A mobile health application for patients eligible for statin therapy: app development and qualitative feedback on design and usability.

BACKGROUND: Cardiovascular disease is the leading cause of death in the United States (US). Despite the well-recognized efficacy of statins, statin discontinuation rates remain high. Statin intolerance is a major cause of statin discontinuation. To accurately diagnose statin intolerance, healthcare professionals must distinguish between statin-associated and non-statin-associated muscle symptoms, because many muscle symptoms can be unrelated to statin therapy. Patients' feedback on muscle-related symptoms would help providers make decisions about statin treatment. Given the potential benefits and feasibility of existing apps for cardiovascular disease (CVD) management and the unmet need for an app specifically addressing statin intolerance management, the objectives of the study were 1) to describe the developmental process of a novel app designed for patients who are eligible for statin therapy to lower the risk of CVD; 2) to explore healthcare providers' feedback of the app; and 3) to explore patients' app usage experience. METHODS: The app was developed by an interdisciplinary team. Healthcare provider participants and patient participants were recruited in the study. Providers were interviewed to provide their feedback about the app based on screenshots of the app. Patients were interviewed after a 30 days of app usage. RESULTS: The basic features of the app included symptom logging, vitals tracking, patient education, and push notifications. Overall, both parties provided positive feedback about the app. Areas to be improved mentioned by both parties included: the pain question asked in symptom tracking and the patient education section. Both parties agreed that it was essential to add the trend report of the logged symptoms. CONCLUSIONS: The results indicated that providers were willing to use patient-reported data for disease management and perceived that the app had the potential to facilitate doctor-patient communication. Results also indicated that user engagement is the key to the success of app efficacy. To promote app engagement, app features should be tailored to individual patient's needs and goals. In the future, after it is upgraded, we plan to test the app usability and feasibility among a more diverse sample.

Contemporary patterns of lipoprotein(a) testing and associated clinical care and outcomes.

Objective: Elevated lipoprotein(a) [Lp(a)] is associated with atherosclerotic cardiovascular disease, yet little is known about Lp(a) testing patterns in real-world practice. The objective of this analysis was to determine how Lp(a) testing is used in clinical practice in comparison with low density lipoprotein cholesterol (LDL-C) testing alone, and to determine whether elevated Lp(a) level is associated with subsequent initiation of lipid-lowering therapy (LLT) and incident cardiovascular (CV) events. Methods: This is an observational cohort study, based on lab tests administered between Jan 1, 2015 and Dec 31, 2019. We used electronic health record (EHR) data from 11 United States health systems participating in the National Patient-Centered Clinical Research Network (PCORnet). We created two cohorts for comparison: 1) the Lp(a) cohort, of adults with an Lp(a) test and 2) the LDL-C cohort, of 4:1 date- and site-matched adults with an LDL-C test, but no Lp(a) test. The primary exposure was the presence of an Lp(a) or LDL-C test result. In the Lp(a) cohort, we used logistic regression to assess the relationship between Lp(a) results in mass units (< 50, 50-100, and > 100mg/dL) and molar units (<125, 125-250, > 250nmol/L) and initiation of LLT within 3 months. We used multivariable adjusted Cox proportional hazards regression to evaluate these Lp(a) levels and time to composite CV hospitalization, including hospitalization for myocardial infarction, revascularization and ischemic stroke. Results: Overall, 20,551 patients had Lp(a) test results and 2,584,773 patients had LDL-C test results (82,204 included in the matched LDL-C cohort). Compared with the LDL-C cohort, the Lp(a) cohort more frequently had prevalent ASCVD (24.3% vs. 8.5%) and multiple prior CV events (8.6% vs. 2.6%). Elevated Lp(a) was associated with greater odds of subsequent LLT initiation. Elevated Lp(a) reported in mass units was also associated with subsequent composite CV hospitalization [aHR (95% CI): Lp(a) 50-100mg/dL 1.25 (1.02-1.53), p<0.03, Lp(a) > 100mg/dL 1.23 (1.08-1.40), p<0.01]. Conclusion: Lp(a) testing is relatively infrequent in health systems across the U.S. As new therapies for Lp(a) emerge, improved patient and provider education is needed to increase awareness of the utility of this risk marker.

Transferrin predicts trimethylamine-N-oxide levels and is a potential biomarker of cardiovascular disease.

