Heart Health Research Articles

Technical Requirements, Design, and Automation Process for a Statewide Registry-Based Tailored Text Messaging System: Protocol for a Longitudinal Observational Study.

Tailored text messaging is a low-cost mobile health intervention approach shown to effectively improve self-care behaviors and clinical outcomes for patients with chronic cardiometabolic conditions. Given the ubiquitous nature of mobile phones, text messages have the potential to reach a large audience. However, automating and disseminating tailored text messages to large populations at low cost presents major logistical challenges that serve as barriers to implementation. This study aimed to describe the protocol for a longitudinal observational study designed to assess the feasibility of an innovative approach for automating and disseminating personalized and tailored text messages to large populations at risk of cardiovascular events using a low-cost registry-based tailored text messaging system known as the Heart Health Messages (HHM) program. Further, it describes the technical requirements, architectural design, automation process, and challenges associated with program implementation. Patients at high risk of cardiovascular diseases are identified using a statewide population health registry known as the Tennessee Population Data Network. Tailored invitation messages and enrollment surveys are sent to eligible patients via Twilio. Upon completion of the receipt of consent and enrollment forms, participants receive tailored text messages from a library of generic messages based on participant-selected frequency of message delivery (daily or every other day). In addition, participants receive monthly text-based check-in survey messages designed to assess intervention adherence and improvement in self-care. Participants are also sent quarterly follow-up surveys to update enrollment information and preferences. All enrolled participants will receive tailored text messages for a 12-month intervention period. Since the start of the program, 18,974 patients from 2 major health systems have met the inclusion criteria and were eligible for the HHM program. A total of 3 phases of HHM 1.0 have been implemented so far, reaching 225 eligible patients in phase 1, a total of 5288 patients in phase 2, and 13,461 patients in phase 3, with an enrollment of approximately 2% (n=4/225), 3% (n=137/5228), and 3% (n=350/13461), respectively. Efforts are underway to implement strategies in collaboration with the health systems to enhance the HHM program rollout and patient participation. The HHM program is a low-cost tailored text messaging intervention set for broader dissemination and potential replication. The program has the capacity to improve outcomes for people with chronic medical conditions. DERR1-10.2196/62874.

Does the heart eat along? A two years lifestyle intervention in shift workers

Background The present study investigates whether it is possible to reduce heart rate by nutritional information and lifestyle modification. Methods In this exploratory study 18 male rotating shift workers (39.7 ± 7.5 y) were randomly divided into two groups by using the urn model. At the beginning of the study, all subjects wore a heart rate sensor for 24 hours during a night shift. This recording was repeated after 1 year, when groups switched, and at the end of the study. Participants received nutritional information every other month for 1 year. The nutritional counseling was provided by a dietician/nutritionist and only contained information about healthy eating. By using the food diaries, nutritional errors were uncovered and could easily be corrected. Subjects were also encouraged to incorporate more endurance and resistance training into their daily routines. Results After the intervention, heart rate in group A decreased during the day from 75 ± 6.3 beats per minute (bpm) before to 73 ± 7.5 bpm afterward and during the night from 72 ± 9.8 bpm before to 70 ± 9.5 bpm afterward. In group B heart rate increased during the day from 72 ± 9.1 bpm before to 76 ± 7.2 bpm afterward and decreased at night from 69 ± 10.0 bpm before to 66 ± 11.2 bpm afterward. All values were highly significant (p < 0.001). Conclusions Motivation to adopt a better lifestyle in terms of healthy eating and daily exercise could be a cost-effective contribution to heart health among rotating shift workers. However, the individually adapted interventions need to occur more frequently.

Patterns of heart rate reduction during sleep onset in participants with and without insomnia.

