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ImportanceSelf-measured blood pressure (SMBP) with commercially available connected smartphone applications may help patients effectively use SMBP measurements.ObjectiveTo determine if enhanced SMBP paired with a connected smartphone application was superior to standard SMBP for blood pressure (BP) reduction or patient satisfaction.Design, Setting, and ParticipantsThis randomized clinical trial was conducted among 23 health systems participating in PCORnet, the National Patient-Centered Clinical Research Network, and included patients who reported having uncontrolled BP at their last clinic visit, a desire to lower their BP, and a smartphone. Enrollment and randomization occurred from August 3, 2019, to December 31, 2020, which was followed by 6 months of follow-up for each patient. Analysis commenced shortly thereafter.InterventionsEligible participants were randomly assigned to enhanced SMBP using a device that paired with a connected smartphone application (enhanced) or a standard device (standard). Participants received their device in the mail, along with web-based educational materials and phone-based support as needed. No clinician engagement was undertaken, and the study provided no special mechanisms for delivering measurements to clinicians for use in BP management.Main Outcomes and MeasuresReduction in systolic BP, defined as the difference between clinic BP at baseline and the most recent clinic BP extracted from electronic health records at 6 months.ResultsEnrolled participants (1051 enhanced [50.0%] vs 1050 standard [50.0%]; 1191 women [56.7%]) were mostly middle-aged or older (mean [SD] age, 58 [13] years), nearly a third were Black or Hispanic (645 [31%]), and most were relatively comfortable using technology (mean [SD], 4.1 [1.1] of 5). The mean (SD) change in systolic BP from baseline to 6 months was −10.8 (18) mm Hg vs −10.6 (18) mm Hg (enhanced vs standard: adjusted difference, −0.19 mm Hg; 95% CI, −1.83 to 1.44; P = .81). Secondary outcomes were mostly null, except for documented attainment of BP control to lower than 140/Conclusions and RelevanceThis randomized clinical trial found that enhanced SMBP paired with a smartphone application is not superior to standard SMBP for BP reduction or patient satisfaction.Trial RegistrationClinicalTrials.gov Identifier: NCT03796689

BACKGROUND AND OBJECTIVE The Newborn Weight Tool (NEWT) can inform newborn feeding decisions and might reduce health care utilization by preventing excess weight loss. Clinical decision support (CDS) displaying NEWT might facilitate its use. Our study’s objective is to determine the effect of CDS displaying NEWT on feeding and health care utilization. METHODS At an hospital involved in NEWT development, we randomly assigned 2682 healthy infants born ≥36 weeks gestation in 2018–2019 either to CDS displaying NEWT with an electronic flag if most recent weight was ≥75th weight loss centile or to a control of usual care with NEWT accessed at clinician discretion. Our primary outcome was feeding type concordant with weight loss, defined as exclusive breastfeeding for those not flagged, exclusive breastfeeding or supplementation for those flagged once, and supplementation for those flagged more than once. Secondary outcomes included inpatient and outpatient utilization in the first 30 days. We used χ2 and Student’s t tests to compare intervention infants with control and to compare trial infants with those born in 2017. RESULTS Feeding was concordant with for 1854 (74.5%) trial infants and did not differ between randomized groups (P = .65); concordant feeding was higher for all trial infants than for infants born in 2017 (64.4%; P < .0005). Readmission occurred for 51 (3.8%) CDS infants and 45 (3.4%) control infants (P = .56). Among the 60% of trial infants with outpatient records available, there were 3.5 ± 1.7 visits with no differences between randomized groups (P = .10). CONCLUSIONS At an hospital involved in NEWT development, CDS displaying NEWT did not alter either feeding or health care utilization compared with discretionary NEWT access.

IMPORTANCE: Sleep has major consequences for physical and emotional well-being. Hospitalized patients experience frequent iatrogenic sleep interruptions and there is evidence that such interruptions can be safely reduced. OBJECTIVE: To determine whether a clinical decision support tool, powered by real-time patient data and a trained prediction algorithm, can help physicians identify clinically stable patients and safely discontinue their overnight vital sign checks. DESIGN, SETTING, AND PARTICIPANTS: A randomized clinical trial, with inpatient encounters randomized 1:1 to intervention vs usual care, was conducted from March 11 to November 24, 2019. Participants included physicians serving on the primary team of 1699 patients on the general medical service (not in the intensive care unit) of a tertiary care academic medical center. INTERVENTIONS: A clinical decision support notification informed the physician if the patient had a high likelihood of nighttime vital signs within the reference ranges based on a logistic regression model that used real-time patient data as input. The notification provided the physician an opportunity to discontinue measure of nighttime vital signs, dismiss the notification for 1 hour, or dismiss the notification for that day. MAIN OUTCOMES AND MEASURES: The primary outcome was delirium, as determined by bedside nurse assessment of Nursing Delirium Screening Scale scores, a standardized delirium screening tool (delirium diagnosed with score ≥2). Secondary outcomes included mean nighttime vital sign checks. Potential harms included intensive care unit transfers and code blue alarms. All analyses were conducted on the basis of intention-to-treat. RESULTS: A total of 1930 inpatient encounters in 1699 patients (intervention encounters: 566 of 966 [59%] men; mean [SD] age, 53 [15] years) were randomized. In the intervention vs control arm, there was a significant decrease in the mean (SD) number of nighttime vital sign checks (0.97 [0.95] vs 1.41 [0.86]; P

Objective To utilize, in an individual and institutional privacy-preserving manner, electronic health record (EHR) data from 202 hospitals by analyzing answers to COVID-19-related questions and posting these answers online. Materials and Methods We developed a distributed, federated network of 12 health systems that harmonized their EHRs and submitted aggregate answers to consortia questions posted at https://www.covid19questions.org. Our consortium developed processes and implemented distributed algorithms to produce answers to a variety of questions. We were able to generate counts, descriptive statistics, and build a multivariate, iterative regression model without centralizing individual-level data. Results Our public website contains answers to various clinical questions, a web form for users to ask questions in natural language, and a list of items that are currently pending responses. The results show, for example, that patients who were taking angiotensin-converting enzyme inhibitors and angiotensin II receptor blockers, within the year before admission, had lower unadjusted in-hospital mortality rates. We also showed that, when adjusted for, age, sex, and ethnicity were not significantly associated with mortality. We demonstrated that it is possible to answer questions about COVID-19 using EHR data from systems that have different policies and must follow various regulations, without moving data out of their health systems. Discussion and Conclusions We present an alternative or a complement to centralized COVID-19 registries of EHR data. We can use multivariate distributed logistic regression on observations recorded in the process of care to generate results without transferring individual-level data outside the health systems.

The global burden of diabetes is rapidly increasing, from 451 million people in 2019 to 693 million by 20451. The insidious onset of type 2 diabetes delays diagnosis and increases morbidity2. Given the multifactorial vascular effects of diabetes, we hypothesized that smartphone-based photoplethysmography could provide a widely accessible digital biomarker for diabetes. Here we developed a deep neural network (DNN) to detect prevalent diabetes using smartphone-based photoplethysmography from an initial cohort of 53,870 individuals (the ‘primary cohort’), which we then validated in a separate cohort of 7,806 individuals (the ‘contemporary cohort’) and a cohort of 181 prospectively enrolled individuals from three clinics (the ‘clinic cohort’). The DNN achieved an area under the curve for prevalent diabetes of 0.766 in the primary cohort (95% confidence interval: 0.750–0.782; sensitivity 75%, specificity 65%) and 0.740 in the contemporary cohort (95% confidence interval: 0.723–0.758; sensitivity 81%, specificity 54%). When the output of the DNN, called the DNN score, was included in a regression analysis alongside age, gender, race/ethnicity and body mass index, the area under the curve was 0.830 and the DNN score remained independently predictive of diabetes. The performance of the DNN in the clinic cohort was similar to that in other validation datasets. There was a significant and positive association between the continuous DNN score and hemoglobin A1c (P ≤ 0.001) among those with hemoglobin A1c data. These findings demonstrate that smartphone-based photoplethysmography provides a readily attainable, non-invasive digital biomarker of prevalent diabetes. A deep neural network applied to smartphone-based vascular imaging can detect diabetes, opening new possibilities for non-invasive diagnosis.

