Medina‐Inojosa, José R.

Background: In general, women report higher stress levels than men. High baseline anxiety, depression, and stress levels are associated with greater risk of cardiovascular diseases. Current evidence for efficacy of stress management interventions for women is limited. This study aimed at assessing the effect of a stress management and resiliency training (SMART) program for decreasing stress, anxiety, and depressive symptoms. Methods: Fifty moderately or severely stressed Women's Heart/Preventive Cardiology Clinic patients consented to the SMART intervention delivered online ( n = 36) or in-person ( n = 9). Primary outcome measures were the observed changes between baseline and at 12 weeks for the following psychometric tools: General Anxiety Disorder-7 (GAD-7), Patient Health Questionnaires (PHQ-9), Perceived Stress Scale (PSS), and Brief Resiliency Scale (BRS). Results: Forty-five patients completed the study. We observed significant improvements in PSS and GAD-7, but not in PHQ-9 or BRS, after the SMART intervention. When assessing outcomes among those with depressive symptoms at baseline (PHQ-9 > 15), we observed significant changes in PSS, GAD-7, and PHQ-9. No differences between online and in-person program delivery methods were found (all p -values >0.05). Conclusions: Training exposure using the SMART program to decrease stress and anxiety in women seeking preventive cardiology services was feasible and similarly effective, whether delivered online or in a single in-person session. Impacts on depression and resilience likely require a more intensive approach. In the future, larger randomized clinical trials with additional training and longer follow-up are warranted.

Obesity and hypertension independently promote pathological left ventricular remodelling (LVR) and left ventricular hypertrophy (LVH), but to what extent they do so when they do not coexist is unclear. We used data from the Cardiovision Brno 2030 study to assess—for the first time in a region where no investigations have been previously carried out—the independent association of obesity and hypertension with LV geometry, and to evaluate the effects of hypertension in normal weight patients and the effects of obesity in normotensive patients. Overall, 433 individuals, aged 25–65 years, with no history of cardiovascular disease and/or antihypertensive treatment, were stratified into four groups according to BMI and hypertension: normal weight non-hypertensive (NWNH), normal weight hypertensive (NWH), overweight/obese non-hypertensive (ONH) and overweight/obese hypertensive (OH). LVR was classified as normal, concentric LVR (cLVR), concentric LVH (cLVH) or eccentric LVH (eLVH). Linear regression analysis demonstrated that body mass index (BMI) and systolic blood pressure (SBP) are the main predictors of LV mass and that they interact: SBP had a stronger effect in overweight/obese (β = 0.195; p = 0.033) compared to normal weight patients (β = 0.134; p = 0.048). Hypertension increased the odds of cLVR (OR = 1.78; 95%CI = 1.04–3.06; p = 0.037) and cLVH (OR = 8.20; 95% CI = 2.35–28.66; p = 0.001), independent of age, sex and BMI. Stratified analyses showed that NWH had a greater odd of cLVH (OR = 7.96; 95%CI = 1.70–37.08; p = 0.008) and cLVR (OR = 1.62; 95%CI = 1.02–3.34; p = 0.047) than NWNH. In the absence of hypertension, obesity was not associated with LVM and abnormal LV geometry, suggesting that it is not per se a determinant of LVR. Thus, antihypertensive therapy still remains the first-line approach against LVH in hypertensive patients, though weight loss interventions might be helpful in those who are obese.