Hyperarousal is common in patients with insomnia. Autonomic stress may reflect hyperarousal and distinguish participants with insomnia vs good sleepers. Slope analysis of heart rate reduction during sleep onset might be a promising measure of such autonomic modulation. We aim to explore the potential utility of this measure with data collected from home settings from the Sleep Heart Health Study. In this secondary analysis with 743 participants, we applied two approaches to compute slopes for heart rate reduction during sleep onset. We compared slopes among participants with and without insomnia symptoms, with short versus long sleep onset latency, with or without difficulty falling asleep during the study night, and with sleep-onset insomnia versus other insomnia subtypes. We also explored correlations between heart rate reduction and sleep outcome measures. We found that the slopes of heart rate reduction during sleep onset were most significantly associated with objectively measured sleep onset latency, followed by subjectively reported sleep onset latency, regardless of the approach used to compute the slopes. Participants with self-reported difficulty falling asleep during the study night had significantly blunted heart rate reduction. The slopes were significantly blunted in participants with self-reported sleep-onset insomnia compared to other types of insomnia. As measures of autonomic activity, the slopes of heart rate reduction may serve as a physiological biomarker to indicate hyperarousal during wakefulness before sleep onset. Tracking changes of heart rate reduction during sleep onset may have potential value in the evaluation of insomnia treatments, especially those targeting sleep onset difficulties.

Estimation of global average treatment effect in National Heart, Lung, and Blood Institute (NHLBI) Growth and Health Study.

We propose a procedure to estimate the "time-specific average treatment effect" and "global average treatment effect" for observational studies with outcomes and covariates repeatedly measured over time. This research is motivated by the National Heart, Lung and Blood Institute Growth and Health Study (NGHS), a longitudinal cohort study that aims to evaluate the influences of race and other risk factors on the levels of blood pressure for children and adolescents. As with most longitudinal cohort studies, we do not have a known propensity score model to further discuss the average treatment effects in the NGHS. To solve this problem, a nonparametric machine learning method, the generalized boosted models (GBMs), is used to estimate the propensity score. Based on the estimated propensity score, the "time-specific average treatment effect" can be obtained through the inverse probability weighting methods, then the "global average treatment effect" is also obtained. We apply the proposed GBM-based estimation method to the NGHS blood pressure data and demonstrate through a simulation study that the GBM-based estimation method is superior to the commonly used logistic regression-based method.

Vascular dementia: at the crossroads of brain and heart health.

Vascular dementia: at the crossroads of brain and heart health.

Iron and Heart Health: A Game Changer for Patients with Heart Failure?

Iron and Heart Health: A Game Changer for Patients with Heart Failure?

Electrically Stable and Reliably Adhered E-Skin for Heart Health Monitoring.

Electronic skin (e-skin) has been extensively investigated for its potential application in heart health monitoring, such as screening cardiovascular diseases and evaluating cardiac activity. Nevertheless, the poor electrical stability of traditional metal electrodes and insufficient adhesion of ordinary flexible substrates are primary impediments that hinder its further product marketing in the healthcare field. Herein, we propose a novel integrated e-skin that incorporates embedded stretchable electrodes with high electrical stability (within 20% strain) and a microsucker array with improved adhesion, which facilitates the effective reduction of motion artifact interference. Moreover, a wireless heart health monitoring system based on the e-skin is designed to realize synchronous electrocardiogram (ECG) and ballistocardiogram (BCG) detection by collecting chest epidermal mechano-acoustic signals and vibration-voltage signals. The monitoring results of the same adult volunteer indicate that the ECG and BCG data recorded by this system have good consistency with data from commercial cardiovascular monitoring devices. Furthermore, the ECG and BCG signal monitoring results of different volunteers further validated the potential of this system in cardiovascular disease diagnosis and long-term heart health monitoring.

Developing Lifestyle-Focused Digital Twin Archetypes in Heart Care.

Digital twin technology is a potential transformative tool in heart care, enabling precise modeling of cardiovascular functions. However, current applications predominantly focus on physiological processes and short-term medical interventions, neglecting the integration of long-term lifestyle factors such as diet, physical activity, stress management, and sleep patterns-key contributors to heart health. This paper addresses this critical research gap by proposing a three-level framework for lifestyle-focused digital twin archetypes: basic (utilizing self-reported data for general health guidance), intermediate (incorporating wearable-generated data for dynamic feedback), and advanced (combining comprehensive clinical and lifestyle data for detailed simulations and personalized treatment planning). By integrating lifestyle factors, the framework could enhance personalization, patient engagement, and improve long-term health outcomes. The approach emphasizes multidisciplinary collaboration and paves the way for a holistic understanding of heart health, offering scalable solutions to bridge technology and lifestyle for better cardiovascular care.

