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While the relationship between circulating osteoprotegerin (OPG) and cardiovascular events is well-established in the general population, its association with cardiovascular risks in chronic kidney disease (CKD) patients remains less robust. This study hypothesized that elevated circulating OPG levels might be associated with an increased risk of major adverse cardiac events (MACE) in CKD patients, a total of 2,109 patients with CKD stages 1 through pre-dialysis 5 from the KNOW-CKD cohort were categorized into quartiles based on serum OPG levels. The primary outcome of the study was 3-point MACE, defined as a composite of nonfatal myocardial infarction, nonfatal stroke, or cardiac death. The median follow-up duration was 7.9 years. The cumulative incidence of 3-point MACE significantly varied across serum OPG levels in Kaplan–Meier curve analysis (P < 0.001, log-rank test), with the highest incidence observed in the 4th quartile. Cox regression analysis indicated that, relative to the 1st quartile, the risk of 3-point MACE was significantly higher in the 3rd (adjusted hazard ratio 2.901, 95% confidence interval 1.009 to 8.341) and the 4th quartiles (adjusted hazard ratio 4.347, 95% confidence interval 1.410 to 13.395). In conclusion, elevated circulating OPG levels are associated with adverse cardiovascular outcomes in pre-dialysis CKD patients. [ABSTRACT FROM AUTHOR]

Despite the clear association between low BMD and all-cause mortality in the general population, the association has not been validated in patients with nondialysis CKD. To investigate the association of low BMD with all-cause mortality in this population, a total of 2089 patients with nondialysis CKD at stages 1 to predialysis 5 were categorized into normal BMD (T-score ≥ −1.0), osteopenia (−2.5 < T-score < −1.0), and osteoporosis (T-score ≤ − 2.5) by the BMD at femoral neck. The study outcome was all-cause mortality. Kaplan–Meier curve depicted a significantly increased number of all-cause death events in the subjects with osteopenia or osteoporosis during the follow-up period compared with subjects with normal BMD. Cox regression models demonstrated that osteoporosis, but not osteopenia, was significantly associated with an increased risk of all-cause mortality (adjusted hazard ratio 2.963, 95% confidence interval 1.655 to 5.307). Smoothing curve fitting model visualized a clear inverse correlation between BMD T-score and the risk of all-cause mortality. Even after recategorizing the subjects by BMD T-scores at total hip or lumbar spine, the result was similar to the primary analyses. Subgroup analyses revealed that the association was not significantly modified by clinical contexts, such as age, gender, body mass index, estimated glomerular filtration rate, and albuminuria. In conclusion, low BMD is associated with an increased risk of all-cause mortality in patients with nondialysis CKD. This emphasizes that the routine measurement of BMD by DXA may confer an additional benefit beyond the prediction of fracture risk in this population. [ABSTRACT FROM AUTHOR]

The prognostic value of urinary angiotensinogen (UAGT) in patients with chronic kidney disease (CKD) has not been completely evaluated, although the association of UAGT with renal outcomes has been suggested in specific subsets of CKD. In the present study, to investigate the association of UAGT with renal outcomes in patients with non-dialysis CKD irrespective of the primary cause, a total of 1688 subjects from the Korean Cohort Study for Outcomes in Patients With Chronic Kidney Disease (KNOW-CKD) were prospectively analyzed. The subjects were divided into the quintile by UAGT to urine creatinine ratio (UAGT/Cr) level. The primary outcomes of interest were composite renal event, which included decline in kidney function and onset of end-stage renal disease during follow-up periods. The median follow-up duration was 6.257 years. Cox regression model analysis unveiled that the risk of composite renal event was significantly higher in the fifth quintile (adjusted hazard ratio 1.528, 95% confidence interval 1.156 to 2.021) compared to that of the first quartile. The association between high UAGT/Cr level and adverse renal outcome remained consistent in sensitivity analyses, including the analysis of the cause-specific hazard model. Subgroup analyses revealed that the association of UAGT level with renal outcomes is modified by certain clinical contexts, such as BMI and albuminuria. In conclusion, high UAGT level is associated with adverse renal outcomes in patients with non-dialysis CKD. Further studies are warranted to elaborate and expand the predictive role of UAGT as a biomarker for renal outcomes in CKD. [ABSTRACT FROM AUTHOR]