INTRODUCTION: Trimethylamine-N-oxide (TMAO) is a circulating biomarker associated with cardiovascular disease (CVD). Production of TMAO is facilitated by gut microbiota and dependent on micronutrients such as choline, betaine, and L-carnitine, present in foods such as red meat and eggs. HYPOTHESIS: We sought to predict serum TMAO quartile levels among healthy individuals at increased risk of CVD using clinical data via an ordinal logistic model. METHODS: Data from participants (n = 127) enrolled in a longitudinal observational study on CVD were used to build a predictive model for TMAO using ordinal logistic regression with demographic variables and 40 other variables considered related to CVD risk. First, univariate models for each covariate were tested (with serum TMAO quartiles as the dependent variable), and only variables with P < 0.30 were evaluated further. Second, demographic variables (age, gender, white vs. non-white race) were included in a multivariable model with each previously identified independent variable controlling for potential confounding. Last, the final model included fixed demographics and candidates from the confounder-adjusted model with P < 0.10. RESULTS: Eight candidate variables were included in the final model, with only transferrin, high-density lipoprotein cholesterol (HDL-C) and race (white vs. non-white) showing significant associations with TMAO. Participants had 0.16 (Q2), 0.31 (Q3), and 0.20 (Q4) odds of being in a higher TMAO quartile compared with participants in the lowest transferrin quartile. Non-white participants had 2.92 times higher odds of being in the highest TMAO quartile compared to white individuals. Participants in the second quartile of HDL-C had 2.68 times higher odds of being in a higher TMAO quartile compared with participants in the lowest HDL-C quartile. CONCLUSIONS: Transferrin demonstrated a significant predictive association with TMAO and may represent a novel potential biomarker of increased CVD risk worthy of further study. These results warrant further examination of iron, metabolism, homeostasis, and gut microbiome to better understand and mitigate known increased CVD risk.

mHealth Interventions for Self-management of Hypertension: Framework and Systematic Review on Engagement, Interactivity, and Tailoring.

BACKGROUND: Engagement is essential for the effectiveness of digital behavior change interventions. Existing systematic reviews examining hypertension self-management interventions via mobile apps have primarily focused on intervention efficacy and app usability. Engagement in the prevention or management of hypertension is largely unknown. OBJECTIVE: This systematic review explores the definition and role of engagement in hypertension-focused mobile health (mHealth) interventions, as well as how determinants of engagement (ie, tailoring and interactivity) have been implemented. METHODS: A systematic review of mobile app interventions for hypertension self-management targeting adults, published from 2013 to 2020, was conducted. A total of 21 studies were included in this systematic review. RESULTS: The engagement was defined or operationalized as a microlevel concept, operationalized as interaction with the interventions (ie, frequency of engagement, time or duration of engagement with the program, and intensity of engagement). For all 3 studies that tested the relationship, increased engagement was associated with better biomedical outcomes (eg, blood pressure change). Interactivity was limited in digital behavior change interventions, as only 7 studies provided 2-way communication between users and a health care professional, and 9 studies provided 1-way communication in possible critical conditions; that is, when abnormal blood pressure values were recorded, users or health care professionals were notified. The tailoring of interventions varied at different aspects, from the tailoring of intervention content (including goals, patient education, advice and feedback from health professionals, reminders, and motivational messages) to the tailoring of intervention dose and communication mode. Tailoring was carried out in a number of ways, considering patient characteristics such as goals, preferences, disease characteristics (eg, hypertension stage and medication list), disease self-management experience levels, medication adherence rate, and values and beliefs. CONCLUSIONS: Available studies support the importance of engagement in intervention effectiveness as well as the essential roles of patient factors in tailoring, interactivity, and engagement. A patient-centered engagement framework for hypertension self-management using mHealth technology is proposed here, with the intent of facilitating intervention design and disease self-management using mHealth technology.

A multistate transition model for statin-induced myopathy and statin discontinuation.