Plasma Proteomic Profiling Reveals ITGA2B as A Key Regulator of Heart Health in High-altitude Settlers.

Plasma Proteomic Profiling Reveals ITGA2B as A Key Regulator of Heart Health in High-altitude Settlers.

Heart Disease Prediction

We are living in the modern Technological era, and we are trying to solve the problem using technology for that we are striving for more knowledge with help of our technology, the more our lifestyle is changing. In the fast growing world everyone is neglecting their Health.Result of this Health diseases are increasing day by day due to our lifestyle and other hereditary reasons. Especially Heart Diseases have become a major issue these days.WHO report that over 11 million deaths are caused each year worldwide due to heart related complications. Using this we can understand that the condition is very serious.There is an urgent need for some technological solutions which can help in educating people and early diagnosis of these disease. This requires a string infrastructure including a large enough work force, which is a slow process. In the recent year machine learning has evolved a lot .To resolve this problem we can use Machine Learning that can help us in this. Sudden increase in the number of patients depict the need for scalability in our medical system. While work force may be limited, we can look for algorithmic solutions for screening and diagnosis stages, due to their correlation with Our project "Heart Health Classification and Early Diagnosis of Heart Disease" is a system that uses predictive capability of machine learning models based on similar data points collected in past. We are going to use the previous medical report data to predict the risk of heart disease.Using our system user can estimate the chance of being suffer from heart disease.Our system takes input data and runs 5 Machine Learning Models on the data and gives the result. We are trying to provide the user friendly platform to user that can be access remotely to screening facilities that will predict the risk of heart disease and that will eliminate the load on the medical system.

Mobile Apps and Wearable Devices for Cardiovascular Health: Narrative Review.

Cardiovascular diseases (CVDs) continue to be the leading cause of global morbidity and mortality. Aiming to reduce the risk of CVD development and better manage them, an increasing number of individuals are adopting mobile health (mHealth) apps and wearable devices (wearables). These technologies provide critical insights into heart health and fitness, supporting users to monitor their lifestyle behaviors and adhere to preventative medication. In this review, we aimed to investigate the current state of mHealth apps and wearables designed for cardiovascular health, with a specific focus on the DACH region (Germany, Austria, and Switzerland). We assessed the benefits these technologies provide to clinicians and patients, particularly in addressing unmet needs like sex-specific symptoms, while also examining their potential integration into the broader health care ecosystem. To identify heart health apps, a keyword search was performed on both the Swiss Apple App Store and Google Play Stores. A separate search was performed on Google to identify heart health wearables. The identified apps and wearables were evaluated using the foundational and contextual criteria of the sociotechnical framework for assessing patient-facing eHealth tools. After filtering out apps and wearables that did not meet our inclusion criteria, 20 apps and 22 wearables were included in the review. While all the apps were available in the DACH region, only 30% (6/20) were specifically designed for these countries. Only 25% (5/20) of the apps included sex-specific information; 40% (8/20) provided information from evidence-based research, 35% (7/20) provided general health information without academic and clinical references, and 25% (5/20) did not include any evidence-based or general health information. While 20% (4/20) of the included apps had clinical integration features such as clinician dashboards, only 10% (2/20) had the potential to effectively enhance clinician workflows. Privacy policies were present in 95% (19/20) of the apps, with 75% (15/20) adhering to General Data Protection Regulation (GDPR) regulations; 1 app had no data protection policy. Only 20% (4/20) of the apps were medically certified. For wearables, only 9% (2/22) were tailored to the DACH region, and 40% (9/22) addressed women's health. While around 60% (13/22) offered features to support clinical integration, only 9% (2/22) had the potential to improve clinical workflows. More than half (12/22) of the wearables were medically certified, and 77% (17/22) referenced scientific or peer-reviewed research. All wearables included a privacy policy. While many mHealth tools for cardiovascular health are available, only a few provide meaningful value to both patients and clinicians or have the potential to integrate effectively into the health care system. Women's sex-specific needs are often overlooked, and the benefits for clinicians are limited. In addition, mHealth apps largely lack robust evidence, whereas wearables showed comparatively stronger support through evidence-based and medical certification.