The measurement of peak oxygen uptake (VO2peak) is an important metric for evaluating cardiac transplantation (HTx) eligibility. However, it is unclear which factors (e.g., recipient demographics, clinical parameters, cardiac rehabilitation (CR) participation) influence VO2peak following HTx. Consecutive HTx patients with cardiopulmonary exercise testing (CPET) between 2007–2016 were included. VO2peak was measured from CPET standard protocol. Regression analyses determined predictors of the highest post-HTx VO2peak (i.e., quartile 4: VO2peak > 20.1 mL/kg/min). One hundred-forty HTx patients (women: n = 41 (29%), age: 52 ± 12 years, body mass index (BMI): 27 ± 5 kg/m2) were included. History of diabetes (Odds Ratio (OR): 0.17, 95% Confidence Interval (CI): 0.04–0.77, p = 0.021), history of dyslipidemia (OR: 0.42, 95% CI: 0.19–0.93, p = 0.032), BMI (OR: 0.90, 95% CI: 0.82–0.99, p = 0.022), hemoglobin (OR: 1.29, 95% CI: 1.04–1.61, p = 0.020), white blood cell count (OR: 0.81, 95% CI: 0.66–0.98, p = 0.033), CR exercise sessions (OR: 1.10, 95% CI: 1.04–1.15, p < 0.001), and pre-HTx VO2peak (OR: 1.17, 95% CI: 1.07–1.29, p = 0.001) were significant predictors. Multivariate analysis showed CR exercise sessions (OR: 1.10, 95% CI: 1.03–1.16, p = 0.002), and pre-HTx VO2peak (OR: 1.16, 95% CI: 1.04–1.30, p = 0.007) were independently predictive of higher post-HTx VO2peak. Pre-HTx VO2peak and CR exercise sessions are predictive of a greater VO2peak following HTx. These data highlight the importance of CR exercise session attendance and pre-HTx fitness in predicting VO2peak post-HTx.

Hypertrophic obstructive cardiomyopathy (HOCM) patients exhibit compromised peak exercise capacity (VO2peak). Importantly, severely reduced VO2peak is directly related to increased morbidity and mortality in these patients. Therefore, we sought to determine clinical predictors of VO2peak in HOCM patients. HOCM patients who performed symptom-limited cardiopulmonary exercise testing between 1995 and 2016 were included for analysis. Peak VO2 was reported as absolute peak VO2, indexed to body weight and analyzed as quartiles, with quartile 1 representing the lowest VO2peak. Step-wise regression models using demographic features and clinical and physiologic characteristics were created to determine predictors of HOCM patients with the lowest VO2peak. We included 1177 HOCM patients (age: 53 ± 14 years; BMI: 24 ± 12 kg/m2) with a VO2peak of 18.0 ± 5.6 mL/kg/min. Significant univariate predictors of the lowest VO2peak included age, female sex, New York Health Association (NYHA) class, BMI, left atrial volume index, E/e’, E/A, hemoglobin, N-terminal pro b-type natriuretic peptide (NT-proBNP), and a history of diabetes, hypertension, stroke, atrial fibrillation, or coronary artery disease. Independent predictors of the lowest VO2peak included age (OR, CI: 1.03, 1.02–1.06; p < 0.0001), women (4.66, 2.94–7.47; p = 0.001), a history of diabetes (2.05, 1.17–3.60; p = 0.01), BMI (0.94, 0.92–0.96; p < 0.0001), left atrial volume index (1.07, 1.05–1.21; p = 0.04), E/e’ (1.05, 1.01–1.08; p = 0.004), hemoglobin (0.76, 0.65–0.88; p = 0.0004), and NT-proBNP (1.72, 1.42–2.11; p < 0.0001). These findings demonstrate that demographic factors (i.e., age and sex), comorbidities (e.g., diabetes and obesity), echocardiography indices, and biomarkers (e.g., hemoglobin and NT-proBNP) are predictive of severely compromised VO2peak in HOCM patients.

The notion that cardiovascular disease (CVD) primarily occurs in men is slowly disappearing. More women than men die of CVD every year, and when women survive, the burden and consequences are worse than in men. Markers of stress and other psychosocial factors have been associated with poor outcomes. Multiple studies have demonstrated sex-based differences in the vascular and endothelial responses to mental stress. Psychosocial stressors were also found to be independent risk factors for the development and progression of CVD. This review arises from accumulating evidence suggesting that psychological well-being may improve cardiac-related outcomes, independent of cardiac risk factors. Despite the fact that positive physician-patient engagement is likely to play a critical role in promoting positive psychological traits and healthy behaviors, current physician awareness and advocacy are rather suboptimal, despite active awareness campaigns such as the American Heart Association's Go Red for Women ® . There is a need to further study the role and management of stress as a CVD risk factor, especially in women, who are disproportionately affected.

