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Aims: To test whether an index based on the combination of demographics and body volumes obtained with a multisensor 3D body volume (3D-BV) scanner and biplane imaging using a mobile application (myBVI®) will reliably predict the severity and presence of metabolic syndrome (MS)., Methods and Results: We enrolled 1280 consecutive subjects who completed study protocol measurements, including 3D-BV and myBVI®. Body volumes and demographics were screened using the least absolute shrinkage and selection operator to select features associated with an MS severity score and prevalence. We randomly selected 80% of the subjects to train the models, and performance was assessed in 20% of the remaining observations and externally validated on 133 volunteers who prospectively underwent myBVI® measurements. The mean ± SD age was 43.7 ± 12.2 years, 63.7% were women, body mass index (BMI) was 28.2 ± 6.2 kg/m 2 , and 30.2% had MS and an MS severity z -score of -0.2 ± 0.9. Features β coefficients equal to zero were removed from the model, and 14 were included in the final model and used to calculate the body volume index (BVI), demonstrating an area under the receiving operating curve (AUC) of 0.83 in the validation set. The myBVI® cohort had a mean age of 33 ± 10.3 years, 61% of whom were women, 10.5% MS, an average MS severity z -score of -0.8, and an AUC of 0.88., Conclusion: The described BVI model was associated with an increased severity and prevalence of MS compared with BMI and waist-to-hip ratio. Validation of the BVI had excellent performance when using myBVI®. This model could serve as a powerful screening tool for identifying MS., Competing Interests: Conflict of interest: Select Research (Worcester, UK), the company that designed the multisensor 3D-BV scanning system technology, provided the scanner used for this and other studies at Mayo Clinic and has a licence agreement over 3D-BV measurement technology. Mayo Clinic and authors J.R.M.-I., and F.L.-J. may receive financial benefits from this technology, but at no point will Mayo Clinic benefit financially from its use for the care of patients at the clinic. All other authors declare no conflict of interest., (© The Author(s) 2024. Published by Oxford University Press on behalf of the European Society of Cardiology.)

Artificial intelligence-enhanced identification of organs, lesions, and other structures in medical imaging is typically done using convolutional neural networks (CNNs) designed to make voxel-accurate segmentations of the region of interest. However, the labels required to train these CNNs are time-consuming to generate and require attention from subject matter experts to ensure quality. For tasks where voxel-level precision is not required, object detection models offer a viable alternative that can reduce annotation effort. Despite this potential application, there are few options for general-purpose object detection frameworks available for 3-D medical imaging. We report on MedYOLO, a 3-D object detection framework using the one-shot detection method of the YOLO family of models and designed for use with medical imaging. We tested this model on four different datasets: BRaTS, LIDC, an abdominal organ Computed tomography (CT) dataset, and an ECG-gated heart CT dataset. We found our models achieve high performance on a diverse range of structures even without hyperparameter tuning, reaching mean average precision (mAP) at intersection over union (IoU) 0.5 of 0.861 on BRaTS, 0.715 on the abdominal CT dataset, and 0.995 on the heart CT dataset. However, the models struggle with some structures, failing to converge on LIDC resulting in a mAP@0.5 of 0.0., (© 2024. The Author(s) under exclusive licence to Society for Imaging Informatics in Medicine.)

Background: Extended sedentary behavior is a risk factor for chronic disease and mortality, even among those who exercise regularly. Given the time constraints of incorporating physical activity into daily schedules, and the high likelihood of sitting during office work, this environment may serve as a potentially feasible setting for interventions to reduce sedentary behavior., Methods and Results: A randomized cross-over clinical trial was conducted at an employee wellness center. Four office settings were evaluated on 4 consecutive days: stationary or sitting station on day 1 (referent), and 3 subsequent active workstations (standing, walking, or stepper) in randomized order. Neurocognitive function (Selective Attention, Grammatical Reasoning, Odd One Out, Object Reasoning, Visuospatial Intelligence, Limited-Hold Memory, Paired Associates Learning, and Digit Span) and fine motor skills (typing speed and accuracy) were tested using validated tools. Average scores were compared among stations using linear regression with generalized estimating equations to adjust standard errors. Bonferroni method adjusted for multiple comparisons. Healthy subjects were enrolled (n=44), 28 (64%) women, mean±SD age 35±11 years, weight 75.5±17.1 kg, height 168.5±10.0 cm, and body mass index 26.5±5.2 kg/m 2 . When comparing active stations to sitting, neurocognitive test either improved or remained unchanged, while typing speed decreased without affecting typing errors. Overall results improved after day 1, suggesting habituation. We observed no major differences across active stations, except decrease in average typing speed 42.5 versus 39.7 words per minute with standing versus stepping ( P =0.003)., Conclusions: Active workstations improved cognitive performance, suggesting that these workstations can help decrease sedentary time without work performance impairment., Registration: URL: https://www.clinicaltrials.gov; Unique identifier: NCT06240286.

Background: Loneliness and social isolation are associated with poor health outcomes such as an increased risk of cardiovascular diseases., Objectives: The authors aimed to explore the association between social isolation with biological aging which was determined by artificial intelligence-enabled electrocardiography (AI-ECG) as well as the risk of all-cause mortality., Methods: The study included adults aged ≥18 years seen at Mayo Clinic from 2019 to 2022 who respond to a survey for social isolation assessment and had a 12-lead ECG within 1 year of completing the questionnaire. Biological age was determined from ECGs using a previously developed and validated convolutional neural network (AI-ECG age). Age-Gap was defined as AI-ECG age minus chronological age, where positive values reflect an older-than-expected age. The status of social isolation was measured by the previously validated multiple-choice questions based on Social Network Index (SNI) with score ranges between 0 (most isolated) and 4 (least isolated)., Results: A total of 280,324 subjects were included (chronological age 59.8 ± 16.4 years, 50.9% female). The mean Age-Gap was -0.2 ± 9.16 years. A higher SNI was associated with a lower Age-Gap (β of SNI = 4 was -0.11; 95% CI: -0.22 to -0.01; P  < 0.001, adjusted to covariates). Cox proportional hazard analysis revealed the association between social connection and all-cause mortality (HR for SNI = 4, 0.47; 95% CI: 0.43-0.5; P  < 0.001)., Conclusions: Social isolation is associated with accelerating biological aging and all-cause mortality independent of conventional cardiovascular risk factors. This observation underscores the need to address social connection as a health care determinant., Competing Interests: Drs Friedman, Lopez-Jimenez, and Attia are coinvestigators of the AI-ECG age algorithm, which has been licensed to Alumana, Mayo Clinic. All other authors have reported that they have no relationships relevant to the contents of this paper to disclose., (© 2024 The Authors.)

Clinical guidelines recommend influenza vaccination for cardiac patients, and COVID-19 vaccination is also beneficial given their increased risk. Patient education regarding vaccination was developed for cardiac rehabilitation (CR); impact on knowledge and attitudes were evaluated. A single-group pre-post design was applied at a Spanish CR program in early 2022. After baseline assessment, a nurse delivered the 40-minute group education. Knowledge and attitudes were re-assessed. Sixty-one (72%) of the 85 participants were vaccinated for influenza, and 40 (47%) for pneumococcus. Most participants perceived vaccines were important, and that the COVID-19 vaccine specifically was important, with three-quarters not influenced by vaccine myths/misinformation. The education intervention resulted in significant improvements in perceptions of the importance of vaccines (Hake's index 69%), understanding of myths (48%), knowledge of the different types of COVID vaccines (92%), and when they should be vaccinated. Vaccination rates are low despite their importance; while further research is needed, education in the CR setting could promote greater uptake., Competing Interests: The authors have declared that no competing interests exist., (Copyright: © 2024 Solera et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)

Background: Although several studies have documented the impact of the COVID-19 pandemic on mental health, the long-term effects remain unclear., Aims: To examine longitudinal changes in mental health before and during the consecutive COVID-19 waves in a well-established probability sample., Method: An online survey was completed by the participants of the COVID-19 add-on study at four time points: pre-COVID-19 period (2014-2015, n = 1823), first COVID-19 wave (April to May 2020, n = 788), second COVID-19 wave (August to October 2020, n = 532) and third COVID-19 wave (March to April 2021, n = 383). Data were collected via a set of validated instruments, and analysed with latent growth models., Results: During the pandemic, we observed a significant increase in stress levels (standardised β = 0.473, P < 0.001) and depressive symptoms (standardised β = 1.284, P < 0.001). The rate of increase in depressive symptoms (std. covariance = 0.784, P = 0.014), but not in stress levels (std. covariance = 0.057, P = 0.743), was associated with the pre-pandemic mental health status of the participants. Further analysis showed that secondary stressors played a predominant role in the increase in mental health difficulties. The main secondary stressors were loneliness, negative emotionality associated with the perception of COVID-19 disease, lack of resilience, female gender and younger age., Conclusions: The surge in stress levels and depressive symptoms persisted across all three consecutive COVID-19 waves. This persistence is attributable to the effects of secondary stressors, and particularly to the status of mental health before the COVID-19 pandemic. Our findings reveal mechanisms underlying the surge in mental health difficulties during the COVID-19 waves, with direct implications for strategies promoting mental health during pandemics.

