A simplified approach to identification of risk status in patients with atherosclerotic cardiovascular disease

OBJECTIVE

The 2018 American Heart Association/American College of Cardiology (AHA/ACC) Blood Cholesterol Guideline recommendation to classify patients with atherosclerotic cardiovascular disease (ASCVD) as very high-risk (VHR) vs not-VHR (NVHR) has important implications for escalation of medical therapy. We aimed to define the prevalence and clinical characteristics of these two groups within a large multi-state healthcare system and develop a simpler means to assist clinicians in identifying VHR patients using classification and regression tree (CART) analysis.

METHODS

We performed a retrospective analysis of all patients in a 28-hospital US healthcare system in 2018. ICD-10 codes were used to define the ASCVD population. Per the AHA/ACC Guideline, VHR status was defined by ≥2 major ASCVD events or 1 major ASCVD event and ≥2 high-risk conditions. CART analysis was performed on training and validation datasets. A random forest model was used to verify results.

RESULTS

Of 180,669 ASCVD patients identified, 58% were VHR. Among patients with a history of myocardial infarction (MI) or recent acute coronary syndrome (ACS), 99% and 96% were classified as VHR, respectively. Both CART and random forest models identified recent ACS, ischemic stroke, hypertension, peripheral artery disease, history of MI, and age as the most important predictors of VHR status. Using five rules identified by CART analysis, fewer than 50% of risk factors were required to assign VHR status.

CONCLUSION

CART analysis helped to streamline the identification of VHR patients based on a limited number of rules and risk factors. This approach may help improve clinical decision making by simplifying ASCVD risk assessment at the point of care. Further validation is needed, however, in more diverse populations.

The Use of Blood Biomarkers in Precision Medicine for the Primary Prevention of Atherosclerotic Cardiovascular Disease: a Review

Introduction

A biomarker is a substance, structure, or process that indicates the presence of a disease, infection, or environmental exposure. Clinically useful biomarkers are measurable, improve diagnostic or prognostic performance, and ultimately aid clinicians in determining the initiation, duration, or magnitude of therapy.

Areas Covered

The purpose of this review is to explore the roles of various blood biomarkers of atherosclerotic cardiovascular disease (ASCVD) and how their use may improve the precision with which clinicians can identify, treat, and ultimately prevent ASCVD. Our review will include lipid biomarkers, markers of cardiac injury and wall stress, markers of inflammation, and a few others.

Expert Opinion

Several biomarkers have recently been highlighted as "risk-enhancing factors" in the 2019 American College of Cardiology/American Heart Association Guideline for the Primary Prevention of ASCVD, which can help guide shared decision-making. These included elevated low-density lipoprotein cholesterol, triglycerides, lipoprotein(a), apolipoprotein B, or high-sensitivity C-reactive protein. However, some other biomarkers mentioned in this review are not commonly used despite showing initial promise as prognostic of ASCVD risk, as it is not clear how treatment decisions should be changed after their measurement among asymptomatic individuals. Future studies should focus on whether biomarker-directed management strategies can improve clinical outcomes.

Health Information Technology Use Among Persons With Self-reported Atherosclerotic Cardiovascular Disease: Analysis of the 2011-2018 National Health Interview Survey

BACKGROUND

Atherosclerotic cardiovascular disease (ASCVD) is the leading cause of morbidity and mortality in the United States. Health information technologies (HITs) have recently emerged as a viable intervention to mitigate the burden of ASCVD. Approximately 60% of US adults report searching the internet for health information; however, previous research has not examined the prevalence of general technology or HIT use among adults with and without ASCVD. In addition, social determinants in HIT use among adults with ASCVD are not well understood.

OBJECTIVE

The aim of this study was to evaluate the prevalence and social determinants of HIT use among US adults with versus without self-reported ASCVD.

METHODS

We pooled cross-sectional data from the 2011-2018 National Health Interview Survey (NHIS) to examine the general technology and HIT use among adults aged ≥18 years with and without self-reported ASCVD (coronary heart disease, stroke, or both). General technology use was defined as mobile phone ownership, internet use, and computer use. HIT use was defined as looking up health information on the internet, filling a web-based prescription, scheduling a medical appointment on the internet, communicating with a health care provider by email, or using web-based group chats to learn about health topics. We evaluated sociodemographic differences in HIT use among respondents by using Poisson regression. Analyses were weighted according to NHIS standards.

