Use of Artificial Intelligence in Improving Outcomes in Heart Disease: A Scientific Statement From the American Heart Association.

A major focus of academia, industry, and global governmental agencies is to develop and apply artificial intelligence and other advanced analytical tools to transform health care delivery. The American Heart Association supports the creation of tools and services that would further the science and practice of precision medicine by enabling more precise approaches to cardiovascular and stroke research, prevention, and care of individuals and populations. Nevertheless, several challenges exist, and few artificial intelligence tools have been shown to improve cardiovascular and stroke care sufficiently to be widely adopted. This scientific statement outlines the current state of the art on the use of artificial intelligence algorithms and data science in the diagnosis, classification, and treatment of cardiovascular disease. It also sets out to advance this mission, focusing on how digital tools and, in particular, artificial intelligence may provide clinical and mechanistic insights, address bias in clinical studies, and facilitate education and implementation science to improve cardiovascular and stroke outcomes. Last, a key objective of this scientific statement is to further the field by identifying best practices, gaps, and challenges for interested stakeholders.

Principles for Health Information Collection, Sharing, and Use: A Policy Statement From the American Heart Association.

The evolution of the electronic health record, combined with advances in data curation and analytic technologies, increasingly enables data sharing and harmonization. Advances in the analysis of health-related and health-proxy information have already accelerated research discoveries and improved patient care. This American Heart Association policy statement discusses how broad data sharing can be an enabling driver of progress by providing data to develop, test, and benchmark innovative methods, scalable insights, and potential new paradigms for data storage and workflow. Along with these advances come concerns about the sensitive nature of some health data, equity considerations about the involvement of historically excluded communities, and the complex intersection of laws attempting to govern behavior. Data-sharing principles are therefore necessary across a wide swath of entities, including parties who collect health information, funders, researchers, patients, legislatures, commercial companies, and regulatory departments and agencies. This policy statement outlines some of the key equity and legal background relevant to health data sharing and responsible management. It then articulates principles that will guide the American Heart Association's engagement in public policy related to data collection, sharing, and use to continue to inform its work across the research enterprise, as well as specific examples of how these principles might be applied in the policy landscape. The goal of these principles is to improve policy to support the use or reuse of health information in ways that are respectful of patients and research participants, equitable in impact in terms of both risks and potential benefits, and beneficial across broad and demographically diverse communities in the United States.

Cardiac contractility modulation in patients with heart failure - A review of the literature.

Experimental in vivo and in vitro studies showed that electric currents applied during the absolute refractory period can modulate cardiac contractility. In preclinical studies, cardiac contractility modulation (CCM) was found to improve calcium handling, reverse the foetal myocyte gene programming associated with heart failure (HF), and facilitate reverse remodeling. Randomized control trials and observational studies have provided evidence about the safety and efficacy of CCM in patients with HF. Clinically, CCM therapy is indicated to improve the 6-min hall walk, quality of life, and functional status of HF patients who remain symptomatic despite guideline-directed medical treatment without an indication for cardiac resynchronization therapy (CRT) and have a left ventricular ejection fraction (LVEF) ranging from 25 to 45%. Although there are promising results about the role of CCM in HF patients with preserved LVEF (HFpEF), further studies are needed to elucidate the role of CCM therapy in this population. Late gadolinium enhancement (LGE) assessment before CCM implantation has been proposed for guiding the lead placement. Furthermore, the optimal duration of CCM application needs further investigation. This review aims to present the existing evidence regarding the role of CCM therapy in HF patients and identify gaps and challenges that require further studies.

Fractal dynamics of individual mitochondrial oscillators measure local inter-mitochondrial coupling.

