Sagittal abdominal diameter and Framingham risk score in non-dialysis chronic kidney disease patients

Association between sagittal abdominal diameter-to-height ratio and arteriosclerotic cardiovascular disease among the United States adults: A cross-sectional study

Objectives

Abdominal obesity is recognized as a significant determinant of Arteriosclerotic cardiovascular disease (ASCVD), with sagittal abdominal diameter (SAD) being considered a more precise indicator of visceral fat. Nevertheless, the association between SAD and ASCVD remains unexplored in large-scale general-population studies.

Methods

The study included 11,211 participants aged 20 to 80 from the National Health and Nutrition Examination Survey. Logistic regression models were utilized to evaluate the association between the SAD-to-height ratio (SADHtR) and ASCVD. Subgroup analyses based on age categories, sex, diabetes, and hypertension were conducted to assess result robustness.

Results

The median SADHtR value was 0.13 (0.12-0.15), and 1,006 cases (7.46 %) of ASCVD were recorded. Multivariable models showed that each standard deviation increase in SADHtR was positively associated with higher odds of ASCVD (OR 1.48, 95 % CI 1.36-1.62 in model 1; OR 1.41, 95 % CI 1.28-1.54 in model 2; OR 1.18, 95 % CI 1.08-1.30 in model 3). Comparing the first quartile of SADHtR to the second to fourth quartiles, positive associations with ASCVD were observed in models 1 and 2. However, in model 3, only the fourth quartile of SADHtR remained statistically significant (OR 1.58, 95 % CI 1.17-2.15), with all p-values for the trend being less than 0.05. No interactions were found in the subgroup analyses.

Conclusion

This study demonstrates a positive association between SADHtR and ASCVD in the general adult population of the United States. Our findings indicate that SADHtR, especially when ≥ 0.155, could be a valuable metric for assessing the risk of ASCVD.

Electrochemical skin conductance and heart rate variability in patients with non-dialysis chronic kidney disease

BACKGROUND

Chronic kidney disease (CKD) is very common now and associates with high overall and cardiovascular mortality. Numerous studies have reported that Heart rate variability (HRV) could also be used to detect cardiovascular autonomic dysfunction (CAD). We investigated the association of electrochemical skin conductance (ESC) of EZSCAN results with HRV in non-dialysis CKD patients.

METHODS

In a cross-sectional study, we enrolled 248 prevalent non-dialysis CKD patients. Patients underwent a 24-h Holter (CB-2302-A, Bio Instrument, China). A time domain analysis of HRV was performed, and the following parameters were obtained: SDNN, SDANN, rMSSD, pNN50. EZSCAN device (Impeto Medical, Paris, France) measures ESC values of each participants. Mean global skin conductance computed as 0.5 * (reflecting (right + left hand)/2 + (right and left foot)/2). Log transforms data into a normal distribution for statistical analysis.

RESULTS

There were 142 males and 106 females included in the present study. Patients' age was 56.6±17.08 years. Logarithm(Log) (global ESC) was independently predicted by age (P<0.01), hypertension history, estimated Glomerular filtration rate (eGFR) and log SDNN (P<0.05). While log SDANN, rMSSD and pNN50 were not independent predictors for log (global ESC).

CONCLUSION

Increased global ESC significantly associated with elevated HRV, specifically SDNN in non-dialysis CKD patients. This suggested that global ESC may appear to be an important predictor of CAD, and even could be used as a cardiovascular risk factor in non-dialysis CKD patients.

Relationship between Depression Symptoms and Different Types of Measures of Obesity (BMI, SAD) in US Women

OBJECTIVE

To estimate the relationship between obesity (defined by both BMI and SAD) and various levels of depressive symptoms in women in the United States.

METHODS

This is a cross-sectional design. All data were collected from NHANES 2011-2012 and 2013-2014. The Patient Health Questionnaire (PHQ-9) was the primary variable used to index depressive symptoms. SAD was assessed using an abdominal caliper. We stratified participates into three groups according to SAD (trisection): T1: low (11.8-18.4 cm), T2: middle (18.5-22.8 cm), and T3: high (22.9-40.1 cm). Other data were collected following the NHANES protocols. We aimed to investigate the effects of obesity on the depression in the NHANES populations.

RESULTS

A total of 4477 women were enrolled in the final study population. Participants with a high SAD had the highest risk of clinical depression symptoms (OR = 1.2, 95% CI: 1.1-1.4), which was, in particular, the case for moderate-severe depression (OR = 1.4, 95% CI: 1.1-1.7) and severe depression (OR = 1.4, 95% CI: 1.0-1.9). We also found a significant relationship between SAD and BMI (r = 0.836). We did, however, not find a significant relationship between BMI and severe depression.

CONCLUSIONS

SAD had a better correlation with clinical depression symptoms than BMI, especially regarding severe depression symptoms.

Cardiometabolic-Based Chronic Disease, Adiposity and Dysglycemia Drivers: JACC State-of-the-Art Review

A new cardiometabolic-based chronic disease (CMBCD) model is presented that provides a basis for early and sustainable, evidence-based therapeutic targeting to promote cardiometabolic health and mitigate the development and ravages of cardiovascular disease. In the first part of this JACC State-of-the-Art Review, a framework is presented for CMBCD, focusing on 3 primary drivers (genetics, environment, and behavior) and 2 metabolic drivers (adiposity and dysglycemia) with applications to 3 cardiovascular endpoints (coronary heart disease, heart failure, and atrial fibrillation). Specific mechanistic pathways are presented configuring early primary drivers with subsequent adiposity, insulin resistance, β-cell dysfunction, and metabolic syndrome, leading to cardiovascular disease. The context for building this CMBCD model is to expose actionable targets for prevention to achieve optimal cardiovascular outcomes. The tactical implementation of this CMBCD model is the subject of second part of this JACC State-of-the-Art Review.

Cardiometabolic-Based Chronic Disease, Adiposity and Dysglycemia Drivers: JACC State-of-the-Art Review

A new cardiometabolic-based chronic disease (CMBCD) model is presented that provides a basis for early and sustainable, evidence-based therapeutic targeting to promote cardiometabolic health and mitigate the development and ravages of cardiovascular disease. In the first part of this JACC State-of-the-Art Review, a framework is presented for CMBCD, focusing on 3 primary drivers (genetics, environment, and behavior) and 2 metabolic drivers (adiposity and dysglycemia) with applications to 3 cardiovascular endpoints (coronary heart disease, heart failure, and atrial fibrillation). Specific mechanistic pathways are presented configuring early primary drivers with subsequent adiposity, insulin resistance, β-cell dysfunction, and metabolic syndrome, leading to cardiovascular disease. The context for building this CMBCD model is to expose actionable targets for prevention to achieve optimal cardiovascular outcomes. The tactical implementation of this CMBCD model is the subject of second part of this JACC State-of-the-Art Review.