Background and aimsIn some states, liver transplantation (LT) for alcohol-associated liver disease (ALD) is covered by Medicaid only with documentation of abstinence and/or alcohol rehabilitation. Different Medicaid policies may affect the distribution of LT for ALD, particularly post-2011, as centers have adopted early (i.e., specific abstinence period not required) LT practices.Approach and resultsWe surveyed Medicaid policies in all states actively performing LT and linked state policies to prospectively collected national registry data on LT recipients from 2002 to 2017 with ALD as the primary listing diagnosis. We categorized Medicaid policies for states as "restrictive" (requiring documentation of a specific abstinence period and/or rehabilitation) versus "unrestrictive" (deferring to center eligibility policies). Difference-of-differences analysis, comparing 2002-2011 versus 2012-2017, evaluated whether restrictive policies were associated with decreased proportion of LTs paid by Medicaid among patients with ALD post-2011. We performed sensitivity analyses to account for any differences by diagnosis of hepatocellular carcinoma, hepatitis C virus, nonalcoholic steatohepatitis, or Medicare insurance. We also performed a sensitivity analysis to account for any difference by prevalence of ALD among restrictive versus unrestrictive states. Of 10,836 LT recipients in 2002-2017, 7,091 were from 24 states in the restrictive group and 3,745 from 14 states in the unrestrictive group. The adjusted proportion (95% confidence interval) of LTs paid by Medicaid among restrictive versus unrestrictive states between 2002 and 2011 was 17.6% (15.4%-19.8%) versus 18.9% (15.4%-22.3%) (P=0.54) and between 2012 and 2017, 17.2% (14.7%-19.7%) versus 23.2% (19.8%-26.6%) (P=0.005). In difference-of-differences analysis, restrictive (versus unrestrictive) policies were associated with a 4.7% (0.8%-8.6%) (P=0.02) absolute lower adjusted proportion of LTs for ALD paid by Medicaid post-2011.ConclusionsRestrictive Medicaid policies are present in most states with active LT centers and are associated with lower proportions of LTs for ALD paid by Medicaid post-2011 compared to states with unrestrictive Medicaid policies. Reevaluation of Medicaid alcohol use policies may be warranted, to align more closely with contemporary center-level practices.

Background Mindfulness can improve overall well-being by training individuals to focus on the present moment without judging their thoughts. However, it is unknown how much mindfulness practice and training are necessary to improve well-being. Objective The primary aim of this study was to determine whether a standard 8-session web-based mindfulness-based cognitive therapy (MBCT) program, compared with a brief 3-session mindfulness intervention, improved overall participant well-being. In addition, we sought to explore whether the treatment effects differed based on the baseline characteristics of the participants (ie, moderators). Methods Participants were recruited from 17 patient-powered research networks, web-based communities of stakeholders interested in a common research area. Participants were randomized to either a standard 8-session MBCT or a brief 3-session mindfulness training intervention accessed on the web. The participants were followed for 12 weeks. The primary outcome of the study was well-being, as measured by the World Health Organization—Five Well-Being Index. We hypothesized that MBCT would be superior to a brief mindfulness training. Results We randomized 4411 participants, 3873 (87.80%) of whom were White and 3547 (80.41%) of female sex assigned at birth. The mean baseline World Health Organization—Five Well-Being Index score was 50.3 (SD 20.7). The average self-reported well-being in each group increased over the intervention period (baseline to 8 weeks; model-based slope for the MBCT group: 0.78, 95% CI 0.63-0.93, and brief mindfulness group: 0.76, 95% CI 0.60-0.91) as well as the full study period (ie, intervention plus follow-up; baseline to 20 weeks; model-based slope for MBCT group: 0.41, 95% CI 0.34-0.48; and brief mindfulness group: 0.33, 95% CI 0.26-0.40). Changes in self-reported well-being were not significantly different between MBCT and brief mindfulness during the intervention period (model-based difference in slopes: −0.02, 95% CI −0.24 to 0.19; P=.80) or during the intervention period plus 12-week follow-up (−0.08, 95% CI −0.18 to 0.02; P=.10). During the intervention period, younger participants (P=.05) and participants who completed a higher percentage of intervention sessions (P=.005) experienced greater improvements in well-being across both interventions, with effects that were stronger for participants in the MBCT condition. Attrition was high (ie, 2142/4411, 48.56%), which is an important limitation of this study. Conclusions Standard MBCT improved well-being but was not superior to a brief mindfulness intervention. This finding suggests that shorter mindfulness programs could yield important benefits across the general population of individuals with various medical conditions. Younger people and participants who completed more intervention sessions reported greater improvements in well-being, an effect that was more pronounced for participants in the MBCT condition. This finding suggests that standard MBCT may be a better choice for younger people as well as treatment-adherent individuals. Trial Registration ClinicalTrials.gov NCT03844321; https://clinicaltrials.gov/ct2/show/NCT03844321

Key Points Question What factors are associated with adverse effects after COVID-19 vaccination? Findings In an online cohort study including 19 586 adults who received a COVID-19 vaccination, the factors most strongly associated with adverse effects were full vaccination dose, brand of vaccine, younger age, female sex, and having had COVID-19 before vaccination. Allergic reaction or anaphylaxis was reported in 0.3% of participants after partial vaccination and 0.2% of participants after full vaccination. Meaning These findings suggest that some individuals experience more adverse effects after COVID-19 vaccination, but serious adverse effects are rare., This cohort study evaluates factors potentially associated with participant-reported adverse effects after COVID-19 vaccination., Importance Little is known about the factors associated with COVID-19 vaccine adverse effects in a real-world population. Objective To evaluate factors potentially associated with participant-reported adverse effects after COVID-19 vaccination. Design, Setting, and Participants The COVID-19 Citizen Science Study, an online cohort study, includes adults aged 18 years and older with a smartphone or internet access. Participants complete daily, weekly, and monthly surveys on health and COVID-19–related events. This analysis includes participants who provided consent between March 26, 2020, and May 19, 2021, and received at least 1 COVID-19 vaccine dose. Exposures Participant-reported COVID-19 vaccination. Main Outcomes and Measures Participant-reported adverse effects and adverse effect severity. Candidate factors in multivariable logistic regression models included age, sex, race, ethnicity, subjective social status, prior COVID-19 infection, medical conditions, substance use, vaccine dose, and vaccine brand. Results The 19 586 participants had a median (IQR) age of 54 (38-66) years, and 13 420 (68.8%) were women. Allergic reaction or anaphylaxis was reported in 26 of 8680 participants (0.3%) after 1 dose of the BNT162b2 (Pfizer/BioNTech) or mRNA-1273 (Moderna) vaccine, 27 of 11 141 (0.2%) after 2 doses of the BNT162b2 or mRNA-1273 vaccine or 1 dose of the JNJ-78436735 (Johnson & Johnson) vaccine. The strongest factors associated with adverse effects were vaccine dose (2 doses of BNT162b2 or mRNA-1273 or 1 dose of JNJ-78436735 vs 1 dose of BNT162b2 or mRNA-1273; odds ratio [OR], 3.10; 95% CI, 2.89-3.34; P

Background The National Patient‐Centered Clinical Research Network Blood Pressure Control Laboratory Surveillance System was established to identify opportunities for blood pressure (BP) control improvement and to provide a mechanism for tracking improvement longitudinally. Methods and Results We conducted a serial cross‐sectional study with queries against standardized electronic health record data in the National Patient‐Centered Clinical Research Network (PCORnet) common data model returned by 25 participating US health systems. Queries produced BP control metrics for adults with well‐documented hypertension and a recent encounter at the health system for a series of 1‐year measurement periods for each quarter of available data from January 2017 to March 2020. Aggregate weighted results are presented overall and by race and ethnicity. The most recent measurement period includes data from 1 737 995 patients, and 11 956 509 patient‐years were included in the trend analysis. Overall, 15% were Black, 52% women, and 28% had diabetes. BP control ( Conclusions Major opportunities exist for improving BP control and reducing disparities, especially through consistent medication intensification when BP is uncontrolled. These data demonstrate substantial room for improvement and opportunities to close health equity gaps.