Mitochondrial inner membrane potentials in cardiomyocytes may oscillate in cycles of depolarization/repolarization when the mitochondrial network is exposed to metabolic or oxidative stress. The frequencies of such oscillations are dynamically changing while clusters of weakly coupled mitochondrial oscillators adjust to a common phase and frequency. Across the cardiac myocyte, the averaged signal of the mitochondrial population follows self-similar or fractal dynamics; however, fractal properties of individual mitochondrial oscillators have not yet been examined. We show that the largest synchronously oscillating cluster exhibits a fractal dimension, D, that is indicative of self-similar behavior with D=1.27±0.11, in contrast to the remaining network mitochondria whose fractal dimension is close to that of Brownian noise, D=1.58±0.10. We further demonstrate that fractal behavior is correlated with local coupling mechanisms, whereas it is only weakly linked to measures of functional connections between mitochondria. Our findings suggest that individual mitochondrial fractal dimensions may serve as a simple measure of local mitochondrial coupling.

Use of the inverse solution guidance algorithm method for RF ablation catheter guidance.

INTRODUCTION: We previously introduced the inverse solution guidance algorithm (ISGA) methodology using a Single Equivalent Moving Dipole model of cardiac electrical activity to localize both the exit site of a re-entrant circuit and the tip of a radiofrequency (RF) ablation catheter. The purpose of this study was to investigate the use of ISGA for ablation catheter guidance in an animal model. METHODS: Ventricular tachycardia (VT) was simulated by rapid ventricular pacing at a target site in eleven Yorkshire swine. The ablation target was established using three different techniques: a pacing lead placed into the ventricular wall at the mid-myocardial level (Type-1), an intracardiac mapping catheter (Type-2), and an RF ablation catheter placed at a random position on the endocardial surface (Type-3). In each experiment, one operator placed the catheter/pacing lead at the target location, while another used the ISGA system to manipulate the RF ablation catheter starting from a random ventricular location to locate the target. RESULTS: The average localization error of the RF ablation catheter tip was 0.31 ± 0.08 cm. After analyzing approximately 35 cardiac cycles of simulated VT, the ISGA system's accuracy in locating the target was 0.4 cm after four catheter movements in the Type-1 experiment, 0.48 cm after six movements in the Type-2 experiment, and 0.67 cm after seven movements in the Type-3 experiment. CONCLUSION: We demonstrated the feasibility of using the ISGA method to guide an ablation catheter to the origin of a VT focus by analyzing a few beats of body surface potentials without electro-anatomic mapping.

Machine learning versus conventional clinical methods in guiding management of heart failure patients-a systematic review.

Machine learning (ML) algorithms "learn" information directly from data, and their performance improves proportionally with the number of high-quality samples. The aim of our systematic review is to present the state of the art regarding the implementation of ML techniques in the management of heart failure (HF) patients. We manually searched MEDLINE and Cochrane databases as well the reference lists of the relevant review studies and included studies. Our search retrieved 122 relevant studies. These studies mainly refer to (a) the role of ML in the classification of HF patients into distinct categories which may require a different treatment strategy, (b) discrimination of HF patients from the healthy population or other diseases, (c) prediction of HF outcomes, (d) identification of HF patients from electronic records and identification of HF patients with similar characteristics who may benefit form a similar treatment strategy, (e) supporting the extraction of important data from clinical notes, and (f) prediction of outcomes in HF populations with implantable devices (left ventricular assist device, cardiac resynchronization therapy). We concluded that ML techniques may play an important role for the efficient construction of methodologies for diagnosis, management, and prediction of outcomes in HF patients.

Utility of a Smartphone-Based System (cvrPhone) in Estimating Minute Ventilation from Electrocardiographic Signals.

Background: We investigated the ability of a novel stand-alone, smartphone-based system, the cvrPhone, in estimating the minute ventilation (MV) from body surface electrocardiographic (ECG) signals. Methods: Twelve lead ECG signals were collected from anesthetized and mechanically ventilated swine (n = 9) using standard surface electrodes and the cvrPhone. The tidal volume delivered to the animals was varied between 0, 250, 500, and 750 mL at respiration rates of 6 and 14 breaths/min. MV estimates were determined by the cvrPhone and were compared with the delivered ones. Results: The median relative estimation errors were 17%, -4%, 35%, -3%, -9%, and 1%, for true MVs of 1,500, 3,000, 3,500, 4,500, 7,000, and 10,500 breaths*mL/min, respectively. The MV estimates at each of the settings were significantly different from each other (p < 0.05). Conclusions: We have demonstrated that accurate MV estimations can be derived from standard body surface ECG signals, using a smartphone.

