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Background: A quality diet and an active lifestyle are both important cornerstones of cardiovascular disease (CVD) prevention. However, despite their interlinked effects on metabolic health, the 2 behaviors are rarely considered jointly, particularly within the context of CVD prevention. We examined the independent, interactive, and joint associations of diet and physical activity with CVD hospitalization, CVD mortality, and all-cause mortality. Methods: CVD-free Australian participants aged 45–74 years (n = 85,545) reported physical activity, diet, sociodemographic, and lifestyle characteristics at baseline (2006–2009) and follow-up (2012–2015), and data were linked to hospitalization and death registries (03/31/2019 for CVD hospitalization and all-cause mortality and 12/08/2017 for CVD mortality). Diet quality was categorized as low, medium, and high based on meeting dietary recommendations. Physical activity was operationalized as (a) total moderate-to-vigorous physical activity (MVPA) as per guidelines, and (b) the composition of MVPA as the ratio of vigorous-intensity physical activity (VPA) to total MVPA. We used a left-truncated cause-specific Cox proportional hazards model using time-varying covariates. Results: During a median of 10.7 years of follow-up, 6576 participants were admitted to the hospital for CVD and 6581 died from all causes (876 from CVD during 9.3 years). A high-quality diet was associated with a 17% lower risk of all-cause mortality than a low-quality diet, and the highest MVPA category (compared with the lowest) was associated with a 44% and 48% lower risk of CVD and all-cause mortality, respectively. Multiplicative interactions between diet and physical activity were non-significant. For all outcomes, the lowest risk combinations involved a high-quality diet and the highest MVPA categories. Accounting for total MVPA, some VPA was associated with further risk reduction of CVD hospitalization and all-cause mortality. Conclusion: For CVD prevention and longevity, one should adhere to both a healthy diet and an active lifestyle and incorporate some VPA when possible.

Abstract Background Coronary heart disease (CHD) is the leading cause of deaths and disability worldwide. Cardiac rehabilitation (CR) effectively reduces the risk of future cardiac events and is strongly recommended in international clinical guidelines. However, CR program quality is highly variable with divergent data systems, which, when combined, potentially contribute to persistently low completion rates. The QUality Improvement in Cardiac Rehabilitation (QUICR) trial aims to determine whether a data-driven collaborative quality improvement intervention delivered at the program level over 12 months: (1) increases CR program completion in eligible patients with CHD (primary outcome), (2) reduces hospital admissions, emergency department presentations and deaths, and costs, (3) improves the proportion of patients receiving guideline-indicated CR according to national and international benchmarks, and (4) is feasible and sustainable for CR staff to implement routinely. Methods QUICR is a multi-centre, type-2, hybrid effectiveness-implementation cluster-randomized controlled trial (cRCT) with 12-month follow-up. Eligible CR programs (n = 40) and the individual patient data within them (n ~ 2,000) recruited from two Australian states (New South Wales and Victoria) are randomized 1:1 to the intervention (collaborative quality improvement intervention that uses data to identify and manage gaps in care) or control (usual care with data collection only). This sample size is required to achieve 80% power to detect a difference in completion rate of 22%. Outcomes will be assessed using intention-to-treat principles. Mixed-effects linear and logistic regression models accounting for clusters within allocated groupings will be applied to analyse primary and secondary outcomes. Discussion Addressing poor participation in CR by patients with CHD has been a longstanding challenge that needs innovative strategies to change the status-quo. This trial will harness the collaborative power of CR programs working simultaneously on common problem areas and using local data to drive performance. The use of data linkage for collection of outcomes offers an efficient way to evaluate this intervention and support the improvement of health service delivery. Ethics Primary ethical approval was obtained from the Northern Sydney Local Health District Human Research Ethics Committee (2023/ETH01093), along with site-specific governance approvals. Trial registration Australian New Zealand Clinical Trials Registry (ANZCTR) ACTRN12623001239651 (30/11/2023) ( https://anzctr.org.au/Trial/Registration/TrialReview.aspx?id=386540&isReview=true ).

Background Little is known about the relationship between physical activity (PA) and sedentary behavior (SB) with death in people with coronary heart disease. The aim was to examine the independent and joint associations of PA and SB with death. Methods and Results This is a prospective cohort study including Australian participants aged ≥45 years with self‐reported coronary heart disease (2006–2020). Self‐reported PA (min/wk) and SB (h/d) were the exposures. Cardiac and all‐cause death were the main outcomes. The cohort included 40 156 participants (mean age, 70.3 (SD, 10.3) years; 15 278 women [38%]). During a median follow‐up of 11.1 (interquartile range, 6.2–14.4) years, 2497 cardiac and 12 240 all‐cause deaths were recorded. Compared with no PA, a 20% to 30% lower risk of cardiac and all‐cause death was associated with any level of PA. Walking and moderate to vigorous PA at 150 to 300 min/wk was associated with a 43% to 44% lower risk of cardiac death and 35% to 40% lower risk of all‐cause death. Compared with ≥10.5 h/d of SB, participants who were sedentary for 7 to 10.4 h/d experienced an ≈25% reduced associated risk of cardiac and all‐cause death. A 56% associated reduction in all‐cause mortality risk was found if SB was limited to 150 min/wk moderate to vigorous PA and spent