Background: Atherosclerotic cardiovascular disease (ASCVD) is the leading cause of death worldwide, driven primarily by coronary artery disease (CAD). ASCVD risk estimators such as the pooled cohort equations (PCE) facilitate risk stratification and primary prevention of ASCVD but their accuracy is still suboptimal., Methods: Using deep electronic health record data from 7,116,209 patients seen at 70+ hospitals and clinics across 5 states in the USA, we developed an artificial intelligence-based electrocardiogram analysis tool (ECG-AI) to detect CAD and assessed the additive value of ECG-AI-based ASCVD risk stratification to the PCE. We created independent ECG-AI models using separate neural networks including subjects without known history of ASCVD, to identify coronary artery calcium (CAC) score ≥300 Agatston units by computed tomography, obstructive CAD by angiography or procedural intervention, and regional left ventricular akinesis in ≥1 segment by echocardiogram, as a reflection of possible prior myocardial infarction (MI). These were used to assess the utility of ECG-AI-based ASCVD risk stratification in a retrospective observational study consisting of patients with PCE scores and no prior ASCVD. The study period covered all available digitized EHR data, with the first available ECG in 1987 and the last in February 2023., Findings: ECG-AI for identifying CAC ≥300, obstructive CAD, and regional akinesis achieved area under the receiver operating characteristic (AUROC) values of 0.88, 0.85, and 0.94, respectively. An ensembled ECG-AI identified 3, 5, and 10-year risk for acute coronary events and mortality independently and additively to PCE. Hazard ratios for acute coronary events over 3-years in patients without ASCVD that tested positive on 1, 2, or 3 versus 0 disease-specific ECG-AI models at cohort entry were 2.41 (2.14-2.71), 4.23 (3.74-4.78), and 11.75 (10.2-13.52), respectively. Similar stratification was observed in cohorts stratified by PCE or age., Interpretation: ECG-AI has potential to address unmet need for accessible risk stratification in patients in whom PCE under, over, or insufficiently estimates ASCVD risk, and in whom risk assessment over time periods shorter than 10 years is desired., Funding: Anumana., Competing Interests: SA, NS, RA, YG, AGA, SA, SB, SS, LH, NV, HA, MB, RB, and VS were employees of nference, inc. and/or Anumana, inc. at the time the work was conducted and held vested or unvested stock. MS is an employee and stockholder of Novartis Pharmaceuticals Corporation. PAF, ZIA, and FLJ are advisors to Anumana. In conjunction with Mayo Clinic, PAF, ZIA, FLJ, and JMRI have filed patents related to the application of AI to the ECG for diagnosis and risk stratification., (© 2023 Mayo Clinic Foundation.)

Background: The performance of the American College of Cardiology/American Heart Association pooled cohort equation (PCE) for atherosclerotic cardiovascular disease (ASCVD) in real-world clinical practice has not been evaluated extensively., Objectives: The goal of this study was to test the performance of PCE to predict ASCVD risk in the community, and determine if including individuals with values outside the PCE range (ie, age, blood pressure, cholesterol) or statin therapy initiation over follow-up would significantly affect PCE predictive capabilities., Methods: The PCE was validated in a community-based cohort of consecutive patients who sought primary care in Olmsted County, Minnesota, between 1997 and 2000, followed-up through 2016. Inclusion criteria were similar to those of PCE derivation. Patient information was ascertained by using the record linkage system of the Rochester Epidemiology Project. ASCVD events (nonfatal and fatal myocardial infarction and ischemic stroke) were validated in duplicate. Calculated and observed ASCVD risk and c-statistics were compared across predefined groups., Results: This study included 30,042 adults, with a mean age of 48.5 ± 12.2 years; 46% were male. Median follow-up was 16.5 years, truncated at 10 years for this analysis. Mean ASCVD risk was 5.6% ± 8.73%. There were 1,555 ASCVD events (5.2%). The PCE revealed good performance overall (c-statistic 0.78) and in sex and race subgroups; it was highest among non-White female subjects (c-statistic 0.81) and lowest in White male subjects (c-statistic 0.77). Out-of-range values and initiation of statin medication did not affect model performance., Conclusions: The PCE performed well in a community cohort representing real-world clinical practice. Values outside PCE ranges and initiation of statin medication did not affect performance. These results have implications for the applicability of current strategies for the prevention of ASCVD., Competing Interests: Funding Support and Author Disclosures This study used the resources of the Rochester Epidemiology Project (REP) medical records linkage system, which is supported by the National Institute on Aging (AG 058738), by the Mayo Clinic Research Committee, and by fees paid annually by REP users. Dr Somers is supported by the Mayo Foundation Alice Sheets Marriott Professorship. The content of this paper is solely the responsibility of the authors and does not represent the views of the funding sources. The authors have reported that they have no relationships relevant to the contents of this paper to disclose., (Copyright © 2023 American College of Cardiology Foundation. Published by Elsevier Inc. All rights reserved.)

Objective: To demonstrate early aging in patients with lamin A/C (LMNA) gene mutations after hypothesizing that they have a biological age older than chronological age, as such a finding impacts care., Patient and Methods: We applied a previously trained convolutional neural network model to predict biological age by electrocardiogram (ECG) [Artificial Intelligence (AI)-ECG age] to LMNA patients evaluated by multiple ECGs from January 1, 2003, to December 31, 2019. The age gap was the difference between chronological age and AI-ECG age. Findings were compared with age-/sex-matched controls., Results: Thirty-one LMNA patients who had a total of 271 ECGs were studied. The median age at symptom onset was 22 years (range, <1-53 years; n=23 patients); eight patients were asymptomatic family members carrying the LMNA mutation. Cardiac involvement was detected by ECG and echocardiogram in 16 patients and consisted of ventricular arrhythmias (13), atrial fibrillation (12), and cardiomyopathy (6). Four patients required cardiac transplantation. Fourteen patients had neurological manifestations, mainly muscular dystrophy. LMNA mutation carriers, including asymptomatic carriers, were 16 years older by AI-ECG than non-LMNA carriers, suggesting accelerated biological age. Most LMNA patients had an age gap of more than 10 years, compared with controls (P<.001). Consecutive AI-ECG analysis showed accelerated aging in the LMNA group compared with controls (P<.0001). There were no significant differences in age-gap among LMNA patients based on phenotype., Conclusion: AI-ECG predicted that LMNA patients have a biological age older than chronological age and accelerated aging even in the absence of cardiac abnormalities by traditional methods. Such a finding could translate into early medical intervention and serve as a disease biomarker., (Copyright © 2022 Mayo Foundation for Medical Education and Research. Published by Elsevier Inc. All rights reserved.)

Background There is a scarcity of validated rapid dietary screening tools for patient use in the clinical setting to improve health and reduce cardiovascular risk. The Healthy Eating Index (HEI) 2015 measures compliance with the 2015 to 2020 Dietary Guidelines for Americans but requires completion of an extensive diet assessment to compute, which is time consuming and impractical. The authors hypothesize that a 19-item dietary survey assessing consumption of common food groups known to affect health will be correlated with the HEI-2015 assessed by a validated food frequency questionnaire and can be further reduced without affecting validity. Methods and Results A 19-item Eating Assessment Tool (EAT) of common food groups was created through literature review and expert consensus. A cross-sectional survey was then conducted in adult participants from a preventive cardiology clinic or cardiac rehabilitation and in healthy volunteers (n=661, mean age, 36 years; 76% women). Participants completed an online 156-item food frequency questionnaire, which was used to calculate the HEI score using standard methods. The association between each EAT question and HEI group was analyzed by Kruskal-Wallis test. Linear regression models were subsequently used to identify univariable and multivariable predictors for HEI score for further reduction in the number of items. The final 9-item model of Mini-EAT was validated by 5-fold cross validation. The 19-item EAT had a strong correlation with the HEI score ( r =0.73) and was subsequently reduced to the 9 items independently predictive of the HEI score: fruits, vegetables, whole grains, refined grains, fish or seafood, legumes/nuts/seeds, low-fat dairy, high-fat dairy, and sweets consumption, without affecting the predictive ability of the tool ( r =0.71). Conclusions Mini-EAT is a 9-item validated brief dietary screener that correlates well with a comprehensive food frequency questionnaire. Future studies to test the Mini-EAT's validity in diverse populations and for development of clinical decision support systems to capture changes over time are needed.

Objective: To characterize the utility of an existing electrocardiogram (ECG)-artificial intelligence (AI) algorithm of left ventricular dysfunction (LVD) in immune-mediated necrotizing myopathy (IMNM)., Patients and Methods: A retrospective cohort observational study was conducted within our tertiary-care neuromuscular clinic for patients with IMNM meeting European Neuromuscular Centre diagnostic criteria (January 1, 2000, to December 31, 2020). A validated AI algorithm using 12-lead standard ECGs to detect LVD was applied. The output was presented as a percent probability of LVD. Electrocardiograms before and while on immunotherapy were reviewed. The LVD-predicted probability scores were compared with echocardiograms, immunotherapy treatment response, and mortality., Results: The ECG-AI algorithm had acceptable accuracy in LVD prediction in 74% (68 of 89) of patients with IMNM with available echocardiograms (discrimination threshold, 0.74; 95% CI, 0.6-0.87). This translates into a sensitivity of 80.0% and specificity of 62.8% to detect LVD. Best cutoff probability prediction was 7 times more likely to have LVD (odds ratio, 6.75; 95% CI, 2.11-21.51; P =.001). Early detection occurred in 18% (16 of 89) of patients who initially had normal echocardiograms and were without cardiorespiratory symptoms, of which 6 subsequently advanced to LVD cardiorespiratory failure. The LVD probability scores improved for patients on immunotherapy (median slope, -3.96; R  = -0.12; P =.002). Mortality risk was 7 times greater with abnormal LVD probability scores (hazard ratio, 7.33; 95% CI, 1.63-32.88; P =.009)., Conclusion: In IMNM, an AI-ECG algorithm assists detection of LVD, enhancing the decision to advance to echocardiogram testing, while also informing on mortality risk, which is important in the decision of immunotherapy escalation and monitoring., (© 2022 The Authors.)

