Wearable technology and the cardiovascular system: the future of patient assessment.

The past decade has seen a dramatic rise in consumer technologies able to monitor a variety of cardiovascular parameters. Such devices initially recorded markers of exercise, but now include physiological and health-care focused measurements. The public are keen to adopt these devices in the belief that they are useful to identify and monitor cardiovascular disease. Clinicians are therefore often presented with health app data accompanied by a diverse range of concerns and queries. Herein, we assess whether these devices are accurate, their outputs validated, and whether they are suitable for professionals to make management decisions. We review underpinning methods and technologies and explore the evidence supporting the use of these devices as diagnostic and monitoring tools in hypertension, arrhythmia, heart failure, coronary artery disease, pulmonary hypertension, and valvular heart disease. Used correctly, they might improve health care and support research.

Video-based AI for beat-to-beat assessment of cardiac function.

Accurate assessment of cardiac function is crucial for the diagnosis of cardiovascular disease1, screening for cardiotoxicity2 and decisions regarding the clinical management of patients with a critical illness3. However, human assessment of cardiac function focuses on a limited sampling of cardiac cycles and has considerable inter-observer variability despite years of training4,5. Here, to overcome this challenge, we present a video-based deep learning algorithm-EchoNet-Dynamic-that surpasses the performance of human experts in the critical tasks of segmenting the left ventricle, estimating ejection fraction and assessing cardiomyopathy. Trained on echocardiogram videos, our model accurately segments the left ventricle with a Dice similarity coefficient of 0.92, predicts ejection fraction with a mean absolute error of 4.1% and reliably classifies heart failure with reduced ejection fraction (area under the curve of 0.97). In an external dataset from another healthcare system, EchoNet-Dynamic predicts the ejection fraction with a mean absolute error of 6.0% and classifies heart failure with reduced ejection fraction with an area under the curve of 0.96. Prospective evaluation with repeated human measurements confirms that the model has variance that is comparable to or less than that of human experts. By leveraging information across multiple cardiac cycles, our model can rapidly identify subtle changes in ejection fraction, is more reproducible than human evaluation and lays the foundation for precise diagnosis of cardiovascular disease in real time. As a resource to promote further innovation, we also make publicly available a large dataset of 10,030 annotated echocardiogram videos.

Yield of whole exome sequencing in undiagnosed patients facing insurance coverage barriers to genetic testing.

BACKGROUND: Despite growing evidence of diagnostic yield and clinical utility of whole exome sequencing (WES) in patients with undiagnosed diseases, there remain significant cost and reimbursement barriers limiting access to such testing. The diagnostic yield and resulting clinical actions of WES for patients who previously faced insurance coverage barriers have not yet been explored. METHODS: We performed a retrospective descriptive analysis of clinical WES outcomes for patients facing insurance coverage barriers prior to clinical WES and who subsequently enrolled in the Undiagnosed Diseases Network (UDN). Clinical WES was completed as a result of participation in the UDN. Payer type, molecular diagnostic yield, and resulting clinical actions were evaluated. RESULTS: Sixty-six patients in the UDN faced insurance coverage barriers to WES at the time of enrollment (67% public payer, 26% private payer). Forty-two of 66 (64%) received insurance denial for clinician-ordered WES, 19/66 (29%) had health insurance through a payer known not to cover WES, and 5/66 (8%) had previous payer denial of other genetic tests. Clinical WES results yielded a molecular diagnosis in 23 of 66 patients (35% [78% pediatric, 65% neurologic indication]). Molecular diagnosis resulted in clinical actions in 14 of 23 patients (61%). CONCLUSIONS: These data demonstrate that a substantial proportion of patients who encountered insurance coverage barriers to WES had a clinically actionable molecular diagnosis, supporting the notion that WES has value as a covered benefit for patients who remain undiagnosed despite objective clinical findings.

The effect of digital physical activity interventions on daily step count: a randomised controlled crossover substudy of the MyHeart Counts Cardiovascular Health Study.