BackgroundThis study evaluates primary care practices' engagement with various features of a quality improvement (QI) intervention for patients with coronary heart disease (CHD) in four Australian states.MethodsTwenty-seven practices participated in the QI intervention from November 2019 -November 2020. A combination of surveys, semi-structured interviews and other materials within the QUality improvement in primary care to prevent hospitalisations and improve Effectiveness and efficiency of care for people Living with heart disease (QUEL) study were used in the process evaluation. Data were summarised using descriptive statistical and thematic analyses for 26 practices.ResultsSixty-four practice team members and Primary Health Networks staff provided feedback, and nine of the 63 participants participated in the interviews. Seventy-eight percent (40/54) were either general practitioners or practice managers. Although 69% of the practices self-reported improvement in their management of heart disease, engagement with the intervention varied. Forty-two percent (11/26) of the practices attended five or more learning workshops, 69% (18/26) used Plan-Do-Study-Act cycles, and the median (Interquartile intervals) visits per practice to the online SharePoint site were 170 (146-252) visits. Qualitative data identified learning workshops and monthly feedback reports as the key features of the intervention.ConclusionPractice engagement in a multi-featured data-driven QI intervention was common, with learning workshops and monthly feedback reports identified as the most useful features. A better understanding of these features will help influence future implementation of similar interventions.Trial registrationAustralian New Zealand Clinical Trials Registry (ANZCTR) number ACTRN12619001790134.

Introduction Physical inactivity is a risk factor for repeat cardiac events and all-cause mortality in coronary heart disease (CHD). Cardiac rehabilitation, a secondary prevention programme, aims to increase physical activity levels in this population from a reported low baseline. This trial will investigate the effectiveness and implementation of a very brief physical activity intervention, comparing different frequencies of physical activity measurement by cardiac rehabilitation clinicians. The Measure It! intervention (

Abstract When implemented in practice, digital technologies have shown improvements in morbidity and mortality outcomes in patients with cardiovascular disease (CVD). For scholars, research into digital technologies in cardiovascular care has been relatively recent, thus it is important to understand the history of digital health technology in cardiovascular research—its emergence, rate of growth, hot topics, and its temporal evolution. The aim of this study was to analyse more than 16,000 articles in this domain based on their scientometric indicators. Web of Science (WoS) Core Collection was accessed and searched at several levels, including titles, abstracts, keywords, authors, sources and individual articles. Analysis examined the temporal shifts in research and scholarly focus based on keywords, networks of collaboration, topical divisions in relation to digital technologies, and influential publications. Findings showed this research area is growing exponentially. Co-citation analysis revealed twenty prominent research streams and identified variation in the magnitude of activities in each stream. A recent emergence of research activities in digital technology in cardiovascular rehabilitation (CR), out-of-hospital cardiac arrest (OHCA), and arrythmia research was also demonstrated. Conversely, wearable technologies, activity tracking and electronic medical records research are now past their peak of reported research activity. With increasing amounts of novel technologies becoming available and more patients taking part in remote health care monitoring, further evaluation and research into digital technologies, including their long-term effectiveness, is needed. Furthermore, emerging technologies, which are evaluated and/or validated should be considered for implementation into clinical practice as treatment and prevention modalities for CVD.

Introduction Many hospital presentations for acute coronary syndrome (ACS) occur in people previously hospitalised with coronary heart disease (CHD), leading to increased costs and health burden. Secondary prevention education including a prehospital discharge plan is recommended for all individuals to reduce the risk of recurrence. However, many clinicians lack the time or support to provide education, and patients’ uptake of secondary prevention programmes is limited. An avatar-based education app is a novel and engaging way to provide self-delivered, evidence-based secondary prevention information during the hospital admission and remains accessible after discharge. This protocol aims to evaluate the effect of an avatar-based education app on individuals with ACS.Methods and analysis This protocol describes a prospective, randomised controlled trial with 3-month follow-up and blinded assessment of 72 participants. Intervention group participants will download the app onto their own device during the hospital admission and independently complete six interactive education modules based on the National Heart Foundation’s six steps to cardiac recovery. All participants will receive a text message reminder of the study after 3 weeks. Both groups will receive usual care consisting of bedside education and a pamphlet about cardiac rehabilitation. The primary outcome is knowledge of CHD, assessed using the Coronary Artery Disease Education Questionnaire II. Secondary outcomes include quality of life, response to heart attack symptoms, cardiac-related readmissions and mortality and modifiable cardiac risk factors. Engagement with the app will be evaluated objectively. Intention-to-treat analysis will be conducted, with between-group comparisons and 95% CIs of the primary outcome analysed using analysis of covariance, adjusting for baseline values.Ethics and dissemination This study protocol has been approved by the Western Sydney Local Health District Human Research Ethics Committee. The results of this study will be disseminated via a peer-reviewed journal and research thesis.Trial registration number Australian New Zealand Clinical Trials Registry (ACTRN12622001436763).

