Chacin‐Suarez, Audry

Background Cardiac rehabilitation (CR) leads to increased exercise capacity (VO 2 peak) and risk reduction of major adverse cardiovascular events (MACEs). Women exhibit blunted VO 2 peak improvements following CR. The purpose was to examine sex differences in the clinical predictors of VO 2 peak improvement and odds of MACEs following CR. Methods From 1999 to 2017, all consecutive patients undergoing cardiopulmonary exercise testing before and after CR were included. Sex differences in peak exercise metrics in response to CR were compared. Multiple logistic regression models were fit to assess clinical predictors of VO 2 peak improvement (defined as >0% from pre‐CR) and MACEs following CR for men and women. Results A total of 513 men and 158 women were included. Men had greater increases in VO 2 peak than women following CR ( P =0.001). For men, independent predictors of VO 2 peak improvement following CR included higher CR session attendance (odds ratio [OR], 1.04 [95% CI, 1.02–1.06]), peripheral artery disease (OR, 0.47 [95% CI, 0.25–0.86]), and pre‐CR VO 2 peak (OR, 0.98 [95% CI, 0.97–0.99]) (all, P <0.02). Independent predictors of lower odds of MACEs following CR in men included higher number of CR sessions (OR, 0.97 [95% CI, 0.95–0.99]), pre‐CR VO 2 peak (OR, 0.98 [95% CI, 0.97–0.99]), surgical CR indication (OR, 0.34 [95% CI, 0.18–0.68]), and no history of peripheral artery disease (OR, 2.94 [95% CI, 1.60–5.38]) (all, P <0.02). For women, the selected clinical characteristics were not statistically significant independent predictors of VO 2 peak improvement or odds of MACEs (except for diabetes) following CR. Conclusions These findings suggest that clinical predictors of VO 2 peak improvement and odds of MACEs following CR are sex specific.

Background Cardiac rehabilitation (CR) is a comprehensive secondary cardiovascular disease program with structured lifestyle interventions to reduce morbidity and mortality. The American Heart Association cardiovascular health (CVH) framework measures health‐promoting behaviors and clinical factors, but it has not been rigorously evaluated in the CR setting. Methods This retrospective cohort study analyzed patients attending CR from January 2018 to September 2020. Patients were evaluated at baseline (pre‐CR) and completion (post‐CR) using 3 clinical factors (blood pressure, cholesterol, and hemoglobin A1c) and 4 health behaviors (smoking, body mass index, physical activity, and diet). CVH score was computed as a composite of each Life's Simple 7 component by assigning 0 points for poor, 1 point for intermediate, or 2 points for ideal (range 0–14 points). CVH scores were further categorized as poor (0–6 points), intermediate (7–8 points), and ideal (9–14 points). Missing data in the analysis were accounted for using a multiple imputation procedure. Results Patients (N=937) were aged 64.0±13.4 years old, 34% women, and attended 11±12 CR sessions. Pre‐CR, 97.2% had poor CVH scores, 2.8% had intermediate scores, and none met ideal CVH criteria. Post‐CR, there was a reduction in poor scores across all metrics except for hemoglobin A1c, which increased (40.6%–43.5%). Younger patients showed improvement in hemoglobin A1c, while older patients improved in body mass index and blood pressure. Conclusions Our study demonstrates the efficacy of CR in improving CVH but underscores the need for better blood glucose management. Tailored interventions based on age and sex may further optimize outcomes for CR participants.

This cohort study examines changes in oxygen consumption among patients with multiple morbidities undergoing cardiac rehabilitation.