Key Points Question How often do persons with new febrile illness access coronavirus testing and receive a test result within 7 days of illness onset? Findings In this cohort study, generally low rates of coronavirus testing were observed in 2679 participants reporting new onset of febrile illness. Although testing rates improved somewhat during the study period, timely coronavirus test results were sought and received by only 25.9% of newly febrile persons at the end of the study analysis period in late October 2020. Meaning Our results suggest systematic underuse of coronavirus testing in patients with febrile illness that may contribute to community transmission., This cohort study examines rates of testing for SARS-CoV-2 and receipt of test results within 7 days of febrile illness onset using data from smartphone-based weekly surveys administered as part of the COVID-19 Citizen Science Study., Importance Active SARS-CoV-2 (coronavirus) transmission continues in the US. It is unclear whether better access to coronavirus testing and more consistent use of testing could substantially reduce transmission. Objective To describe coronavirus testing in persons with new onset of febrile illness and analyze whether there are changes over time and differences by race and ethnicity. Design, Setting, and Participants This cohort study used data from the COVID-19 Citizen Science Study, launched in March 2020, which recruited participants via press release, word-of-mouth, and partner organizations. Participants completed daily surveys about COVID-19 symptoms and weekly surveys about coronavirus testing. All adults (aged at least 18 years) with a smartphone were eligible to join. For this analysis, US participants with new onset of febrile illness from April 2020 to October 2020 were included. Data analysis was performed from November 2020 to March 2021. Main Outcomes and Measures Receipt of a coronavirus test result within 7 days of febrile illness onset. Results Of the 2679 participants included in this analysis, the mean (SD) age was 46.3 (13.4) years, 1983 were female (74%), 2017 were college educated (75%), and a total of 3865 distinct new febrile illness episodes were reported (300 episodes [7.8%] from Hispanic participants, 71 episodes [1.8%] from Black participants, and 3494 episodes [90.4%] from not Black, not Hispanic participants) between April 2 and October 23, 2020. In weekly surveys delivered during the 14 days after fever onset, 12% overall (753 participants) indicated receipt of a test result. Using serial survey responses and parametric time-to-event modeling, it was estimated that by 7 days after onset of febrile illness, a total of 20.5% (95% CI, 19.1%-22.0%) had received a test result. This proportion increased from 9.8% (95% CI, 7.5%-12.0%) early in the epidemic to 24.1% (95% CI, 21.5%-26.7%) at the end of July, but testing rates did not substantially improve since then, increasing to 25.9% (95% CI; 21.6%-30.3%) in late October at the start of the winter surge. Black participants reported receiving a test result about half as often as others (7% [7 of 103] of survey responses vs 12% [53 of 461] for Hispanic vs 13% [693 of 5516] for not Black, not Hispanic; P = .03). This association was not statistically significant in adjusted time-to-event models (hazard ratio = 0.59 vs not Black, not Hispanic participants; 95% CI, 0.26-1.34). Conclusions and Relevance Systematic underuse of coronavirus testing was observed in this cohort study through late October 2020, at the beginning of the winter COVID-19 surge, which may have contributed to preventable coronavirus transmission.

Resting heart rate can predict cardiovascular disease. Heart rate increases with tobacco smoking, but its association with cannabis use is unclear. We studied the association between current and cumulative cannabis use and heart rate.We used data from the Coronary Artery Risk Development in Young Adults (CARDIA) Study, a large prospective cohort of 5115 Black and white women and men followed over 30 years. We explored the association between cannabis exposure and heart rate, adjusted for demographic factors, cardiovascular risk factors, alcohol and other illicit drug use, physical activity, and beta-blockers, in mixed longitudinal models censoring participants with cardiovascular disease.CARDIA participants contributed to 35,654 individual examinations over 30 years. At the Year 30 examination, 471 out of 3269 (14%) currently used cannabis. In multivariable adjusted models, compared to no current use, using cannabis 5 times per month was associated with lower heart rate of -0.7 beats per minute (95% confidence interval: -1.0 to -0.3), and daily use with lower heart rate of -2.1 beats per minute (95% confidence interval: -3.0 to -1.3, overall P.001). Cumulative exposure to cannabis use was not associated with heart rate.Recent current cannabis use was associated with lower resting heart rate. The findings appeared to be transient because past cumulative exposure to cannabis was not associated with heart rate. This adds to the growing body of evidence suggesting a lack of deleterious association of cannabis use at a level typical of the general population on surrogate outcomes of cardiovascular disease.

Background Independent associations between cardiovascular risk factor exposures during midlife and later life development of heart failure (HF) with preserved ejection fraction (HFpEF) versus reduced EF (HFrEF) have not been previously studied. Methods We pooled data from 4 US cohort studies (Atherosclerosis Risk in Communities, Cardiovascular Health, Health , Aging and Body Composition, and Multi-Ethnic Study of Atherosclerosis) and imputed annual risk factor trajectories for body mass index, systolic and diastolic blood pressure, low-density lipoprotein and high-density lipoprotein cholesterol, and glucose starting from age 40 years. Time-weighted average exposures to each risk factor during midlife and later life were calculated and analyzed for associations with the development of HFpEF or HFrEF. Results A total of 23,861 participants were included (mean age at first in-person visit, 61.8 ±1 0.2 years; 56.6% female). During a median follow-up of 12 years, there were 3666 incident HF events, of which 51% had EF measured, including 934 with HFpEF and 739 with HFrEF. A high midlife systolic blood pressure and low midlife high-density lipoprotein cholesterol were associated with HFrEF, and a high midlife body mass index, systolic blood pressure, pulse pressure, and glucose were associated with HFpEF. After adjusting for later life exposures, only midlife pulse pressure remained independently associated with HFpEF. Conclusions Midlife exposure to cardiovascular risk factors are differentially associated with HFrEF and HFpEF later in life. Having a higher pulse pressure during midlife is associated with a greater risk for HFpEF but not HFrEF, independent of later life exposures.

Context The independent contribution of young adult exposure to overweight and obesity to later-life incident diabetes is not well studied. Objective To assess the associations of exposures to elevated body mass index (BMI) and waist circumference (WC) in young adulthood (ages 18-39 years) with incident diabetes later in life (≥40 years). Design Pooled data from 6 US prospective cohorts (Atherosclerosis Risk in Communities Study, Cardiovascular Risk Development in Young Adults Study, Cardiovascular Health Study, (4) Framingham Heart Study Offspring Cohort, (5) Health, Aging and Body Composition Study, and (6) Multi-Ethnic Study of Atherosclerosis. Setting Population-based cohort studies. Participants 30 780 participants (56.1% female, 69.8% non-Hispanic white) without a diagnosis of diabetes by age 40. Interventions We imputed BMI and WC trajectories from age 18 for every participant and estimated time-weighted average exposures to BMI or WC during young adulthood and later life. Main Outcome Measure(s) Incident diabetes defined as fasting glucose ≥126 mg/dL, nonfasting glucose ≥200 mg/dL, or use of diabetes medications. Results During a 9-year median follow-up, 4323 participants developed incident diabetes. Young adult BMI and WC were associated with later-life incident diabetes after controlling for later-life exposures [hazard ratios (HR) 1.99 for BMI ≥ 30 kg/m2 and 2.13 for WC > 88cm (women)/>102cm (men) compared to normal ranges]. Young adult homeostatic model of insulin resistance mediated 49% and 44% of the association between BMI and WC with later-life incident diabetes. High-density lipoproteins and triglycerides mediated a smaller proportion of these associations. Conclusions Elevated BMI and WC during young adulthood were independently associated with later-life incident diabetes. Insulin resistance may be a key mediator.

Background Consumer devices with broad reach may be useful in screening for atrial fibrillation (AF) in appropriate populations. However, currently no consumer devices are capable of continuous monitoring for AF. Objective The purpose of this study was to estimate the sensitivity and specificity of a smartwatch algorithm for continuous detection of AF from sinus rhythm in a free-living setting. Methods We studied a commercially available smartwatch with photoplethysmography (W-PPG) and electrocardiogram (W-ECG) capabilities. We validated a novel W-PPG algorithm combined with a W-ECG algorithm in a free-living setting, and compared the results to those of a 28-day continuous ECG patch (P-ECG). Results A total of 204 participants completed the free-living study, recording 81,944 hours with both P-ECG and smartwatch measurements. We found sensitivity of 87.8% (95% confidence interval [CI] 83.6%–91.0%) and specificity of 97.4% (95% CI 97.1%–97.7%) for the W-PPG algorithm (every 5-minute classification); sensitivity of 98.9% (95% CI 98.1%–99.4%) and specificity of 99.3% (95% CI 99.1%–99.5%) for the W-ECG algorithm; and sensitivity of 96.9% (95% CI 93.7%–98.5%) and specificity of 99.3% (95% CI 98.4%–99.7%) for W-PPG triggered W-ECG with a single W-ECG required for confirmation of AF. We found a very strong correlation of W-PPG in quantifying AF burden compared to P-ECG (r = 0.98). Conclusion Our findings demonstrate that a novel algorithm using a commercially available smartwatch can continuously detect AF with excellent performance and that confirmation with W-ECG further enhances specificity. In addition, our W-PPG algorithm can estimate AF burden. Further research is needed to determine whether this algorithm is useful in screening for AF in select at-risk patients.