Objective: To determine whether the number of cardiac rehabilitation (CR) sessions attended and selected clinical characteristics were predictive of patients who exhibited improvement in peak oxygen uptake (VO 2 peak) after CR., Patients and Methods: Using the Rochester Epidemiology Project records-linkage system, we identified all consecutive patients aged 18 years or older from Olmsted County, Minnesota, who underwent cardiopulmonary exercise testing before and after CR from 1999 to 2017. Regression models were created to assess the clinical predictors of VO 2 peak improvement (>0% baseline) after CR., Results: The analysis included 671 patients, of which 524 (78%) patients exhibited VO 2 peak improvement after CR. The significant univariate predictors of VO 2 peak improvement included younger age (odds ratio [OR], 0.98; 95% CI, 0.96-0.99), lower pre-CR VO 2 peak (OR, 0.96; 95% CI, 0.94-0.99), and no history of peripheral artery disease (OR, 0.50; 95% CI, 0.31-0.81) (all, P <.005). The significant independent predictors of VO 2 peak improvement from the multivariable analysis included the number of CR sessions (OR, 1.04; 95% CI, 1.02-1.05), younger age (OR, 0.96; 95% CI, 0.94-0.98), lower pre-CR VO 2 peak (OR, 0.92; 95% CI, 0.89-0.95), and no history of peripheral artery disease (OR, 0.47; 95% CI, 0.28-0.78) (all, P <.005)., Conclusion: These findings highlight the importance of patient participation in CR sessions and individual clinical characteristics in influencing VO 2 peak improvement after CR in patients with cardiovascular disease., (© 2022 The Authors.)

Background: Cardiac damage (CD) staging is associated with worse survival in aortic stenosis (AS). However, patients with bicuspid aortic valve (BAV) are less likely to develop CD than those with tricuspid aortic valve AS (TAV-AS). The aim of this study was to assess the prognostic value of multichamber strain (MCS) characterization, a sensitive measurement of subclinical CD, in patients with BAV- and TAV-AS., Methods: Offline two-dimensional echocardiographic strain analysis was performed in 209 consecutive patients with BAV and 369 patients with TAV with more than moderate AS (mean gradient, 47 ± 12 vs 47 ± 14 mm Hg, respectively; >90% severe AS), retrospectively identified from the echocardiography database. The extent of abnormal cardiac mechanics was characterized by the number of chambers with impaired longitudinal strain (left ventricle, left atrium, and right ventricle) as preserved or single-chamber, paired-chamber, or triple-chamber impaired strain. Cutoffs of strain parameters to define impaired versus preserved chamber function were 15% for the left ventricle, 24% for the left atrium, and 25% for the right ventricular free wall. CD was staged using a panel of comprehensive echocardiographic parameters. The primary outcome was all-cause death., Results: MCS (per chamber increase) modestly correlated with CD staging (per stage increase) in both groups (BAV, r = 0.36; TAV, r = 0.43). After a median follow-up period of 4.9 years (interquartile range, 2.2-4.6 years), 262 patients died (5-year survival 86.8 ± 2.4% [BAV-AS] vs 49.6 ± 2.7% [TAV-AS], P < .001). In multivariable analysis, MCS was strongly associated with all-cause death in BAV-AS and TAV-AS, separately, and independent of CD staging (P < .001 for both). MCS provided incremental prognostic value to CD staging in both BAV-AS and TAV-AS (P for χ 2 change < .001 for both) and improved risk classification of CD staging in TAV AS (continuous net reclassification index = 0.24, P = .02)., Conclusion: MCS characterization is a robust prognosticator in patients with greater than moderate AS and provides incremental prognostic value to CD staging in both BAV-AS and TAV-AS. Therefore, MCS characterization could represent an alternative or additive method to CD staging., (Copyright © 2022 American Society of Echocardiography. Published by Elsevier Inc. All rights reserved.)

Objective: Cardiovascular disease (CVD) continues to be the leading cause of mortality globally. Cardiac rehabilitation (CR) programs act by modifying the evolution of CVD and mortality; however, CR programs are under-used. The aim was to determine the profile of patients that received rehabilitation after cardiac surgery., Patients and Methods: A retrospective observational study was conducted from January 2017 to December 2017 at a single center. The study sample was chosen among patients admitted to the Intensive Care Unit of the Hospital Gregorio Marañón/Gregorio Marañón General University Hospital. Socio-demographic and clinical variables were collected., Results: In the present study, 336 patients underwent cardiac surgery of which 63.8% were men and 87.1% had ≥1 cardiovascular risk factors. Of the total cohort, 24.7% were operated for ischemic heart disease, 47.9% valvulopathy, 11% underwent combined surgery, 3.6% cardiac transplantation, 6.5% aneurysms, and 3.9% congenital disease. In-hospital respiratory rehabilitation was prescribed to all patients. Only 4.8% of the patients received motor rehabilitation and 13.8% were referred to CR. We found higher referral rates among patients with more cardiovascular risk factors, <65 years of age, and those undergoing coronary surgery and heart transplantation. Age, ischemic heart disease, and overweight were independent predictors of CR referral., Conclusion: The benefit of CR programs after cardiac surgery is widely described; however, the referral rate to CR remains low. It is crucial to optimize referral protocols for these patients., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2022 Gómez González, Supervia, Medina-Inojosa, Smith, López Blanco, Miranda Vivas, López-Jiménez and Arroyo-Riaño.)

Objective: We investigated age-related differences for peak oxygen uptake (peak VO 2 ) improvement with exercise training during cardiac rehabilitation (CR)., Patients and Methods: This was a retrospective cohort study of the Mayo Clinic Rochester CR program including adult patients who attended CR (≥1 session) for any eligible indication between 1999 and 2017 and who had a cardiopulmonary exercise test pre and post CR with VO 2 data (peak respiratory exchange ratio ≥1.0). Younger (20-49 yrs), midlife (50-64 yrs), and older adults (≥65 yrs) were compared using ANOVA for delta and percent change in peak VO 2 ; and percentage of peak VO 2 responders (>0% change)., Results: 708 patients (age: 60.8 ± 12.1 years; 24% female) met inclusion criteria. Delta and percent change in peak VO 2 was lower for older adults (1.6 ± 3.2 mL.kg.min -1 ; 12 ± 27%) compared with younger (3.7 ± 4.0 mL.kg.min -1 , p < 0.001; 23 ± 28%, p = 0.002) and midlife adults (2.8 ± 3.8 mL.kg.min -1 , p < 0.001; 17 ± 28%, p = 0.04). For midlife, delta change, but not percent change in peak VO 2 was significantly lower ( p = 0.02) compared with younger. Percentage of responders was only different between older and younger (72 vs. 86%; p = 0.008). Sensitivity analyses in non-surgical patients showed similar differences for delta change, and differences in percent change remained significant between older and younger adults (10 ± 20% vs. 16 ± 18%; p = 0.04)., Conclusions: In CR patients, older adults had lower improvement in cardiorespiratory fitness than younger and midlife adults. While excluding surgical patients reduced age-related differences, older adults still had lower cardiorespiratory fitness improvement during CR. These findings may have implications for individualizing CR programming in aging populations to reduce future cardiovascular risk., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2022 Taylor, Medina-Inojosa, Chacin-Suarez, Smith, Squires, Thomas, Johnson, Olson and Bonikowske.)

Objective: To provide updated reference standards for cardiorespiratory fitness (CRF) for the United States derived from cardiopulmonary exercise (CPX) testing when using a treadmill or cycle ergometer., Patients and Methods: Thirty-four laboratories in the United States contributed data to the Fitness Registry and the Importance of Exercise National Database. Analysis included 22,379 tests (16,278 treadmill and 6101 cycle ergometer) conducted between January 1, 1968, through March 31, 2021, from apparently healthy adults (aged 20 to 89 years). Percentiles of peak oxygen consumption for men and women were determined for each decade from 20 through 89 years of age for treadmill and cycle exercise modes, as well as when defining maximal effort as respiratory exchange ratio (RER) greater than or equal to 1.0 or RER greater than or equal to 1.1., Results: For both men and women, the 50 th percentile scores for each exercise mode decreased with age and were higher in men across all age groups and higher for treadmill compared with cycle CPX. The average rate of decline per decade over a 6-decade period was 13.5%, 4.0 mLO 2 ·kg -1 ·min -1 for treadmill CPX and 16.4%, 4.3 mLO 2 ·kg -1 ·min -1 for cycle CPX. Observationally, the mean peak oxygen consumption was similar whether using an RER criterion of greater than or equal to 1.0 or greater than or equal to 1.1 across the different test modes, ages, and for both sexes. The updated reference standards for treadmill CPX were 1.5 - 4.6 mLO 2 ·kg -1 ·min -1 lower compared with the previous 2015 standards whereas the updated cycling standards were generally comparable to the original 2017 standards., Conclusion: These updated cardiorespiratory fitness reference standards improve the representativeness of the US population compared with the original standards., (Copyright © 2021 The Authors. Published by Elsevier Inc. All rights reserved.)