Design Implementation and Evaluation of a Mobile Continuous Blood Oxygen Saturation Monitoring System.

OBJECTIVE: In this study, we built a mobile continuous Blood Oxygen Saturation (SpO2) monitor, and for the first time, explored key design principles towards daily applications. METHODS: We firstly built a customized wearable computer that can sense two-channel photoplethysmogram (PPG) signals, and transmit the signals wirelessly to smartphone. Afterwards, we explored many SpO2 model building principles, focusing on linear/nonlinear models, different PPG parameter calculation methods, and different finger types. Moreover, we further compared PPG sensor placement principles by comparing different hand configurations and different finger configurations. Finally, a dataset collected from eleven human subjects was used to evaluate the mobile health monitor and explore all of the above design principles. RESULTS: The experimental results show that the root mean square error of the SpO2 estimation is only 1.8, indicating the effectiveness of the system. CONCLUSION: These results indicate the effectiveness of the customized mobile SpO2 monitor and the selected design principles. SIGNIFICANCE: This research is expected to facilitate the continuous SpO2 monitoring of patients with clinical indications.

Conditional Up-Regulation of SERCA2a Exacerbates RyR2-Dependent Ventricular and Atrial Arrhythmias.

Ryanodine receptor 2 (RyR2) and SERCA2a are two major players in myocyte calcium (Ca) cycling that are modulated physiologically, affected by disease and thus considered to be potential targets for cardiac disease therapy. However, how RyR2 and SERCA2a influence each others' activities, as well as the primary and secondary consequences of their combined manipulations remain controversial. In this study, we examined the effect of acute upregulation of SERCA2a on arrhythmogenesis by conditionally overexpressing SERCA2a in a mouse model featuring hyperactive RyR2s due to ablation of calsequestrin 2 (CASQ2). CASQ2 knock-out (KO) mice were crossbred with doxycycline (DOX)-inducible SERCA2a transgenic mice to generate KO-TG mice. In-vivo ECG studies have shown that induction of SERCA2a (DOX+) overexpression markedly exacerbated both ventricular and atrial arrhythmias in vivo, compared with uninduced KO-TG mice (DOX-). Consistent with that, confocal microscopy in both atrial and ventricular myocytes demonstrated that conditional upregulation of SERCA2a enhanced the rate of occurrence of diastolic Ca release events. Additionally, deep RNA sequencing identified 17 downregulated genes and 5 upregulated genes in DOX+ mice, among which Ppp1r13l, Clcn1, and Agt have previously been linked to arrhythmias. Our results suggest that conditional upregulation of SERCA2a exacerbates hyperactive RyR2-mediated arrhythmias by further elevating diastolic Ca release.

S-Nitrosylation of Calcium-Handling Proteins in Cardiac Adrenergic Signaling and Hypertrophy.