BackgroundIn the absence of universal testing, effective therapies, or vaccines, identifying risk factors for viral infection, particularly readily modifiable exposures and behaviors, is required to identify effective strategies against viral infection and transmission.MethodsWe conducted a world-wide mobile application-based prospective cohort study available to English speaking adults with a smartphone. We collected self-reported characteristics, exposures, and behaviors, as well as smartphone-based geolocation data. Our main outcome was incident symptoms of viral infection, defined as fevers and chills plus one other symptom previously shown to occur with SARS-CoV-2 infection, determined by daily surveys.FindingsAmong 14, 335 participants residing in all 50 US states and 93 different countries followed for a median 21 days (IQR 10-26 days), 424 (3%) developed incident viral symptoms. In pooled multivariable logistic regression models, female biological sex (odds ration [OR] 1.75, 95% CI 1.39-2.20, pInterpretationWhile several immutable characteristics were associated with the risk of developing viral symptoms, multiple immediately modifiable exposures and habits that influence risk were also observed, potentially identifying readily accessible strategies to mitigate risk in the Covid-19 era.FundingThis study was funded by IU2CEB021881-01 and 3U2CEB021881-05S1 from the NIH/ NIBIB to Drs. Marcus, Olgin, and Pletcher.Research in contextEvidence before this studyPredictors of incident viral infection have been determined largely from cross-sectional studies prone to recall bias among individuals representing geographically constrained regions, and most were conducted before the era of the current Covid-19 pandemic.Added value of this studyWe conducted a world-wide, mobile application-based, longitudinal cohort study utilizing time-updated predictors and outcomes, providing novel and current information regarding risk-factors for incident viral symptoms based on real-time information in the era of Covid-19.Implications of all the available evidenceThese data suggest that certain immutable characteristics influence the risk for incident viral symptoms, while smoking cessation, physical distancing to avoid contact with individuals outside the household, regular exercise, and sanitizing one’s phone may each help mitigate the risk of viral infection.

IMPORTANCE: Atrial fibrillation (AF) is the most common arrhythmia. Although patients have reported that various exposures determine when and if an AF event will occur, a prospective evaluation of patient-selected triggers has not been conducted, and the utility of characterizing presumed AF-related triggers for individual patients remains unknown. OBJECTIVE: To test the hypothesis that n-of-1 trials of self-selected AF triggers would enhance AF-related quality of life. DESIGN, SETTING, AND PARTICIPANTS: A randomized clinical trial lasting a minimum of 10 weeks tested a smartphone mobile application used by symptomatic patients with paroxysmal AF who owned a smartphone and were interested in testing a presumed AF trigger. Participants were screened between December 22, 2018, and March 29, 2020. INTERVENTIONS: n-of-1 Participants received instructions to expose or avoid self-selected triggers in random 1-week blocks for 6 weeks, and the probability their trigger influenced AF risk was then communicated. Controls monitored their AF over the same time period. MAIN OUTCOMES AND MEASURES: AF was assessed daily by self-report and using a smartphone-based electrocardiogram recording device. The primary outcome comparing n-of-1 and control groups was the Atrial Fibrillation Effect on Quality-of-Life (AFEQT) score at 10 weeks. All participants could subsequently opt for additional trigger testing. RESULTS: Of 446 participants who initiated (mean [SD] age, 58 [14] years; 289 men [58%]; 461 White [92%]), 320 (72%) completed all study activities. Self-selected triggers included caffeine (n = 53), alcohol (n = 43), reduced sleep (n = 31), exercise (n = 30), lying on left side (n = 17), dehydration (n = 10), large meals (n = 7), cold food or drink (n = 5), specific diets (n = 6), and other customized triggers (n = 4). No significant differences in AFEQT scores were observed between the n-of-1 vs AF monitoring-only groups. In the 4-week postintervention follow-up period, significantly fewer daily AF episodes were reported after trigger testing compared with controls over the same time period (adjusted relative risk, 0.60; 95% CI, 0.43- 0.83; P

The risks of industrial pollutants are well documented,1 but few studies have examined the public health consequences of climate change–related events such as wildfires. The health benefits of physical activity and harms of sedentary behavior are well established.2,3 Although air pollution has been associated with self-reported reductions in physical activity, such ascertainment may be prone to recall bias.4,5 Accelerometer-based trackers have become increasingly used to estimate physical activity and can accurately measure step counts.6

Background Long-term cardiovascular health effects of marijuana are understudied. Future cardiovascular disease is often indicated by subclinical atherosclerosis for which carotid intima-media thickness is an established parameter. Methods Using the data from the Coronary Artery Risk Development in Young Adults (CARDIA) study, a cohort of 5115 Black and white women and men at Year 20 visit, we studied the association between carotid intima-media thickness in midlife and lifetime exposure to marijuana (1 marijuana year = 365 days of use) and tobacco smoking (1 pack-year = 20 cigarettes/day for 365 days). We measured carotid intima-media thickness by ultrasound and defined high carotid intima-media thickness at the threshold of the 75th percentile of all examined participants. We fit logistic regression models stratified by tobacco smoking exposure, adjusting for demographics, cardiovascular risk factors, and other drug exposures. Results Data was complete for 3257 participants; 2722 (84%) reported ever marijuana use; 374 (11%) were current users; 1539 (47%) reported ever tobacco smoking; 610 (19%) were current smokers. Multivariable adjusted models showed no association between cumulative marijuana exposure and high carotid intima-media thickness in never or ever tobacco smokers, odds ratio (OR) 0.87 (95% confidence interval [CI]: 0.63-1.21) at 1 marijuana-year among never smokers and OR 1.11 (95% CI: 0.85-1.45) among ever tobacco smokers. Cumulative exposure to tobacco was strongly associated with high carotid intima-media thickness, OR 1.88 (95%CI: 1.20-2.94) for 20 pack-years of exposure. Conclusions This study adds to the growing body of evidence that there might be no association between the average population level of marijuana use and subclinical atherosclerosis.

Background Regular physical activity is an important determinant of cardiovascular health and quality of life. Previous investigations examining the association between exercise and atrial fibrillation (AF) have been limited by self-reported, retrospectively collected activity data. Objective The purpose of this study was to objectively quantify differences in daily physical activity among individuals with and those without AF using electronic wearable activity trackers. Methods Daily exercise data were directly obtained from wrist-worn activity trackers (Fitbit, San Francisco, CA) among participants in the Health eHeart (HeH) study. Average daily step count was compared between individuals with and those without AF both before and after adjusting for comorbidities. AF severity was quantified using the Atrial Fibrillation Effect on QualiTy of Life (AFEQT) survey. Results Among 171,284 HeH study participants, 3333 individuals (234 with AF [7%]) submitted activity data. In unadjusted analysis, AF participants ambulated an average of 723 fewer steps per day (95% confidence interval [CI] 292–1154; P = .001) compared to individuals without AF. After adjustment for demographics and comorbid diseases, participants with AF demonstrated 591 fewer steps per day (95% CI 149–1033; P = .009). Among AF patients, AF severity was associated with less physical activity. For each single point decrease in AFEQT score (corresponding to more symptomatic AF), physical activity decreased by a mean 24 steps per day (95% CI 1–46; P = .04). Conclusion Objective, automatically collected step count data demonstrate that individuals with AF engage in significantly less average daily physical activity. In addition, worsening AF symptom severity is associated with reduced daily exercise.

Importance Determining blood pressure (BP) patterns in young adulthood that are associated with cardiovascular disease (CVD) events in later life may help to identify young adults who have an increased risk for CVD. Objective To determine whether the long-term variability of BP across clinical visits and the rate of change in BP from young adulthood to midlife are associated with CVD and all-cause mortality by middle age, independently of mean BP during young adulthood and a single BP in midlife. Design, Setting, and Participants This prospective cohort study included a community-based sample of 3394 African American and white participants in the Coronary Artery Risk Development in Young Adults (CARDIA) Study, enrolled from March 1985 through June 1986. Patterns of systolic BP (SBP) were evaluated with measurements at year 0 (baseline) and 2, 5, 7, and 10 years after baseline. Visit-to-visit SBP variability was estimated as BP variability independent of the mean (VIM). Data were collected from March 1985 through August 2015 and analyzed from June through October 2019. Main Outcomes and Measures Cardiovascular disease and all-cause mortality experienced through August 2015 were adjudicated. The associations of each SBP pattern with CVD events and all-cause mortality were determined using Cox proportional hazards regression models. Results At year 10, the mean (SD) age of the 3394 participants was 35.1 (3.6) years; 1557 (45.9%) were African American; 1892 (55.7%) were women; and 103 (3.0%) were taking antihypertensive medication. During a median follow-up of 20.0 (interquartile range, 19.4-20.2) years, 162 CVD events and 181 deaths occurred. When all BP pattern measurements were entered into the same model including a single SBP measurement at the year 10 examination, the hazard ratios for CVD events for each 1-SD increase in SBP measures were 1.25 (95% CI, 0.90-1.74) for mean SBP, 1.23 (95% CI, 1.07-1.43) for VIM SBP, and 0.99 (95% CI, 0.81-1.26) for annual change of SBP. The VIM for SBP was the only BP pattern associated with all-cause mortality (hazard ratio, 1.24; 95% CI, 1.09-1.41). Conclusions and Relevance The results of this study suggest that the assessment of visit-to-visit SBP variability may help identify young adults at increased risk for CVD and all-cause mortality later in life.