RESULTS

A total sample of 256,117 individuals were included, of which 2194 (0.9%) reported prior ASCVD. Among adults with prior ASCVD, the mean age was 70.6 (SD 11.5) years, and 47.4% (1048/2194) of the adults were females. General technology use differed between participants with and without prior ASCVD, with 36.0% (614/1826) and 76.2% (157,642/213,816) indicating internet usage and 24.6% (374/1575) and 60.7% (107,742/184,557) indicating using a computer every day, respectively. Similarly, adults with ASCVD were less likely to use HIT than those without ASCVD (515/2194, 25.1% vs 123,966/253,923, 51.0%; P<.001). Among adults with prior ASCVD, social determinants that were associated with HIT use included younger age, higher education, higher income, being employed, and being married.

CONCLUSIONS

HIT use was low among adults with a history of ASCVD, which may represent a barrier to delivering care via emerging HIT. Given the associations with social determinants such as income, education, and employment, targeted strategies and policies are needed to eliminate barriers to impact HIT usage.

Smart wearable devices in cardiovascular care: where we are and how to move forward

Technological innovations reach deeply into our daily lives and an emerging trend supports the use of commercial smart wearable devices to manage health. In the era of remote, decentralized and increasingly personalized patient care, catalysed by the COVID-19 pandemic, the cardiovascular community must familiarize itself with the wearable technologies on the market and their wide range of clinical applications. In this Review, we highlight the basic engineering principles of common wearable sensors and where they can be error-prone. We also examine the role of these devices in the remote screening and diagnosis of common cardiovascular diseases, such as arrhythmias, and in the management of patients with established cardiovascular conditions, for example, heart failure. To date, challenges such as device accuracy, clinical validity, a lack of standardized regulatory policies and concerns for patient privacy are still hindering the widespread adoption of smart wearable technologies in clinical practice. We present several recommendations to navigate these challenges and propose a simple and practical 'ABCD' guide for clinicians, personalized to their specific practice needs, to accelerate the integration of these devices into the clinical workflow for optimal patient care.

Assessment of Coronary Artery Calcium Scoring to Guide Statin Therapy Allocation According to Risk-Enhancing Factors: The Multi-Ethnic Study of Atherosclerosis

Importance

The 2018 American Heart Association/American College of Cardiology Guideline on the Management of Blood Cholesterol recommends the use of risk-enhancing factor assessment and the selective use of coronary artery calcium (CAC) scoring to guide the allocation of statin therapy among individuals with an intermediate risk of atherosclerotic cardiovascular disease (ASCVD).

Objective

To examine the association between risk-enhancing factors and incident ASCVD by CAC burden among those at intermediate risk of ASCVD.

Design, Setting, and Participants

The Multi-Ethnic Study of Atherosclerosis is a multicenter population-based prospective cross-sectional study conducted in the US. Baseline data for the present study were collected between July 15, 2000, and July 14, 2002, and follow-up for incident ASCVD events was ascertained through August 20, 2015. Participants were aged 45 to 75 years with no clinical ASCVD or diabetes at baseline, were at intermediate risk of ASCVD (≥7.5% to <20.0%), and had a low-density lipoprotein cholesterol level of 70 to 189 mg/dL.

Exposures

Family history of premature ASCVD, premature menopause, metabolic syndrome, chronic kidney disease, lipid and inflammatory biomarkers, and low ankle-brachial index.

Main Outcomes and Measures

Incident ASCVD over a median follow-up of 12.0 years.

Results

A total of 1688 participants (mean [SD] age, 65 [6] years; 976 men [57.8%]). Of those, 648 individuals (38.4%) were White, 562 (33.3%) were Black, 305 (18.1%) were Hispanic, and 173 (10.2%) were Chinese American. A total of 722 participants (42.8%) had a CAC score of 0. Among those with 1 to 2 risk-enhancing factors vs those with 3 or more risk-enhancing factors, the prevalence of a CAC score of 0 was 45.7% vs 40.3%, respectively. Over a median follow-up of 12.0 years (interquartile range [IQR], 11.5-12.6 years), the unadjusted incidence rate of ASCVD among those with a CAC score of 0 was less than 7.5 events per 1000 person-years for all individual risk-enhancing factors (with the exception of ankle-brachial index, for which the incidence rate was 10.4 events per 1000 person-years [95% CI, 1.5-73.5]) and combinations of risk-enhancing factors, including participants with 3 or more risk-enhancing factors. Although the individual and composite addition of risk-enhancing factors to the traditional risk factors was associated with improvement in the area under the receiver operating curve, the use of CAC scoring was associated with the greatest improvement in the C statistic (0.633 vs 0.678) for ASCVD events. For incident ASCVD, the net reclassification improvement for CAC was 0.067.

