Prevalence of Baseline Cardiac Arrhythmias in Participants with Overweight or Obesity in Phase 1 Clinical Trials: Analysis of 24-Hour Holter Electrocardiogram Recordings

Enhanced piezoelectric sensor to distinguish real-time arrhythmia for predicting heart failure

Monitoring cardiac rhythm is crucial for diagnosis of heart failure. However, the deficient sensitivity of polyvinylidene fluoride (PVDF) sensors impede their application in monitoring of cardiac rhythm due to the limited piezoelectricity. Here, doping of CoFe2O4 and aligning fibers were jointly adopted to enhance the piezoelectricity of PVDF, attributed to the transformation of α-PVDF to β-PVDF from 51.54 to 82.36 % confirmed by FTIR and First Principles simulation. Then the higher sensitivity piezoelectric sensors were developed based on aligned PVDF/CoFe2O4 accompanying with the superior frequency characteristics, rapid response, endurance stability, permeability and self-cleaning capabilities, compared to that of random PVDF/CoFe2O4 and PVDF sensors, which were 17.28, 13.40 and 2.16 mV kPa -1, respectively. Thus, the sensitivity of PVDF/CoFe2O4 sensors was sufficient to distinguish the variations of cardiac rhythm or arrhythmia of the established and verified heart failure rat model, including amplitude, cycle and frequency. The notable characteristic of an evolving heart failure was the significantly decreased amplitude initially, followed by a dramatic drop in the cycles of cardiac impulse. Hence, this non-invasive method is promise in providing valuable warning signs for predicting heart failure based on aligned PVDF/CoFe2O4 sensors, as well as in the prevention its occurrence.

The Prevalence of Arrhythmias, Including Premature Supraventricular and Ventricular Beats and Other Electrocardiographic Patterns, in 24-Hour Holter Monitoring in Patients with Overweight and Obesity

OBJECTIVES

this study aims to evaluate the prevalence of various arrhythmias and other electrocardiographic patterns within the group of individuals with overweight and obesity.

METHODS

One hundred eighty-one adults (90 females and 91 males) were qualified for inclusion in the experimental group. All participants had a body mass index (BMI) exceeding 25 kg/m2 (98 patients with obesity and 83 with overweight). The mean BMI in the obesity group was 33.6 kg/m2, and all participants had class 1 obesity. The control group comprised 69 individuals (56 females and 13 males) with normal BMI. The basic measurements were performed, and the participants filled out questionnaires describing their health conditions and lifestyles. Each participant underwent an electrocardiographic (ECG) examination and a 24 h Holter ECG examination.

RESULTS

In patients with class 1 obesity compared to the control patients, the average numbers of premature ventricular beats (PVBs) and premature supraventricular beats (SPBs) were statistically significantly higher (p = 0.030 and p = 0.042). There was a positive correlation between body weight and PVB (p = 0.028) and between body weight and SPB (p = 0.028). Moreover, BMI and waist circumference were correlated with SPB (p = 0.043 and p = 0.031). In the backward stepwise multivariate regression model considering 24 h Holter ECG monitoring, concerning SPB as the dependent variable, it was observed that BMI (especially obesity class 1), type 2 diabetes, and thyroid disease exhibited the highest regression coefficients.

CONCLUSIONS

obesity, even in class 1, might be a factor in a more frequent occurrence of abnormalities in electrocardiographic tests.

Harmony in Chaos: Deciphering the Influence of Ischemic Cardiomyopathy and Non-Cardiac Comorbidities on Holter ECG Parameters in Chronic Heart Failure Patients: A Pilot Study

Background and Objective: In the landscape of heart failure, non-cardiac comorbidities represent a formidable challenge, imparting adverse prognostic implications. Holter ECG monitoring assumes a supplementary role in delineating myocardial susceptibility and autonomic nervous system dynamics. This study aims to explore the potential correlation between Holter ECG parameters and comorbidities in individuals with ischemic cardiomyopathy experiencing heart failure (HF), with a particular focus on the primary utility of these parameters as prognostic indicators. Materials and Methods: In this prospective inquiry, a cohort of 60 individuals diagnosed with heart failure underwent stratification into subgroups based on the presence of comorbidities, including diabetes, chronic kidney disease, obesity, or hyperuricemia. Upon admission, a thorough evaluation of all participants encompassed echocardiography, laboratory panel analysis, and 24 h Holter monitoring. Results: Significant associations were uncovered between diabetes and unconventional physiological indicators, specifically the Triangular index (p = 0.035) and deceleration capacity (p = 0.002). Pertaining to creatinine clearance, notable correlations surfaced with RMSSD (p = 0.026), PNN50 (p = 0.013), and high-frequency power (p = 0.026). An examination of uric acid levels and distinctive Holter ECG patterns unveiled statistical significance, particularly regarding the deceleration capacity (p = 0.045). Nevertheless, in the evaluation of the Body Mass Index, no statistically significant findings emerged concerning Holter ECG parameters. Conclusions: The identified statistical correlations between non-cardiac comorbidities and patterns elucidated in Holter ECG recordings underscore the heightened diagnostic utility of this investigative modality in the comprehensive evaluation of individuals grappling with HF. Furthermore, we underscore the critical importance of the thorough analysis of Holter ECG recordings, particularly with regard to subtle and emerging parameters that may be overlooked or insufficiently acknowledged.