BackgroundCardiac arrhythmias have been observed among patients hospitalised with acute COVID-19 infection, and palpitations remain a common symptom among the much larger outpatient population of COVID-19 survivors in the convalescent stage of the disease.ObjectiveTo determine arrhythmia prevalence among outpatients after a COVID-19 diagnosis.MethodsAdults with a positive COVID-19 test and without a history of arrhythmia were prospectively evaluated with 14-day ambulatory electrocardiographic monitoring. Participants were instructed to trigger the monitor for palpitations.ResultsA total of 51 individuals (mean age 42±11 years, 65% women) underwent monitoring at a median 75 (IQR 34–126) days after a positive COVID-19 test. Median monitoring duration was 13.2 (IQR 10.5–13.8) days. No participant demonstrated atrial fibrillation, atrial flutter, sustained supraventricular tachycardia (SVT), sustained ventricular tachycardia or infranodal atrioventricular block. Nearly all participants (96%) had an ectopic burden of ConclusionsWe did not find evidence of malignant or sustained arrhythmias in outpatients after a positive COVID-19 diagnosis. While palpitations were common, symptoms frequently corresponded to sinus rhythm/sinus tachycardia or non-malignant arrhythmias such as isolated ectopy or non-sustained SVT. While these findings cannot exclude the possibility of serious arrhythmias in select individuals, they do not support a strong or widespread proarrhythmic effect of COVID-19 infection after resolution of acute illness.

Despite the high rate of sudden death after myocardial infarction among patients with a low ejection fraction, implantable cardioverter-defibrillators are contraindicated until 40 to 90 days after myocardial infarction. Whether a wearable cardioverter-defibrillator would reduce the incidence of sudden death during this high-risk period is unclear.We randomly assigned (in a 2:1 ratio) patients with acute myocardial infarction and an ejection fraction of 35% or less to receive a wearable cardioverter-defibrillator plus guideline-directed therapy (the device group) or to receive only guideline-directed therapy (the control group). The primary outcome was the composite of sudden death or death from ventricular tachyarrhythmia at 90 days (arrhythmic death). Secondary outcomes included death from any cause and nonarrhythmic death.Of 2302 participants, 1524 were randomly assigned to the device group and 778 to the control group. Participants in the device group wore the device for a median of 18.0 hours per day (interquartile range, 3.8 to 22.7). Arrhythmic death occurred in 1.6% of the participants in the device group and in 2.4% of those in the control group (relative risk, 0.67; 95% confidence interval [CI], 0.37 to 1.21; P=0.18). Death from any cause occurred in 3.1% of the participants in the device group and in 4.9% of those in the control group (relative risk, 0.64; 95% CI, 0.43 to 0.98; uncorrected P=0.04), and nonarrhythmic death in 1.4% and 2.2%, respectively (relative risk, 0.63; 95% CI, 0.33 to 1.19; uncorrected P=0.15). Of the 48 participants in the device group who died, 12 were wearing the device at the time of death. A total of 20 participants in the device group (1.3%) received an appropriate shock, and 9 (0.6%) received an inappropriate shock.Among patients with a recent myocardial infarction and an ejection fraction of 35% or less, the wearable cardioverter-defibrillator did not lead to a significantly lower rate of the primary outcome of arrhythmic death than control. (Funded by the National Institutes of Health and Zoll Medical; VEST ClinicalTrials.gov number, NCT01446965 .).

Cardiac devices are increasingly an element of treatment for the elderly, leading to more frequent transvenous lead removal (TLR) procedures in this population. Data on TLR in very elderly patients, especially nonagenarians, is scarce. We used Healthcare Cost and Utilization Project Nationwide Inpatient Sample to identify a total of 36,099 patients ≥70 years who underwent TLR from 2005 to 2012, with outcomes including in-hospital mortality and complications. The in-hospital mortality rate was significantly higher in nonagenarians without device infection (0.9% in age 70 to 79 vs 0.7% in age 80 to 89 vs 2.6% in age ≥90, p = 0.012), but overall complication rates were not different in age groups regardless of infection status and co-morbidity index (all p >0.05). Among patients with device infection, octogenarians, and nonagenarians were not associated with increased risk of in-hospital mortality relative to septuagenarians after controlling for all other confounders. However, in patients without device infection, logistic regression showed significantly higher mortality in patients age ≥90 years (odd ratio 4.22, 95% confidence interval 1.66 to 10.75, p = 0.003), but not in patients age 80 to 89 years (odd ratio 1.05, 95% confidence interval 0.48 to 2.30, p = 0.907), compared with patients age 70 to 79 years. In conclusion, in nonagenarians with infection, mortality is driven more by the patient's other conditions than by age. For patients without infection, however, nonagenarians experienced higher mortality than younger patients.

The relationship between sleep disruption, independent of obstructive sleep apnea (OSA), and atrial fibrillation (AF) is unknown.The purpose of this study was to determine whether poor sleep itself is a risk factor for AF.We first performed an analysis of participants in the Health eHeart Study and validated those findings in the longitudinal Cardiovascular Health Study, including a subset of patients undergoing polysomnography. To determine whether the observed relationships readily translated to medical practice, we examined 2005-2009 data from the California Healthcare Cost and Utilization Project.Among 4553 Health eHeart participants, the 526 with AF exhibited more frequent nighttime awakening (odd ratio [OR] 1.47; 95% confidence interval [CI] 1.14-1.89; P = .003). In 5703 Cardiovascular Health Study participants followed for a median 11.6 years, frequent nighttime awakening predicted a 33% greater risk of AF (hazard ratio [HR] 1.33; 95% CI 1.17-1.51; P.001). In patients with polysomnography (N = 1127), every standard deviation percentage decrease in rapid eye movement (REM) sleep was associated with a 18% higher risk of developing AF (HR 1.18; 95% CI 1.00-1.38; P = .047). Among 14,330,651 California residents followed for a median 3.9 years, an insomnia diagnosis predicted a 36% increased risk of new AF (HR 1.36; 95% CI 1.30-1.42; P.001).Sleep disruption consistently predicted AF before and after adjustment for OSA and other potential confounders across several different populations. Sleep quality itself may be important in the pathogenesis of AF, potentially representing a novel target for prevention.

OBJECTIVE Individuals with type 1 diabetes have experienced an increase in life expectancy, yet it is unknown what level of glycemic control is ideal for maintaining late-life brain health. We investigated the association of long-term glycemic control with dementia in older individuals with type 1 diabetes. RESEARCH DESIGN AND METHODS We followed 3,433 members of a health care system with type 1 diabetes, aged ≥50 years, from 1996 to 2015. Repeated measurements of hemoglobin A1c (HbA1c), dementia diagnoses, and comorbidities were ascertained from health records. Cox proportional hazards models were fit to evaluate the association of time-varying glycemic exposure with dementia, with adjustment for age, sex, race/ethnicity, baseline health conditions, and frequency of HbA1c measurement. RESULTS Over a mean follow-up of 6.3 years, 155 individuals (4.5%) were diagnosed with dementia. Patients with ≥50% of HbA1c measurements at 8–8.9% (64–74 mmol/mol) and ≥9% (≥75 mmol/mol) had 65% and 79% higher risk of dementia, respectively, compared with those with CONCLUSIONS Among older patients with type 1 diabetes, those with majority exposure to HbA1c 8–8.9% and ≥9% had increased dementia risk, while those with majority exposure to HbA1c 6–6.9% and 7–7.9% had reduced risk. Currently recommended glycemic targets for older patients with type 1 diabetes are consistent with healthy brain aging.

