Heart failure (HF) remains a significant burden on global healthcare systems, necessitating innovative approaches for its management. This manuscript critically evaluates the role of remote monitoring and telemedicine in revolutionizing HF care delivery. Drawing upon a synthesis of current literature and clinical practices, it delineates the pivotal benefits, challenges, and personalized strategies associated with these technologies in HF management. The analysis highlights the potential of remote monitoring and telemedicine in facilitating timely interventions, enhancing patient engagement, and optimizing treatment adherence, thereby ameliorating clinical outcomes. However, technical intricacies, regulatory frameworks, and socioeconomic factors pose formidable hurdles to widespread adoption. The manuscript emphasizes the imperative of tailored interventions, leveraging advancements in artificial intelligence and machine learning, to address individual patient needs effectively. Looking forward, sustained innovation, interdisciplinary collaboration, and strategic investment are advocated to realize the transformative potential of remote monitoring and telemedicine in HF management, thereby advancing patient-centric care paradigms and optimizing healthcare resource allocation.

UNASSIGNED: Use of healthcare wearable devices holds significant potential for improving the prevention and management of cardiovascular diseases (CVD). However, we have limited knowledge on the actual use of wearable devices by CVD patients and the key factors associated with their use. This study aims to assess wearable device use and willingness to share health data among CVD patients, while identifying socio-demographic, health, and technology-related factors associated with wearable technology use.
UNASSIGNED: Using a national survey of 933 CVD patients, we assess use of wearable healthcare devices (use, frequency of use and willingness to share health data from wearable with a provider), and a set of socio-demographic factors (age, gender, race, education and household income), health-related variables (general health, presence of comorbid conditions: diabetes and high blood pressure, attitude towards exercise) and technology self-efficacy using logistic regression.
UNASSIGNED: Of the 933 CVD patients, 18.34% reported using a healthcare wearable device in the prior 12 months. Of those, 41.92% indicated using it every day and another 19.76% indicated using it \'almost every day\'. 83.54% of wearable users indicated their willingness to share health data with their healthcare providers. Female CVD patients are more likely to use wearables compared to men (odds ratio (OR) = 1.65, 95% confidence interval (CI) = 1.04-2.63). The odds decrease with age, and are significantly high in patients with higher income levels. In comparison with non-Hispanic White, Hispanic (OR = 0.14, 95% CI = 0.03-0.70) and African Americans (OR = 0.17, 95% CI = 0.04-0.86) are less likely to use healthcare wearables. CVD patients who perceive their general health to be better (OR = 1.45, 95% CI = 1.11-1.89) and those who enjoy exercising (OR = 1.76, 95% CI = 1.22-2.55) are more likely to use wearables. CVD patients who use the internet for searching for medical information (OR = 2.10, 95% CI = 1.17-3.77) and those who use electronic means to make appointments with their providers (OR = 2.35, 95% CI = 1.48-3.74) are more inclined to use wearables.
UNASSIGNED: Addressing low wearable device usage among CVD patients requires targeted policy interventions to ensure equitable access. Variations in gender, age, race/ethnicity, and income levels emphasize the need for tailored strategies. Technological self-efficacy, positive health perceptions, and exercise enjoyment play significant roles in promoting wearable use. These insights should guide healthcare leaders in designing effective strategies for integrating wearables into cardiovascular care.

Chat Generative Pre-Trained Transformer (ChatGPT) is a chatbot based on a large language model that has gained public interest since its release in November 2022. This systematic review examines the current literature on the potential applications of ChatGPT in cardiology. A systematic literature search was conducted to retrieve all publications on ChatGPT in PubMed, Scopus, MedRxiv, and the Cochrane Library published on or before September 30, 2023. Search terms relating to ChatGPT and cardiology were used. Publications without relevance to ChatGPT and cardiology were excluded. The included publications were divided into cohorts. Cohort A examined ChatGPT\'s role in improving patient health literacy. Cohort B explored ChatGPT\'s role in clinical care. Cohort C examined ChatGPT\'s role in future literature and research. Cohort D included case reports that used ChatGPT. A total of 115 publications were found across all databases. Twenty-four publications met the inclusion criteria and were included in the review. Cohort A-C included a total of 14 records comprised of editorials/letters to the editor (29%), research letters/correspondence (21%), review papers (21%), observational studies (7%), research studies (7%), and short reports (7%). Cohort D included 10 case reports. No relevant systematic literature reviews, meta-analyses, or randomized controlled trials were identified in the search.  Based on this review of the literature, ChatGPT has the potential to enhance patient education, support clinicians providing clinical care, and enhance the development of future literature. However, further studies are needed to understand the potential applications of ChatGPT in cardiology and to address ethical concerns regarding the delivery of medical advice and the authoring of manuscripts.