Objective: This study aimed to assess the association of bipolar disorder (BD) with risk of major adverse cardiac events (MACEs) after adjusting for established cardiovascular disease (CVD) risk factors., Methods: We conducted a population-based historical cohort study using the Rochester Epidemiology Project. Patients older than 30 years with a clinical encounter from 1998 to 2000 with no prior MACE, atrial fibrillation, or heart failure were followed up through March 1, 2016. BD diagnosis was validated by chart review. Cox proportional hazards regression models were adjusted for established CVD risk factors, alcohol use disorder, other substance use disorders (SUDs), and major depressive disorder (MDD)., Results: The cohort included 288 individuals with BD (0.81%) and 35,326 individuals without BD as the reference group (Ref). Median (interquartile range) follow-up was 16.5 (14.6-17.5) years. A total of 5636 MACE events occurred (BD, 59; Ref, 5577). Survival analysis showed an association between BD and MACE (median event-free-survival rates: BD, 0.80; Ref, 0.86; log-rank p = .018). Multivariate regression adjusting for age and sex also yielded an association between BD and MACE (hazard ratio [HR] = 1.93; 95% confidence interval [CI] = 1.43-2.52; p < .001). The association remained significant after further adjusting for smoking, diabetes mellitus, hypertension, high-density lipoprotein cholesterol, and body mass index (HR = 1.66; 95% CI = 1.17-2.28; p = .006), and for alcohol use disorder, SUD, and MDD (HR = 1.56; 95% CI = 1.09-2.14; p = .010)., Conclusions: In this study, BD was associated with an increased risk of MACE, which persisted after adjusting for established CVD risk factors, SUDs, and MDD. These results suggest that BD is an independent risk factor for major clinical cardiac disease outcomes., (Copyright © 2021 by the American Psychosomatic Society.)

We here posit that measurements of midlife cognition can be instructive in understanding cognitive disorders. Even though molecular events signal possible onset of cognitive disorders decades prior to their clinical diagnoses, cognition and its possible early changes in midlife remain poorly understood. We characterize midlife cognition in a cognitively healthy population-based sample using the Cogstate Brief Battery and test for associations with cardiovascular, adiposity-related, lifestyle-associated, and psychosocial variables. Learning and working memory showed significant variability and vulnerability to psychosocial influences in midlife. Furthermore, midlife aging significantly and progressively increased prevalence of suboptimal cognitive performance. Our findings suggest that physiological changes in cognition, measured with simple tests suitable for use in everyday clinical setting, may signal already in midlife the first clinical manifestations of the presymptomatic biologically defined cognitive disorders. This pilot study calls for longitudinal studies investigating midlife cognition to identify clinical correlates of biologically defined cognitive disorders., Competing Interests: The authors report no conflicts of interest., (© 2021 The Authors. Alzheimer's & Dementia: Diagnosis, Assessment & Disease Monitoring published by Wiley Periodicals, LLC on behalf of Alzheimer's Association.)

Objective: To assess whether an electrocardiography-based artificial intelligence (AI) algorithm developed to detect severe ventricular dysfunction (left ventricular ejection fraction [LVEF] of 35% or below) independently predicts long-term mortality after cardiac surgery among patients without severe ventricular dysfunction (LVEF>35%)., Methods: Patients who underwent valve or coronary bypass surgery at Mayo Clinic (1993-2019) and had documented LVEF above 35% on baseline electrocardiography were included. We compared patients with an abnormal vs a normal AI-enhanced electrocardiogram (AI-ECG) screen for LVEF of 35% or below on preoperative electrocardiography. The primary end point was all-cause mortality., Results: A total of 20,627 patients were included, of whom 17,125 (83.0%) had a normal AI-ECG screen and 3502 (17.0%) had an abnormal AI-ECG screen. Patients with an abnormal AI-ECG screen were older and had more comorbidities. Probability of survival at 5 and 10 years was 86.2% and 68.2% in patients with a normal AI-ECG screen vs 71.4% and 45.1% in those with an abnormal screen (log-rank, P<.01). In the multivariate Cox survival analysis, the abnormal AI-ECG screen was independently associated with a higher all-cause mortality overall (hazard ratio [HR], 1.31; 95% CI, 1.24 to 1.37) and in subgroups of isolated valve surgery (HR, 1.30; 95% CI, 1.18 to 1.42), isolated coronary artery bypass grafting (HR, 1.29; 95% CI, 1.20 to 1.39), and combined coronary artery bypass grafting and valve surgery (HR, 1.19; 95% CI, 1.08 to 1.32). In a subgroup analysis, the association between abnormal AI-ECG screen and mortality was consistent in patients with LVEF of 35% to 55% and among those with LVEF above 55%., Conclusion: A novel electrocardiography-based AI algorithm that predicts severe ventricular dysfunction can predict long-term mortality among patients with LVEF above 35% undergoing valve and/or coronary bypass surgery., (Copyright © 2021 Mayo Foundation for Medical Education and Research. Published by Elsevier Inc. All rights reserved.)

Ideal cardiovascular health (CVH) is defined for the presence of ideal behavioral and health metrics known to prevent cardiovascular disease (CVD). The association of circulatory phospho- and sphingo-lipids to primary reduction in cardiovascular risk is unclear. Our aim was to determine the association of CVH metrics with the circulating lipid profile of a population-based cohort. Serum sphingolipid and phospholipid species were extracted from 461 patients of the randomly selected prospective Kardiovize study based on Brno, Czech Republic. Lipids species were measured by a hyphenated mass spectrometry technique, and were associated with poor CVH scores, as defined by the American Heart Association. Phosphatidylcholine (PC), phosphatidylethanolamine (PE), lysophosphatidylcholine (LPC), lysophosphatidylethanolamine (LPE) species were significantly lower in ideal and intermediate scores of health dietary metric, blood pressure, total cholesterol and blood fasting glucose compared to poor scores. Current smokers presented higher levels of PC, PE and LPE individual species compared to non-smokers. Ceramide (Cer) d18:1/14:0 was altered in poor blood pressure, total cholesterol and fasting blood glucose metrics. Poor cardiovascular health metric is associated with a specific phospho- and sphingolipid pattern. Circulatory lipid profiling is a potential biomarker to refine cardiovascular health status in primary prevention strategies.

Background There is wide variability in cardiac rehabilitation (CR) dose (ie, number of sessions) delivered, and no evidence-based recommendations regarding what dose to prescribe. We aimed to test what CR dose impacts major adverse cardiovascular events (MACEs). Methods and Results This is an historical cohort study of all patients who had coronary artery disease and who initiated supervised CR between 2002 and 2012 from a single major CR center. CR dose was defined as number of visits including exercise and patient education. Follow-up was performed using record linkage from the Rochester Epidemiology Project. MACEs included acute myocardial infarction, unstable angina, ventricular arrhythmias, stroke, revascularization, or all-cause mortality. Dose was analyzed in several ways, including tertiles, categories, and as a continuous variable. Cox models were adjusted for factors associated with dose and MACE. The cohort consisted of 2345 patients, who attended a mean of 12.5±11.1 of 36 prescribed sessions. After a mean follow-up of 6 years, 695 (29.65%) patients had a MACE, including 231 who died. CR dose was inversely associated with MACE (hazard ratio, 0.66 [95% CI]; 0.55-0.91) in those completing ≥20 sessions, when compared with those not exposed to formal exercise sessions (≤1 session; log-rank P =0.007). We did not find evidence of nonlinearity ( P ≥0.050), suggesting no minimal threshold nor ceiling. Each additional session was associated with a lower rate of MACE (fully adjusted hazard ratio, 0.98 [95% CI, 0.97-0.99]). Greater session frequency was also associated with lower MACE risk (fully adjusted hazard ratio, 0.74 [95% CI, 0.58-0.94]). Conclusions CR reduces MACEs, but the benefit appears to be linear, with greater risk reduction with higher doses, and no upper threshold.

Background: This study aimed to establish availability and characteristics of cardiac rehabilitation (CR) in Latin America and the Caribbean (LAC), where cardiovascular disease is highly prevalent., Methods: In this cross-sectional sub-analysis focusing on the 35 LAC countries, local cardiovascular societies identified CR programs globally. An online survey was administered to identified programs, assessing capacity and characteristics. CR need was computed relative to ischemic heart disease (IHD) incidence from the Global Burden of Disease study., Results: ≥1 CR program was identified in 24 LAC countries (68.5% availability; median = 3 programs/country). Data were collected in 20/24 countries (83.3%); 139/255 programs responded (54.5%), and compared to responses from 1082 programs in 111 countries. LAC density was 1 CR spot per 24 IHD patients/year (vs 18 globally). Greatest need was observed in Brazil, Dominican Republic and Mexico (all with >150,000 spots needed/year). In 62.8% (vs 37.2% globally P < .001) of CR programs, patients pay out-of-pocket for some or all of CR. CR teams were comprised of a mean of 5.0 ± 2.3 staff (vs 6.0 ± 2.8 globally; P < .001); Social workers, dietitians, kinesiologists, and nurses were significantly less common on CR teams than globally. Median number of core components offered was 8 (vs 9 globally; P < .001). Median dose of CR was 36 sessions (vs 24 globally; P < .001). Only 27 (20.9%) programs offered alternative CR models (vs 31.1% globally; P < .01)., Conclusion: In LAC countries, there is very limited CR capacity in relation to need. CR dose is high, but comprehensiveness low, which could be rectified with a more multidisciplinary team., (Copyright © 2021 Elsevier Inc. All rights reserved.)