Conclusions and Relevance

In this cross-sectional study, among participants with CAC scores of 0, the presence of risk-enhancing factors was generally not associated with an overall ASCVD risk that was higher than the recommended treatment threshold for the initiation of statin therapy. The use of CAC scoring was associated with significant improvements in the reclassification and discrimination of incident ASCVD. The results of this study support the utility of CAC scoring as an adjunct to risk-enhancing factor assessment to more accurately classify individuals with an intermediate risk of ASCVD who might benefit from statin therapy.

Understanding myocardial infarction trends during the early COVID-19 pandemic: an infodemiology study

During the first months of the coronavirus disease 2019 (COVID‐19) pandemic in early 2020, Google Trends data in the United States showed a strong increase in search query frequency for chest pain symptoms despite a concurrent decrease in search interest for myocardial infarction. This suggests a reduced attention to acute coronary syndrome (ACS) and chest pain as its main symptom during this time period. These observations could help explain why cardiovascular mortality rose dramatically despite a strong decrease in hospitalisation rates for ACS.

Digital Health Intervention in Acute Myocardial Infarction

BACKGROUND

Thirty-day readmissions among patients with acute myocardial infarction (AMI) contribute to the US health care burden of preventable complications and costs. Digital health interventions (DHIs) may improve patient health care self-management and outcomes. We aimed to determine if patients with AMI using a DHI have lower 30-day unplanned all-cause readmissions than a historical control.

METHODS

This nonrandomized controlled trial with a historical control, conducted at 4 US hospitals from 2015 to 2019, included 1064 patients with AMI (DHI n=200, control n=864). The DHI integrated a smartphone application, smartwatch, and blood pressure monitor to support guideline-directed care during hospitalization and through 30-days post-discharge via (1) medication reminders, (2) vital sign and activity tracking, (3) education, and (4) outpatient care coordination. The Patient Activation Measure assessed patient knowledge, skills, and confidence for health care self-management. All-cause 30-day readmissions were measured through administrative databases. Propensity score-adjusted Cox proportional hazard models estimated hazard ratios of readmission for the DHI group relative to the control group.

RESULTS

Following propensity score adjustment, baseline characteristics were well-balanced between the DHI versus control patients (standardized differences <0.07), including a mean age of 59.3 versus 60.1 years, 30% versus 29% Women, 70% versus 70% White, 54% versus 54% with private insurance, 61% versus 60% patients with a non ST-elevation myocardial infarction, and 15% versus 15% with high comorbidity burden. DHI patients were predominantly in the highest levels of patient activation for health care self-management (mean score 71.7±16.6 at 30 days). The DHI group had fewer all-cause 30-day readmissions than the control group (6.5% versus 16.8%, respectively). Adjusting for hospital site and a propensity score inclusive of age, sex, race, AMI type, comorbidities, and 6 additional confounding factors, the DHI group had a 52% lower risk for all-cause 30-day readmissions (hazard ratio, 0.48 [95% CI, 0.26-0.88]). Similar results were obtained in a sensitivity analysis employing propensity matching.

CONCLUSIONS

Our results suggest that in patients with AMI, the DHI may be associated with high patient activation for health care self-management and lower risk of all-cause unplanned 30-day readmissions. Registration: URL: https://www.clinicaltrials.gov; Unique identifier: NCT03760796.

Interprofessional education and collaboration among healthcare students and professionals: a systematic review and call for action

Interprofessional education (IPE) is a prerequisite to building a collaborative practice environment and optimizing patient care. The purpose of this systematic review was to assess the impact of IPE on outcomes related to health-care pre-licensure learners and professionals, including: changes in attitudes/perceptions; acquisition of knowledge regarding other disciplines' roles and development of collaborative skills; and change in collaborative behavior. We searched PubMed, CINAHL, Embase, and ERIC for studies published from 2007 to 2017 in English; 19 studies were eligible. The Joanna Briggs Institute appraisal tool was used to assess the quality of the studies. Thirteen studies used a quasi-experimental design. The studies varied in terms of setting, teaching methods, assessment measures, and quality. Seventeen of the 19 studies (89%) that assessed change in attitudes toward other disciplines and value placed on a team-based approach for improving patient care, found statistically significant improvements. All seven of the studies that assessed change in collaborative behavior found statistically significant improvements. Among the 12 studies that assessed the development of collaborative skills, there were mixed results. Future directions include: conducting more studies among health-care professionals, assessing the long-term impact of IPE, objectively assessing change in collaborative behavior, and assessing the impact of IPE on patient-centered outcomes.