This study evaluated the capabilities of the newly released ChatGPT-4V, a large language model with visual recognition abilities, in interpreting electrocardiogram waveforms and answering related multiple-choice questions for assisting with cardiovascular care.

Cardiovascular diseases (CVD) are a major public health concern in the Caribbean. Cardiovascular care in the Caribbean revealed encouraging improvements but still less than expectations. This study aims to gain insight into CVD and identify gaps in cardiovascular care in the Caribbean compared to high-income countries. More specifically, this review reports on the epidemiology, CVD risk factors, management practices, and patient outcomes (quality of life (QOL) and mortality). A systematic review of peer-reviewed articles was conducted to assess the CVD of individuals in the Caribbean from 1959 to 2022.Using multiple search engines and keywords, a systematic review of relevant peer-reviewed CVD articles was conducted using the necessary inclusion and exclusion criteria. Relevant data of studies were classified by title, publication year, location, type and size of samples, and results. Further analysis grouped patients by epidemiological profile, CVD risk, management, and selected outcomes (quality of life and inpatient mortality).  From the initial review of 1,553 articles, 36 were analyzed from Trinidad and Tobago (20), Barbados (4), Jamaica (7), along with the Bahamas (2), British Virgin Islands (1), Bonaire (1), and one article from a Caribbean study. The social environment of fast food, sedentary jobs, and stress determinants are postulated to be precursors for an increase in CV risks. CVD in the Caribbean reveals a high prevalence of CV risks, suboptimal care, poor compliance, and high inpatient mortality compared with high-income countries. Greater efforts are required to improve CVD care at all stages, including in the social environment.

The Nordic countries, including Denmark, Finland, Iceland, Norway, and Sweden have seen a steep decline in cardiovascular mortality in recent decades. They are among the most egalitarian countries by several measures, and all have universal, publicly funded welfare systems providing healthcare for all citizens. However, despite these seemingly ideal conditions, disparities in access to cardiovascular care and outcomes persist. To address this challenge, The Lancet Region Health-Europe convened experts from a broad range of countries to summarize the current state of knowledge on cardiovascular disease disparities across Europe. This Series Paper presents the main challenges in Nordic countries based on evidence from high-quality nationwide registries. Focusing on major cardiovascular health determinants, areas in need of improvement were identified. There is a need for addressing structural causes underlying these disparities, such as poverty and discrimination, but also to improve access to healthcare in deprived neighborhoods and to address underlying social determinants of health that may mitigate disparities in cardiovascular outcomes. Overall, while the Nordic countries have made great strides in promoting egalitarianism and providing universal healthcare, there is still much work to be done to ensure equitable access to care and improved cardiovascular outcomes for all members of society.

BACKGROUND: Standardized Mortality Ratios (SMRs) are case-mix adjusted mortality rates per hospital and are used to evaluate quality of care. However, acute care is increasingly organized on a regional level, with more severe patients admitted to specialized hospitals. We hypothesize that the current case-mix adjustment insufficiently captures differences in case-mix between non-specialized and specialized hospitals. We aim to improve the SMR by adding proxies of disease severity to the model and by calculating a regional SMR (RSMR) for acute cerebrovascular disease (CVD) and myocardial infarction (MI).
METHODS: We used data from the Dutch National Basic Registration of Hospital Care. We selected all admissions from 2016 to 2018. SMRs and RSMRs were calculated by dividing the observed in-hospital mortality by the expected in-hospital mortality. The expected in-hospital mortality was calculated using logistic regression with adjustment for age, sex, socioeconomic status, severity of main diagnosis, urgency of admission, Charlson comorbidity index, place of residence before admission, month/year of admission, and in-hospital mortality as outcome.
RESULTS: The IQR of hospital SMRs of CVD was 0.85-1.10, median 0.94, with higher SMRs for specialized hospitals (median 1.12, IQR 1.00-1.28, 71%-SMR > 1) than for non-specialized hospitals (median 0.92, IQR 0.82-1.07, 32%-SMR > 1). The IQR of RSMRs was 0.92-1.09, median 1.00. The IQR of hospital SMRs of MI was 0.76-1.14, median 0.98, with higher SMRs for specialized hospitals (median 1.00, IQR 0.89-1.25, 50%-SMR > 1 versus median 0.94, IQR 0.74-1.11, 44%-SMR > 1). The IQR of RSMRs was 0.90-1.08, median 1.00. Adjustment for proxies of disease severity mostly led to lower SMRs of specialized hospitals.
CONCLUSIONS: SMRs of acute regionally organized diseases do not only measure differences in quality of care between hospitals, but merely measure differences in case-mix between hospitals. Although the addition of proxies of disease severity improves the model to calculate SMRs, real disease severity scores would be preferred. However, such scores are not available in administrative data. As a consequence, the usefulness of the current SMR as quality indicator is very limited. RSMRs are potentially more useful, since they fit regional organization and might be a more valid representation of quality of care.