Women’s Heart Health: Should the physical activity recommendations be different?

Women’s Heart Health: Should the physical activity recommendations be different?

Psychological screening in cardiovascular care

Abstract Approximately one in three patients with cardiovascular disease experience psychological distress, often with associated poor prognosis. Early detection and intervention can improve patients’ heart and mental health, yet minimal guidance on psychological screening is offered for clinicians working in cardiovascular care. This paper describes a pragmatic approach to conducting psychological screening during routine clinical care, including when and how to screen and what to do in the case of a positive screen. A psychological screening protocol is proposed to enable clinicians to assess and, where necessary, intervene or refer for further evaluation.

WIRELESS ECG MONITORING SYSTEM

In today’s healthcare environment, continuous monitoring of a patient’s heart activity is crucial for early diagnosis and timely medical intervention. This paper presents a Wireless ECG Monitoring System that enables real-time ECG data acquisition and transmission using IoT technology. The system consists of an AD8232 ECG sensor, an ESP32 microcontroller, and electrodes for signal acquisition. The collected data is processed using Arduino and displayed on Ubidots, allowing remote monitoring of heart health. This system provides an efficient, cost- effective, and wireless alternative to traditional ECG machines.

Deep Learning-Powered IoT Wearables for Early Detection of Cardiovascular Diseases

Cardiovascular illnesses (CVDs) are still the top cause of death around the world. To improve prognoses and lower healthcare costs, early monitoring systems are needed. This study introduces a new system that combines deep learning algorithms with smart IoT devices to make it easier to track and find CVDs early in real time. Wearable monitors collect constant physiological data like heart rate, blood pressure, oxygen levels, and electrocardiogram (ECG) readings that are used in the suggested system. We used a CNN-LSTM design that combines a Convolutional Neural Network and Long Short-Term Memory to handle the signals' time and spatial patterns. The CNN part pulls out important features from raw, multidimensional sensor data, and the LSTM part finds time relationships to make predictions more accurate. The dataset used includes PhysioNet's publicly available cardiovascular health records and real-time data from smart devices. To balance class distributions, simulated minority oversampling was added to the dataset. Precision, memory, F1-score, and accuracy were used as measures to evaluate performance. It did better than standard models like CNN, LSTM, and classic machine learning classifiers, with a total accuracy of 96.4%, a precision of 95.7%, and an F1-score of 96.1% in finding early signs of CVD. The system also allows implementation at the edge, which ensures low delay and energy-efficient processing that is good for constant tracking. The results show that combining deep learning with IoT gadgets could greatly improve early identification of CVD, allowing for proactive actions and personalised healthcare. The suggested structure offers an adaptable and affordable way to keep an eye on people's heart health in real time, especially in places that are far away and don't have a lot of resources.

Promoting heart health during Heart Week 2025

Promoting heart health during Heart Week 2025

Recent developments, challenges, and prospects of dietary omega-3 PUFA-fortified foods: Focusing on their effects on cardiovascular diseases.

Recent developments, challenges, and prospects of dietary omega-3 PUFA-fortified foods: Focusing on their effects on cardiovascular diseases.

Lymphatic Endothelial Branched-Chain Amino Acid Catabolic Defects Undermine Cardiac Lymphatic Integrity and Drive HFpEF.