Sociodemographic Characteristics Predicting Digital Health Intervention Use After Acute Myocardial Infarction

Increasing evidence suggests that digital health interventions (DHIs) are an effective tool to reduce hospital readmissions by improving adherence to guideline-directed therapy. We investigated whether sociodemographic characteristics influence use of a DHI targeting 30-day readmission reduction after acute myocardial infarction (AMI). Covariates included age, sex, race, native versus loaner iPhone, access to a Bluetooth-enabled blood pressure monitor, and disease severity as marked by treatment with CABG. Age, sex, and race were not significantly associated with DHI use before or after covariate adjustment (fully adjusted OR 0.98 (95%CI: 0.95-1.01), 0.6 (95%CI: 0.29-1.25), and 1.22 (95% CI: 0.60-2.48), respectively). Being married was associated with high DHI use (OR 2.12; 95% CI 1.02-4.39). Our findings suggest that DHIs may have a role in achieving equity in cardiovascular health given similar use by age, sex, and race. The presence of a spouse, perhaps a proxy for enhanced caregiver support, may encourage DHI use.

Multidisciplinary prevention and management strategies for colorectal cancer and cardiovascular disease

Colorectal cancer (CRC) and cardiovascular disease (CVD) are leading causes of morbidity and mortality worldwide. Their numerous shared and modifiable risk factors underscore the importance of effective prevention strategies for these largely preventable diseases. Conventionally regarded as separate disease entities, clear pathophysiological links and overlapping risk factors represent an opportunity for synergistic collaborative efforts of oncologists and cardiologists. In addition, current CRC treatment approaches can exert cardiotoxicity and thus increase CVD risk. Given the complex interplay of both diseases and increasing numbers of CRC survivors who are at increased risk for CVD, multidisciplinary cardio-oncological approaches are warranted for optimal patient care from primary prevention to acute disease treatment and long-term surveillance.

A Mobile Health Intervention to Increase Physical Activity in Pulmonary Arterial Hypertension

BACKGROUND

Supervised exercise training improves outcomes in patients with pulmonary arterial hypertension (PAH). The effect of an unsupervised activity intervention has not been tested.

RESEARCH QUESTION

Can a text-based mobile health intervention increase step counts in patients with PAH?

STUDY DESIGN AND METHODS

We performed a randomized, parallel arm, single-blind clinical trial. We randomized patients to usual care or a text message-based intervention for 12 weeks. The intervention arm received three automated text messages per day with real-time step count updates and encouraging messages rooted in behavioral change theory. Individual step targets increased by 20% every 4 weeks. The primary end point was mean week 12 step counts. Secondary end points included the 6-min walk test, quality of life, right ventricular function, and body composition.

RESULTS

Among 42 randomized participants, the change in raw steps between baseline and week 12 was higher in the intervention group (1,409 steps [interquartile range, -32 to 2,220] vs -149 steps [interquartile range, -1,010 to 735]; P = .02), which persisted after adjustment for age, sex, baseline step counts, and functional class (model estimated difference, 1,250 steps; P = .03). The intervention arm took a higher average number of steps on all days between days 9 and 84 (P < .05, all days). There was no difference in week 12 six-minute walk distance. Analysis of secondary end points suggested improvements in the emPHasis-10 score (adjusted change, -4.2; P = .046), a reduction in visceral fat volume (adjusted change, -170 mL; P = .023), and nearly significant improvement in tricuspid annular plane systolic excursion (model estimated difference, 1.2 mm; P = .051).

INTERPRETATION

This study demonstrated the feasibility of an automated text message-based intervention to increase physical activity in patients with PAH. Additional studies are warranted to examine the effect of the intervention on clinical outcomes.

CLINICAL TRIAL REGISTRATION

ClinicalTrials.gov; No. NCT03069716; URL: www.clinicaltrials.gov.

Coronary heart disease risk: Low-density lipoprotein and beyond

Coronary heart disease (CHD) is the leading cause of morbidity and mortality world-wide and has been characterized as a chronic immunoinflammatory, fibroproliferative disease fueled by lipids. Great advances have been made in elucidating the complex mechanistic interactions among risk factors associated with CHD, yielding abundant success towards preventive measures and the development of pharmaceuticals to prevent and treat CHD via attenuation of lipoprotein-mediated risk. However, significant residual risk remains. Several potentially modifiable CHD risk factors ostensibly contributing to this residual risk have since come to the fore, including systemic inflammation, diabetes mellitus, high-density lipoprotein, plasma triglycerides (TG) and remnant lipoproteins (RLP), lipoprotein(a) (Lp[a]), and vascular endothelial dysfunction (ED). Herein, we summarize the body of evidence implicating each of these risk factors in residual CHD risk.