Cardiovascular diseases are the leading cause of death globally and contribute significantly to the cost of healthcare. Artificial intelligence (AI) is poised to reshape cardiology. Using supervised and unsupervised learning, the two main branches of AI, several applications have been developed in recent years to improve risk prediction, allow large-scale analysis of medical data, and phenotype patients for personalized medicine. In this review, we examine the key advances in AI in cardiology and its limitations regarding bias in the data, standardization in reporting, data access, and model trust and accountability in cases of error. Finally, we discuss implementation methods to unleash AI\'s potential in making healthcare more accurate and efficient. Several steps need to be followed and challenges overcome in order to successfully integrate AI in clinical practice and ensure its longevity.

UNASSIGNED: Improving performance often requires health care teams to employ creativity in problem solving, a key attribute of learning health systems. Despite increasing interest in the role of creativity in health care, empirical evidence documenting how this concept manifests in real-world contexts remains limited.
UNASSIGNED: We conducted a qualitative study to understand how creativity was fostered during problem solving in 10 hospitals that took part in a 2-year collaborative to improve cardiovascular care outcomes. We analyzed interviews with 197 hospital team members involved in the collaborative, focusing on work processes or outcomes that participants self-identified as creative or promoting creativity. We sought to identify recurrent patterns across instances of creativity in problem solving.
UNASSIGNED: Participants reported examples of creativity at both stages typically identified in problem solving research and practice: uncovering non-obvious problems and finding novel solutions. Creativity generally involved the assembly of an \"ecological view\" of the care process, which reflected a more complete understanding of relationships between individual care providers, organizational sub-units, and their environment. Teams used three prominent behaviors to construct the ecological view: (a) collecting new and diverse information, (b) accepting (rather than dismissing) disruptive information, and (c) employing empathy to understand and share feelings of others.
UNASSIGNED: We anticipate that findings will be useful to researchers and practitioners who wish to understand how creativity can be fostered in problem solving to improve clinical outcomes and foster learning health systems.

BACKGROUND: Cardiovascular disease remains the number one cause of death globally. Patients with cardiovascular disease are at risk of poor outcomes from deferral of healthcare during the coronavirus disease 2019 (COVID-19) pandemic. Little is known about recovery of cardiovascular hospitalizations or procedural volume following the COVID-19 surges. We sought to examine the cardiovascular diagnoses requiring healthcare utilization surrounding the first and second COVID-19 waves and characterize trends in return to pre-pandemic levels at a tertiary care center in Massachusetts.
METHODS: Using electronic health records and administrative claims data, we performed a retrospective analysis of patients undergoing cardiovascular procedures and admitted to inpatient cardiology services throughout the first two COVID surges. ICD-10 codes were used to categorize admissions.
RESULTS: Patients who presented for care during the initial COVID-19 surge were younger, had higher comorbidity burden, and longer length-of-stay compared with pre- and post-surge. Marked declines in admissions in the first wave (to 29% of pre-surge levels) followed eventually by complete recovery were noted across all cardiac diagnoses, with smaller declines seen in the second wave. Cardiac procedural volume declined significantly during the initial surge but quickly rebounded post-surge, eventually eclipsing pre-COVID.
CONCLUSIONS: There was a gradual but initially incomplete recovery to pre-surge levels of hospitalizations and procedures during the reopening phase, which eventually rebounded to meet or exceed pre-COVID-19 levels. To the extent that this reflects deferred or foregone essential care, it may adversely affect long-term cardiovascular outcomes. These results should inform planning for cardiovascular care delivery during future pandemic surges.