The Relationship between Autonomic Regulation of Cardiovascular Function and Body Composition

Relationship between syncopal symptoms and head-up tilt test modes

OBJECTIVE

Head-up tilt test (HUTT) is an important tool in the diagnosis of pediatric vasovagal syncope. This research will explore the relationship between syncopal symptoms and HUTT modes in pediatric vasovagal syncope.

METHODS

A retrospective analysis was performed on the clinical data of 2513 children aged 3-18 years, who were diagnosed with vasovagal syncope, from Jan. 2001 to Dec. 2021 due to unexplained syncope or pre-syncope. The average age was 11.76 ± 2.83 years, including 1124 males and 1389 females. The patients were divided into the basic head-up tilt test (BHUT) group (596 patients) and the sublingual nitroglycerine head-up tilt test (SNHUT) group (1917 patients) according to the mode of positive HUTT at the time of confirmed pediatric vasovagal syncope.

RESULTS

(1) Baseline characteristics: Age, height, weight, heart rate (HR), systolic blood pressure (SBP), diastolic blood pressure (DBP), and composition ratio of syncope at baseline status were higher in the BHUT group than in the SNHUT group (all P < 0.05). (2) Univariate analysis: Age, height, weight, HR, SBP, DBP, and syncope were potential risk factors for BHUT positive (all P < 0.05). (3) Multivariate analysis: syncope was an independent risk factor for BHUT positive, with a probability increase of 121% compared to pre-syncope (P<0.001).

CONCLUSION

The probability of BHUT positivity was significantly higher than SNHUT in pediatric vasovagal syncope with previous syncopal episodes.

Predictors of Cardiac Autonomic Dysfunction in Obesity-Related Hypertension

INTRODUCTION

Cardiac Autonomic Dysfunction (CAD) is an overlooked cardiovascular risk factor in individuals with obesity-related hypertension. Despite its clinical significance, there is a notable lack of clarity regarding the pathophysiological correlates involved in its onset and progression.

AIM

The present study aimed to identify potential predictors of CAD in obesity-related hypertension.

METHODS

A total of 72 participants (34 men and 38 women) were enrolled. Comprehensive evaluations were conducted, including cardiac autonomic function assessments, body composition estimation and biochemical analysis. Participants were categorized as CAD-positive or CAD-negative based on Ewing's criteria for autonomic dysfunction. Univariate logistic regression analysis was performed to identify potential predictors for CAD. Multivariate logistic regression models were further constructed by adjusting clinically relevant covariates to identify independent predictors of CAD.

RESULTS

Multivariate logistic regression analysis revealed that resting heart rate (HRrest), (odds ratio, confidence interval: 0.85, 0.78-0.93; p = 0.001) and percentage body fat (BF%), (odds ratio, confidence interval: 0.78, 0.64-0.96; p = 0.018) were significant independent predictors of CAD. Receiver Operating Characteristic curve analysis depicted optimal cut-off values for HRrest and BF% as > 74.1 bpm and > 33.6%, respectively. Multicolinearity analysis showed variance inflation factors (VIF) below the cautionary threshold of 3.

CONCLUSIONS

The HRrest and BF% emerged as significant independent predictors of CAD in obesity-related hypertension. Therapeutic strategies should target HRrest < 74.1 bpm and BF% < 33.6% to mitigate CAD risk in this population. Future trials are required to establish causal relationships and may consider additional confounding variables in obesity-related hypertension.

Linking Electronic Health Records With Wearable Technology From the All of Us Research Program

OBJECTIVE

To evaluate the feasibility of using electronic health records (EHRs) and wearable data to describe patterns of longitudinal change in day-level heart rate before, during, and after pregnancy and how these patterns differ by age and body mass index.

DESIGN

Descriptive secondary analysis feasibility study using data from the National Institutes of Health All of Us Research Program.

SETTING

United States.

PARTICIPANTS

Women (N = 89) who had a birth or length of gestation code in the EHR and at least 60 days of Fitbit heart rate data during pregnancy.