Study objective: This study aims to identify predictors of health related quality of life (HRQoL) among patients with heart failure (HF) and assess whether HRQoL was a predictor of rehospitalisation and mortality, and if age influenced the findings. Design: Observational cohort study. Setting: Seven hospitals in the Northern Sydney Local Health District, Sydney, Australia. Participants: Community dwelling patients who completed a Minnesota Living with HF questionnaire (MLHFQ) within 30 days of discharge after a HF hospitalisation. Main outcome measure: Multivariable linear regression models were used to identify predictors of MLHFQ scores (higher score = worse HRQoL) and adjusted Cox regression models to assess the impact of MLHFQ scores on one-year rehospitalisation and mortality. Separate analyses were conducted for those aged ≤80 or >80 years. Results: 1911 patients of mean age 79 years (57 % aged >80 years) were included in this analysis. Among those aged ≤80 years; younger age, lower haemoglobin and presenting symptoms at hospitalisation of exertional dyspnoea, peripheral oedema and fatigue were predictors of worse post-discharge MLHFQ scores. In patients aged >80 years, living alone, chronic kidney disease, exertional dyspnoea and peripheral oedema were predictors of worse MLHFQ scores. Worse MLHFQ scores predicted one-year HF readmissions in those aged >80 years (HR 1.22, 95 % CI 1.07–1.37) but not those aged ≤80 years (HR 0.90 95 % CI 0.71–1.10). Conclusions: In-hospital predictors can be identified for worse HRQoL post-discharge for HF. These vary according to age, and should be addressed prior to discharge.

Background: For older adults with severe aortic stenosis (AS) undergoing aortic valve replacement (AVR), recovery of physical function is important, yet few studies objectively measure it in real-world environments. This exploratory study explored the acceptability and feasibility of using wearable trackers to measure incidental physical activity (PA) in AS patients before and after AVR. Methods: Fifteen adults with severe AS wore an activity tracker at baseline, and ten at one month follow-up. Functional capacity (six-minute walk test, 6MWT) and HRQoL (SF 12) were also assessed. Results: At baseline, AS participants (n = 15, 53.3% female, mean age 82.3 ± 7.0 years) wore the tracker for four consecutive days more than 85% of the total prescribed time, this improved at follow-up. Before AVR, participants demonstrated a wide range of incidental PA (step count median 3437 per day), and functional capacity (6MWT median 272 m). Post-AVR, participants with the lowest incidental PA, functional capacity, and HRQoL at baseline had the greatest improvements within each measure; however, improvements in one measure did not translate to improvements in another. Conclusion: The majority of older AS participants wore the activity trackers for the required time period before and after AVR, and the data attained were useful for understanding AS patients’ physical function.

Contemporary myocardial infarction (MI) care and management has evolved dramatically since the 1950’s; yet outpatient rehabilitation remains underutilized. Deepening our understanding of the origins and history of cardiac rehabilitation highlights a contemporary shift required for policy and practice related to secondary prevention of coronary disease in light of societal changes as well as medical, digital and surgical advancements. Contemporary “cardiac rehabilitation” began when bed rest and physical inactivity was recommended and commonplace for MI survivors. Today, most patients who survive an MI, undergo reperfusion therapy, a short inpatient stay and are discharged with minimal physical morbidity. Despite this, the majority of modern day programs continue to be structured in the same way they have been for the past 50 years and this model has become incongruent with the contemporary context, especially in the COVID-19 era. This review aims to describe the historical foundations of cardiac rehabilitation to inform solutions and meet the demands of contemporary MI management. Delivering health systems reform to address modernization is current healthcare challenge where a united and interdisciplinary effort is needed.