To investigate the association between abdominal aortic calcification score (AACS) assessed by plain radiograph of the lateral abdomen and the risk of cardiovascular (CV) events in patients with pre-dialysis chronic kidney disease (CKD), a total of 2090 pre-dialysis CKD patients from the Korean Cohort Study for Outcome in Patients with Chronic Kidney Disease (KNOW-CKD) were categorized by AACS into 0, 1–2, 3–4, 5–6, and ≥7. The primary outcome of the study was the composite CV events, defined as a composite of non-fatal CV events and all-cause death. The risk of composite CV events was significantly higher in the subjects with AACS ≥ 7 (adjusted hazard ratio (HR) 1.888, 95% confidence interval (CI) 1.219 to 2.923), compared to that of the subjects with AACS 0. The risks of fatal and non-fatal CV events (adjusted HR 1.052, 95% CI 1.030 to 1.073) and all-cause death (adjusted HR 1.949, 95% CI 1.073 to 3.539) were also significantly higher in the subjects with AACS ≥ 7. In conclusion, AACS assessed by plain radiograph is independently associated with adverse CV outcomes in patients with pre-dialysis CKD. A simple radiographic examination of the lateral abdomen may help CV risk stratification in this population. [ABSTRACT FROM AUTHOR]

Circulating osteoprotegerin (OPG) is a biomarker for cardiovascular complications that are closely related to chronic kidney disease (CKD). To investigate the association between circulating OPG level with long-term visit-to-visit blood pressure variability (BPV) in patients with pre-dialysis CKD, a total of 1855 subjects with CKD from stage 1 to pre-dialysis stage 5 from a prospective cohort were analyzed. Long-term visit-to-visit BPV was determined by average real variability (ARV), standard deviation (SD), and coefficient of variation (CoV) of systolic and diastolic blood pressure (SBP and DBP). ARV of SBP (Adjusted β coefficient 0.143, 95% confidence interval 0.021 to 0.264) was significantly associated with serum OPG level. Although SD and CoV of SBP were not significantly associated with serum OPG level in multivariate linear regression analyses, restricted cubic spline visualized the linear correlation of serum OPG level with all of ARV, SD, and CoV. The association between serum OPG level and DBP variability was not significant. Subgroup analyses revealed that the association of serum OPG with BPV is more prominent in the subjects with Charlson comorbidity index ≤3 and in the subjects without history of diabetes mellitus. In conclusion, circulating OPG level is potentially associated with long-term visit-to-visit BPV in patients with pre-dialysis CKD. [ABSTRACT FROM AUTHOR]

Cardiovascular disease is a major complication of chronic kidney disease. The coronary artery calcium (CAC) score is a surrogate marker for the risk of coronary artery disease. The purpose of this study is to predict outcomes for non-dialysis chronic kidney disease patients under the age of 60 with high CAC scores using machine learning techniques. We developed the predictive models with a chronic kidney disease representative cohort, the Korean Cohort Study for Outcomes in Patients with Chronic Kidney Disease (KNOW-CKD). We divided the cohort into a training dataset (70%) and a validation dataset (30%). The test dataset incorporated an external dataset of patients that were not included in the KNOW-CKD cohort. Support vector machine, random forest, XGboost, logistic regression, and multi-perceptron neural network models were used in the predictive models. We evaluated the model's performance using the area under the receiver operating characteristic (AUROC) curve. Shapley additive explanation values were applied to select the important features. The random forest model showed the best predictive performance (AUROC 0.87) and there was a statistically significant difference between the traditional logistic regression model and the test dataset. This study will help identify patients at high risk of cardiovascular complications in young chronic kidney disease and establish individualized treatment strategies. [ABSTRACT FROM AUTHOR]

Apparent treatment-resistant hypertension (ATRH) is closely related to chronic kidney disease (CKD); however, the long-term outcomes and the effects of improvement in ATRH in patients with CKD are not well understood. We evaluated the relationship between the persistence of ATRH and the progression of CKD. This cohort study enrolled 1921 patients with CKD. ATRH was defined as blood pressure above 140/90 mmHg and intake of three different types of antihypertensive agents, including diuretics, or intake of four or more different types of antihypertensive agents, regardless of blood pressure. We defined ATRH subgroups according to the ATRH status at the index year and two years later. The prevalence of ATRH at baseline was 14.0%. The presence of ATRH at both time points was an independent risk factor for end-point renal outcome (HR, 1.41; 95% CI, 1.04–1.92; p = 0.027). On the other hand, the presence of ATRH at any one of the time points was not statistically significant. In conclusion, persistent ATRH is more important for the prognosis of renal disease than the initial ATRH status. Continuous follow-up and appropriate treatment are important to improve the renal outcomes. [ABSTRACT FROM AUTHOR]