001). Opposite results were observed in subjects with a body mass index <25 kg/m2 for CKD (5%, 7.1%, 7.2%; p = 0.07) and GHF prevalence (6.1%, 1%, 0.6%; p < 0.001). DISCUSSION/CONCLUSIONS: The prevalence of CKD is overestimated, and the prevalence of GHF is underestimated in obese subjects using the CKD EPI equation, i.e., the CKD EPI equation is unreliable in one-third of the population. De-indexed equations should be recommended instead of the CKD EPI equation in epidemiological studies until direct measurement of the glomerular filtration rate becomes more available.

CHRONIC KIDNEY DISEASE IN RURAL POPULATION.

The aims of the study were to provide data on chronic kidney disease (CKD) prevalence in rural population and to analyze the association with cardiovascular risk factors and aging. A random sample of 2193 farmers (1333 female (F) and 860 male (M), mean age 50.61±17.12) were enrolled. Questionnaire and clinical examination were conducted. Participants provided a spot urine and fasting blood sample. Estimated glomerular filtration rate (eGFR) was estimated using Chronic Kidney Disease Epidemiology Collaboration (CKD-EPI) equation. Subjects were classified according to the KDIGO guidelines. The overall prevalence of CKD (eGFR <60 mL/min/1.73 m2) was 8.83% (F vs. M 9.9% vs. 6.3%; p<0.001). Albuminuria (albumin-to-creatinine ratio >30 mg/g) was found in 8.45% (F vs. M p>0.05). Sharp increase in CKD prevalence was found to begin after the sixth decade (29.44% in subjects older than 65 years; F vs. M 30.9% vs. 26.8%; p<0.01). The strongest predictor factors for CKD were age >65 years (OR 22.12), hypertension (OR 6.53), albuminuria (OR 5.71), fasting blood glucose >7 mmol/L (OR 5.49), diabetes (OR 3.07), abdominal obesity (OR 2.05) and non-smoking (OR 0.41). In multivariate analysis, age (OR 1.13), female gender (OR 0.60) and diabetes (OR 1.75) were the independent predictor factors for CKD. In conclusion, CKD prevalence is high in rural population, being higher in women than in men. In both genders, eGFR significantly decreased with aging. Aging is a significant independent predictor of CKD.