Life's Simple 7 and Nonalcoholic Fatty Liver Disease: The Multiethnic Study of Atherosclerosis

BACKGROUND

The American Heart Association (AHA) has defined Life's Simple 7 (LS7) as a measure of overall cardiovascular health . Nonalcoholic fatty liver disease (NAFLD) has been involved as a risk factor for cardiovascular disease. We evaluated the association between LS7 and NAFLD.

METHODS

We evaluated participants form the Multi-Ethnic Study of Atherosclerosis (MESA) cohort. Cardiovascular health score was calculated from the Life's Simple 7 metrics. A score of 0-8 was considered inadequate, 9-10 average, and 11-14 optimal. NAFLD was defined using noncontrast cardiac computed tomography (CT) and a liver/spleen attenuation ratio (L/S) < 1. Multivariable regression were performed to evaluate the association.

RESULTS

Our cross-sectional analysis of 3901 participants showed 19% (n = 747) had optimal cardiovascular health, 33% (n = 1270) had average, and 48% (n = 1884) had inadequate. White participants were most likely to have an optimal score (51%, n = 378), whereas African American participants had the lowest proportion with optimal scores (16%, n = 120; P < 0.001). The overall prevalence of NAFLD was 18% with a distribution of 7%, 14%, and 25% in the optimal, average, and inadequate score categories, respectively (P < 0.001). Adjusted for risk factors, average and optimal health categories had lower odds of NAFLD compared to those with inadequate scores: odds ratio for average, 0.44 (95% confidence interval 0.36-0.54); optimal, odds ratio 0.19 (95% confidence interval 0.14-0.26). This association was similar across gender, race and age groups.

CONCLUSION

A more favorable cardiovascular health score was associated with a lower prevalence of NAFLD. This study may suggest a potential of Life's Simple 7 in the prevention of liver disease.

Conventional and Novel Lipid Measures and Risk of Peripheral Artery Disease

OBJECTIVE

The aim of this study was to comprehensively assess the association of multiple lipid measures with incident peripheral artery disease (PAD). Approach and Results: We used Cox proportional hazards models to characterize the associations of each of the fasting lipid measures (total cholesterol, LDL-C [low-density lipoprotein cholesterol], HDL-C [high-density lipoprotein cholesterol], triglycerides, RLP-C [remnant lipoprotein cholesterol], LDL-TG [LDL-triglycerides], sdLDL-C [small dense LDL-C], and Apo-E-HDL [Apo-E-containing HDL-C]) with incident PAD identified by pertinent International Classification of Diseases, Ninth Revision, Clinical Modification (ICD-9-CM) hospital discharge codes (eg, 440.2) among 8330 Black and White ARIC (Atherosclerosis Risk in Communities) participants (mean age 62.8 [SD 5.6] years) free of PAD at baseline (1996-1998) through 2015. Since lipid traits are biologically correlated to each other, we also conducted principal component analysis to identify underlying components for PAD risk. There were 246 incident PAD cases with a median follow-up of 17 years. After accounting for potential confounders, the following lipid measures were significantly associated with PAD (hazard ratio per 1-SD increment [decrement for HDL-C and Apo-E-HDL]): triglycerides, 1.21 (95% CI, 1.08-1.36); RLP-C, 1.18 (1.08-1.29); LDL-TG, 1.18 (1.05-1.33); HDL-C, 1.39 (1.16-1.67); and Apo-E-HDL, 1.27 (1.07-1.51). The principal component analysis identified 3 components (1: mainly loaded by triglycerides, RLP-C, LDL-TG, and sdLDL-C; 2: by HDL-C and Apo-E-HDL; and 3: by LDL-C and RLP-C). Components 1 and 2 showed independent associations with incident PAD.

CONCLUSIONS

Triglyceride-related and HDL-related lipids were independently associated with incident PAD, which has implications on preventive strategies for PAD. However, none of the novel lipid measures outperformed conventional ones. Graphic Abstract: A graphic abstract is available for this article.