Background: Vest Prevention of Early Sudden Death Trial did not demonstrate a significant reduction in arrhythmic death with the wearable cardioverter‐defibrillator (WCD), but compliance with the device may have substantially affected the results. ThePletcher influence of WCD compliance on outcomes has not yet been fully evaluated. Methods: Using linear and pooled logistic models, we performed as‐treated analyses omitting person‐time in the hospital and adjusted for correlates of WCD compliance. To assess the impact of early stopping of WCD, we performed a per‐protocol Kaplan‐Meier analysis, censoring after the last day the WCD was worn. Interactions of potential effect modifiers with treatment assignment and WCD compliance on outcomes were investigated. Finally, we used linear models to identify predictors of WCD compliance. Results: A per‐protocol analysis demonstrated a significant reduction in total (P

Aims To evaluate the prevalence of electrocardiogram (ECG) abnormalities in marijuana users as an indirect measure of subclinical cardiovascular disease (CVD). Design Longitudinal and cross-sectional secondary data analysis from the CARDIA (Coronary Artery Risk Development in Young Adults) study. Setting Four communities in the United States. Participants A total of 2585 participants from the 5115 black and white men and women recruited at age 18-30 years in 1985 to 1986 in CARDIA. Measurements ECG abnormalities coded as minor and major abnormalities with the Minnesota code of electrocardiographic findings at year 20. Self-reported current (past 30 days) and computed cumulative life-time marijuana use (one 'marijuana-year' corresponds to 365 days of use) through assessments every 2-5 years. We fitted logistic regression models adjusting for sex, race, center, education, age, tobacco smoking, physical activity, alcohol use and body mass index. Findings Among the 2585 participants with an ECG at year 20, mean age was 46, 57% were women, 45% were black; 83% had past exposure to marijuana and 11% were using marijuana currently. One hundred and seventy-three participants (7%) had major abnormalities and 944 (37%) had minor abnormalities. Comparing current with never use in multivariable-adjusted models, the odds ratio (OR) for major ECG abnormalities was 0.60 [95% confidence interval (CI) = 0.32-1.15] and for minor ECG abnormalities 1.21 (95% CI = 0.87-1.68). Results did not change after stratifying by sex and race. Cumulative marijuana use was not associated with ECG abnormalities. Conclusion In a middle-aged US population, life-time cumulative and occasional current marijuana use were not associated with increases in electrocardiogram abnormalities. This adds to the growing body of evidence that occasional marijuana use and cardiovascular disease events and markers of subclinical atherosclerosis are not associated.

Low-density lipoprotein cholesterol (LDL-C) is a major risk factor for cardiovascular disease (CVD). Most observational studies on the association between LDL-C and CVD have focused on LDL-C level at a single time point (usually in middle or older age), and few studies have characterized long-term exposures to LDL-C and their role in CVD risk.To evaluate the associations of cumulative exposure to LDL-C, time-weighted average (TWA) LDL-C, and the LDL-C slope change during young adulthood and middle age with incident CVD later in life.This cohort study analyzed pooled data from 4 prospective cohort studies in the US (Atherosclerosis Risk in Communities Study, Coronary Artery Risk Development in Young Adults Study, Framingham Heart Study Offspring Cohort, and Multi-Ethnic Study of Atherosclerosis). Participants were included if they had 2 or more LDL-C measures that were at least 2 years apart between ages 18 and 60 years, with at least 1 of the LDL-C measures occurring during middle age at 40 to 60 years. Data from 1971 to 2017 were collected and analyzed from September 25, 2020, to January 10, 2021.Cumulative exposure to LDL-C, TWA LDL-C, and LDL-C slope from age 18 to 60 years.Incident coronary heart disease (CHD), ischemic stroke, and heart failure (HF).A total of 18 288 participants were included in this study. These participants had a mean (SD) age of 56.4 (3.7) years and consisted of 10 309 women (56.4%). During a median follow-up of 16 years, 1165 CHD, 599 ischemic stroke, and 1145 HF events occurred. In multivariable Cox proportional hazards regression models that adjusted for the most recent LDL-C level measured during middle age and for other CVD risk factors, the hazard ratios for CHD were as follows: 1.57 (95% CI, 1.10-2.23; P for trend = .01) for cumulative LDL-C level, 1.69 (95% CI, 1.23-2.31; P for trend.001) for TWA LDL-C level, and 0.88 (95% CI, 0.69-1.12; P for trend = .28) for LDL-C slope. No association was found between any of the LDL-C variables and ischemic stroke or HF.This cohort study showed that cumulative LDL-C and TWA LDL-C during young adulthood and middle age were associated with the risk of incident CHD, independent of midlife LDL-C level. These findings suggest that past levels of LDL-C may inform strategies for primary prevention of CHD and that maintaining optimal LDL-C levels at an earlier age may reduce the lifetime risk of developing atherosclerotic CVD.

Background & Aims In patients with chronic liver disease (CLD) with or without cirrhosis, existing studies on the outcomes with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection have limited generalizability. We used the National COVID Cohort Collaborative (N3C), a harmonized electronic health record dataset of 6.4 million, to describe SARS-CoV-2 outcomes in patients with CLD and cirrhosis. Methods We identified all patients with CLD with or without cirrhosis who had SARS-CoV-2 testing in the N3C Data Enclave as of July 1, 2021. We used survival analyses to associate SARS-CoV-2 infection, presence of cirrhosis, and clinical factors with the primary outcome of 30-day mortality. Results We isolated 220,727 patients with CLD and SARS-CoV-2 test status: 128,864 (58%) were noncirrhosis/negative, 29,446 (13%) were noncirrhosis/positive, 53,476 (24%) were cirrhosis/negative, and 8941 (4%) were cirrhosis/positive patients. Thirty-day all-cause mortality rates were 3.9% in cirrhosis/negative and 8.9% in cirrhosis/positive patients. Compared to cirrhosis/negative patients, cirrhosis/positive patients had 2.38 times adjusted hazard of death at 30 days. Compared to noncirrhosis/positive patients, cirrhosis/positive patients had 3.31 times adjusted hazard of death at 30 days. In stratified analyses among patients with cirrhosis with increased age, obesity, and comorbid conditions (ie, diabetes, heart failure, and pulmonary disease), SARS-CoV-2 infection was associated with increased adjusted hazard of death. Conclusions In this study of approximately 221,000 nationally representative, diverse, and sex-balanced patients with CLD; we found SARS-CoV-2 infection in patients with cirrhosis was associated with 2.38 times mortality hazard, and the presence of cirrhosis among patients with CLD infected with SARS-CoV-2 was associated with 3.31 times mortality hazard. These results provide an additional impetus for increasing vaccination uptake and further research regarding immune responses to vaccines in patients with severe liver disease.

Background: Statins are effective in the primary prevention of atherosclerotic cardiovascular disease. The 2013 American College of Cardiology/American Heart Association (ACC/AHA) guideline expands recommended statin use, but its cost-effectiveness has not been compared with other guidelines. Methods: We used the Cardiovascular Disease Policy Model to estimate the cost-effectiveness of the ACC/AHA guideline relative to current use, Adult Treatment Panel III guidelines, and universal statin use in all men 45 to 74 years of age and women 55 to 74 years of age over a 10-year horizon from 2016 to 2025. Sensitivity analyses varied costs, risks, and benefits. Main outcomes were incremental cost-effectiveness ratios and numbers needed to treat for 10 years per quality-adjusted life-year gained. Results: Each approach produces substantial benefits and net cost savings relative to the status quo. Full adherence to the Adult Treatment Panel III guideline would result in 8.8 million more statin users than the status quo, at a number needed to treat for 10 years per quality-adjusted life-year gained of 35. The ACC/AHA guideline would potentially result in up to 12.3 million more statin users than the Adult Treatment Panel III guideline, with a marginal number needed to treat for 10 years per quality-adjusted life-year gained of 68. Moderate-intensity statin use in all men 45 to 74 years of age and women 55 to 74 years of age would result in 28.9 million more statin users than the ACC/AHA guideline, with a marginal number needed to treat for 10 years per quality-adjusted life-year gained of 108. In all cases, benefits would be greater in men than women. Results vary moderately with different risk thresholds for instituting statins and statin toxicity estimates but depend greatly on the disutility caused by daily medication use (pill burden). Conclusions: At a population level, the ACC/AHA guideline for expanded statin use for primary prevention is projected to treat more people, to save more lives, and to cost less compared with Adult Treatment Panel III in both men and women. Whether individuals benefit from long-term statin use for primary prevention depends more on the disutility associated with pill burden than their degree of cardiovascular risk.