Background: Cardiac rehabilitation (CR) patients demonstrate a high burden of chronic conditions (CC). Both multimorbidity (MM; ≥2 coexisting CC) and aging negatively impact functional capacity, whereas CR improves performance. Age-related difference in cardiorespiratory fitness (CRF, peak oxygen uptake (VO 2 )) in CR patients with MM has not been studied. Hypothesis: We hypothesized improvement in CRF will be attenuated by MM with increasing age in CR patients. Aims: We aimed to identify age-related differences in CRF improvement in CR patients with MM. Methods: Patients ≥18 yrs old who attended ≥1 CR sessions from 1999-2017 and completed cardiopulmonary exercise stress test before and after CR were included. The prevalence of CC was assessed using Rochester Epidemiology Project records-linkage system. Age categories included: Younger (18-49 yrs), Midlife (50-64 yrs) and Older (≥65 yrs). CRF categories included: <0%, 0-8% and >8%. Analysis included Kruskal-Wallis and Chi-squared. Results: Of 622 patients, 75.4% were male. Mean age: 62.9±11.2 yrs; Younger (n=70) age: 42.7±6.8 yrs, 67.1% male; Midlife (n=283) age: 58.3±4.3 yrs, 78.8% male; Older (n=269) age: 73.0±5.2 yrs, 74.0% male. BMI was 29.9±5.4 kg/m 2 (Younger: 30.0±6.7, Midlife: 30.4±5.6, Older: 29.3±4.7; p<.05). Median (Q1, Q3) no. of CR sessions attended was 33(22, 35), with lower attendance in the Younger group: 25(16,34) vs Midlife: 33(20,35) and Older: 34 (29,35), p<.05. Overall, percent change in peak VO 2 was 11.5±21.6% (Younger: 18.8±22.8%, Midlife: 11.6±19.5%, Older: 9.4±23.1%; p<.01). The median number of CC was 7(5,8) with significant differences across groups: Younger: 5(3,7), Midlife: 6(5,8), Older: 7(6,9), p<.01. Number of CC increased with age across all CRF categories (p<.01, Fig. 1). However, there was no difference in number of CC within age groups across categories of CRF, Table 1. Conclusions: Our results suggest that MM increases with age in patients attending CR; however, within a given age group, improvement in CRF does not appear dependent on MM. The impact of age appears to have a greater impact than MM on CRF improvement. Individualized treatment plans should focus on the impact of age-related disparities on CRF improvement among CR patients with MM.

Introduction: LMNA encodes the nuclear envelope proteins lamin A/C that are involved in ageing processes. Mutations in LMNA cause a spectrum of phenotypes which include muscular dystrophy, arrhythmogenic dilated cardiomyopathy, peripheral neuropathy, progeroid syndrome and overlap syndrome. Early diagnosis is crucial to prevent sudden cardiac death. We hypothesized that LMNA mutations result in an ECG biological age older than chronological age. Methods: In this study, we used AI-enabled ECG network to investigate standard digital 12-lead ECGs in genetically characterized LMNA patients. Results: We identified 33 LMNA patients with 331, 12-lead ECG available for analysis. Median age at symptoms onset was 23.5 (range: <1 to 61 years;15 females). Mean follow up time was 86 months (range: <1 to 367 months). Symptoms at onset included muscle weakness (n=10) or cardiac symptoms (n=18) and asymptomatic (n=5). We included a total of 1532 age sex matched controls. We found significant differences in positive age-gap (biologically older than chronological age) comparing LMNA patients (median of 17.5) versus controls (4.9 years; p<0.001, Figure 1 ). AI-ECG age with 10 years or higher age-gap was observed in 73% of LMNA patients compared to 27% in the controls (p<0.001). Consecutive serial analysis for all ECG’s in the study versus predicted age showed faster aging when comparing the rates of age-gap overtime in the LMNA group compared to controls (p<0.0001, Figure 2 ). Moreover, the subset analysis of 23 ECG in the 5 asymptomatic patients versus controls also showed significantly higher AI-ECG age-gap (p=0.004) Conclusions: An AI-ECG algorithm to detect biological age effectively demonstrates accelerated aging in patients with LMNA mutations related to physiological aging. Our findings further validate the role of AI-ECG to detect accelerated aging, expanding previous studies demonstrating higher mortality among individuals with in increased positive age-gap.