METHODS

We estimated pregnancy-related episodes using EHR codes. Time consisted of five 3-month periods: before pregnancy, first trimester, second trimester, third trimester, and after birth. We analyzed data using descriptive statistics and locally estimated scatterplot smoothing.

RESULTS

An average of 330 days (SD = 112) of Fitbit heart rate data (29,392 days) were available from participants. During pregnancy, distinct peaks in heart rate occurred during the first trimester (6% increase) and third trimester (15% increase).

CONCLUSION

Future researchers can examine whether longitudinal timing and patterns of heart rate from wearable devices could be leveraged to detect health problems early in pregnancy.

Relationship between Body Composition and Cardiac Autonomic Regulation in a Large Population of Italian Olympic Athletes

Athletic performance is determined by many factors, such as cardiorespiratory fitness, muscular strength and psychological features, which all interact simultaneously. The large Italian National Olympic Committee database of Olympic athletes offers a unique healthy population to verify the strength of the interplay among a number of major elements of training, including autonomic nervous system (ANS) modulation, biochemical indicators and body composition, in a system medicine approach. This observational, retrospective study involved 583 individuals. As part of the yearly precompetitive examination, cardiac autonomic (heart rate variability), psychological, physical (cycloergometer stress test), biochemical and body composition (BOD POD) evaluations were performed. In subsequent analysis, we first considered the relationship between body composition and single individual variables in a simple correlation matrix, including a multitude of variables; then, Exploratory Factor Analysis (EFA) restricted the information to six latent domains, each combining congruent information in relation to body composition. Finally, we employed a multiple quantile regression model to evaluate possible relationships between ANSIs (index capable of synthetizing ANS regulation) and the latent domains indicated by EFA reflecting body composition. We observed a clear relationship between ANS and body mass composition parameters, as indicated by both bivariate correlations and the quantile regression result of ANSIs versus the latent domain aggregating mainly body composition data expressed in % (p = 0.002). In conclusion, these results suggest that specific training may elicit parallel adaptation of ANS control and body composition. The analysis of Olympic athletes’ data allowed us to obtain a better understanding of the complex, multidimensional factors involved in determining sport performance. The latter appears to be determined by the simultaneous interaction not only of cardiorespiratory fitness, muscular strength and psychological features, but also of ANS cardiovascular modulation and body composition.

Differences in heart rate variability and body composition in breast cancer survivors and women without cancer

The aim of this study was to explore cardiac autonomic changes assessed by linear and nonlinear indexes of heart rate variability (HRV) and body composition modifications in breast cancer survivors and cancer-free control women. Women who were breast cancer survivors (BCS, n = 27) and without cancer with similar characteristics (Control, n = 31) were recruited for this study. We calculated some relevant linear and nonlinear parameters of 5 min of RR interval time series such as mean RR interval (RRave), the corrected Poincaré index (cSD1/SD2), the sample entropy (SampEn), the long-term fractal scaling exponent (α2) and 2UV from symbolic dynamics. Additionally, we indirectly assessed body composition measures such as body weight, fat mass, visceral fat rating (VFR), normalized VRF (nVFR), muscle mass, metabolic age, and total body water. We found that diverse HRV indexes and only one body composition measure showed statistical differences (p < 0.05) between the BCS and Control groups. RRave: 729 (648-802) vs. 795 (713-852) ms; cSD2/SD1: 3.4 (2.7-5.0) vs. 2.9 (2.3-3.5); SampEn: 1.5 (1.3-1.8) vs. 1.7 (1.5-1.8); α2: 0.6 (0.3-0.6) vs. 0.5 (0.4-0.5); 2UV: 7.1 (4.3-11.5) vs. 10.8 (6.4-15.7) and nVFR 0.12 (0.11-0.13) vs. 0.10 (0.08-0.12) points/kg, respectively. The nVFR was strongly significantly correlated with several indexes of HRV only in the BCS group.Our findings suggest that BCS exhibit lower parasympathetic cardiac activity and changes in HRV patterns compared to Controls. A concomitant increase of visceral fat, among other factors, may contribute to cardiac autonomic disturbances and changes in HRV patterns in BCS.