Remote Health Monitoring Outcome Success Prediction Using Baseline and First Month Intervention Data.

Remote health monitoring (RHM) systems are becoming more widely adopted by clinicians and hospitals to remotely monitor and communicate with patients while optimizing clinician time, decreasing hospital costs, and improving quality of care. In the Women's heart health study (WHHS), we developed Wanda-cardiovascular disease (CVD), where participants received healthy lifestyle education followed by six months of technology support and reinforcement. Wanda-CVD is a smartphone-based RHM system designed to assist participants in reducing identified CVD risk factors through wireless coaching using feedback and prompts as social support. Many participants benefitted from this RHM system. In response to the variance in participants' success, we developed a framework to identify classification schemes that predicted successful and unsuccessful participants. We analyzed both contextual baseline features and data from the first month of intervention such as activity, blood pressure, and questionnaire responses transmitted through the smartphone. A prediction tool can aid clinicians and scientists in identifying participants who may optimally benefit from the RHM system. Targeting therapies could potentially save healthcare costs, clinician, and participant time and resources. Our classification scheme yields RHM outcome success predictions with an F-measure of 91.9%, and identifies behaviors during the first month of intervention that help determine outcome success. We also show an improvement in prediction by using intervention-based smartphone data. Results from the WHHS study demonstrates that factors such as the variation in first month intervention response to the consumption of nuts, beans, and seeds in the diet help predict patient RHM protocol outcome success in a group of young Black women ages 25-45.

Remote health monitoring: predicting outcome success based on contextual features for cardiovascular disease.

Current studies have produced a plethora of remote health monitoring (RHM) systems designed to enhance the care of patients with chronic diseases. Many RHM systems are designed to improve patient risk factors for cardiovascular disease, including physiological parameters such as body mass index (BMI) and waist circumference, and lipid profiles such as low density lipoprotein (LDL) and high density lipoprotein (HDL). There are several patient characteristics that could be determining factors for a patient's RHM outcome success, but these characteristics have been largely unidentified. In this paper, we analyze results from an RHM system deployed in a six month Women's Heart Health study of 90 patients, and apply advanced feature selection and machine learning algorithms to identify patients' key baseline contextual features and build effective prediction models that help determine RHM outcome success. We introduce Wanda-CVD, a smartphone-based RHM system designed to help participants with cardiovascular disease risk factors by motivating participants through wireless coaching using feedback and prompts as social support. We analyze key contextual features that secure positive patient outcomes in both physiological parameters and lipid profiles. Results from the Women's Heart Health study show that health threat of heart disease, quality of life, family history, stress factors, social support, and anxiety at baseline all help predict patient RHM outcome success.

Clinical implications of the Women's Ischemia Syndrome Evaluation: inter-relationships between symptoms, psychosocial factors and cardiovascular outcomes.

Cardiovascular disease remains the leading cause of death in the USA and is associated with several modifiable (hypertension, diabetes, high cholesterol, tobacco use, physical inactivity, obesity and unhealthy diet) and nonmodifiable (age, gender and family history) risk factors. The role of psychosocial risk factors in the development of cardiovascular disease has a growing body of literature, and differences in men and women have been identified. The Women's Ischemia Syndrome Evaluation provides insight into psychosocial risk factors in a cohort of women presenting with chest pain who had a comprehensive battery of psychosocial assessments and long-term follow-up. This review focuses on symptom presentation for chest pain and its relationship to cardiovascular disease morbidity and mortality, quality of life, healthcare costs and psychosocial predictor variables, including anxiety, depression, hostility and social networks. In the Women's Ischemia Syndrome Evaluation, persistent chest pain was associated with an increased rate of adverse events and relatively high rates of depression and anxiety, with reduced functional capacity and impaired quality of life, over a median of 6 years of follow-up. More research is needed to better understand the relationships between symptoms and negative emotions and to determine whether psychological (pharmacologic and/or cognitive) interventions might impact both psychological and cardiovascular outcomes.