Background and objectives Marijuana use has become more widely accepted in the United States and has been legalized in many areas. Although it is biologically plausible that marijuana could affect kidney function, epidemiologic data are lacking. Design, setting, participants, & measurements We conducted a cohort study among young adults with preserved eGFR (i.e., eGFR≥60 ml/min per 1.73 m2) using data from the Coronary Artery Risk Development in Young Adults (CARDIA) study. At scheduled examinations occurring every 5 years and starting at study year 10 (calendar years, 1995–1996), cystatin C was collected over a 10-year period, and urine albumin-to-creatinine ratio was collected over a 15-year period. We investigated the cross-sectional association between current and cumulative marijuana use (in marijuana-years; one marijuana-year equals 365 days of marijuana use) and eGFR by cystatin C (eGFRcys) at year 10. In longitudinal analyses, we investigated the association between cumulative marijuana use and eGFRcys change and rapid (≥3%/year) eGFRcys decline over two 5-year intervals and prevalent albuminuria (urine albumin-to-creatinine ratio ≥30 mg/g) over a 15-year period. Results Past or current marijuana use was reported by 83% (3131 of 3765) of the cohort, and the mean eGFRcys was 111 ml/min per 1.73 m2 at year 10. Over the following 10 years, 504 had rapid eGFRcys decline, and over the following 15 years, 426 had prevalent albuminuria. Compared with no use, daily current use and ≥5 marijuana-years of cumulative use were associated with lower eGFRcys at year 10: −4.5% (95% confidence interval, −8.1 to −0.7%; P=0.02) and −3.0% (95% confidence interval, −5.6 to −0.4%; P=0.03), respectively. Marijuana use was not significantly associated with eGFRcys change, rapid eGFRcys decline, or prevalent albuminuria. Conclusions Although we identified a modest cross-sectional association between higher marijuana exposure and lower eGFRcys among young adults with preserved eGFR, our findings were largely null and did not demonstrate a longitudinal association between marijuana use and eGFRcys change, rapid eGFRcys decline, or prevalent albuminuria. Podcast This article contains a podcast at https://www.asn-online.org/media/podcast/CJASN/2017_08_24_CJASNPodcast_17_10.mp3

Disability measures in multiple sclerosis (MS) rely heavily on ambulatory function, and current metrics fail to capture potentially important variability in walking behavior. We sought to determine whether remote step count monitoring using a consumer-friendly accelerometer (Fitbit Flex) can enhance MS disability assessment. 99 adults with relapsing or progressive MS able to walk ≥2-min were prospectively recruited. At 4weeks, study retention was 97% and median Fitbit use was 97% of days. Substudy validation resulted in high interclass correlations between Fitbit, ActiGraph and manual step count tally during a 2-minute walk test, and between Fitbit and ActiGraph (ICC=0.76) during 7-day home monitoring. Over 4 weeks of continuous monitoring, daily steps were lower in progressive versus relapsing MS (mean difference 2546 steps, p&nbsp

IMPORTANCE: American College of Cardiology/American Heart Association cholesterol guidelines prioritize primary prevention statin therapy based on 10-year absolute risk (AR(10)) of atherosclerotic cardiovascular disease (ASCVD). However, given the same AR(10), patients with higher levels of low-density lipoprotein cholesterol (LDL-C) experience greater absolute risk reduction from statin therapy. OBJECTIVES: To estimate the cost-effectiveness of expanding preventive statin treatment eligibility from standard care to patients at borderline risk (AR(10), 5.0%-7.4%) for ASCVD and with high levels of LDL-C and to estimate cost-effectiveness of statin treatment across ranges of age, sex, AR(10), and LDL-C levels. DESIGN, SETTING, AND PARTICIPANTS: This study evaluated 100 simulated cohorts, each including 1 million ASCVD-free survey respondents (50% men and 50% women) aged 40 years at baseline. Cohorts were created by probabilistic sampling of the 1999-2014 US National Health and Nutrition Examination Surveys from the perspective of the US health care sector. The CVD Policy Model microsimulation version projected lifetime health and cost outcomes. Probability of first-ever coronary heart disease or stroke event was estimated by analysis of 6 pooled US cohort studies and recalibrated to match contemporary event rates. Other model variables were derived from national surveys, meta-analyses, and published literature. Data were analyzed from May 15, 2018, through June 10, 2019. EXPOSURES: Four statin treatment strategies were compared: (1) treat all patients with AR(10) of at least 7.5%, diabetes, or LDL-C of at least 190 mg/dL (standard care); (2) add treatment for borderline risk and LDL-C levels of 160 to 189 mg/dL; (3) add treatment for borderline risk and LDL-C levels of 130 to 159 mg/dL; and (4) add treatment for remainder of patients with AR(10) of at least 5.0%. Statin treatment was also compared with no statin treatment in age, sex, AR(10), and LDL-C strata. MAIN OUTCOMES AND MEASURES: Lifetime quality-adjusted life-years (QALYs) and costs (2019 US dollars) were projected and discounted 3.0% annually. The primary outcome was the incremental cost-effectiveness ratio. RESULTS: In these 100 simulated cohorts, each with 1 million patients aged 40 years at baseline (50% women and 50% men), adding preventive statins to individuals with borderline AR(10) and LDL-C levels of 160 to 189 mg/dL would be cost-saving; further treating borderline AR(10) and LDL-C levels of 130 to 159 mg/dL would also be cost-saving; and treating all individuals with AR(10) of at least 5.0% would be highly cost-effective ($33 558/QALY) and would prevent the most ASCVD events. Within age, AR(10), and sex categories, individuals with higher baseline LDL-C levels gained more QALYs from statin therapy. Cost-effectiveness increased with LDL-C level and AR(10). CONCLUSIONS AND RELEVANCE: In this study, lifetime statin treatment of patients in a hypothetical cohort with borderline ASCVD risk and LDL-C levels of 160 to 189 mg/dL was found to be cost-saving. Results suggest that treating all patients at borderline risk regardless of LDL-C level would likely be highly cost-effective.

The global burden of diabetes is rapidly increasing, from 451 million people in 2019 to 693 million by 2045

ObjectiveTo assess the effect of cannabis legalisation on health effects and healthcare utilisation in Colorado (CO), the first state to legalise recreational cannabis, when compared with two control states, New York (NY) and Oklahoma (OK).DesignWe used the 2010 to 2014 Healthcare Cost and Utilisation Project (HCUP) inpatient databases to compare changes in rates of healthcare utilisation and diagnoses in CO versus NY and OK.SettingPopulation-based, inpatient.ParticipantsHCUP state-wide data comprising over 28 million individuals and over 16 million hospitalisations across three states.Main outcome measuresWe used International Classification of Diseases-Ninth Edition codes to assess changes in healthcare utilisation specific to various medical diagnoses potentially treated by or exacerbated by cannabis. Diagnoses were classified based on weight of evidence from the National Academy of Science (NAS). Negative binomial models were used to compare rates of admissions between states.ResultsIn CO compared with NY and OK, respectively, cannabis abuse hospitalisations increased (risk ratio (RR) 1.27, 95% CI 1.26 to 1.28 and RR 1.16, 95% CI 1.15 to 1.17; both pConclusionsRecreational cannabis legalisation is associated with neutral effects on healthcare utilisation. In line with previous evidence, cannabis liberalisation is linked to an increase in motor vehicle accidents, alcohol abuse, overdose injuries and a decrease in chronic pain admissions. Such population-level effects may help guide future decisions regarding cannabis use, prescription and policy.

Blood pressure (BP) and cholesterol are major modifiable risk factors for cardiovascular disease (CVD), but effects of exposures during young adulthood on later life CVD risk have not been well quantified.The authors sought to evaluate the independent associations between young adult exposures to risk factors and later life CVD risk, accounting for later life exposures.The authors pooled data from 6 U.S. cohorts with observations spanning the life course from young adulthood to later life, and imputed risk factor trajectories for low-density lipoprotein (LDL) and high-density lipoprotein cholesterols, systolic and diastolic BP starting from age 18 years for every participant. Time-weighted average exposures to each risk factor during young (age 18 to 39 years) and later adulthood (age ≥40 years) were calculated and linked to subsequent risks of coronary heart disease (CHD), heart failure (HF), or stroke.A total of 36,030 participants were included. During a median follow-up of 17 years, there were 4,570 CHD, 5,119 HF, and 2,862 stroke events. When young and later adult risk factors were considered jointly in the model, young adult LDL ≥100 mg/dl (compared with 100 mg/dl) was associated with a 64% increased risk for CHD, independent of later adult exposures. Similarly, young adult SBP ≥130 mm Hg (compared with 120 mm Hg) was associated with a 37% increased risk for HF, and young adult DBP ≥80 mm Hg (compared with 80 mm Hg) was associated with a 21% increased risk.Cumulative young adult exposures to elevated systolic BP, diastolic BP and LDL were associated with increased CVD risks in later life, independent of later adult exposures.