Objective: To validate an artificial intelligence-augmented electrocardiogram (AI-ECG) algorithm for the detection of preclinical left ventricular systolic dysfunction (LVSD) in a large community-based cohort., Methods: We identified a randomly selected community-based cohort of 2041 subjects age 45 years or older in Olmsted County, Minnesota. All participants underwent a study echocardiogram and ECG. We first assessed the performance of the AI-ECG to identify LVSD (ejection fraction ≤40%). After excluding participants with clinical heart failure, we further assessed the AI-ECG to detect preclinical LVSD among all patients (n=1996) and in a high-risk subgroup (n=1348). Next we modelled an imputed screening program for preclinical LVSD detection where a positive AI-ECG triggered an echocardiogram. Finally, we assessed the ability of the AI-ECG to predict future LVSD. Participants were enrolled between January 1, 1997, and September 30, 2000; and LVSD surveillance was performed for 10 years after enrollment., Results: For detection of LVSD in the total population (prevalence, 2.0%), the area under the receiver operating curve for AI-ECG was 0.97 (sensitivity, 90%; specificity, 92%); in the high-risk subgroup (prevalence 2.7%), the area under the curve was 0.97 (sensitivity, 92%; specificity, 93%). In an imputed screening program, identification of one preclinical LSVD case would require 88.3 AI-ECGs and 8.7 echocardiograms in the total population and 65.7 AI-ECGs and 5.5 echocardiograms in the high-risk subgroup. The unadjusted hazard ratio for a positive AI-ECG for incident LVSD over 10 years was 2.31 (95% CI, 1.32 to 4.05; P=.004)., Conclusion: Artificial intelligence-augmented ECG can identify preclinical LVSD in the community and warrants further study as a screening tool for preclinical LVSD., (Copyright © 2021 Mayo Foundation for Medical Education and Research. Published by Elsevier Inc. All rights reserved.)

Objective: To carry out a systematic review of the effect of cardiac rehabilitation (CR) and its components on cardiovascular outcomes in patients with stable angina., Methods: We searched the databases including Ovid MEDLINE, Ovid Embase, Scopus, Web of Science, Google Scholar, and EBSCO CINAHL from their inception up to November 1, 2017. The search was not restricted to time or publication status but was limited to the English language. Two independent investigators screened the identified studies and extracted the data in duplicate. We reviewed the included studies and, where possible, pooled their results and conducted meta-analyses. Risk of bias was assessed using Cochrane Collaboration tools., Results: The search identified 7508 studies. Ten randomized trials including 4005 participants with the mean (SD) age of 59.6 (5.7) years were considered eligible for inclusion in our analyses. The results of meta-analyses of exercise-based CR for patients with stable angina revealed that CR improved exercise capacity (the difference between baseline and follow-up was 0.76 watt [0.49 to 1.02] higher in the CR group vs the non-CR group) and decreased angina frequency (standard mean difference, -0.27 [CI, -0.43 to 0.11]). No significant differences were noted in other outcomes, including quality of life. Mortality could not be adequately assessed because it was analyzed in only 1 exercise-based CR study., Conclusion: Our systematic review, involving a relatively small number of studies with low to moderate risk of bias and with considerable heterogeneity, found a significant decrease in angina frequency and increase in exercise capacity in patients with stable angina who participated in an exercise-based CR program. Studies involving the impact of components of CR are limited and generally report beneficial outcomes. Additional studies are needed to clarify the possible role of CR in the management of patients with stable angina., (© 2021 Published by Elsevier Inc on behalf of Mayo Foundation for Medical Education and Research.)

In contrast to the decreasing burden related to cardiovascular disease (CVD), the burden related to dysglycemia and adiposity complications is increasing in Czechia, and local drivers must be identified. A comprehensive literature review was performed to evaluate biological, behavioral, and environmental drivers of dysglycemia and abnormal adiposity in Czechia. Additionally, the structure of the Czech healthcare system was described. The prevalence of obesity in men and diabetes in both sexes has been increasing over the past 30 years. Possible reasons include the Eastern European eating pattern, high prevalence of physical inactivity and health illiteracy, education, and income-related health inequalities. Despite the advanced healthcare system based on the compulsory insurance model with free-for-service healthcare and a wide range of health-promoting initiatives, more effective strategies to tackle the adiposity/dysglycemia are needed. In conclusion, the disease burden related to dysglycemia and adiposity in Czechia remains high but is not translated into greater CVD. This discordant relationship likely depends more on other factors, such as improvements in dyslipidemia and hypertension control. A reconceptualization of abnormal adiposity and dysglycemia into a more actionable cardiometabolic-based chronic disease model is needed to improve the approach to these conditions. This review can serve as a platform to investigate causal mechanisms and secure effective management of cardiometabolic-based chronic disease.

Background: Visceral fat is associated with adiposity-based complications. Bioimpedance measurement allows estimation of visceral fat area (VFA) in an easy manner. However, a validated cut-off value for VFA by bioimpedance associated with cardiometabolic risk is lacking in European population., Aim: To determine cut-off values of VFA measured via bioimpedance associated with cardiometabolic risk., Methods: Random cross-sectional Czech population-based sample of 25-64 years old subjects. Receiver Operating Characteristic (ROC) curves were used and the area under the curve (AUC), sensitivity, and specificity were calculated. The Cardiometabolic Disease Staging System (CMDS) was used to classify cardiometabolic risk: Stage 1 - 1 or 2 metabolic syndrome (MetS) components, without impaired fasting glucose (IFG); Stage 2 - MetS or IFG; Stage 3 - MetS with IFG; Stage 4 - type 2 diabetes and/or cardiovascular disease., Results: 2052 participants (54.5% females, median age 49 years) were included. Median VFA (inter-quartile range) were 82.2 cm 2 (54.8) in men and 89.8 cm 2 (55.6) in women. The best VFA cut-offs associated with Stage 1 in men and women were 71 cm 2 (sensitivity = 0.654; specificity = 0.427) and 83 cm 2 (sensitivity = 0.705; specificity = 0.556) ; Stage 2: 84 cm 2 (sensitivity = 0.673; specificity = 0.551) and 98 cm 2 (sensitivity = 0.702; specificity = 0.628) ; Stage 3: 90 cm 2 (sensitivity = 0.886; specificity = 0.605) and 109 cm 2 (sensitivity = 0.755; specificity = 0.704); Stage 4: 91 cm 2 (sensitivity = 0.625; specificity = 0.611) and 81 cm 2 (sensitivity = 0.695; specificity = 0.448), respectively., Conclusion: A cut-off value of VFA of 71 cm 2 in men and 83 cm 2 in women exhibited the earliest stage of cardiometabolic risk, and 90 cm 2 in men and 109 cm 2 in women showed the best performance to detect risk., (Copyright © 2021 Asia Oceania Association for the Study of Obesity. Published by Elsevier Ltd. All rights reserved.)

Background: To help clarify a potential barrier to cardiac rehabilitation (CR) participation we sought to examine the association between musculoskeletal limitations (MSLs) and CR enrollment and participation. Methods: Consecutive CR eligible individuals hospitalized for a cardiac event (myocardial infarction, percutaneous coronary intervention, and/or coronary artery bypass graft) between the months of November 2007 and May 2008, were asked to complete a mailed survey within 2 weeks after hospital discharge, assessing demographic factors, Patient Health Questionnaire (PHQ-9), participation in CR and MSLs through a validated MSLs screening tool. CR enrollment rates were compared between patients with and without MSLs. Results: Three hundred and twenty-one (37%) of patients contacted responded to our survey, including 228 males (71%), with a mean age 68 ± 10.8 years, of whom 98% were Caucasian. Eighty-two percent of responders reported a musculoskeletal disorder at the time of hospital discharge. Arthritis was the most frequent diagnosis (45%). Muscle or joint pain sufficient to limit the ability to do moderate exercise was reported in 52% of the respondents. Problems with balance affected 37%, of whom 45% reported a fall within the previous year. No significant difference in CR enrollment was observed in respondents with and without MSLs [OR = 0.98, 95% CI (0.88-1.09), p = 0.750]. Similar results were found when severity and number of MSLs were taken into account. However, we found that when compared to those without MSLs, the presence of MSLs was associated with lower CR participation (OR = 0.80, 95%, CI: 0.65-0.97, p = 0.0252). Conclusion: Despite a high prevalence of MSLs among CR-eligible patients, we found no association between MSLs and CR enrollment. However, patients with MSLs attended significantly fewer CR sessions as compared to patients without them. CR programs should consider providing additional support and interventions to patients with MSLs in order to optimize their adherence to prescribed CR sessions., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2021 Supervia, Medina-Inojosa, Pérez-Terzic, Sharma, Goel, Vickers Douglas, Salz and Thomas.)

Objective: The objective of the study was to assess the physical activity (PA) and exercise patterns among participants in a large multinational spontaneous coronary artery dissection (SCAD) registry. Patients and Methods: Participants with SCAD enrolled from March 2011 to November 2019 completed surveys including details regarding PA and exercise habits prior to SCAD, and PA counseling received from their provider after SCAD. Demographics and clinical characteristics were collected by electronic record review. Exercise prescribed to patients after SCAD was categorized according to exercise components: type, intensity, frequency, time/session, and extreme environmental conditions. Results: We included 950 participants; mean ± age was 46.8 ± 9.5 years old at the time of first SCAD; most (96.3%) were women and (77.0%) attended ≥1 cardiac rehabilitation session. Hyperlipidemia (34.3%), hypertension (32.8%), and elevated body weight (overweight = 27.0%; obesity = 20.0%) were the most common comorbidities. Prior to SCAD, 48.5% performed aerobic exercise ≥3 times/week, and only 32.0% performed strength-building exercise regularly. PA counseling details after SCAD in 299/950 participants showed that most (93.3%) patients received some form of counseling including exercise prescription (EXP), non-specific recommendations, and discouraged from any exercise. Limits regarding exercise type and intensity were the most common advice among participants who received EXP. Conclusion: Insights from our study suggest that only 48% of the patients performed some aerobic exercise three or more times per week, and 32.0% performed strength-building exercises, which suggest that most of them may not be as active as assumed. Furthermore, 70% of the SCAD patients have ≥1 cardiovascular risk factors. We suggest guiding patients based on individual assessment, taking into consideration baseline PA habits, treatment, and risk factors. SCAD-tailored PA guidelines are needed for optimal EXP without compromising patient safety., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2021 Chacin-Suarez, Bonikowske, Medina-Inojosa, Gulati, Best, Hayes and Tweet.)