RATIONALE: The regulation of calcium (Ca(2+)) homeostasis by ß-adrenergic receptor (ßAR) activation provides the essential underpinnings of sympathetic regulation of myocardial function, as well as a basis for understanding molecular events that result in hypertrophic signaling and heart failure. Sympathetic stimulation of the ßAR not only induces protein phosphorylation but also activates nitric oxide-dependent signaling, which modulates cardiac contractility. Nonetheless, the role of nitric oxide in ßAR-dependent regulation of Ca(2+) handling has not yet been explicated fully. OBJECTIVE: To elucidate the role of protein S-nitrosylation, a major transducer of nitric oxide bioactivity, on ßAR-dependent alterations in cardiomyocyte Ca(2+) handling and hypertrophy. METHODS AND RESULTS: Using transgenic mice to titrate the levels of protein S-nitrosylation, we uncovered major roles for protein S-nitrosylation, in general, and for phospholamban and cardiac troponin C S-nitrosylation, in particular, in ßAR-dependent regulation of Ca(2+) homeostasis. Notably, S-nitrosylation of phospholamban consequent upon ßAR stimulation is necessary for the inhibitory pentamerization of phospholamban, which activates sarcoplasmic reticulum Ca(2+)-ATPase and increases cytosolic Ca(2+) transients. Coincident S-nitrosylation of cardiac troponin C decreases myocardial sensitivity to Ca(2+). During chronic adrenergic stimulation, global reductions in cellular S-nitrosylation mitigate hypertrophic signaling resulting from Ca(2+) overload. CONCLUSIONS: S-Nitrosylation operates in concert with phosphorylation to regulate many cardiac Ca(2+)-handling proteins, including phospholamban and cardiac troponin C, thereby playing an essential and previously unrecognized role in cardiac Ca(2+) homeostasis. Manipulation of the S-nitrosylation level may prove therapeutic in heart failure.

Functional Implications of Cardiac Mitochondria Clustering.

The spatio-temporal organization of mitochondria in cardiac myocytes facilitates myocyte-wide, cluster-bound, mitochondrial inner membrane potential oscillatory depolarizations, commonly triggered by metabolic or oxidative stressors. Local intermitochondrial coupling can be mediated by reactive oxygen species (ROS) that activate inner membrane pores to initiate a ROS-induced-ROS-release process that produces synchronized limit cycle oscillations of mitochondrial clusters within the whole mitochondrial network. The network's dynamic organization, structure and function can be assessed by quantifying dynamic local coupling constants and dynamic functional clustering coefficients, both providing information about the network's response to external stimuli. In addition to its special organization, the mitochondrial network of cardiac myocytes exhibits substrate-sensitive coupling constants and clustering coefficients. The myocyte's ability to form functional clusters of synchronously oscillating mitochondria is sensitive to conditions such as substrate availability (e.g., glucose, pyruvate, ß-hydroxybutyrate), antioxidant status, respiratory chain activity, or history of oxidative challenge (e.g., ischemia-reperfusion). This underscores the relevance of quantitative methods to characterize the network's functional status as a way to assess the myocyte's resilience to pathological stressors.

Mitochondrial networks in cardiac myocytes reveal dynamic coupling behavior.

Oscillatory behavior of mitochondrial inner membrane potential (ΔΨm) is commonly observed in cells subjected to oxidative or metabolic stress. In cardiac myocytes, the activation of inner membrane pores by reactive oxygen species (ROS) is a major factor mediating intermitochondrial coupling, and ROS-induced ROS release has been shown to underlie propagated waves of ΔΨm depolarization as well as synchronized limit cycle oscillations of ΔΨm in the network. The functional impact of ΔΨm instability on cardiac electrophysiology, Ca(2+) handling, and even cell survival, is strongly affected by the extent of such intermitochondrial coupling. Here, we employ a recently developed wavelet-based analytical approach to examine how different substrates affect mitochondrial coupling in cardiac cells, and we also determine the oscillatory coupling properties of mitochondria in ventricular cells in intact perfused hearts. The results show that the frequency of ΔΨm oscillations varies inversely with the size of the oscillating mitochondrial cluster, and depends on the strength of local intermitochondrial coupling. Time-varying coupling constants could be quantitatively determined by applying a stochastic phase model based on extension of the well-known Kuramoto model for networks of coupled oscillators. Cluster size-frequency relationships varied with different substrates, as did mitochondrial coupling constants, which were significantly larger for glucose (7.78 × 10(-2) ± 0.98 × 10(-2) s(-1)) and pyruvate (7.49 × 10(-2) ± 1.65 × 10(-2) s(-1)) than lactate (4.83 × 10(-2) ± 1.25 × 10(-2) s(-1)) or ß-hydroxybutyrate (4.11 × 10(-2) ± 0.62 × 10(-2) s(-1)). The findings indicate that mitochondrial spatiotemporal coupling and oscillatory behavior is influenced by substrate selection, perhaps through differing effects on ROS/redox balance. In particular, glucose-perfusion generates strong intermitochondrial coupling and temporal oscillatory stability. Pathological changes in specific catabolic pathways, which are known to occur during the progression of cardiovascular disease, could therefore contribute to altered sensitivity of the mitochondrial network to oxidative stress and emergent ΔΨm instability, ultimately scaling to produce organ level dysfunction.