In the European Union, Czech Republic ranks 3rd and 6th for the incidence of obesity and cardiovascular diseases, respectively. Worldwide, short sleep duration and excessive daytime sleepiness (EDS) characterize obese subjects, which in turn exhibit scarce physical activity and unhealthy diet. We aimed to understand the relationship between irregular sleep patterns, obesity and lifestyle factors, such as diet and physical activity, in a vulnerable Czech population. 1482 members of the Kardiovize cohort, a random sample of the Czech urban population, were included in a cross-sectional study. Exposure variables included self-reported sleep duration and EDS, assessed by the Epworth Sleepiness Scale. Primary outcomes were BMI and waist-to-hip ratio or prevalence of obesity and central obesity. Covariates included physical activity and diet. Associations and interactions between variables were evaluated using logistic regression analyses. After adjustment for covariates, short sleep duration (<7 h) was associated with greater odds of overweight (BMI > 25; OR = 1.42; 95%CI = 1.06–1.90; p = 0.020) and obesity (BMI > 30; OR = 1.40; 95%CI = 1.02–1.94; p = 0.047), while EDS was associated with greater odds of central obesity (OR = 1.72; 95%CI = 1.06–2.79; p = 0.030), independent of diet and physical activity. However, due to the cross-sectional nature of our study, further prospective, large-scale studies are needed to evaluate the etiological link and causality between sleep disturbances and obesity.

Background: Intima-media thickness (IMT) has been proposed as a measurement of subclinical atherosclerosis and has been associated with cardiovascular disease (CVD). Epicardial adipose tissue (EAT) is a fat depot between the pericardium and myocardium and has been associated with coronary atherosclerosis. The relationship between IMT and EAT thickness has not been reported before. We investigated the relationship between EAT thickness, IMT, CVD risk factors, and ideal cardiovascular health (CVH) metrics using subjects from the Kardiovize Brno 2030 cohort study, a random urban sample population in Central Europe. Methods: We studied 102 individuals (65 males) aged 25–64 years (median = 37 years) with no current or past CVD history. We measured IMT using a vascular ultrasound and EAT thickness using transthoracic echocardiography, and collected data on anthropometric factors, CVD risk factors, and CVH score. Correlation tests and multiple linear regression models were applied. Results: In the age- and gender-adjusted model, we demonstrated that, among CVD risk factors, only BMI was significantly and positively associated with EAT thickness (β = 0.182, SE = 0.082, p = 0.030), while no significant associations with IMT were evident. Although both EAT thickness and IMT were negatively correlated with CVH score (r = −0.45, p < 0.001, and r = −0.38, p < 0.001, respectively), we demonstrated that overall CVH score (β = −0.262; SE = 0.077; p = 0.001), as well as BMI (β = −1.305; SE = 0.194; p < 0.001) and blood pressure CVH metrics (β = −0.607; SE = 0.206; p = 0.004) were significantly associated with EAT thickness but not with IMT. Conclusions: Our study is important as it demonstrated for the first time that CVH is associated with EAT thickness. Interestingly, this relationship seems to be dependent on BMI and blood pressure rather than on the other CVH metrics. However, outcome-driven studies are required to confirm these findings.

Background Prognosis based on body fat percentage ( BF %) in patients with coronary artery disease has not been extensively studied. We tested the hypothesis that patients with coronary artery disease and increased BF % have a higher risk for major adverse cardiovascular events ( MACEs ) and that fat‐free mass is associated with better prognosis. Methods and Results We included 717 patients referred to cardiac rehabilitation after coronary artery disease events or procedures who underwent air displacement plethysmography to assess BF %; 75% were men, with a mean age 61.4±11.4 years and a mean body mass index of 30±5.4 kg/m 2 . Follow‐up was performed using a record linkage system. Patients were classified in sex‐specific quartiles of BF % and fat‐free mass index. The composite outcome of MACEs included acute coronary syndromes, coronary revascularization, stroke, or death from any cause. After a median follow‐up of 3.9 years, 201 patients had a MACE . After adjusting for covariates, body mass index was not associated with MACEs ( P =0.12). However, the risk of MACEs for those in the highest BF % quartile was nearly double when compared with those in the lowest quartile (hazard ratio, 1.89; 95% confidence interval, 1.30–2.77; P =0.0008). In contrast, fat‐free mass was inversely associated with MACEs . The risk of MACEs for those in the fourth fat‐free mass quartile was lower (adjusted hazard ratio, 0.53; 95% confidence interval, 0.35–0.82; P =0.004), when compared with those in the first quartile. Conclusions In patients with coronary artery disease, there is no obesity paradox when measuring BF % instead of body mass index. BF % is associated with a higher risk of MACEs , whereas fat‐free mass is associated with a lower risk of MACEs . Body mass index was not associated with MACEs .