BACKGROUND: Smartphone apps might enable interventions to increase physical activity, but few randomised trials testing this hypothesis have been done. The MyHeart Counts Cardiovascular Health Study is a longitudinal smartphone-based study with the aim of elucidating the determinants of cardiovascular health. We aimed to investigate the effect of four different physical activity coaching interventions on daily step count in a substudy of the MyHeart Counts Study. METHODS: In this randomised, controlled crossover trial, we recruited adults (aged ≥18 years) in the USA with access to an iPhone smartphone (Apple, Cupertino, CA, USA; version 5S or newer) who had downloaded the MyHeart Counts app (version 2.0). After completion of a 1 week baseline period of interaction with the MyHeart Counts app, participants were randomly assigned to receive one of 24 permutations (four combinations of four 7 day interventions) in a crossover design using a random number generator built into the app. Interventions consisted of either daily prompts to complete 10 000 steps, hourly prompts to stand following 1 h of sitting, instructions to read the guidelines from the American Heart Association website, or e-coaching based upon the individual's personal activity patterns from the baseline week of data collection. Participants completed the trial in a free-living setting. Due to the nature of the interventions, participants could not be masked from the intervention. Investigators were not masked to intervention allocation. The primary outcome was change in mean daily step count from baseline for each of the four interventions, assessed in the modified intention-to-treat analysis set, which included all participants who had completed 7 days of baseline monitoring and at least 1 day of one of the four interventions. This trial is registered with ClinicalTrials.gov, NCT03090321. FINDINGS: Between Dec 12, 2016, and June 6, 2018, 2783 participants consented to enrol in the coaching study, of whom 1075 completed 7 days of baseline monitoring and at least 1 day of one of the four interventions and thus were included in the modified intention-to-treat analysis set. 493 individuals completed the full set of assigned interventions. All four interventions significantly increased mean daily step count from baseline (mean daily step count 2914 [SE 74]): mean step count increased by 319 steps (75) for participants in the American Heart Association website prompt group (p<0·0001), 267 steps (74) for participants in the hourly stand prompt group (p=0·0003), 254 steps (74) for participants in the cluster-specific prompts group (p=0·0006), and by 226 steps (75) for participants in the 10 000 daily step prompt group (p=0·0026 vs baseline). INTERPRETATION: Four smartphone-based physical activity coaching interventions significantly increased daily physical activity. These findings suggests that digital interventions delivered via a mobile app have the ability to increase short-term physical activity levels in a free-living cohort. FUNDING: Stanford Data Science Initiative.

Effect of Genetic Diagnosis on Patients with Previously Undiagnosed Disease.

BACKGROUND: Many patients remain without a diagnosis despite extensive medical evaluation. The Undiagnosed Diseases Network (UDN) was established to apply a multidisciplinary model in the evaluation of the most challenging cases and to identify the biologic characteristics of newly discovered diseases. The UDN, which is funded by the National Institutes of Health, was formed in 2014 as a network of seven clinical sites, two sequencing cores, and a coordinating center. Later, a central biorepository, a metabolomics core, and a model organisms screening center were added. METHODS: We evaluated patients who were referred to the UDN over a period of 20 months. The patients were required to have an undiagnosed condition despite thorough evaluation by a health care provider. We determined the rate of diagnosis among patients who subsequently had a complete evaluation, and we observed the effect of diagnosis on medical care. RESULTS: A total of 1519 patients (53% female) were referred to the UDN, of whom 601 (40%) were accepted for evaluation. Of the accepted patients, 192 (32%) had previously undergone exome sequencing. Symptoms were neurologic in 40% of the applicants, musculoskeletal in 10%, immunologic in 7%, gastrointestinal in 7%, and rheumatologic in 6%. Of the 382 patients who had a complete evaluation, 132 received a diagnosis, yielding a rate of diagnosis of 35%. A total of 15 diagnoses (11%) were made by clinical review alone, and 98 (74%) were made by exome or genome sequencing. Of the diagnoses, 21% led to recommendations regarding changes in therapy, 37% led to changes in diagnostic testing, and 36% led to variant-specific genetic counseling. We defined 31 new syndromes. CONCLUSIONS: The UDN established a diagnosis in 132 of the 382 patients who had a complete evaluation, yielding a rate of diagnosis of 35%. (Funded by the National Institutes of Health Common Fund.).

Genotype and Lifetime Burden of Disease in Hypertrophic Cardiomyopathy: Insights from the Sarcomeric Human Cardiomyopathy Registry (SHaRe).

