Suarez, Audry Chacin

Introduction: The presence of chronic somatic and mental health conditions is complex and challenging for patients and the health care system due to the health deficit accumulation, worsening outcomes, and increased health care utilization. While previous studies on multimorbidity have focused on somatic chronic conditions, we aim to assess the relation between somatic, mental, and combined somatic-mental multimorbidity (SMM) and impact on Major Adverse Cardiac Events (MACE) in patients enrolled in phase II outpatient cardiac rehabilitation (CR). Methods: Using the Rochester Epidemiology Project records-linkage system, we identified patients from Olmsted County, Minnesota who were 18 years old and attended (≥1) CR sessions at Mayo Clinic Rochester. The prevalence of 18 (somatic=13; mental=5) chronic conditions defined by the US Department of Health and Human Services was ascertained electronically. Results: We included 618 patients; 24.4% were female. Patients were 61.5±11.0 years old with 38.0% ≥65 years old. Overall median number of chronic conditions was 6 (Range 0-13) with 98.8% of patients having ≥2 conditions. The prevalence of combined SMM was 44.6%. Mean follow-up was 7.3± 4.5 years, 147 (23.7%) patients had MACE (number): acute coronary syndrome (46), percutaneous coronary intervention (33), heart failure (16), stroke (8), coronary artery bypass grafting (4), ventricular arrhythmias (4), or death (65). Risk of MACE in patients with SMM was significantly higher compared to patients with only somatic conditions (HR: 1.62, 95% CI: 1.14-2.30, p=0.01 ), Figure 1. The association remained significant after adjustment for age and sex ( p=0.006 ). Conclusions: Our results show that somatic-mental multimorbidity (SMM) in CR patients is highly prevalent and imposes a higher risk of MACE compared with patients who have only somatic conditions highlighting the importance of individualized assessment and care plans to reduce adverse events and mortality.

Introduction: Cardiac rehabilitation (CR) is associated with improvements in exercise capacity (peak oxygen uptake (VO 2 peak)); however, 23% of CR patients do not improve VO 2 peak following CR. CR adherence (i.e. number of CR sessions attended) has been proposed to play an important role in VO 2 peak improvement following CR, but has not been investigated. Identifying clinical predictors of VO 2 peak improvement are critical as the degree of VO 2 peak improvement is associated with improved long-term outcomes in these patients. Purpose: To determine if clinical characteristics and number of CR sessions attended were predictive of patients who exhibited improvement in VO 2 peak following CR. Methods: Using the Rochester Epidemiology Project records-linkage system, we identified all consecutive patients >18 years old from Olmsted County, Minnesota who underwent cardiopulmonary exercise testing prior to and following CR from 1999 to 2017. Regression models were created to assess clinical predictors of VO 2 peak improvement (>0% baseline) following CR. Results: The analysis included 804 patients (75% men) with a mean age of 60.7±12.4 years. Of the 804 patients, 609 (76%) patients exhibited VO 2 peak improvement following CR. Significant univariate predictors of VO 2 peak improvement included younger age (OR: 0.99, 95% CI: 0.97-1.00), lower pre-CR VO 2 peak (OR: 0.97, 95% CI: 0.94-0.99), history of peripheral artery disease (OR: 0.48, 95% CI: 0.32-0.73), and smoking (OR: 0.63, 95% CI: 0.45-0.90). Significant independent predictors of VO 2 peak improvement from a multivariate analysis included younger age (OR: 0.98, 95% CI: 0.96-1.00), number of CR sessions (OR: 1.02, 95% CI: 1.01-1.03), lower pre-CR VO 2 peak (OR: 0.94, 95% CI: 0.91-0.96), history of peripheral artery disease (OR: 0.42, 95% CI: 0.27-0.66), and smoking (OR: 0.56, 95% CI: 0.39-0.82). Conclusions: These findings demonstrate the importance of CR adherence and individual clinical characteristics in influencing VO 2 peak improvement following CR in patients with CVD. These findings may influence the clinical practice by providing specific clinical characteristics to account for when personalizing the CR treatment plan to maximize positive outcomes.

