Purpose of review To describe the relationship between three pandemics: hypertension, obesity, and heart failure. From pathophysiology to treatment, understanding how these disease entities are linked can lead to breakthroughs in their prevention and treatment. The relevance of this review lies in its discussion of novel pharmacological and surgical treatment strategies for obesity and hypertension, and their role in the prevention and treatment of heart failure. Recent findings Novel medications such as GLP-1 agonists have demonstrated sustained weight loss in patients with obesity, and concurrent improvements in their cardiometabolic profile, and possibly also reductions in hypertension-related comorbidities including heart failure. Surgical therapies including laparoscopic bariatric surgery represent an important treatment strategy in obese patients, and recent studies describe their use even in patients with advanced heart failure, including those with ventricular assist devices. Summary These developments have deep implications on our efforts to understand, mitigate, and ultimately prevent the three pandemics, and offer promising improvements to quality of life, survival, and the cost burden of these diseases.
Abstract 11444: Pattern of V
E
/VCO
2
Abnormalities in Chronic Thromboembolic Pulmonary Hypertension
Introduction: Breathing efficiency (V E /VCO 2 slope or nadir) predicts mortality in heart failure (HF). The usual pattern of V E /VCO 2 vs. exercise intensity is a characteristic “shallow bowl” configuration allowing estimate of a V E vs. VCO 2 slope both in normal controls (C) and HF patients. Slope or nadir in HF is generally > 33 vs. 25-30 in C. This pattern of V E /VCO 2 may not be true for other CV diseases. Objective: Compare V E /VCO 2 versus exercise time curves in patients with history of chronic thromboembolic pulmonary hypertension type 4 (PHT4) to HF and C referred for dyspnea on exertion. Methods: We identified 40 consecutive cases of PHT4 versus 40 HF and 40 C over the same age range retrospectively selected from our cardiopulmonary exercise test (CPX) database. V E /VCO 2 was plotted against exercise time (minutes of exercise ≈ METs), and groups were compared statistically for V E /VCO 2 and peak VO 2 by ANOVA followed with Tukey test, with significance set at P < .05. Results: Figure shows higher V E /VCO 2 in PHT4 vs. HF and C with a different pattern vs. exercise intensity. In severe cases (example shown) V E /VCO 2 may increase continuously without plateau reaching peak values > 80. There was statistically significant difference between peak VO 2 between C group vs HF and PHT4, but not among HF and PHT4, although V E /VCO 2 was significant different among the three groups. Age and sex was not different among them. Conclusion: V E /VCO 2 was elevated in PHT4 compared to HF and C. We interpret continuously increasing V E /VCO 2 as a marker of progressively worsening ventilation: perfusion mismatch. Interpretation of V E /VCO 2 in PHT4 cannot be based simply on nadir or slope as in HF, but a plot of the data should be visually examined to gain full understanding of the ventilatory abnormality.
Peak Systolic Blood Pressure During the Exercise Test: Reference Values by Sex and Age and Association With Mortality
We sought to update norms for peak systolic blood pressure (SBP) on the graded exercise test and examine its prognostic value in patients without baseline cardiovascular disease. Mayo graded exercise test data (1993–2010) were reviewed for nonimaging tests using Bruce protocol, selecting Minnesota residents 30 to 79 years without baseline cardiovascular disease. We formed a pure cohort of patients without factors significantly affecting peak SBP to determine peak SBP percentile norms by age and sex. Then we divided the full cohort of patients into 5 groups based on peak SBP percentiles: low (<10th), borderline low (10th–25th), referent (25th–75th), borderline high (75th–90th), and high (>90th). The relationship between peak SBP and mortality was tested using Cox regression adjusting for age, sex, and comorbidities affecting peak SBP or mortality. We identified 20 760 eligible patients with 7313 females (35%) and mean age 51.5±10.7 years. Our pure cohort included 7810 patients. Over 12.5±5.0 years follow-up, there were 1582 deaths, including 541 cardiovascular deaths. In the fully adjusted model, low-peak SBP was associated with increased total mortality (heart rate, 1.41 [1.19–1.66], P <0.0001) and cardiovascular mortality (heart rate, 1.54 [1.16–2.03], P =0.001), while borderline low-peak SBP was associated with increased cardiovascular mortality only (heart rate, 1.36 [1.02–1.81], P =0.027). High peak SBP was associated with increased total mortality only in the age-sex adjusted model (heart rate, 1.18 [1.02–1.36], P =0.026), not after full adjustment. We conclude that low exercise peak SBP is an independent predictor of higher total and cardiovascular mortality.