Functional brown adipose tissue limits cardiomyocyte injury and adverse remodeling in catecholamine-induced cardiomyopathy.

Brown adipose tissue (BAT) has well recognized thermogenic properties mediated by uncoupling protein 1 (UCP1); more recently, BAT has been demonstrated to modulate cardiovascular risk factors. To investigate whether BAT also affects myocardial injury and remodeling, UCP1-deficient (UCP1(-/-)) mice, which have dysfunctional BAT, were subjected to catecholamine-induced cardiomyopathy. At baseline, there were no differences in echocardiographic parameters, plasma cardiac troponin I (cTnI) or myocardial fibrosis between wild-type (WT) and UCP1(-/-) mice. Isoproterenol infusion increased cTnI and myocardial fibrosis and induced left ventricular (LV) hypertrophy in both WT and UCP1(-/-) mice. UCP1(-/-) mice also demonstrated exaggerated myocardial injury, fibrosis, and adverse remodeling, as well as decreased survival. Transplantation of WT BAT to UCP1(-/-) mice prevented the isoproterenol-induced cTnI increase and improved survival, whereas UCP1(-/-) BAT transplanted to either UCP1(-/-) or WT mice had no effect on cTnI release. After 3 days of isoproterenol treatment, phosphorylated AKT and ERK were lower in the LV's of UCP1(-/-) mice than in those of WT mice. Activation of BAT was also noted in a model of chronic ischemic cardiomyopathy, and was correlated to LV dysfunction. Deficiency in UCP1, and accompanying BAT dysfunction, increases cardiomyocyte injury and adverse LV remodeling, and decreases survival in a mouse model of catecholamine-induced cardiomyopathy. Myocardial injury and decreased survival are rescued by transplantation of functional BAT to UCP1(-/-) mice, suggesting a systemic cardioprotective role of functional BAT. BAT is also activated in chronic ischemic cardiomyopathy.

Prospective Use of Microvolt T-Wave Alternans Testing to Guide Primary Prevention Implantable Cardioverter Defibrillator Therapy.

BACKGROUND: We hypothesized that a negative microvolt T-wave alternans (MTWA) test would identify patients unlikely to benefit from primary prevention implantable cardioverter defibrillator (ICD) therapy in a prospective cohort. METHODS AND RESULTS: Data were pooled from 8 centers where MTWA testing was performed specifically for the purpose of guiding primary prevention ICD implantation. Cohorts were included if the ratio of ICDs implanted in patients who were MTWA "non-negative" to patients who were MTWA negative was >2:1, indicating that MTWA testing had a significant impact on the decision to implant an ICD. The pooled cohort included 651 patients: 371 MTWA non-negative and 280 MTWA negative. Among non-negative patients, 62% underwent ICD implantation whereas only 13% of MTWA-negative patients received an ICD (P<0.01). Despite a substantially lower prevalence of ICDs, long-term survival (6.9 years) was significantly better among MTWA-negative patients (68.2% non-negative vs. 87.1% negative, P=0.026). CONCLUSIONS: MTWA-negative patients had significantly better survival than MTWA non-negative patients, the majority of whom had ICDs. Despite a very low prevalence of ICDs, long-term survival among patients with left ventricular ejection fraction ≤40% and a negative MTWA test was better than in the ICD arm of any study to date that has demonstrated a benefit of ICDs. This provides further evidence that MTWA-negative patients are unlikely to benefit from primary prevention ICD therapy.

