Elucidating the relationship between nutrition indices and coronary artery calcification in patients undergoing maintenance hemodialysis

Phase angle and donor type are determinants of coronary artery calcification in stable kidney transplant recipients at twelve months after transplantation

BACKGROUND AND AIM

Coronary artery calcification (CAC) partially explains the excess cardiovascular morbidity and mortality after kidney transplantation. This study aimed to investigate determinants of CAC in stable kidney transplant recipients at 12 months post-transplantation.

METHODS AND RESULTS

CAC-score was quantified by the Agatston method using non-contrast enhanced computed tomography, and age- and sex-standardized CAC-percentiles were calculated. Univariable and multivariable multinomial logistic regression was performed to study potential determinants of CAC. The independent determinants were included in multivariable multinomial logistic regression adjusting for potential confounders. 203 KTRs (age 54.0 ± 14.7 years, 61.1% male) were included. Participants were categorized into four groups according to CAC percentiles (p = 0 [CAC-score = 0], n = 68; p ≥ 1%-p ≤ 50% [CAC score = 29.0 (4.0-166.0)], n = 31; p > 50 ≤ 75% [CAC score = 101.0 (23.8-348.3)], n = 26; and p>75% [CAC score = 581.0 (148.0-1652)], n = 83). Upon multivariable multinomial logistic regression, patients with a narrower phase angle and patients who had received a graft from a deceased donor had a higher risk of being in the >75th CAC-percentile.

CONCLUSIONS

This study identifies not only metabolic and transplant-related factors, but also phase angle, a composite marker of cell integrity, as an independent determinant of CAC at 12 months after kidney transplantation. This study offers new perspectives for future research into the value of bioelectrical impedance analysis in relation to vascular calcification in kidney transplant recipients.

Circulating miR-129-3p in combination with clinical factors predicts vascular calcification in hemodialysis patients

Background

Vascular calcification (VC) commonly occurs and seriously increases the risk of cardiovascular events and mortality in patients with hemodialysis. For optimizing individual management, we will develop a diagnostic multivariable prediction model for evaluating the probability of VC.

Methods

The study was conducted in four steps. First, identification of miRNAs regulating osteogenic differentiation of vascular smooth muscle cells (VSMCs) in calcified condition. Second, observing the role of miR-129-3p on VC in vitro and the association between circulating miR-129-3p and VC in hemodialysis patients. Third, collecting all indicators related to VC as candidate variables, screening predictors from the candidate variables by Lasso regression, developing the prediction model by logistic regression and showing it as a nomogram in training cohort. Last, verifying predictive performance of the model in validation cohort.

Results

In cell experiments, miR-129-3p was found to attenuate vascular calcification, and in human, serum miR-129-3p exhibited a negative correlation with vascular calcification, suggesting that miR-129-3p could be one of the candidate predictor variables. Regression analysis demonstrated that miR-129-3p, age, dialysis duration and smoking were valid factors to establish the prediction model and nomogram for VC. The area under receiver operating characteristic curve of the model was 0.8698. The calibration curve showed that predicted probability of the model was in good agreement with actual probability and decision curve analysis indicated better net benefit of the model. Furthermore, internal validation through bootstrap process and external validation by another independent cohort confirmed the stability of the model.

Conclusion

We build a diagnostic prediction model and present it as an intuitive tool based on miR-129-3p and clinical indicators to evaluate the probability of VC in hemodialysis patients, facilitating risk stratification and effective decision, which may be of great importance for reducing the risk of serious cardiovascular events.

Application of Bioelectrical Impedance Analysis in Nutritional Management of Patients with Chronic Kidney Disease

Body composition measurement plays an important role in the nutritional diagnosis and treatment of diseases. In the past 30 years, the detection of body composition based on bioelectrical impedance analysis (BIA) has been widely used and explored in a variety of diseases. With the development of technology, bioelectrical impedance analysis has gradually developed from single-frequency BIA (SF-BIA) to multi-frequency BIA (multi-frequency BIA, MF-BIA) and over a range of frequencies (bioimpedance spectroscopy, BIS). As the clinical significance of nutrition management in chronic kidney disease has gradually become prominent, body composition measurement by BIA has been favored by nephrologists and nutritionists. In the past 20 years, there have been many studies on the application of BIA in patients with CKD. This review describes and summarizes the latest research results of BIA in nutritional management of patients with CKD including pre-dialysis, hemodialysis, peritoneal dialysis and kidney transplantation, in order to provide reference for the application and research of BIA in nutritional management of chronic kidney disease in the future.

Association between phase angle and coronary artery calcium score in patients on peritoneal dialysis

Introduction

The phase angle (PhA) has been used as a nutritional marker and predictor of mortality in patients on peritoneal dialysis (PD). The coronary artery calcium (CAC) score has shown to predict the incidence of acute myocardial infarction and death from cardiovascular disease in these patients. However, the association between PhA and CAC score in patients with PD is not well-established, which is the objective of this study.

Materials and methods

Cross-sectional study with patients on PD, followed up at a University Hospital, between March 2018 and August 2019. PhA was evaluated by unifrequency bioimpedance (BIA). The CAC score was calculated based on cardiovascular computed tomography, considering positive when greater than or equal to 100 Agatston and negative when less than 100 Agatston.

Results

We evaluated 44 patients on dialysis, with a mean age of 56 years and median time on dialysis therapy was 11.7 months. In the statistical analysis, a significant association was only observed between the CAC score and the PhA.

Conclusion

The PhA is associated with a positive CAC score in patients with PD, and despite other factors, may be useful as a risk marker for coronary artery disease in this population.