Background: Screening for cognitive impairment in primary care is important, yet primary care physicians (PCPs) report conducting routine cognitive assessments for less than half of patients older than 60 years of age. Linus Health's Core Cognitive Evaluation (CCE), a tablet-based digital cognitive assessment, has been used for the detection of cognitive impairment, but its application in primary care is not yet studied.
Objective: This study aimed to explore the integration of CCE implementation in a primary care setting.
Atrial fibrillation (AF) is a prevalent and morbid abnormality of the heart rhythm with a strong genetic component. Here, we meta-analyzed genome and exome sequencing data from 36 studies that included 52,416 AF cases and 277,762 controls. In burden tests of rare coding variation, we identified novel associations between AF and the genes MYBPC3, LMNA, PKP2, FAM189A2 and KDM5B.
View Article and Find Full Text PDFAtrial fibrillation (AF) is the most common heart rhythm abnormality and is a leading cause of heart failure and stroke. This large-scale meta-analysis of genome-wide association studies increased the power to detect single-nucleotide variant associations and found more than 350 AF-associated genetic loci. We identified candidate genes related to muscle contractility, cardiac muscle development and cell-cell communication at 139 loci.
View Article and Find Full Text PDFBackground: Despite the known benefits of physical activity, cancer survivors remain insufficiently active. Prior trials have adopted digital health methods, although several have been pedometer-based and enrolled mainly female, non-Hispanic White, and more highly educated survivors of breast cancer.
Objective: The objective of this study was to test a previously developed mobile health system consisting of a Fitbit activity tracker and the MyDataHelps smartphone app for feasibility in a diverse group of cancer survivors, with the goal of refining the program and setting the stage for a larger future trial.
: Fatal coronary heart disease (FCHD) affects ~650,000 people yearly in the US. Electrocardiographic artificial intelligence (ECG-AI) models can predict adverse coronary events, yet their application to FCHD is understudied. : The study aimed to develop ECG-AI models predicting FCHD risk from ECGs.
View Article and Find Full Text PDFIn the early stages of atrial fibrillation (AF), most cases are paroxysmal (pAF), making identification only possible with continuous and prolonged monitoring. With the advent of wearables, smartwatches equipped with photoplethysmographic (PPG) sensors are an ideal approach for continuous monitoring of pAF. There have been numerous studies demonstrating successful capture of pAF events, especially using deep learning.
View Article and Find Full Text PDFBackground: The relationship between severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) viral dynamics during acute infection and the development of long coronavirus disease 2019 (COVID-19), or "long COVID," is largely unknown.
Methods: Between October 2021 and February 2022, 7361 people not known to have COVID-19 self-collected nasal swab samples for SARS-CoV-2 reverse-transcription polymerase chain reaction testing every 24-48 hours for 10-14 days. Participants whose first known SARS-CoV-2 infection was detected were surveyed for long COVID in August 2023.
JACC Clin Electrophysiol
January 2025
Background/objective: Hypertensive disorders of pregnancy (HDP) are a major cause of maternal morbidity and mortality in the US. Improved diagnosis and treatment of HDP may be achieved through home blood pressure monitoring (HBPM). However, there are challenges to effective HBPM during pregnancy.
View Article and Find Full Text PDFJ Am Coll Cardiol
November 2024
Background: Atrial fibrillation (AF) often remains undiagnosed, and it independently raises the risk of ischemic stroke, which is largely reversible by oral anticoagulation. Although randomized trials using longer term screening approaches increase identification of AF, no studies have established that AF screening lowers stroke rates.
Objectives: To address this knowledge gap, the GUARD-AF (Reducing Stroke by Screening for Undiagnosed Atrial Fibrillation in Elderly Individuals) trial screened participants in primary care practices using a 14-day continuous electrocardiographic monitor to determine whether screening for AF coupled with physician/patient decision-making to use oral anticoagulation reduces stroke and provides a net clinical benefit compared with usual care.