Opportunities to improve cardiovascular health in the new American workplace

Adult working-class Americans spend on average 50% of their workday awake time at their jobs. The vast majority of these jobs involve mostly physically inactive tasks and frequent exposure to unhealthy food options. Traditionally, the workplace has been a challenging environment for cardiovascular prevention, where cardiovascular guidelines have had limited implementation. Despite the impact that unhealthy lifestyles at the workplace may have on the cardiovascular health of U.S. workers, there is currently no policy in place aimed at improving this. In this review, we discuss recent evidence on the prevalence of physical inactivity among Americans, with a special focus on the time spent at the workplace; and the invaluable opportunity that workplace-based lifestyle interventions may represent for improving the prevention of cardiovascular disease. We describe the current regulatory context, the key stakeholders involved, and present specific, guideline-inspired initiatives to be considered by both Congress and employers to improve the "cardiovascular safety" of US jobs. Additionally, we discuss how the COVID-19 pandemic has forever altered the workplace, and what lessons can be taken from this experience and applied to cardiovascular disease prevention in the new American workplace. For many Americans, long sitting hours at their job represent a risk to their cardiovascular health. We discuss how a paradigm shift in how we approach cardiovascular health, from focusing on leisure time to also focusing on work time, may help curtail the epidemic of cardiovascular disease in this country.

Heart Disease and Stroke Statistics-2021 Update: A Report From the American Heart Association

BACKGROUND

The American Heart Association, in conjunction with the National Institutes of Health, annually reports the most up-to-date statistics related to heart disease, stroke, and cardiovascular risk factors, including core health behaviors (smoking, physical activity, diet, and weight) and health factors (cholesterol, blood pressure, and glucose control) that contribute to cardiovascular health. The Statistical Update presents the latest data on a range of major clinical heart and circulatory disease conditions (including stroke, congenital heart disease, rhythm disorders, subclinical atherosclerosis, coronary heart disease, heart failure, valvular disease, venous disease, and peripheral artery disease) and the associated outcomes (including quality of care, procedures, and economic costs).

METHODS

The American Heart Association, through its Statistics Committee, continuously monitors and evaluates sources of data on heart disease and stroke in the United States to provide the most current information available in the annual Statistical Update. The 2021 Statistical Update is the product of a full year's worth of effort by dedicated volunteer clinicians and scientists, committed government professionals, and American Heart Association staff members. This year's edition includes data on the monitoring and benefits of cardiovascular health in the population, an enhanced focus on social determinants of health, adverse pregnancy outcomes, vascular contributions to brain health, the global burden of cardiovascular disease, and further evidence-based approaches to changing behaviors related to cardiovascular disease.

RESULTS

Each of the 27 chapters in the Statistical Update focuses on a different topic related to heart disease and stroke statistics.

CONCLUSIONS

The Statistical Update represents a critical resource for the lay public, policy makers, media professionals, clinicians, health care administrators, researchers, health advocates, and others seeking the best available data on these factors and conditions.

Heart Rate Measurements in Patients with Obstructive Sleep Apnea and Atrial Fibrillation: Prospective Pilot Study Assessing Apple Watch's Agreement With Telemetry Data

Background

Patients with obstructive sleep apnea (OSA) are at a higher risk for atrial fibrillation (AF). Consumer wearable heart rate (HR) sensors may be a means for passive HR monitoring in patients with AF.

Objective

The aim of this study was to assess the Apple Watch’s agreement with telemetry in measuring HR in patients with OSA in AF.

Methods

Patients with OSA in AF were prospectively recruited prior to cardioversion/ablation procedures. HR was sampled every 10 seconds for 60 seconds using telemetry and an Apple Watch concomitantly. Agreement of Apple Watch with telemetry, which is the current gold-standard device for measuring HR, was assessed using mixed effects limits agreement and Lin’s concordance correlation coefficient.

Results

A total of 20 patients (mean 66 [SD 6.5] years, 85% [n=17] male) participated in this study, yielding 134 HR observations per device. Modified Bland–Altman plot revealed that the variability of the paired difference of the Apple Watch compared with telemetry increased as the magnitude of HR measurements increased. The Apple Watch produced regression-based 95% limits of agreement of 27.8 – 0.3 × average HR – 15.0 to 27.8 – 0.3 × average HR + 15.0 beats per minute (bpm) with a mean bias of 27.8 – 0.33 × average HR bpm. Lin’s concordance correlation coefficient was 0.88 (95% CI 0.85-0.91), suggesting acceptable agreement between the Apple Watch and telemetry.

Conclusions

In patients with OSA in AF, the Apple Watch provided acceptable agreement with HR measurements by telemetry. Further studies with larger sample populations and wider range of HR are needed to confirm these findings.