The overarching goal of this study was to simultaneously model the dynamic relationships among statin exposure, statin discontinuation, and potentially statin-related myopathic outcomes. We extracted data from the Indiana Network of Patient Care for 134,815 patients who received statin therapy between January 4, 2004, and December 31, 2008. All individuals began statin treatment, some discontinued statin use, and some experienced myopathy and/or rhabdomyolysis while taking the drug or after discontinuation. We developed a militate model to characterize 12 transition probabilities among six different states defined by use or discontinuation of statin and its associated myopathy or rhabdomyolysis. We found that discontinuation of statin therapy was common and frequently early, with 44.4% of patients discontinuing therapy after 1 month, and discontinuation is a strong indicator for statin-induced myopathy (risk ratio, 10.8; p < 0.05). Women more likely than men (p < 0.05) and patients aged 65 years and older had a higher risk than those aged younger than 65 years to discontinue statin use or experience myopathy. In conclusion, we introduce an innovative multistate model that allows clear depiction of the relationship between statin discontinuation and statin-induced myopathy. For the first time, we have successfully demonstrated and quantified the relative risk of myopathy between patients who continued and discontinued statin therapy. Age and sex were two strong risk factors for both statin discontinuation and incident myopathy.

Inherited Variants in SCARB1 Cause Severe Early-Onset Coronary Artery Disease.

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Usefulness of Integrating Heart Failure Risk Factors Into Impairment of Global Longitudinal Strain to Predict Anthracycline-Related Cardiac Dysfunction.

The prediction of cancer therapeutics-related cardiac dysfunction (CTRCD) is an essential aspect of care for individuals who receive potentially cardiotoxic oncologic treatments. Certain clinical risk factors have been described for incident CTRCD, and measurement of left ventricular (LV) longitudinal strain by speckle tracking 2-dimensional echocardiography (2DE) is the best-validated myocardial mechanical imaging assessment to detect subtle changes in LV function during cancer treatment. However, the direct integration of clinical and imaging risk factors to predict CTRCD has not yet been extensively examined. This was a retrospective study of 183 women with breast cancer aged 50.9 ± 10.8 years who received treatment with anthracyclines (doxorubicin dose of 422 ± 69 mg/m2, with 41.2% of subjects also receiving trastuzumab) and underwent 2DE at clinically determined intervals. CTRCD was diagnosed when LV ejection fraction dropped ≥10% to a subnormal (<53%) value by 2DE. Left ventricular global longitudinal strain (LV-GLS) was assessed offline. The risk prediction tool based only on clinical factors previously described by Ezaz et al was applied to our cohort and accurately stratified these subjects into low-, intermediate-, and high-risk groups, with incident CTRCD in 7.4%, 26.9%, and 54.6%, respectively (chi-square = 20.7, p <0.0001). We developed novel multivariate models to predict CTRCD using (1) demographic variables only (c = 0.8674), (2) echocardiographic (peak LV-GLS) variables only (c = 0.8440), or (3) a combination of demographic and echocardiographic variables, with the combined model exhibiting superior receiver-operating characteristics (c = 0.9629). In conclusion, estimation of CTRCD risk should integrate all available data, including both clinical variables and an imaging assessment.

Clinical significance of intermediate left ventricular trabeculations in cardiac magnetic resonance.

OBJECTIVE: Although the clinical importance of left ventricular noncompaction cardiomyopathy (LVNC) is known, few data exist that describe the prognosis associated with intermediate levels of LV trabeculations that do not meet criteria for LVNC. METHODS: Trabeculation/possible LVNC by CMR was retrospectively observed among 122 consecutive cases. We assessed the end-systolic noncompacted-to-compacted ratios (ESNCCR) along with deaths, embolic events, congestive heart failure (CHF) readmissions, ventricular arrhythmias, myocardial thickening (MT), and ejection fraction (EF). ESNCCRs were categorized as follows: <1, 1<1.5, 1.5<2, ≥2. General linear models were used to compare combined events (death, CHF readmission, embolism, ventricular arrhythmia) between categories of ESNCCR. There were 3 models used: model 1: unadjusted; model 2: adjusted for age, race, gender, body surface area, LV ejection fraction, and trabeculated segments; model 3: model 2+adjustment for myocardial thickening. RESULTS: In model 1, those with an ESNCCR<1 had a lower association with composite clinical events than those with a ratio between 1.5<2 and those≥2 (P<0.002 and P<0.001, respectively). In model 2, the lower association continued, (P=0.009 and P<0.001, respectively), but in model 3, those with a ratio from 1.5-2 only had a trend towards a higher association with composite clinical events than those with a ratio<1 (P=-0.09). Those with a ratio≥2 continued to have a higher association (P=-0.001). CONCLUSION: Patients with intermediate trabeculations not meeting criteria for LVNC had a higher association with composite clinical events, but it was mediated by decreased myocardial thickening in the associated compacted layer.