AimsCardiac rehabilitation (CR) is an evidence-based intervention promoting risk factor modification following coronary artery disease events but the relative benefits for patient subgroups is not clear. This review synthesizes the available evidence on the effectiveness of modern CR programs and determines outcomes for age, sex and prior level of fitness.MethodsMEDLINE, CINAHL, and EMBASE were examined for RCT and cohort studies involving exercise prescription or phase II or III CR following Myocardial Infarction (MI), Percutaneous Coronary Intervention (PCI) and cardiac surgery from January 2010 to February 2021. Outcomes assessed included peakVO2max, 6-min walk test and Metabolic Equivalent of Task. Meta-regression was used to determine CR impact for change in fitness and age and sex influences.ResultsThe mean age of study participants was 59.5 years and 82.7% were male. Females, younger people and those of average or above cardiorespiratory fitness were substantially under-represented in data and attendance, with 13% of study groups with a mean age

BackgroundPatients hospitalized with acute coronary syndrome (ACS) or heart failure (HF) are frequently readmitted. This is the first randomized controlled trial of a mobile health intervention that combines telemonitoring and education for inpatients with ACS or HF to prevent readmission. ObjectiveThis study aims to investigate the feasibility, efficacy, and cost-effectiveness of a smartphone app–based model of care (TeleClinical Care [TCC]) in patients discharged after ACS or HF admission. MethodsIn this pilot, 2-center randomized controlled trial, TCC was applied at discharge along with usual care to intervention arm participants. Control arm participants received usual care alone. Inclusion criteria were current admission with ACS or HF, ownership of a compatible smartphone, age ≥18 years, and provision of informed consent. The primary end point was the incidence of unplanned 30-day readmissions. Secondary end points included all-cause readmissions, cardiac readmissions, cardiac rehabilitation completion, medication adherence, cost-effectiveness, and user satisfaction. Intervention arm participants received the app and Bluetooth-enabled devices for measuring weight, blood pressure, and physical activity daily plus usual care. The devices automatically transmitted recordings to the patients’ smartphones and a central server. Thresholds for blood pressure, heart rate, and weight were determined by the treating cardiologists. Readings outside these thresholds were flagged to a monitoring team, who discussed salient abnormalities with the patients’ usual care providers (cardiologists, general practitioners, or HF outreach nurses), who were responsible for further management. The app also provided educational push notifications. Participants were followed up after 6 months. ResultsOverall, 164 inpatients were randomized (TCC: 81/164, 49.4%; control: 83/164, 50.6%; mean age 61.5, SD 12.3 years; 130/164, 79.3% men; 128/164, 78% admitted with ACS). There were 11 unplanned 30-day readmissions in both groups (P=.97). Over a mean follow-up of 193 days, the intervention was associated with a significant reduction in unplanned hospital readmissions (21 in TCC vs 41 in the control arm; P=.02), including cardiac readmissions (11 in TCC vs 25 in the control arm; P=.03), and higher rates of cardiac rehabilitation completion (20/51, 39% vs 9/49, 18%; P=.03) and medication adherence (57/76, 75% vs 37/74, 50%; P=.002). The average usability rating for the app was 4.5/5. The intervention cost Aus $6028 (US $4342.26) per cardiac readmission saved. When modeled in a mainstream clinical setting, enrollment of 237 patients was projected to have the same expenditure compared with usual care, and enrollment of 500 patients was projected to save approximately Aus $100,000 (approximately US $70,000) annually. ConclusionsTCC was feasible and safe for inpatients with either ACS or HF. The incidence of 30-day readmissions was similar; however, long-term benefits were demonstrated, including fewer readmissions over 6 months, improved medication adherence, and improved cardiac rehabilitation completion. Trial RegistrationAustralian New Zealand Clinical Trials Registry ACTRN12618001547235; https://www.anzctr.org.au/Trial/Registration/TrialReview.aspx?id=375945

Concordant assessments of physical activity (PA) and related measures in cardiac rehabilitation (CR) is essential for exercise prescription. This study compared exercise measurement from an in-person walk test; wearable activity tracker; and self-report at CR entry, completion (8-weeks) and follow-up (16-weeks). Forty patients beginning CR completed the Six-Minute Walk Test (6MWT), Physical Activity Scale for the Elderly (PASE), and wore Fitbit-Flex for four consecutive days including two weekend days. The sample mean age was 66 years; 67% were male. Increased exercise capacity at CR completion and follow-up was detected by a 6MWT change in mean distance (39 m and 42 m; p = 0.01, respectively). Increased PA participation at CR completion was detected by Fitbit-Flex mean change in step counts (1794; p = 0.01). Relative changes for Fitbit-Flex step counts and a 6MWT were consistent with previous research, demonstrating Fitbit-Flex’s potential as an outcome measure. With four days of data, Fitbit-Flex had acceptable ICC values in measuring step counts and MVPA minutes. Fitbit-Flex steps and 6MWT meters are more responsive to changes in PA patterns following exposure to a cardiac rehabilitation program than Fitbit-Flex or PASE-estimated moderate–vigorous PA (MVPA) minutes. Fitbit-Flex step counts provide a useful additional measure for assessing PA outside of the CR setting and accounts for day-to-day variations. Two weekend days and two weekdays are needed for Fitbit-Flex to estimate PA levels more precisely.