Digital Health Interventions for Cardiac Rehabilitation: Systematic Literature Review

Background

Cardiovascular disease (CVD) is the leading cause of death worldwide. Despite strong evidence supporting the benefits of cardiac rehabilitation (CR), over 80% of eligible patients do not participate in CR. Digital health technologies (ie, the delivery of care using the internet, wearable devices, and mobile apps) have the potential to address the challenges associated with traditional facility-based CR programs, but little is known about the comprehensiveness of these interventions to serve as digital approaches to CR. Overall, there is a lack of a systematic evaluation of the current literature on digital interventions for CR.

Objective

The objective of this systematic literature review is to provide an in-depth analysis of the potential of digital health technologies to address the challenges associated with traditional CR. Through this review, we aim to summarize the current literature on digital interventions for CR, identify the key components of CR that have been successfully addressed through digital interventions, and describe the gaps in research that need to be addressed for sustainable and scalable digital CR interventions.

Methods

Our strategy for identifying the primary literature pertaining to CR with digital solutions (defined as technology employed to deliver remote care beyond the use of the telephone) included a consultation with an expert in the field of digital CR and searches of the PubMed (MEDLINE), Embase, CINAHL, and Cochrane databases for original studies published from January 1990 to October 2018.

Results

Our search returned 31 eligible studies, of which 22 were randomized controlled trials. The reviewed CR interventions primarily targeted physical activity counseling (31/31, 100%), baseline assessment (30/31, 97%), and exercise training (27/31, 87%). The most commonly used modalities were smartphones or mobile devices (20/31, 65%), web-based portals (18/31, 58%), and email-SMS (11/31, 35%). Approximately one-third of the studies addressed the CR core components of nutrition counseling, psychological management, and weight management. In contrast, less than a third of the studies addressed other CR core components, including the management of lipids, diabetes, smoking cessation, and blood pressure.

Conclusions

Digital technologies have the potential to increase access and participation in CR by mitigating the challenges associated with traditional, facility-based CR. However, previously evaluated interventions primarily focused on physical activity counseling and exercise training. Thus, further research is required with more comprehensive CR interventions and long-term follow-up to understand the clinical impact of digital interventions.

User Engagement With Smartphone Apps and Cardiovascular Disease Risk Factor Outcomes: Systematic Review

Background

The use of mobile health (mHealth) interventions, including smartphone apps, for the prevention of cardiovascular disease (CVD) has demonstrated mixed results for obesity, hypercholesterolemia, diabetes, and hypertension management. A major factor attributing to the variation in mHealth study results may be mHealth user engagement.

Objective

This systematic review aims to determine if user engagement with smartphone apps for the prevention and management of CVD is associated with improved CVD health behavior change and risk factor outcomes.

Methods

We conducted a comprehensive search of PubMed, CINAHL, and Embase databases from 2007 to 2020. Studies were eligible if they assessed whether user engagement with a smartphone app used by an individual to manage his or her CVD risk factors was associated with the CVD health behavior change or risk factor outcomes. For eligible studies, data were extracted on study and sample characteristics, intervention description, app user engagement measures, and the relationship between app user engagement and the CVD risk factor outcomes. App user engagement was operationalized as general usage (eg, number of log-ins or usage days per week) or self-monitoring within the app (eg, total number of entries made in the app). The quality of the studies was assessed.

Results

Of the 24 included studies, 17 used a randomized controlled trial design, 4 used a retrospective analysis, and 3 used a single-arm pre- and posttest design. Sample sizes ranged from 55 to 324,649 adults, with 19 studies recruiting participants from a community setting. Most of the studies assessed weight loss interventions, with 6 addressing additional CVD risk factors, including diabetes, sleep, stress, and alcohol consumption. Most of the studies that assessed the relationship between user engagement and reduction in weight (9/13, 69%), BMI (3/4, 75%), body fat percentage (1/2, 50%), waist circumference (2/3, 67%), and hemoglobin A_1c (3/5, 60%) found statistically significant results, indicating that greater app user engagement was associated with better outcomes. Of 5 studies, 3 (60%) found a statistically significant relationship between higher user engagement and an increase in objectively measured physical activity. The studies assessing the relationship between user engagement and dietary and diabetes self-care behaviors, blood pressure, and lipid panel components did not find statistically significant results.