Objectives: This study sought to compare aortic stenosis (AS) progression rates, AS-related cardiac damage (AS-CD) indicator incidence and determinants, and survival between patients with tricuspid aortic valve (TAV)-AS and those with bicuspid aortic valve (BAV)-AS., Background: Differences in AS progression and AS-CD between patients with BAV and patients with TAV are unknown., Methods: We retrospectively studied consecutive patients with baseline peak aortic valve velocity (peakV) ≥2.5 m/s and left ventricular ejection fraction ≥50%. Follow-up echocardiograms (n = 4,818) provided multiparametric AS progression rates and AS-CD., Results: The study included 330 BAV (age 54 ± 14 years) and 581 patients with TAV (age 72 ± 11 years). At last echocardiogram (median: 5.9 years; interquartile range: 3.9 to 8.5 years), BAV-AS exhibited similar peakV and mean pressure gradient (MPG) as TAV-AS, but larger calculated aortic valve area due to larger aortic annulus (p < 0.0001). Multiparametric progression rates were similar between BAV-AS and TAV-AS (all p ≥ 0.08) and did not predict age-/sex-adjusted survival (p ≥ 0.45). Independent determinants of rapid progression were male sex and baseline AS severity for TAV (all p ≤ 0.024), and age, baseline AS severity, and cardiac risk factors (age interaction: p = 0.02) for BAV (all p ≤ 0.005). At 12 years, patients with TAV-AS had a higher incidence of AS-CD than BAV-AS patients (p < 0.0001), resulting in significantly worse survival compared to BAV-AS (p < 0.0001). AS-CD were independently determined by multiple factors (MPG, age, sex, comorbidities, cardiac function; all p ≤ 0.039), and BAV was independently protective of most AS-CD (all p ≤ 0.05)., Conclusions: In this cohort, TAV-AS and BAV-AS progression rates were similar. Rapid progression did not affect survival and was determined by cardiac risk factors for BAV-AS (particularly in patients with BAV <60 years of age) and unmodifiable factors for TAV-AS. AS-CD and mortality were significantly higher in TAV-AS. Independent determinants of AS-CD were multifactorial, and BAV morphology was AS-CD protective. Therefore, the totality of AS burden (cardiac damage) is clinically crucial for TAV-AS, whereas attention to modifiable risk factors may be preventive for BAV-AS., Competing Interests: Funding Support and Author Disclosures Internal funding has been received from the Mayo Clinic Department of Cardiovascular Medicine. All authors have reported that they have no relationships relevant to the contents of this paper to disclose., (Copyright © 2021 American College of Cardiology Foundation. Published by Elsevier Inc. All rights reserved.)

Objective: Arterial stiffness (ArSt) describes a loss of arterial wall elasticity and is an independent predictor of cardiovascular events. A cardiometabolic-based chronic disease model integrates concepts of adiposity-based chronic disease (ABCD), dysglycemia-based chronic disease (DBCD), and cardiovascular disease. We assessed if ABCD and DBCD models detect more people with high ArSt compared with traditional adiposity and dysglycemia classifiers using the cardio-ankle vascular index (CAVI)., Methods: We evaluated 2070 subjects aged 25 to 64 years from a random population-based sample. Those with type 1 diabetes were excluded. ABCD and DBCD were defined, and ArSt risk was stratified based on the American Association of Clinical Endocrinologists criteria., Results: The highest prevalence of a high CAVI was in stage 2 ABCD (18.5%) and stage 4 DBCD (31.8%), and the lowest prevalence was in stage 0 ABCD (2.2%). In univariate analysis, stage 2 ABCD and all DBCD stages increased the risk of having a high CAVI compared with traditional classifiers. After adjusting for age and gender, only an inverse association between obesity (body mass index ≥30 kg/m 2 ) and CAVI remained significant. Nevertheless, body mass index was responsible for only 0.3% of CAVI variability., Conclusion: The ABCD and DBCD models showed better performance than traditional classifiers to detect subjects with ArSt; however, the variables were not independently associated with age and gender, which might be explained by the complexity and multifactoriality of the relationship of CAVI with the ABCD and DBCD models, mediated by insulin resistance., (Copyright © 2021 AACE. Published by Elsevier Inc. All rights reserved.)

Aims/hypothesis: The need for understanding obesity as a chronic disease, its stigmatization, and the lack of actionability related to it demands a new approach. The adiposity-based chronic disease (ABCD) model is based on adiposity amount, distribution, and function, with a three stage complication-centric rather than a body mass index (BMI)-centric approach. The prevalence rates and associated risk factors are presented., Methods: In total, 2159 participants were randomly selected from Czechia. ABCD was established as BMI ≥ 25 kg/m 2 or high body fat percent, or abdominal obesity and then categorized by their adiposity-based complications: Stage 0: none; Stage 1: mild/moderate; Stage 2: severe., Results: ABCD prevalence was 62.8%. Stage 0 was 2.3%; Stage 1 was 31.4%; Stage 2 was 29.1%. Comparing with other classifiers, participants in Stage 2 were more likely to have diabetes, hypertension, and metabolic syndrome than those with overweight, obesity, abdominal obesity, and increased fat mass. ABCD showed the highest sensitivity and specificity to detect participants with peripheral artery disease, increased intima media, and vascular disease., Conclusion/interpretation: The ABCD model provides a more sensitive approach that facilitates the early detection and stratification of participants at risk compared to traditional classifiers., Competing Interests: Dr. Mechanick has received honoraria for lectures and program development from Abbott Nutrition International. The other authors have not conflict of interest., (© 2021 The Authors. Obesity Science & Practice published by World Obesity and The Obesity Society and John Wiley & Sons Ltd.)

Objective: To determine the prevalence rate and associated risk factors for each stage of the Dysglycemia-Based Chronic Disease (DBCD) model, which 4 distinct stages and prompts early prevention to avert Diabetes and cardiometabolic complications., Methods: Subjects between 25 and 64 years old from a random population-based sample were evaluated in Czechia from 2013 to 2014 using a cross-sectional design. DBCD stages were: stage 1 "insulin resistance" (inferred risk from abdominal obesity or a family history of diabetes); stage 2 "prediabetes"(fasting glucose between 5.6 and 6.9 mmol/L); stage 3 "type 2 diabetes (T2D)" (self-report of T2D or fasting glucose ≥7 mmol/L); and stage 4 "vascular complications" (T2D with cardiovascular disease)., Results: A total of 2147 subjects were included (57.8% women) with a median age of 48 years. The prevalence of each DBCD stage were as follows: 54.2% (stage 1); 10.3% (stage 2), 3.7% (stage 3); and 1.2% (stage 4). Stages 2 to 4 were more frequent in men and stage 1 in women (P < .001). Using binary logistic regression analysis adjusting by age/sex, all DBCD stages were strongly associated with abnormal adiposity, hypertension, dyslipidemia, and smoking status. Subjects with lower educational levels and lower income were more likely to present DBCD., Conclusion: Using the new DBCD framework and available metrics, 69.4% of the population had DBCD, identifying far more people at risk than a simple prevalence rate for T2D (9.2% in Czechia, 2013-2014). All stages were associated with traditional cardiometabolic risk factors, implicating common pathophysiologic mechanisms and a potential for early preventive care. The social determinants of health were related with all DBCD stages in alarming proportions and will need to be further studied., (Copyright © 2020 AACE. Published by Elsevier Inc. All rights reserved.)

Background: Type 2 myocardial infarction (T2MI) is commonly encountered in clinical practice, yet little is known about this challenging condition. Outpatient cardiac rehabilitation (CR) is an integral component in the care of patients with MI. However, specific recommendations for CR, information on the feasibility of participation, and outcome measures for patients with T2MI are lacking., Clinical Considerations: The frequency of T2MI is markedly variable and depends on the studied population, disease definition, adjudication process, cardiac troponin assays, and cutoff values used to make the diagnosis of T2MI. Clinically, it is difficult to distinguish T2MI from type 1 MI or myocardial injury. Type 2 myocardial infarction occurs due to myocardial oxygen supply-demand mismatch without acute atherothrombotic plaque disruption and is associated with adverse short- and long-term prognoses. Currently, there are substantial gaps in knowledge regarding T2MI and there are no clear guidelines for the optimal management of these patients., Summary: In this article, we present important current concepts surrounding T2MI including the definition, pathophysiology, epidemiology, diagnosis, prognosis, and management. We also discuss referral patterns to CR and participation rates and provide our experience with a case series of 17 patients. Very few patients with T2MI are referred to and participate in CR. Our small case series indicated that patients with T2MI respond favorably to CR and that exercise training following standard guidelines appears safe and is well tolerated., Competing Interests: The authors declare no conflicts of interest., (Copyright © 2021 Wolters Kluwer Health, Inc. All rights reserved.)