Background: Life's Simple 7 (LS7) have been identified as key health factors aimed at achieving ideal cardiovascular health (CVH) and improving healthy life expectancy; however, it is unclear if different patient populations respond similarly to optimization of health behaviors. We sought to quantify the contribution of sex and age differences to changes in LS7 components in patients participating in cardiac rehabilitation. Methods: We included 937 adult patients who participated in CR from January 2018 to September 2020. LS7 metrics at baseline (pre-CR) and completion of CR (post-CR) were collected and changes in LS7 components (body mass index (BMI), diet, smoking, physical activity (PA), blood pressure (PB), cholesterol, glucose) were assessed by sex and age groups (<65 vs ≥65 years old). Each LS7 component was assigned 0 (poor), 1 (intermediate), or 2 (ideal) points and a final score was computed to estimate an individual’s level of CVH (0-14 pts): 0-6 = poor, 7-8= intermediate, 9 -14= ideal. Results: The mean age was 64±13 years, and 34% were female. Patients attended a mean of 11.1±12.5 CR sessions. LS7 components with the highest proportion within the poor category were HbA1c (41%) and BMI (50%) at the time of CR enrollment; neither women nor men showed improvement on either component. The trend towards improvement from poor to intermediate range on cholesterol and BP metrics was seen only in older patients (Table 1). Mean LS7 score improvement was greater in the older group, P=.01 (Fig 1). Both women and men equally improved LS7 scores (Table 2, Fig 2). Conclusions: Patients participating in CR demonstrated improvement in overall LS7 scores regardless of sex and age. However, age disparities exist in LS7 metrics, with exacerbated differences noted by a lack of improvement in LS7 components such as BP and cholesterol in younger patients. Our insights provide opportunities to explore equitable CVH.

Introduction: The Community Practice Center (CPC) in North Philadelphia serves a community with significant socioeconomic barriers leading to inability to access care necessary for management of hypertension (HTN). Prior studies have shown the efficacy of SMBP programs in improving blood pressure (BP) control. Methods: All sequential patients presenting to the CPC with stage 2 HTN were screened for eligibility. Upon enrollment, patients received a Bluetooth-enabled BP cuff connected to a mobile health app and HTN education. Patients completed validated social and behavioral assessments including social determinants of health (SD)H) assessment via WellRx screen, depression screening (PHQ-9), and self-efficacy screening ( Self-Efficacy to Manage Chronic Disease Scale ). A behavior change plan was created using Brief Problem Solving Therapy based on the aforementioned assessments. Staff continuously monitored usage, BP, and provided individualized interventions. We conducted a cross-sectional quality improvement study using daily BP data from June 2022 - April 2023 to assess the correlation between baseline sociodemographic characteristics and Time in Target Range (TTR) through multivariable linear regression. We calculated TTR, defined as the percentage of time with systolic BP within 100-130 mmHg, through linear interpolation. Results: A total of 133 patients were enrolled in the program. We analyzed data from 78 patients with ≥3 days of readings (average 33; SD 49) and complete baseline characteristics (Table 1). Female sex and non-smoking status were associated with TTR, while diabetes, positive depression screening, positive SDOH screening, and self-efficacy were not (Table 2). Conclusions: In a socioeconomically disadvantaged population participating in a comprehensive SMBP program, depression, SDOH, and self-efficacy screening at time of enrollment did not predict TTR. Participation in a SMBP program may be valuable in these populations.

Background: Meta-analyses have shown the success of SMBP in BP control. We aim to describe an SMBP QI program at our primary care clinic and assess its impact on BP. The Einstein CPC is a safety net practice that serves a socially and economically disadvantaged population facing many HTN management barriers. Methods: This program utilized a QI approach for BP control and patient-provider connection. Patient demographics, clinical features, and SDOH were assessed at baseline. Patients with uncontrolled HTN (SBP >140 mmHg) were asked to participate. To date, 111 patients enrolled. Patients were given a Bluetooth-enabled BP monitor connected to a mobile health app, HTN education, DASH diet recommendations, and orientation to SMBP protocols. Those reporting social needs or depression were referred to behavioral resources. Health staff continuously telemonitored patient usage, BP, and individualized interventions. We evaluated the difference in BP from baseline BP and estimated the change in time using a linear multilevel model with random intercept and random slope for each patient. We also calculated time in target range defined as time in SBP 100-130 and DBP 70-80 in mmHg. Results: Patient characteristics (Table 1). Those with at least 3 d of BP readings - 93% (103/111) were included in the BP analysis (Figure 1); mean follow-up 69±67 d and BP readings 42±52. Over 90 d, SBP, and DBP decreased by 11 (95% CI: 4-17) and 5 (95% CI: 3-8) mmHg, respectively. Conclusions: A QI-based SMBP program with robust telemonitoring and individualized interventions may effectively promote short-term adherence to remote BP monitoring and BP control in a socially and economically disadvantaged population.