0719 The Association of Sleep Apnea and Cardiorespiratory Fitness with Long-Term Major Cardiovascular Events
Abstract Introduction Sleep disordered breathing (SDB) is associated with adverse cardiovascular outcomes and decreased cardiorespiratory fitness (CRF). The risk of long-term major adverse cardiovascular events (MACE) when SDB and decreased CRF co-occur has not been determined. Methods We included consecutive patients that underwent a symptom-limited cardiopulmonary exercise test followed by first-time diagnostic polysomnography within 6 months. Patients were stratified based on the presence of moderate-severe SDB (apnea/hypopnea index ≥15/hour) and decreased CRF defined as <70% predicted peak oxygen consumption (VO2). MACE was a composite outcome of myocardial infarction (MI), coronary artery bypass graft (CABG), percutaneous coronary intervention (PCI), stroke/transient ischemic attack (TIA) and death. Cox-proportional hazard models adjusting for factors known to influence CRF and MACE were constructed. Results Of 498 included patients (60±13 years, 28.1% female), 175 (35%) had MACE (MI=17, PCI=14, CABG=13, stroke=20, TIA=12, deaths=99) at a median follow-up of 8.7 years (interquartile range=6.5-10.3 years). After adjusting for age, sex, beta-blockers, systemic hypertension, diabetes mellitus, coronary artery disease, cardiac arrhythmia, chronic obstructive pulmonary disease, smoking and positive airway pressure (PAP) usage, decreased CRF alone (HR=1.91, 95%CI=1.15-3.18, p=0.012), but not SDB alone (HR=1.26, 95%CI=0.75-2.13, p=0.389) was associated with increased risk of MACE. Those with SDB and decreased CRF had increased risk of MACE compared to patients with decreased CRF alone (HR=1.85, 95%CI=1.21-2.84, p<0.005) after accounting for these confounders; the risk was attenuated after additionally adjusting for adequate adherence to PAP (HR=1.85, 95%CI=0.99-3.05, p=0.05). Conclusion The incidence of MACE, including mortality, was high in this sample. Moderate-severe SDB with concurrent decreased CRF was associated with higher risk of MACE than decreased CRF alone. These results highlight the importance of including CRF in the risk assessment of patients with SDB, and conversely, that of screening for SDB in patients with low peak VO2. Support None.
Fat Mass Index Better Identifies Metabolic Syndrome: Insights from Patients in Early Outpatient Cardiac Rehabilitation
Body mass index (BMI) does not differentiate fat and lean mass or the distribution of adipose tissue. The purpose of this study was to examine the prevalence of metabolic syndrome (MetS) among patients entering outpatient cardiac rehabilitation (CR) across fat mass index (FMI) categories compared with BMI. This retrospective cross-sectional study evaluated dual-energy x-ray absorptiometry in 483 CR patients from 1 January 2014, through 31 December 2017. Clinical data were extracted from the electronic health record. Patients were grouped by FMI and BMI categories. Mean (SD) age of patients was 64.3 (14) years. The normal FMI category had 15 patients; excess fat, 74; and obese, 384. In contrast, 93, 174, and 216 were in the normal, overweight, and obese BMI categories, respectively. Prevalence of MetS was 0 (0%) in normal, 5 (1%) in excess fat, and 167 (54%) in obese FMI, with 97% in the obese category. MetS prevalence was 4 patients (0.8%) in normal, 39 (8%) in overweight, and 129 (27%) in obese BMI categories, with 75% of MetS in the obese category. FMI more accurately classified CR patients with metabolically abnormal fat (p < 0.001). FMI is a more sensitive index than BMI for metabolically abnormal fat of outpatient CR patients.