Anxiety associations with cardiac symptoms, angiographic disease severity, and healthcare utilization: the NHLBI-sponsored Women's Ischemia Syndrome Evaluation.

BACKGROUND: Anxiety is common among patients presenting with suspected coronary artery disease (CAD). In a sample of women with signs and symptoms of ischemia, we examined three anxiety markers as predictors of CAD endpoints including: 1) cardiac symptom indicators; 2) angiographic CAD severity; and 3) healthcare utilization (cardiac hospitalizations and 5-year cardiovascular [CVD] healthcare costs). METHODS: Participants completed a baseline protocol including coronary angiogram, cardiac symptoms, psychosocial measures and a median 5.9-year follow-up to track hospitalizations. We calculated CVD costs based on cardiac hospitalizations, treatment visits, and CVD medications. Anxiety measures included anxiolytic medication use, Spielberger Trait Anxiety Inventory (STAI) scores, and anxiety disorder treatment history. RESULTS: The sample numbered 514 women with anxiety measure data and covariates (mean age=57.5 [11.1]). One in five (20.4%) women reported using anxiolytic agents. Anxiety correlated with cardiac symptom indicators (anxiolytic use with nighttime angina and nitroglycerine use; STAI scores and anxiety disorder treatment history with nighttime angina, shortness of breath, and angina frequency). Anxiety disorder treatment history (but not STAI scores or anxiolytics) predicted less severe CAD. Anxiolytic use (but not STAI scores or anxiety disorder treatment history) predicted hospitalizations for chest pain and coronary catheterization (HRs=2.0, 95% CIs=1.1-4.7). Anxiety measures predicted higher 5-year CVD costs (+9.0-42.7%) irrespective of CAD severity. CONCLUSIONS: Among women with signs and symptoms of myocardial ischemia, anxiety measures predict cardiac endpoints ranging from cardiac symptom severity to healthcare utilization. Based on these findings, anxiety may warrant greater consideration among women with suspected CAD.

Self-rated versus objective health indicators as predictors of major cardiovascular events: the NHLBI-sponsored Women's Ischemia Syndrome Evaluation.

OBJECTIVE: To determine the association between self-rated health and major cardiovascular events in a sample of women with suspected myocardial ischemia. Previous studies showed that self-rated health is a predictor of objective health outcomes, such as mortality. METHOD: At baseline, 900 women rated their health on a 5-point scale ranging from poor to excellent as part of a protocol that included quantitative coronary angiography, cardiovascular disease (CVD) risk factor assessment, cardiac symptoms, psychotropic medication use, and functional impairment. Participants were followed for a maximum of 9 years (median, 5.9 years) to determine the prevalence of major CVD events (myocardial infarction, heart failure, stroke, and CVD-related death). RESULTS: A total of 354 (39.3% of sample) participants reported their health as either poor or fair. After adjusting for demographic factors, CVD risk factors, and coronary artery disease severity, women who rated their health as poor (hazard ratio, 2.1 [1.1-4.2]) or fair (hazard ratio, 2.0 [1.2-3.6]) experienced significantly shorter times to major CVD events compared with women who rated their health as excellent or very good. Further adjustment for functional impairment, however, attenuated the self-rated health relationships with major CVD events. CONCLUSIONS: Among women with suspected myocardial ischemia, self-rated health predicted major CVD events independent of demographic factors, CVD risk factors, and angiogram-defined disease severity. However, functional impairment seemed to explain much of the self-rated health association. These results support the clinical utility of self-rated health scores in women and encourage a multidimensional approach to conceptualizing these measures.

Gender differences in coronary artery disease.

Coronary artery disease in women is associated with higher morbidity and mortality than in men. The purpose of this article is to summarize recent literature concerning gender-based differences. Specific differences in pathophysiology, traditional and psychosocial risk factors, symptom presentation, treatments, and outcomes between women and men will be reviewed.