An optimized method for estimating the tidal volume from intracardiac or body surface electrocardiographic signals: implications for estimating minute ventilation.

The ability to accurately monitor tidal volume (TV) from electrocardiographic (ECG) signals holds significant promise for improving diagnosis treatment across a variety of clinical settings. The objective of this study was to develop a novel method for estimating the TV from ECG signals. In 10 mechanically ventilated swine, we collected intracardiac electrograms from catheters in the coronary sinus (CS), left ventricle (LV), and right ventricle (RV), as well as body surface electrograms, while TV was varied between 0 and 750 ml at respiratory rates of 7-14 breaths/min. We devised an algorithm to determine the optimized respirophasic modulation of the amplitude of the ECG-derived respiratory signal. Instantaneous measurement of respiratory modulation showed an absolute error of 72.55, 147.46, 85.68, 116.62, and 50.89 ml for body surface, CS, LV, RV, and RV-CS leads, respectively. Minute TV estimation demonstrated a more accurate estimation with an absolute error of 69.56, 153.39, 79.33, 122.16, and 48.41 ml for body surface, CS, LV, RV, and RV-CS leads, respectively. The RV-CS and body surface leads provided the most accurate estimations that were within 7 and 10% of the true TV, respectively. Finally, the absolute error of the bipolar RV-CS lead was significantly lower than any other lead configuration (P < 0.0001). In conclusion, we have demonstrated that ECG-derived respiratory modulation provides an accurate estimation of the TV using intracardiac or body surface signals, without the need for additional hardware.

A translational approach to probe the proarrhythmic potential of cardiac alternans: a reversible overture to arrhythmogenesis?

Electrocardiographic alternans, a phenomenon of beat-to-beat alternation in cardiac electrical waveforms, has been implicated in the pathogenesis of ventricular arrhythmias and sudden cardiac death (SCD). In the clinical setting, a positive microvolt T-wave alternans test has been associated with a heightened risk of arrhythmic mortality and SCD during medium- and long-term follow-up. However, rather than merely being associated with an increased risk for SCD, several lines of preclinical and clinical evidence suggest that cardiac alternans may play a causative role in generating the acute electrophysiological substrate necessary for the onset of ventricular arrhythmias. Deficiencies in Ca(2+) transport processes have been implicated in the genesis of alternans at the subcellular and cellular level and are hypothesized to contribute to the conditions necessary for dispersion of refractoriness, wave break, reentry, and onset of arrhythmia. As such, detecting acute surges in alternans may provide a mechanism for predicting the impending onset of arrhythmia and opens the door to delivering upstream antiarrhythmic therapies. In this review, we discuss the preclinical and clinical evidence to support a causative association between alternans and acute arrhythmogenesis and outline the potential clinical implications of such an association.

An optimized method for the estimation of the respiratory rate from electrocardiographic signals: implications for estimating minute ventilation.

It is well-known that respiratory activity influences electrocardiographic (ECG) morphology. In this article we present a new algorithm for the extraction of respiratory rate from either intracardiac or body surface electrograms. The algorithm optimizes selection of ECG leads for respiratory analysis, as validated in a swine model. The algorithm estimates the respiratory rate from any two ECG leads by finding the power spectral peak of the derived ratio of the estimated root-mean-squared amplitude of the QRS complexes on a beat-by-beat basis across a 32-beat window and automatically selects the lead combination with the highest power spectral signal-to-noise ratio. In 12 mechanically ventilated swine, we collected intracardiac electrograms from catheters in the right ventricle, coronary sinus, left ventricle, and epicardial surface, as well as body surface electrograms, while the ventilation rate was varied between 7 and 13 breaths/min at tidal volumes of 500 and 750 ml. We found excellent agreement between the estimated and true respiratory rate for right ventricular (R(2) = 0.97), coronary sinus (R(2) = 0.96), left ventricular (R(2) = 0.96), and epicardial (R(2) = 0.97) intracardiac leads referenced to surface lead ECGII. When applied to intracardiac right ventricular-coronary sinus bipolar leads, the algorithm exhibited an accuracy of 99.1% (R(2) = 0.97). When applied to 12-lead body surface ECGs collected in 4 swine, the algorithm exhibited an accuracy of 100% (R(2) = 0.93). In conclusion, the proposed algorithm provides an accurate estimation of the respiratory rate using either intracardiac or body surface signals without the need for additional hardware.