Background: A better understanding of the factors that contribute to heterogeneous outcomes and lifetime disease burden in hypertrophic cardiomyopathy (HCM) is critically needed to improve patient management and outcomes. The Sarcomeric Human Cardiomyopathy Registry (SHaRe) was established to provide the scale of data required to address these issues, aggregating longitudinal datasets curated by eight international HCM specialty centers. Methods: Data on 4591 HCM patients (2763 genotyped), followed for a mean of 5.4±6.9 years (24,791 patient-years; median [interquartile range] 2.9 [0.3-7.9] years) were analyzed regarding cardiac arrest, cardiac transplantation, appropriate implantable cardioverter-defibrillator (ICD) therapy, all-cause death, atrial fibrillation, stroke, New York Heart Association Functional Class III/IV symptoms (all comprising the overall composite endpoint), and left ventricular ejection fraction (LVEF)<35%. Outcomes were analyzed individually and as composite endpoints. Results: Median age of diagnosis was 45.8 [30.9-58.1] years and 37% of patients were female. Age of diagnosis and sarcomere mutation status were predictive of outcomes. Patients <40 years old at diagnosis had a 77% [95% confidence interval: 72%, 80%] cumulative incidence of the overall composite outcome by age 60, compared to 32% [29%, 36%] by age 70 for patients diagnosed >60 years. Young HCM patients (20-29 years) had 4-fold higher mortality than the general United States population at a similar age. Patients with pathogenic/likely pathogenic sarcomere mutations had two-fold greater risk for adverse outcomes compared to patients without mutations; sarcomere variants of uncertain significance were associated with intermediate risk. Heart failure and atrial fibrillation were the most prevalent adverse events, although typically not emerging for several years after diagnosis. Ventricular arrhythmias occurred in 32% [23%, 40%] of patients <40 years at diagnosis, but in 1% [1%, 2%] >60 years. Conclusions: The cumulative burden of HCM is substantial and dominated by heart failure and atrial fibrillation occurring many years following diagnosis. Young age of diagnosis and the presence of a sarcomere mutation are powerful predictors of adverse outcomes. These findings highlight the need for close surveillance throughout life, and the need to develop disease-modifying therapies.

Accuracy in Wrist-Worn, Sensor-Based Measurements of Heart Rate and Energy Expenditure in a Diverse Cohort.

The ability to measure physical activity through wrist-worn devices provides an opportunity for cardiovascular medicine. However, the accuracy of commercial devices is largely unknown. The aim of this work is to assess the accuracy of seven commercially available wrist-worn devices in estimating heart rate (HR) and energy expenditure (EE) and to propose a wearable sensor evaluation framework. We evaluated the Apple Watch, Basis Peak, Fitbit Surge, Microsoft Band, Mio Alpha 2, PulseOn, and Samsung Gear S2. Participants wore devices while being simultaneously assessed with continuous telemetry and indirect calorimetry while sitting, walking, running, and cycling. Sixty volunteers (29 male, 31 female, age 38 ± 11 years) of diverse age, height, weight, skin tone, and fitness level were selected. Error in HR and EE was computed for each subject/device/activity combination. Devices reported the lowest error for cycling and the highest for walking. Device error was higher for males, greater body mass index, darker skin tone, and walking. Six of the devices achieved a median error for HR below 5% during cycling. No device achieved an error in EE below 20 percent. The Apple Watch achieved the lowest overall error in both HR and EE, while the Samsung Gear S2 reported the highest. In conclusion, most wrist-worn devices adequately measure HR in laboratory-based activities, but poorly estimate EE, suggesting caution in the use of EE measurements as part of health improvement programs. We propose reference standards for the validation of consumer health devices (http://precision.stanford.edu/).

A Rapid, High-Quality, Cost-Effective, Comprehensive and Expandable Targeted Next-Generation Sequencing Assay for Inherited Heart Diseases.