Conclusions

Increased app user engagement for prevention and management of CVD may be associated with improved weight and BMI; however, only a few studies assessed other outcomes, limiting the evidence beyond this. Additional studies are needed to assess user engagement with smartphone apps targeting other important CVD risk factors, including dietary behaviors, hypercholesterolemia, diabetes, and hypertension. Further research is needed to assess mHealth user engagement in both inpatient and outpatient settings to determine the effect of integrating mHealth interventions into the existing clinical workflow and on CVD outcomes.

The role of a clinician amid the rise of mobile health technology

Mobile health (mHealth) interventions have demonstrated promise in improving outcomes by motivating patients to adopt and maintain healthy lifestyle changes as well as improve adherence to guideline-directed medical therapy. Early results combining behavioral economic strategies with mHealth delivery have demonstrated mixed results. In reviewing these studies, we propose that the success of a mHealth intervention links more strongly with how well it connects patients back to routine clinical care, rather than its behavior modification technique in isolation. This underscores the critical role of clinician-patient partnerships in the design and delivery of such interventions, while also raising important questions regarding long-term sustainability and scalability. Further exploration of our hypothesis may increase opportunities for multidisciplinary clinical teams to connect with and engage patients using mHealth technologies in unprecedented ways.

Inflammation and cardiovascular disease: From mechanisms to therapeutics

Inflammation constitutes a complex, highly conserved cascade of molecular and cellular events. Inflammation has been labeled as “the fire within,” is highly regulated, and is critical to host defense and tissue repair. In general, inflammation is beneficial and has evolved to promote survival. However, inflammation can also be maladaptive when chronically activated and sustained, leading to progressive tissue injury and reduced survival. Examples of a maladaptive response include rheumatologic disease and atherosclerosis. Despite evidence gathered by Virchow over 100 years ago showing that inflammatory white cells play a role in atherogenesis, atherosclerosis was until recently viewed as a disease of passive cholesterol accumulation in the subendothelial space. This view has been supplanted by considerable basic scientific and clinical evidence demonstrating that every step of atherogenesis, from the development of endothelial cell dysfunction to foam cell formation, plaque formation and progression, and ultimately plaque rupture stemming from architectural instability, is driven by the cytokines, interleukins, and cellular constituents of the inflammatory response. Herein we provide an overview of the role of inflammation in atherosclerotic cardiovascular disease, discuss the predictive value of various biomarkers involved in inflammation, and summarize recent clinical trials that evaluated the capacity of various pharmacologic interventions to attenuate the intensity of inflammation and impact risk for acute cardiovascular events.

Importance of the triglyceride level in identifying patients with a Type III Hyperlipoproteinemia phenotype using the ApoB algorithm

BACKGROUND

Hyperlipoproteinemia Type III (HLP3), also known as dysbetalipoproteinemia, is defined by cholesterol and triglyceride (TG) enriched remnant lipoprotein particles (RLP). The gold standard for diagnosis requires demonstration of high remnant lipoprotein particle cholesterol (RLP-C) by serum ultracentrifugation (UC), which is not readily available in daily practice. The apoB algorithm can identify HLP3 using total cholesterol (TC), plasma triglyceride (TG), and apoB. However, the optimal TG cutoff is unknown.

OBJECTIVE

We analyzed apoB algorithm defined HLP3 at different TG levels to optimize the TG cutoff for the algorithm.

METHODS

128,485 UC lipid profiles in the Very Large Database of Lipids (VLDbL) were analyzed. RLP-C was assessed at TG ≥ 133 mg/dL, ≥175 mg/dL, ≥200 mg/dL, and ≥ 250 mg/dL. Sensitivity (Sn), specificity (Sp), positive predictive value (PPV), negative predictive value (NPV), and prevalence adjusted and bias-adjusted kappa (PABAK) were calculated against UC Criterion (VLDL-C/TG ≥ 0.25) for HLP3.

RESULTS

The median age (IQR) was 57 years (46-68). 45% were men, 20.1% had diabetes, and 25.5% had hypertension. The median RLP-C level for the TG cutoffs (mg/dL) of ≥ 133, ≥ 175, ≥ 200, and ≥ 250 were 34, 43, 50, and 62 mg/dL, respectively, compared to 67 mg/dL in UC defined HLP3. TG ≥ 133 mg/dL yielded optimal results (Sn 29.5%, Sp 98.5%, PABAK 0.96, PPV 13.6%, NPV 99.4%).

CONCLUSION

TG ≥ 133 mg/dL allows for high sensitivity in screening for HLP3. Higher TG cutoffs may identify more severe HLP3 phenotypes, but with a large loss in sensitivity for HLP3.