A method to noninvasively identify cardiac bioelectrical sources.

BACKGROUND: We have introduced a method to guide radiofrequency catheter ablation (RCA) procedures that estimates the location of a catheter tip used to pace the ventricles and the target site for ablation using the single equivalent moving dipole (SEMD). OBJECTIVE: To investigate the accuracy of this method in resolving epicardial and endocardial electrical sources. METHODS: Two electrode arrays, each of nine pacing electrodes at known distances from each other, sutured on the left- and right-ventricular (LV and RV) epicardial surfaces of swine, were used to pace the heart at multiple rates, while body surface potentials from 64 sites were recorded and used to estimate the SEMD location. A similar approach was followed for pacing from catheters in the LV and RV. RESULTS: The overall (RV & LV) error in estimating the interelectrode distance of adjacent epicardial electrodes was 0.38 ± 0.45 cm. The overall endocardial (RV & LV) interelectrode distance error, was 0.44 ± 0.26 cm. Heart rate did not significantly affect the error of the estimated SEMD location (P > 0.05). The guiding process error became progressively smaller as the SEMD approached an epicardial target site and close to the target, the overall absolute error was ∼ 0.28 cm. The estimated epicardial SEMD locations preserved their topology in image space with respect to their corresponding physical location of the epicardial electrodes. CONCLUSION: The proposed algorithm suggests one can efficiently and accurately resolve epicardial electrical sources without the need of an imaging modality. In addition, the error in resolving these sources is sufficient to guide RCA procedures.

Data Interoperability for Ambulatory Monitoring of Cardiovascular Disease: A Scientific Statement From the American Heart Association.

Wearable devices are increasingly used by a growing portion of the population to track health and illnesses. The data emerging from these devices can potentially transform health care. This requires an interoperability framework that enables the deployment of platforms, sensors, devices, and software applications within diverse health systems, aiming to facilitate innovation in preventing and treating cardiovascular disease. However, the current data ecosystem includes several noninteroperable systems that inhibit such objectives. The design of clinically meaningful systems for accessing and incorporating these data into clinical workflows requires strategies to ensure the quality of data and clinical content and patient and caregiver accessibility. This scientific statement aims to address the best practices, gaps, and challenges pertaining to data interoperability in this area, with considerations for (1) data integration and the scope of measures, (2) application of these data into clinical approaches/strategies, and (3) regulatory/ethical/legal issues.

The Science of Precision Prevention: Research Opportunities and Clinical Applications to Reduce Cardiovascular Health Disparities.

Precision prevention embraces personalized prevention but includes broader factors such as social determinants of health to improve cardiovascular health. The quality, quantity, precision, and diversity of data relatable to individuals and communities continue to expand. New analytical methods can be applied to these data to create tools to attribute risk, which may allow a better understanding of cardiovascular health disparities. Interventions using these analytic tools should be evaluated to establish feasibility and efficacy for addressing cardiovascular disease disparities in diverse individuals and communities. Training in these approaches is important to create the next generation of scientists and practitioners in precision prevention. This state-of-the-art review is based on a workshop convened to identify current gaps in knowledge and methods used in precision prevention intervention research, discuss opportunities to expand trials of implementation science to close the health equity gaps, and expand the education and training of a diverse precision prevention workforce.