RATIONALE: Thousands of mutations across >50 genes have been implicated in inherited cardiomyopathies. However, options for sequencing this rapidly evolving gene set are limited because many sequencing services and off-the-shelf kits suffer from slow turnaround, inefficient capture of genomic DNA, and high cost. Furthermore, customization of these assays to cover emerging targets that suit individual needs is often expensive and time consuming. OBJECTIVE: We sought to develop a custom high throughput, clinical-grade next-generation sequencing assay for detecting cardiac disease gene mutations with improved accuracy, flexibility, turnaround, and cost. METHODS AND RESULTS: We used double-stranded probes (complementary long padlock probes), an inexpensive and customizable capture technology, to efficiently capture and amplify the entire coding region and flanking intronic and regulatory sequences of 88 genes and 40 microRNAs associated with inherited cardiomyopathies, congenital heart disease, and cardiac development. Multiplexing 11 samples per sequencing run resulted in a mean base pair coverage of 420, of which 97% had >20× coverage and >99% were concordant with known heterozygous single nucleotide polymorphisms. The assay correctly detected germline variants in 24 individuals and revealed several polymorphic regions in miR-499. Total run time was 3 days at an approximate cost of $100 per sample. CONCLUSIONS: Accurate, high-throughput detection of mutations across numerous cardiac genes is achievable with complementary long padlock probe technology. Moreover, this format allows facile insertion of additional probes as more cardiomyopathy and congenital heart disease genes are discovered, giving researchers a powerful new tool for DNA mutation detection and discovery.

Cardiopulmonary responses and prognosis in hypertrophic cardiomyopathy: a potential role for comprehensive noninvasive hemodynamic assessment.

OBJECTIVES: This study sought to discover the key determinants of exercise capacity, maximal oxygen consumption (oxygen uptake [Vo2]), and ventilatory efficiency (ventilation/carbon dioxide output [VE/Vco2] slope) and assess the prognostic potential of metabolic exercise testing in hypertrophic cardiomyopathy (HCM). BACKGROUND: The intrinsic mechanisms leading to reduced functional tolerance in HCM are unclear. METHODS: The study sample included 156 HCM patients consecutively enrolled from January 1, 2007 to January 1, 2012 with a complete clinical assessment, including rest and stress echocardiography and cardiopulmonary exercise test (CPET) with impedance cardiography. Patients were also followed for the composite outcome of cardiac-related death, heart transplant, and functional deterioration leading to septal reduction therapy (myectomy or septal alcohol ablation). RESULTS: Abnormalities in CPET responses were frequent, with 39% (n = 61) of the sample showing a reduced exercise tolerance (Vo2 max <80% of predicted) and 19% (n = 30) characterized by impaired ventilatory efficiency (VE/Vco2 slope >34). The variables most strongly associated with exercise capacity (expressed in metabolic equivalents), were peak cardiac index (r = 0.51, p < 0.001), age (r = -0.25, p < 0.01), male sex (r = 0.24, p = 0.02), and indexed right ventricular end-diastolic area (r = 0.31, p = 0.002), resulting in an R(2) of 0.51, p < 0.001. Peak cardiac index was the main predictor of peak Vo2 (r = 0.61, p < 0.001). The variables most strongly related to VE/VCO2 slope were E/E' (r = 0.23, p = 0.021) and indexed left atrial volume index (LAVI) (r = 0.34, p = 0.005) (model R(2) = 0.15). The composite endpoint occurred in 21 (13%) patients. In an exploratory analysis, 3 variables were independently associated with the composite outcome (mean follow-up 27 ± 11 months): peak Vo2 <80% of predicted (hazard ratio: 4.11; 95% confidence interval [CI]: 1.46 to 11.59; p = 0.008), VE/Vco2 slope >34 (hazard ratio: 3.14; 95% CI: 1.26 to 7.87; p = 0.014), and LAVI >40 ml/m(2) (hazard ratio: 3.32; 95% CI: 1.08 to 10.16; p = 0.036). CONCLUSIONS: In HCM, peak cardiac index is the main determinant of exercise capacity, but it is not significantly related to ventilatory efficiency. Peak Vo2, ventilatory inefficiency, and LAVI are associated with an increased risk of major events in the short-term follow-up.

Future translational applications from the contemporary genomics era: a scientific statement from the American Heart Association.