Background: The body Mass Index (BMI) is commonly used in clinical practice to screen for obesity and resulting cardiometabolic conditions. Nonetheless, BMI has limited utility as it cannot differentiate body fat (BF). Hypothesis: We tested the hypothesis that BF content measured by air displacement plethysmography (Bod-Pod®) had a stronger association with prevalent hypertension (HTN), diabetes mellitus (DM) and dyslipidemia (DLP) when compared to BMI. Methods: We performed a community-based cross-sectional study on adults attending an employee wellness center from January 2007-December 2011 who had had a body composition assessment with Bod-Pod®. We excluded subjects with history of myocardial infarction, coronary artery disease, congestive heart failure, stroke at baseline. The prevalence of HTN, DM and DLP was assessed across quartiles of BF% and BMI categories. Their association with BF% and BMI was evaluated using linear regression models that adjusted for age, sex, and white race. Results: We included 3,052 individuals; 68 % were women, and the mean age ± SD was 42.09±12.8, BMI was 27.9±6.2; BF% 31.88±10.69, 892 (29.2%) were obese by BMI. Cardiometabolic conditions were prevalent in 496 (16.2%) with HTN, 378 (12.4%) with DM and 743 (24.4%) with DLP. While the prevalence of DM, HTN and DLP increased across BF% quartiles (all p for linearity>0.01), this was not always the case across BMI categories (p for linearity<0.05 for HTN and DLP, and 0.04 for DM) see Figure A . Elevated BF %, better identified individuals with HTN (AUC 0.766 vs 0.625; p<0.001), DM (AUC 0.643 vs. 0.568; p<0.001), DLP (AUC 0.758 vs. 0.593; p<0.001). Conclusion: BF content is better associated with a higher prevalence of HTN, DM, and DLP. Highlighting the role of body composition assessment in primary prevention. Dyslipidemia.

Introduction: Arrhythmias commonly occur during clinical exercise stress testing (EST), however there are limited data on prognostic significance, particularly differences between individuals with minor versus significant arrhythmia burden. Hypothesis: We hypothesized that significant but not minor arrhythmia burden during EST would be predictive of future all-cause mortality. Methods: Adults who underwent clinically indicated EST at Mayo Clinic Rochester between September 1993 and April 2017 were included and followed-up until March 2021 using the National Death Index to ascertain survival status. Expert clinician coding pertaining to arrhythmia burden during EST were used to group individuals (see Table 1 ). Cox proportional hazard models adjusted for known predictors of exercise-induced arrhythmias, were used to test the association of arrhythmia burden with all-cause mortality. Results: A total of 30796 individuals were included (age: 55±14yrs; female: 36%; Table 1 ). Mean follow-up was 8.8±3.6yrs, with a total of 2516 deaths. Arrhythmia during EST was associated with all-cause mortality compared with no arrhythmia (HR: 1.72; 95% CI: 1.58-1.88; p<0.001), however significant arrhythmia showed greater association compared with minor arrhythmia (HR: 2.07; 95% CI: 1.81-2.38; p<0.001). Both minor and significant arrhythmia during EST were significant predictors of all-cause mortality compared with no arrhythmia ( Figure, Table 2 ), however, after model adjustments, only significant arrhythmia was associated with all-cause mortality (HR: 1.40; 95% CI: 1.21-1.63; p<0.001) ( Table 2 ). Conclusions: After multivariate adjustment, significant arrhythmia burden during EST showed a 40% increased future risk of all-cause mortality, Conversely, adjusting for age and sex attenuated the effect of minor arrhythmia burden during EST on incidence of death. These results highlight the clinical significance of arrhythmia burden during exercise testing.