Introduction: Body fat (BF) content better predicts adiposity-related cardiovascular risk than the body mass index (BMI). Accurate and accepted methods to assess BF are complex, expensive, and accessible only in clinical settings. Multi-sensor 3D body volume (3D-BV) measurement technology has been shown to accurately estimate BF. We assessed the hypothesis that 3D models generated from biplane imaging (i.e., front and side facing photographs) using mobile devices (App), could be used to predict body volume measurements and derive BF. Methods: We prospectively enrolled 196 subjects, who underwent 3D-BV (gold standard for body volume) within 24 hours, dual-energy X-ray Absorptiometry (iDEXA) (gold standard for BF) and photographs taken with an Ipad® App at a predefined distance and pose. These photos were post-processed with a computer-assisted algorithm to estimate body length, girth, and volume. These were used to calculate body density (BD) using the bicompartmental principles of body composition (BD=Body Mass/Volume) and derive BF% using the Siri equation [(4.95/BD-4.50) X 100]. Correlation indexes and residual plots were created to compare 3D-BV and iDEXA with the App. Mean differences were compared using a paired t-test. Results: Mean ±SD age was 31.9±9.15 years, 53% were women, weight 72.8±14.1 kg, BMI was 25.5±4.5 kg/m 2 .The App volume correlated with 3D-BV (R 2 =0.95,95%CI 0.90,0.95, p<.0001, Figure 1-A ) ; average difference between App volume vs 3D-BV volume was -1.2 Liters, 95%CI,0.03, 2.42, p=0.06, ( Figure 1-B ). App BF% correlated with iDEXA BF% (R 2 =0.92, 95%CI 0.90,0.94, p<.0001, Figure 1-C ) ; while average difference between App BF% vs iDEXA BF% was -0.13 %, 95%CI -0.6,0.4, p=0.6, ( Figure 1-D ). Conclusion: BF can be estimated using volume measurements obtained by biplane imaging from mobile devices and could serve as a home-based, portable, scalable, cost-effective, and convenient measure to assess BF and track changes in body composition over time.

Introduction: Spontaneous coronary artery dissection (SCAD) is an important cause of myocardial infarction in otherwise healthy and most times presumably fit young women. In the absence of evidence for benefit or harm, exercise prescription (EXP) after SCAD remains arbitrary. We assessed EXP patterns among participants in a large multinational SCAD registry. Methods: Participants with SCAD as confirmed by coronary angiography completed surveys detailing exercise (EX) habits prior to SCAD (initial survey), and EXP from their provider on initial and subsequent visits after SCAD (follow-up survey). Demographic and clinical characteristics were collected by electronic health record review by trained nurse abstractors. EXP was categorized according to EX components that include: type, intensity, frequency, time/session, and external conditions. Results: Among 950 participants, mean ± age was 46.8 ± 9.5 years, 96% were women and 77% reported attending ≥1 Cardiopulmonary Rehabilitation session. Prior to SCAD, 49% were aerobically exercising ≥ 3times per week, and only 32% performed strength-building EX regularly. Initial and subsequent post-SCAD visit details in 299/950 participants showed that most (93%) patients received some form of EX (Figure 1-A) counseling, namely: EXP, unspecific advice or were discouraged from any EX (Figure 1-B) . Limits regarding EX type and intensity were the most common advice received among EXP group (Figure 1-C) . Conclusions: Insights from our study show that only 40% of patients were achieving current exercise recommendations for adults prior to SCAD (vs 53% adult U.S population; CDC, 2018) which suggests that SCAD patients may not be as active as previously described. Most patients receive some form of EX counseling after SCAD; however, a structured EXP is needed to avoid overly cautious approaches that could lead to uncertainty, deconditioning, impaired quality of life, or increase risks associated with a sedentary lifestyle.