The field of genetics and genomics has advanced considerably with the achievement of recent milestones encompassing the identification of many loci for cardiovascular disease and variable drug responses. Despite this achievement, a gap exists in the understanding and advancement to meaningful translation that directly affects disease prevention and clinical care. The purpose of this scientific statement is to address the gap between genetic discoveries and their practical application to cardiovascular clinical care. In brief, this scientific statement assesses the current timeline for effective translation of basic discoveries to clinical advances, highlighting past successes. Current discoveries in the area of genetics and genomics are covered next, followed by future expectations, tools, and competencies for achieving the goal of improving clinical care.

Clinical assessment incorporating a personal genome.

BACKGROUND: The cost of genomic information has fallen steeply, but the clinical translation of genetic risk estimates remains unclear. We aimed to undertake an integrated analysis of a complete human genome in a clinical context. METHODS: We assessed a patient with a family history of vascular disease and early sudden death. Clinical assessment included analysis of this patient's full genome sequence, risk prediction for coronary artery disease, screening for causes of sudden cardiac death, and genetic counselling. Genetic analysis included the development of novel methods for the integration of whole genome and clinical risk. Disease and risk analysis focused on prediction of genetic risk of variants associated with mendelian disease, recognised drug responses, and pathogenicity for novel variants. We queried disease-specific mutation databases and pharmacogenomics databases to identify genes and mutations with known associations with disease and drug response. We estimated post-test probabilities of disease by applying likelihood ratios derived from integration of multiple common variants to age-appropriate and sex-appropriate pre-test probabilities. We also accounted for gene-environment interactions and conditionally dependent risks. FINDINGS: Analysis of 2.6 million single nucleotide polymorphisms and 752 copy number variations showed increased genetic risk for myocardial infarction, type 2 diabetes, and some cancers. We discovered rare variants in three genes that are clinically associated with sudden cardiac death-TMEM43, DSP, and MYBPC3. A variant in LPA was consistent with a family history of coronary artery disease. The patient had a heterozygous null mutation in CYP2C19 suggesting probable clopidogrel resistance, several variants associated with a positive response to lipid-lowering therapy, and variants in CYP4F2 and VKORC1 that suggest he might have a low initial dosing requirement for warfarin. Many variants of uncertain importance were reported. INTERPRETATION: Although challenges remain, our results suggest that whole-genome sequencing can yield useful and clinically relevant information for individual patients. FUNDING: National Institute of General Medical Sciences; National Heart, Lung And Blood Institute; National Human Genome Research Institute; Howard Hughes Medical Institute; National Library of Medicine, Lucile Packard Foundation for Children's Health; Hewlett Packard Foundation; Breetwor Family Foundation.

Cost-effectiveness of preparticipation screening for prevention of sudden cardiac death in young athletes.

BACKGROUND: Inclusion of 12-lead electrocardiography (ECG) in preparticipation screening of young athletes is controversial because of concerns about cost-effectiveness. OBJECTIVE: To evaluate the cost-effectiveness of ECG plus cardiovascular-focused history and physical examination compared with cardiovascular-focused history and physical examination alone for preparticipation screening. DESIGN: Decision-analysis, cost-effectiveness model. DATA SOURCES: Published epidemiologic and preparticipation screening data, vital statistics, and other publicly available data. TARGET POPULATION: Competitive athletes in high school and college aged 14 to 22 years. TIME HORIZON: Lifetime. PERSPECTIVE: Societal. INTERVENTION: Nonparticipation in competitive athletic activity and disease-specific treatment for identified athletes with heart disease. OUTCOME MEASURE: Incremental health care cost per life-year gained. RESULTS OF BASE-CASE ANALYSIS: Addition of ECG to preparticipation screening saves 2.06 life-years per 1000 athletes at an incremental total cost of $89 per athlete and yields a cost-effectiveness ratio of $42 900 per life-year saved (95% CI, $21 200 to $71 300 per life-year saved) compared with cardiovascular-focused history and physical examination alone. Compared with no screening, ECG plus cardiovascular-focused history and physical examination saves 2.6 life-years per 1000 athletes screened and costs $199 per athlete, yielding a cost-effectiveness ratio of $76 100 per life-year saved ($62 400 to $130 000). RESULTS OF SENSITIVITY ANALYSIS: Results are sensitive to the relative risk reduction associated with nonparticipation and the cost of initial screening. LIMITATIONS: Effectiveness data are derived from 1 major European study. Patterns of causes of sudden death may vary among countries. CONCLUSION: Screening young athletes with 12-lead ECG plus cardiovascular-focused history and physical examination may be cost-effective. PRIMARY FUNDING SOURCE: Stanford Cardiovascular Institute and the Breetwor Foundation.