Background: We have demonstrated that a neural network is able to predict a person's age from the electrocardiogram (ECG) [artificial intelligence (AI) ECG age]. However, some discrepancies were observed between ECG-derived and chronological ages. We assessed whether the difference between AI ECG and chronological age (Age-Gap) represents biological ageing and predicts long-term outcomes., Methods and Results: We previously developed a convolutional neural network to predict chronological age from ECGs. In this study, we used the network to analyse standard digital 12-lead ECGs in a cohort of 25 144 subjects ≥30 years who had primary care outpatient visits from 1997 to 2003. Subjects with coronary artery disease, stroke, and atrial fibrillation were excluded. We tested whether Age-Gap was correlated with total and cardiovascular mortality. Of 25 144 subjects tested (54% females, 95% Caucasian) followed for 12.4 ± 5.3 years, the mean chronological age was 53.7 ± 11.6 years and ECG-derived age was 54.6 ± 11 years ( R 2 = 0.79, P < 0.0001). The mean Age-Gap was small at 0.88 ± 7.4 years. Compared to those whose ECG-derived age was within 1 standard deviation (SD) of their chronological age, patients with Age-Gap ≥1 SD had higher all-cause and cardiovascular disease (CVD) mortality. Conversely, subjects whose Age-Gap was ≤1 SD had lower all-cause and CVD mortality. Results were unchanged after adjusting for CVD risk factors and other survival influencing factors., Conclusion: The difference between AI ECG and chronological age is an independent predictor of all-cause and cardiovascular mortality. Discrepancies between these possibly reflect disease independent biological ageing., (© The Author(s) 2021. Published by Oxford University Press on behalf of the European Society of Cardiology.)

Objective: To validate a novel artificial-intelligence electrocardiogram algorithm (AI-ECG) to detect left ventricular systolic dysfunction (LVSD) in an external population., Background: LVSD, even when asymptomatic, confers increased morbidity and mortality. We recently derived AI-ECG to detect LVSD using ECGs based on a large sample of patients treated at the Mayo Clinic., Methods: We performed an external validation study with subjects from the Know Your Heart Study, a cross-sectional study of adults aged 35-69 years residing in two cities in Russia, who had undergone both ECG and transthoracic echocardiography. LVSD was defined as left ventricular ejection fraction ≤ 35%. We assessed the performance of the AI-ECG to identify LVSD in this distinct patient population., Results: Among 4277 subjects in this external population-based validation study, 0.6% had LVSD (compared to 7.8% of the original clinical derivation study). The overall performance of the AI-ECG to detect LVSD was robust with an area under the receiver operating curve of 0.82. When using the LVSD probability cut-off of 0.256 from the original derivation study, the sensitivity, specificity, and accuracy in this population were 26.9%, 97.4%, 97.0%, respectively. Other probability cut-offs were analysed for different sensitivity values., Conclusions: The AI-ECG detected LVSD with robust test performance in a population that was very different from that used to develop the algorithm. Population-specific cut-offs may be necessary for clinical implementation. Differences in population characteristics, ECG and echocardiographic data quality may affect test performance., Competing Interests: Declaration of Competing Interest Mayo Clinic has licensed the underlying technology to EKO, a maker of digital stethoscopes with embedded ECG electrodes. Mayo Clinic may receive financial benefit from the use of this technology, but at no point will Mayo Clinic benefit financially from its use for the care of subjects at Mayo Clinic. P.A.F., F.L.-J., S.K., and Z.I.A. may also receive financial benefit from this agreement., (Copyright © 2020. Published by Elsevier B.V.)

Objective: To determine whether early Roux-en-Y gastric bypass surgery (RYGB) reduces the risk of Major adverse cardiovascular events (MACE) in patients with obesity. Patients and Methods: We conducted a study of patients with class II and III obesity [body mass index (BMI) > 35 kg/m 2 ] from Olmsted County, Minnesota, who underwent obesity clinic consultation between the years 1993-2012, and had either RYGB surgery within 1 year (RYGB-1Y group), or medically managed (No-RYGB group). The composite endpoint of MACE (all-cause mortality, stroke, heart failure admission and acute myocardial infarction) was the primary endpoint, with new-onset AF as the secondary endpoint. Results: Of the 1,009 study patients, 308 had RYGB-1Y and 701 were medically managed (No-RYGB). Overall, the age was 44.0 ± 12.4 (mean ± SD) years; BMI was 45.0 ± 6.8 kg/m 2 . The RYGB-1Y group had a lower rate of MACE (adjusted hazard ratio (HR), 0.62; 95% CI, 0.44-0.88; P = 0.008) and lower mortality (adjusted HR, 0.51; 95% CI, 0.26-0.96; P = 0.04) than the No-RYGB group. The RYGB-1Y surgery was not associated with lower AF occurrence (HR, 0.66; 95% CI, 0.40-1.10; P = 0.11). Conclusion: An early RYGB approach for BMI reduction was associated with lower rates of MACE., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2021 Yuan, Medina-Inojosa, Lopez-Jimenez, Miranda, Collazo-Clavell, Sarr, Chamberlain, Hodge, Bailey, Wang, Chen and Cha.)

[Figure: see text].

Objective: To determine the risk of long-term major adverse cardiovascular events (MACE) when sleep-disordered breathing (SDB) and decreased cardiorespiratory fitness (CRF) co-occur., Methods: We included consecutive patients who underwent symptom-limited cardiopulmonary exercise tests between January 1, 2005, and January 1, 2010, followed by first-time diagnostic polysomnography within 6 months. Patients were stratified based on the presence of moderate-to-severe SDB (apnea/hypopnea index ≥15 per hour) and decreased CRF defined as <70% predicted peak oxygen consumption (VO 2 ). Long-term MACE was a composite outcome of myocardial infarction (MI), coronary artery bypass graft (CABG), percutaneous coronary intervention (PCI), stroke or transient ischemic attack (TIA), and death, assessed until May 21, 2018. Cox-proportional hazard models were adjusted for factors known to influence CRF and MACE., 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 to 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 use of positive airway pressure (PAP), decreased CRF alone (hazard ratio [HR]=1.91, 95% confidence interval [CI], 1.15 to 3.18; P=.01), but not SDB alone (HR=1.26, 95% CI, 0.75 to 2.13, P=.39) was associated with increased risk of MACE. Those with SDB and decreased CRF had greater risk of MACE compared with patients with decreased CRF alone (HR=1.85; 95% CI, 1.21 to 2.84; P<.005) after accounting for these confounders. The risk of MACE was attenuated in those with reduced CRF alone after additionally adjusting for adequate adherence to PAP (HR=1.59; 95% CI, 0.77 to 3.31; P=.21)., Conclusion: The incidence of MACE, especially mortality, was high in this sample. Moderate-to-severe SDB with concurrent decreased CRF was associated with higher risk of MACE than decreased CRF alone. These results highlight the importance of possibly including CRF in the risk assessment of patients with SDB and, conversely, that of screening for SDB in patients with low peak VO 2 ., (Copyright © 2020 Mayo Foundation for Medical Education and Research. Published by Elsevier Inc. All rights reserved.)

Purpose: Integrative therapies such as yoga are potential treatments for many psychological and physical symptoms that occur during and/or after treatment for cancer. The purpose of the current study was to evaluate the patient-perceived benefit of yoga for symptoms commonly experienced by breast cancer survivors., Methods: 1,049 breast cancer survivors who had self-reported use of yoga on a follow up survey, in an ongoing prospective Mayo Clinic Breast Disease Registry (MCBDR), received an additional mailed yoga-focused survey asking about the impact of yoga on a variety of symptoms. Differences between pre- and post- scores were assessed using Wilcoxon Signed Rank Test., Results: 802/1,049 (76%) of women who were approached to participate, consented and returned the survey. 507/802 (63%) reported use of yoga during and/or after their cancer diagnosis. The vast majority of respondents (89.4%) reported some symptomatic benefit from yoga. The most common symptoms that prompted the use of yoga were breast/chest wall pain, lymphedema, and anxiety. Only 9% of patients reported that they had been referred to yoga by a medical professional. While the greatest symptom improvement was reported with breast/chest wall pain and anxiety, significant improvement was also perceived in joint pain, muscle pain, fatigue, headache, quality of life, hot flashes, nausea/vomiting, depression, insomnia, lymphedema, and peripheral neuropathy, (all p-values <0.004)., Conclusion: Data supporting the use of yoga for symptom management after cancer are limited and typically focus on mental health. In this study, users of yoga often reported physical benefits as well as mental health benefits. Further prospective studies investigating the efficacy of yoga in survivorship are warranted., Competing Interests: Declaration of Conflicting Interests: The author(s) declared the following potential conflicts of interest with respect to the research, authorship, and/or publication of this article: Dr. Fergus Couch is on Ambry Genetics and Qiagen’s Speakers' Bureau, consults for AstraZeneca, receives travel grants from GRAIL and Qiagen, and receives research funding from GRAIL. Dr. Charles Loprinzi consults for PledPharmaCompany, Metys Pharmaceuticals, Asahi Kasei, Disarm Therapeutics, OnQuality Pharmaceuticals, NKMax, and Mitsubishi Tanabe Pharma, has intellectual property with Janssen, and receives research funding from Bristol-Myers Squibb., (© The Author(s) 2021.)