Heart failure with preserved ejection fraction (HFpEF) has become the most prevalent type of heart failure, but effective treatments are lacking. Cardiac lymphatics play a crucial role in maintaining heart health by draining fluids and immune cells. However, their involvement in HFpEF remains largely unexplored. We examined cardiac lymphatic alterations in mice with HFpEF with comorbid obesity and hypertension, and in heart tissues from patients with HFpEF. Using genetically engineered mouse models and various cellular and molecular techniques, we investigated the role of cardiac lymphatics in HFpEF and the underlying mechanisms. In mice with HFpEF, cardiac lymphatics displayed substantial structural and functional anomalies, including decreased lymphatic endothelial cell (LEC) density, vessel fragmentation, reduced branch connections, and impaired capacity to drain fluids and immune cells. LEC numbers and marker expression levels were also decreased in heart tissues from patients with HFpEF. Stimulating lymphangiogenesis with an adeno-associated virus expressing an engineered variant of vascular endothelial growth factor C (VEGFCC156S) that selectively activates vascular endothelial growth factor receptor 3 (VEGFR3) in LECs restored cardiac lymphatic integrity and substantially alleviated HFpEF. Through discovery-driven approaches, defective branched-chain amino acid (BCAA) catabolism was identified as a predominant metabolic signature in HFpEF cardiac LECs. Overexpression of branched-chain ketoacid dehydrogenase kinase (encoded by the Bckdk gene), which inactivates branched-chain ketoacid dehydrogenase (the rate-limiting enzyme in BCAA catabolism), resulted in spontaneous lymphangiogenic defects in LECs. In mice, inducible Bckdk gene deletion in LECs to enhance their BCAA catabolism preserved cardiac lymphatic integrity and protected against HFpEF. BCAA catabolic defects caused ligand-independent phosphorylation of VEGFR3 in the cytoplasm by Src kinase, leading to lysosomal degradation of VEGFR3 instead of its trafficking to the cell membrane. Reduced VEGFR3 availability on the cell surface impeded downstream Akt (protein kinase B) activation, hindered glucose uptake and utilization, and inhibited lymphangiogenesis in LECs with BCAA catabolic defects. Our study provides evidence that cardiac lymphatic disruption, driven by impaired BCAA catabolism in LECs, is a key factor contributing to HFpEF. These findings unravel the crucial role of BCAA catabolism in modulating lymphatic biology, and suggest that preserving cardiac lymphatic integrity may present a novel therapeutic strategy for HFpEF.

Formulation and Evaluation Study of Bel Powder

Abstract: A long-standing value, both in traditional and modern medicinal practices, is packed into the extract from the bel fruit (Aegle marmelos), primarily native to the Indian subcontinent and Southeast Asia. Bel powder, synonymous with deep cultural significance in Ayurveda, is a convenient, shelf-stable form of fruit containing health benefits while remaining powdered. The fruit is rich in macronutrients, like carbohydrates, with minimal content of fats and moderate amounts of protein, being a good source of vitamins A and C, calcium, potassium, and magnesium. Bioactive compounds, such as tannins, coumarins, and flavonoids, in Bel powder, add antioxidant, anti-inflammatory, and antimicrobial properties. Bel powder is also believed to be very variable in its health benefits—it helps digest food, supports the immune system, and balances blood sugar levels. It has a high content of dietary fibre, which promotes easy digestion and stops the appearance of problems like constipation and dysentery. Antioxidant properties will help to prevent immunity weakness and reduce inflammation inside the body. Therapeutic use in animals has been proven for diabetes problem alleviation, protection of the liver, and maintenance of heart health. This therapeutic activity is mainly attributed to the presence of tannins and coumarins as the primary phytochemicals, which provide nutrition to cells to inhibit inflammation. Both traditional sun drying and modern freeze drying techniques are employed in the production of bel powder to maintain its bioactive properties. On account of its curative potential, it has been widely used in the various realms of culinary application, Ayurvedic medication, nutraceutical, and even cosmetic formulations. Increasing demand for natural supplements as well as products in the Ayurveda line creates a significant requirement for bel powder from countries like India, the U.S., and Europe. Based on available scientific evidence, it is believable that bel of these will provide the health benefits that it has across the different domains; therefore, their potential effects in the treatment of metabolic disorders and chronic diseases need more exploration. It is safe generally, but a visit to the doctor

Accelerating action in women's heart health

Heart disease is the leading cause of death in women, yet systemic gender disparities in diagnosis, treatment and outcomes persist. Addressing these challenges requires the integration of sex-specific research into clinical practice and reform of healthcare policies. This article highlights key issues in women's heart health, outlining strategies for equitable, evidence-based care.