A new era in clinical genetic testing for hypertrophic cardiomyopathy.

Building on seminal studies of the last 20 years, genetic testing for hypertrophic cardiomyopathy (HCM) has become a clinical reality in the form of targeted exonic sequencing of known disease-causing genes. This has been driven primarily by the decreasing cost of sequencing, but the high profile of genome-wide association studies, the launch of direct-to-consumer genetic testing, and new legislative protection have also played important roles. In the clinical management of hypertrophic cardiomyopathy, genetic testing is primarily used for family screening. An increasing role is recognized, however, in diagnostic settings: in the differential diagnosis of HCM; in the differentiation of HCM from hypertensive or athlete's heart; and more rarely in preimplantation genetic diagnosis. Aside from diagnostic clarification and family screening, use of the genetic test for guiding therapy remains controversial, with data currently too limited to derive a reliable mutation risk prediction from within the phenotypic noise of different modifying genomes. Meanwhile, the power of genetic testing derives from the confidence with which a mutation can be called present or absent in a given individual. This confidence contrasts with our more limited ability to judge the significance of mutations for which co-segregation has not been demonstrated. These variants of "unknown" significance represent the greatest challenge to the wider adoption of genetic testing in HCM. Looking forward, next-generation sequencing technologies promise to revolutionize the current approach as whole genome sequencing will soon be available for the cost of today's targeted panel. In summary, our future will be characterized not by lack of genetic information but by our ability to effectively parse it.

Perioperative cardiac risk: pathophysiology, assessment and management.

Cardiac complications are the leading cause of perioperative morbidity and mortality following noncardiac surgery. The annual cost of perioperative cardiovascular events exceeds 20 billion US dollars. A strategic preoperative evaluation holds the potential to reduce perioperative cardiac events and healthcare costs; however, our current understanding of the pathophysiological basis of postoperative acute coronary syndromes is limited. Although significant advances continue to facilitate early and reliable noninvasive detection of high-risk coronary anatomy, the most appropriate interventions remain unclear. Pharmacotherapy, revascularization, safer anesthesia and early detection of perioperative heart failure may all reduce perioperative morbidity and mortality, although the evidence base is incomplete and controversial. A close working relationship between the primary care physician, cardiologist, surgeon and anesthesiologist will facilitate rational, tailored and optimized management decisions that constitute our best opportunity to reduce perioperative cardiovascular risk.

Preoperative cardiac evaluation: mechanisms, assessment, and reduction of risk.

The changing paradigm in cardiovascular disease in which atherosclerotic lesions exist in a spectrum of stable to unstable, the lack of a perfect prediction tool, and the paucity of randomized controlled data on appropriate intervention make protection of cardiac patients undergoing thoracic surgery challenging. Nociception-related sympathetic drive combines with inflammatory stimuli and the cardiodepressant effects of anesthesia to create a window of maximum risk in the early postoperative period (8-24 hours), and although multivariate models have shown that a combination of surgery-specific risk, patient-specific cardiovascular history, and estimated functional capacity best determine the need for further investigation, the optimal choice of investigation is unclear. Exercise or dobutamine stress echocardiography provide the best validated investigations, and in the case of poor images, dobutamine MR imaging is increasingly used. When disease is found, medical and interventional options are available. PCI is often used, but the risk of converting a stable flow-limiting lesion into a less stable non-flow-limiting lesion must be considered, along with a delay for anti-platelet therapy and endothelialization of the stent. Alternatively, medical protection with acute beta-blockade or alpha2-agonists reduces risk (although beta-blockade often is avoided in chronic lung disease, even nonselective agents are safe in patients with non-airways reactive COPD). In addition, it is likely that statin use reduces risk, probably by stabilizing plaques, but patients with cardiac risk are increasingly likely to be taking this medication already. The assessment and management of cardiac risk in the perioperative thoracic surgery patient is challenging. With focused, rational, and individually tailored management; tight monitoring of postoperative pain; and a close working relationship between the surgeon, anesthesiologist, and cardiologist, patient care can be optimized, and risk can be effectively controlled.