Background: The number of individuals using digital health devices has grown in recent years. A higher rate of use in patients suggests that primary care providers (PCPs) may be able to leverage these tools to effectively guide and monitor physical activity (PA) for their patients. Despite evidence that remote patient monitoring (RPM) may enhance obesity interventions, few primary care practices have implemented programs that use commercial digital health tools to promote health or reduce complications of the disease.
View Article and Find Full Text PDFObjectives: To address the challenges of sharing clinical research data through the implementation of cloud-based virtual desktops, enhancing collaboration among researchers while maintaining data security.
Materials And Methods: This case study details the deployment of virtual desktops at UMass Chan Medical School (UMass Chan). The process involved forming a Research Informatics Steering Executive workgroup, identifying key requirements, implementing Amazon WorkSpaces, and establishing configurable data management for research support.
The promise of artificial intelligence has generated enthusiasm among patients, health care professionals, and technology developers who seek to leverage its potential to enhance the diagnosis and management of an increasing number of chronic and acute conditions. Point-of-care testing increases access to care because it enables care outside of traditional medical settings. Collaboration among developers, clinicians, and end users is an effective best practice for solving clinical problems.
View Article and Find Full Text PDFBackground: Step counting is comparable among many research-grade and consumer-grade accelerometers in laboratory settings.
Objective: The purpose of this study was to compare the agreement between Actical and Apple Watch step-counting in a community setting.
Methods: Among Third Generation Framingham Heart Study participants (N=3486), we examined the agreement of step-counting between those who wore a consumer-grade accelerometer (Apple Watch Series 0) and a research-grade accelerometer (Actical) on the same days.
Objectives: Early rehospitalization of frail older adults after hospital discharge is harmful to patients and challenging to hospitals. Mobile integrated health (MIH) programs may be an effective solution for delivering community-based transitional care. The objective of this study was to assess the feasibility and implementation of an MIH transitional care program.
View Article and Find Full Text PDFIntroduction: The relationship between SARS-CoV-2 viral dynamics during acute infection and the development of long COVID is largely unknown.
Methods: A total of 7361 asymptomatic community-dwelling people enrolled in the Test Us at Home parent study between October 2021 and February 2022. Participants self-collected anterior nasal swabs for SARS-CoV-2 RT-PCR testing every 24-48 hours for 10-14 days, regardless of symptom or infection status.
Background: Stroke continues to be a leading cause of death and disability worldwide despite improvements in prevention and treatment. Traditional stroke risk calculators are biased and imprecise. Novel stroke predictors need to be identified.
View Article and Find Full Text PDFBackground: Fatal coronary heart disease (FCHD) is often described as sudden cardiac death (affects >4 million people/year), where coronary artery disease is the only identified condition. Electrocardiographic artificial intelligence (ECG-AI) models for FCHD risk prediction using ECG data from wearable devices could enable wider screening/monitoring efforts.
Objectives: To develop a single-lead ECG-based deep learning model for FCHD risk prediction and assess concordance between clinical and Apple Watch ECGs.
Cardiovasc Digit Health J
June 2024
Background: The use of point-of-care (POC) tests prior to the COVID-19 pandemic was relatively infrequent outside of the health care context. Little is known about how public opinions regarding POC tests have changed during the pandemic.
Methods: We redeployed a validated survey to uncompensated volunteers to assess preferences for point-of-care testing (POCT) benefits and concerns between June and September 2022.
Background: Handheld single-lead electrocardiographic (1L ECG) devices are increasingly used for atrial fibrillation (AF) screening, but their real-world performance is not well understood.
Objectives: The purpose of this study was to quantify the diagnostic test characteristics of 1L ECG automated interpretations for prospective AF screening.
Methods: We calculated the diagnostic test characteristics of the AliveCor KardiaMobile 1L ECG (AliveCor, US) algorithm using unblinded cardiologist overread as the gold standard using single 30s tracings administered by medical assistants among individuals aged ≥65 years participating in the VITAL-AF trial (NCT03515057) of population-based AF screening embedded within routine primary care.