Purpose: The purpose of the present study was to investigate body mass index, multi-morbidity, and COVID-19 Risk Score as predictors of severe COVID-19 outcomes., Patients: Patients from this study are from a well-characterized patient cohort collected at Mayo Clinic between January 1, 2020 and May 23, 2020; with confirmed COVID-19 diagnosis defined as a positive result on reverse-transcriptase-polymerase-chain-reaction (RT-PCR) assays from nasopharyngeal swab specimens., Measures: Demographic and clinical data were extracted from the electronic medical record. The data included: date of birth, gender, ethnicity, race, marital status, medications (active COVID-19 agents), weight and height (from which the Body Mass Index (BMI) was calculated, history of smoking, and comorbid conditions to calculate the Charlson Comorbidity Index (CCI) and the U.S Department of Health and Human Services (DHHS) multi-morbidity score. An additional COVID-19 Risk Score was also included. Outcomes included hospital admission, ICU admission, and death., Results: Cox proportional hazards models were used to determine the impact on mortality or hospital admission. Age, sex, and race (white/Latino, white/non-Latino, other, did not disclose) were adjusted for in the model. Patients with higher COVID-19 Risk Scores had a significantly higher likelihood of being at least admitted to the hospital (HR = 1.80; 95% CI = 1.30, 2.50; P  < .001), or experiencing death or inpatient admission (includes ICU admissions) (HR = 1.20; 95% CI = 1.02, 1.42; P  = .028). Age was the only statistically significant demographic predictor, but obesity was not a significant predictor of any of the outcomes., Conclusion: Age and COVID-19 Risk Scores were significant predictors of severe COVID-19 outcomes. Further work should examine the properties of the COVID-19 Risk Factors Scale.

Objective: To describe the process and outcome of creating a patient cohort in the early stages of the COVID-19 pandemic in order to better understand the process of and predict the outcomes of COVID-19., Patients and Methods: A total of 1169 adults aged 18 years of age or older who tested positive in Mayo Clinic Rochester or the Mayo Clinic Midwest Health System between January 1 and May 23 of 2020., Results: Patients were on average 43.9 years of age and 50.7% were female. Most patients were white (69.0%), and Blacks (23.4%) and Asians (5.8%) were also represented in larger numbers. Hispanics represented 16.3% of the sample. Just under half of patients were married (48.4%). Common comorbid conditions included: cardiovascular diseases (25.1%), dyslipidemia (16.0%), diabetes mellitus (11.2%), chronic obstructive pulmonary disease (6.6%), asthma (7.5%), and cancer (5.1%). All other comorbid conditions were less the 5% in prevalence. Data on 3 comorbidity indices are also available including the: DHHS multi-morbidity score, Charlson Comorbidity Index, and Mayo Clinic COVID-19 Risk Factor Score., Conclusion: In addition to managing the ever raging pandemic and growing death rates, it is equally important that we develop adequate resources for the investigation and understanding of COVID-19-related predictors and outcomes.

Recent reports suggest that the COVID-19 lockdown resulted in changes in mental health, however, potential age-related changes and risk factors remain unknown. We measured COVID-19 lockdown-induced stress levels and the severity of depressive symptoms prior to and during the COVID-19 lockdown in different age groups and then searched for potential risk factors in a well-characterized general population-based sample. A total of 715 participants were tested for mental distress and related risk factors at two time-points, baseline testing prior to COVID-19 and follow-up testing during COVID-19, using a battery of validated psychological tests including the Perceived Stress Scale and the Patient Health Questionnaire. Longitudinal measurements revealed that the prevalence of moderate to high stress and the severity of depressive symptoms increased 1.4- and 5.5-fold, respectively, during the COVID-19 lockdown. This surge in mental distress was more severe in women, but was present in all age groups with the older age group exhibiting, cross-sectionally, the lowest levels of mental distress prior to and during the lockdown. Illness perception, personality characteristics such as a feeling of loneliness, and several lifestyle components were found to be associated with a significant increase in mental distress. The observed changes in mental health and the identified potential risk factors underlying these changes provide critical data justifying timely and public emergency-tailored preventive, diagnostic, and therapeutic mental health interventions, which should be integrated into future public health policies globally., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2020 Novotný, Gonzalez-Rivas, Kunzová, Skladaná, Pospíšilová, Polcrová, Medina-Inojosa, Lopez-Jimenez, Geda and Stokin.)

Objective: To investigate the effect of replacing sitting with standing on cardiovascular risk factors tested in clinical trials., Methods: We searched databases from inception up to August 28, 2019, for studies examining the effect of replacing sitting with standing on fasting blood glucose, fasting insulin, and lipid levels; blood pressure; body fat mass; weight; and waist circumference in healthy adults. Differences in mean ± SD values were used for pooling the data and calculating the mean differences and CIs., Results: The search found 3507 abstracts. Nine clinical trials (8 randomized and 1 nonrandomized) with 877 (64.4% [n=565] women) participants met all inclusion criteria. The mean ± SD age was 45.34±5.41 years; mean follow-up was 3.81 months, and mean difference in standing time between the intervention and control groups was 1.33 hours per day. The follow-up fasting blood glucose and body fat mass values were slightly but significantly lower than baseline records in the intervention groups compared with control groups (-2.53; 95% CI, -4.27 to -0.79 mg/dL; and -0.75; 95% CI, -0.91 to -0.59 kg). The analysis for fasting insulin levels, lipid levels, blood pressure, weight, and waist circumference revealed no significant differences., Conclusion: Replacing sitting with standing can result in very small but statistically significant decreases in fasting blood glucose levels and body fat mass with no significant effect on lipid levels, blood pressure, weight, and waist circumference. Replacing sitting with standing can be used as an adjunctive intervention to decrease the burden of cardiovascular risk factors but cannot be used as an alternative to physical activity to decrease sedentary time., (© 2020 Mayo Foundation for Medical Education and Research. Published by Elsevier Inc.)

Rapid diagnosis of myocardial infarction (MI) using electrocardiography (ECG) is the cornerstone of effective treatment and prevention of mortality; however, conventional interpretation methods has low reliability for detecting MI and is difficulty to apply to limb 6-lead ECG based life type or wearable devices. We developed and validated a deep learning-based artificial intelligence algorithm (DLA) for detecting MI using 6-lead ECG. A total of 412,461 ECGs were used to develop a variational autoencoder (VAE) that reconstructed precordial 6-lead ECG using limb 6-lead ECG. Data from 9536, 1301, and 1768 ECGs of adult patients who underwent coronary angiography within 24 h from each ECG were used for development, internal and external validation, respectively. During internal and external validation, the area under the receiver operating characteristic curves of the DLA with VAE using a 6-lead ECG were 0.880 and 0.854, respectively, and the performances were preserved by the territory of the coronary lesion. Our DLA successfully detected MI using a 12-lead ECG or a 6-lead ECG. The results indicate that MI could be detected not only with a conventional 12 lead ECG but also with a life type 6-lead ECG device that employs our DLA.

Existing data have described benefits and drawbacks of alcohol consumption on cardiovascular diseases (CVD), but no research has evaluated its association with the cardiovascular health (CVH) score proposed by the American Heart Association. Here, we conducted a cross-sectional analysis on the Kardiovize cohort (Brno, Czech Republic), to investigate the relationship between alcohol consumption and CVH. We included 1773 subjects (aged 25-64 years; 44.2% men) with no history of CVD. We compared CVD risk factors, CVH metrics (i.e., BMI, healthy diet, physical activity level, smoking status, blood pressure, fasting glucose, and total cholesterol) and CVH score between and within several drinking categories. We found that the relationship between drinking habits and CVH was related to the amount of alcohol consumed, drinking patterns, and beverage choices. Heavy drinkers were more likely to smoke tobacco, and to report diastolic blood pressure, fasting glucose, triglycerides, and low-density lipoprotein (LDL)-cholesterol at higher level than non-drinkers. Among drinkers, however, people who exclusively drank wine exhibited better CVH than those who exclusively drank beer. Although our findings supported the hypothesis that drinking alcohol was related to the CVH in general, further prospective research is needed to understand whether the assessment of CVH should incorporate information on alcohol consumption.

Background: Methods for reducing major adverse cardiac events (MACE) in patients after heart transplantation (HTx) are critical for long-term quality outcomes., Methods and Results: Patients with cardiopulmonary exercise testing prior to HTx and at least 1 session of cardiac rehabilitation (CR) after HTx were included. Exercise sessions were evaluated as ≥ 23 or < 23 sessions based on recursive partitioning. We included 140 patients who had undergone HTx (women: n = 41 (29%), age: 52 ± 12 years, body mass index: 27 ± 5 kg/m 2 ). Mean follow-up was 4.1 ± 2.7 years, and 44 patients (31%) had a MACE: stroke (n = 1), percutaneous intervention (n = 5), heart failure (n = 6), myocardial infarction (n = 1), rejection (n = 16), or death (n = 15). CR was a significant predictor of MACE, with ≥ 23 sessions associated with a ∼ 60% reduction in MACE risk (hazard ratio [HR]: 0.42, 95% CI: 0.19-0.94, P = 0.035). This remained after adjusting for age, sex and history of diabetes (HR: 0.41, 95% CI: 0.18-0.94, P = 0.035) as well as body mass index and pre-HTx peak oxygen consumption (HR: 0.40, 95% CI: 0.18-0.92, P = 0.031)., Conclusions: After adjustment for covariates of age, sex, diabetes, body mass index, and pre-HTx peak oxygen consumption, CR attendance of ≥ 23 exercise sessions was predictive of lower MACE risk following HTx. In post-HTx patients, CR was associated with MACE prevention and should be viewed as a critical tool in post-HTx treatment strategies., (Copyright © 2020 Elsevier Inc. All rights reserved.)