IntroductionHistorical and current stigmatizing and discriminatory experiences drive sexual and gender minority (SGM) people away from health care and clinical research. Being medically underserved, they face numerous disparities that make them vulnerable to poor health outcomes. Effective methods to engage and recruit SGM people into clinical research studies are needed.ObjectivesTo promote health equity and understand SGM health needs, we sought to design an online, national, longitudinal cohort study entitled The PRIDE (Population Research in Identity and Disparities for Equality) Study that enabled SGM people to safely participate, provide demographic and health data, and generate SGM health-related research ideas.MethodsWe developed an iPhone mobile application ("app") to engage and recruit SGM people to The PRIDE Study-Phase 1. Participants completed demographic and health surveys and joined in asynchronous discussions about SGM health-related topics important to them for future study.ResultsThe PRIDE Study-Phase 1 consented 18,099 participants. Of them, 16,394 provided data. More than 98% identified as a sexual minority, and more than 15% identified as a gender minority. The sample was diverse in terms of sexual orientation, gender identity, age, race, ethnicity, geographic location, education, and individual income. Participants completed 24,022 surveys, provided 3,544 health topics important to them, and cast 60,522 votes indicating their opinion of a particular health topic.ConclusionsWe developed an iPhone app that recruited SGM adults and collected demographic and health data for a new national online cohort study. Digital engagement features empowered participants to become committed stakeholders in the research development process. We believe this is the first time that a mobile app has been used to specifically engage and recruit large numbers of an underrepresented population for clinical research. Similar approaches may be successful, convenient, and cost-effective at engaging and recruiting other vulnerable populations into clinical research studies.

Background In designing prevention strategies, it may be useful to understand how early and midlife cardiovascular disease risk factor (CVDRF) exposures affect outcomes that primarily occur in mid to late life. Few single US cohorts have followed participants from early adulthood to late life. Methods We pooled four prospective cohorts that represent segments of the adult life course, and studied 15 001 White and Black adults aged 18 to 95 years at enrollment. We imputed early and midlife exposure to body mass index (BMI), glucose, lipids and blood pressure (BP). CVDRF trajectories were estimated using linear mixed models. Using the best linear unbiased predictions, we obtained person-specific estimates of CVDRF trajectories beginning at age 20 until each participant’s end of follow-up. We then calculated for each CVDRF, summary measures of early and midlife exposure as time-weighted averages (TWAs). Results In the pooled cohort, 33.7% were Black and 54.8% were female. CVDRF summary measures worsened in midlife compared with early life and varied by sex and race. In particular, systolic and diastolic BP were consistently higher over the adult life course among men, and BMI was higher among Blacks, particularly Black women. Simulation studies suggested acceptable imputation accuracy, especially for the younger cohorts. Correlations of true and imputed CVDRF summary measures ranged from 0.53 to 0.99, and agreement ranged from 67% to 99%. Conclusions These results suggest that imputed CVDRFs may be accurate enough to be useful in assessing the effects of early and midlife exposures on later life outcomes.

As of January 22, 2021, there were more than 98 million confirmed cases of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), more than 24 million of which are attributed to the US alone.1 Recent surges in SARS-CoV-2 and the threat of a second wave have prompted many states to reconsider reopening timelines. During the initial US surge, 45 out of 50 state governments issued shelter-in-place (SIP) orders from March 19, 2020, to April 6, 2020, to slow disease transmission.2 The initial SIP coincided with an observed decrease in daily step counts,3 likely reflective of changes in physical activity and patterns of daily living, as well as concurrent self-reported increases in snacking and overeating.4 We therefore sought to investigate ambulatory weight changes of a longitudinal cohort during initial SIP orders to better understand the possible downstream health implications of prolonged SIP.

Background Commercially acquired wearable activity trackers such as the Fitbit provide objective, accurate measurements of physically active time and step counts, but it is unclear whether these measurements are more clinically meaningful than self-reported physical activity. Objective The aim of this study was to compare self-reported physical activity to Fitbit-measured step counts and then determine which is a stronger predictor of BMI by using data collected over the same period reflecting comparable physical activities. Methods We performed a cross-sectional analysis of data collected by the Health eHeart Study, a large mobile health study of cardiovascular health and disease. Adults who linked commercially acquired Fitbits used in free-living conditions with the Health eHeart Study and completed an International Physical Activity Questionnaire (IPAQ) between 2013 and 2019 were enrolled (N=1498). Fitbit step counts were used to quantify time by activity intensity in a manner comparable to the IPAQ classifications of total active time and time spent being sedentary, walking, or doing moderate activities or vigorous activities. Fitbit steps per day were computed as a measure of the overall activity for exploratory comparisons with IPAQ-measured overall activity (metabolic equivalent of task [MET]-h/wk). Measurements of physical activity were directly compared by Spearman rank correlation. Strengths of associations with BMI for Fitbit versus IPAQ measurements were compared using multivariable robust regression in the subset of participants with BMI and covariates measured. Results Correlations between synchronous paired measurements from Fitbits and the IPAQ ranged in strength from weak to moderate (0.09-0.48). In the subset with BMI and covariates measured (n=586), Fitbit-derived predictors were generally stronger predictors of BMI than self-reported predictors. For example, an additional hour of Fitbit-measured vigorous activity per week was associated with nearly a full point reduction in BMI (–0.84 kg/m2, 95% CI –1.35 to –0.32) in adjusted analyses, whereas the association between self-reported vigorous activity measured by IPAQ and BMI was substantially smaller in magnitude (–0.17 kg/m2, 95% CI –0.34 to –0.00; P Conclusions Fitbit-measured physical activity was more strongly associated with BMI than self-reported physical activity, particularly for moderate activity, vigorous activity, and summary measures of total activity. Consumer-marketed wearable activity trackers such as the Fitbit may be useful for measuring health-relevant physical activity in clinical practice and research.

Background Heart failure (HF) is a major clinical and public health problem, the management of which will benefit from large-scale pragmatic research that leverages electronic medical records (EMR). Requisite to using EMRs for HF research is the development of reliable algorithms to identify HF patients. We aimed to develop and validate computable phenotype algorithms to identify patients with HF using standardized data elements defined by the Patient Centered Outcomes Research Network (PCORnet) Common Data Model (CDM). Methods We built HF computable phenotypes utilizing the data domains of HF diagnosis codes, prescribed HF-related medications and N-terminal B-type natriuretic peptide (NT-proBNP). Algorithms were validated in a cohort (n = 76,254) drawn from Olmsted County, MN between 2010–2012 a sample of whose records were manually reviewed to confirm HF according to Framingham criteria. Results The different algorithms we tested provided different tradeoffs between sensitivity and positive predictive value (PPV). The highest sensitivity (78.7%) algorithm utilized one HF diagnosis code and had the lowest PPV (68.5%). The addition of more algorithm components, such as additional HF diagnosis codes, HF medications or elevated NT-proBNP, improved the PPV while reducing sensitivity. When added to a diagnostic code, the addition of NT-proBNP (>450 pg/mL) had a similar impact compared to additional HF medication criteria, increasing PPV by ∼3–4% and decreasing sensitivity by ∼7–10%. Conclusions Algorithms derived from PCORnet CDM elements can be used to identify patients with HF without manual adjudication with reasonable sensitivity and PPV. Algorithm choice should be driven by the goal of the research.

Self-weighing may promote attainment and maintenance of healthy weight; however, the natural temporal patterns and factors associated with self-weighing behavior are unclear. The aims of this secondary analysis were to (1) identify distinct temporal patterns of self-weighing behaviors; (2) explore factors associated with temporal self-weighing patterns; and (3) examine differences in percent weight changes by patterns of self-weighing over time. We analyzed electronically collected self-weighing data from the Health eHeart Study, an ongoing longitudinal research study coordinated by the University of California, San Francisco. We selected participants with at least 12 months of data since the day of first use of a WiFi- or Bluetooth-enabled digital scale. The sample (N = 1041) was predominantly male (77.5%) and White (89.9%), with a mean age of 46.5 ± 12.3 years and a mean BMI of 28.3 ± 5.9 kg/m(2) at entry. Using group-based trajectory modeling, six distinct temporal patterns of self-weighing were identified: non-users (n = 120, 11.5%), weekly users (n = 189, 18.2%), rapid decliners (n = 109, 10.5%), increasing users (n = 160, 15.4%), slow decliners (n = 182, 17.5%), and persistent daily users (n = 281, 27.0%). Individuals who were older, female, or self-weighed 6–7 days/week at week 1 were more likely to follow the self-weighing pattern of persistent daily users. Predicted self-weighing trajectory group membership was significantly associated with weight change over time (p < .001). In conclusion, we identified six distinct patterns of self-weighing behavior over the 12-month period. Persistent daily users lost more weight compared with groups with less frequent patterns of scale use.

E-cigarettes are promoted as healthier alternatives to conventional cigarettes. Many cigarette smokers use both products. It is unknown whether the additional use of e-cigarettes among cigarette smokers (dual users) is associated with reduced exposure to tobacco-related health risks. Cross-sectional analysis was performed using baseline data from the Health eHeart Study, among English-speaking adults, mostly from the United States. Cigarette use (# cigarettes/day) and/or e-cigarette use (# days, # cartridges, and # puffs) were compared between cigarette only users vs. dual users. Additionally, we examined cardiopulmonary symptoms/ conditions across product use: no product (neither), e-cigarettes only, cigarettes only, and dual use. Among 39,747 participants, 573 (1.4%) reported e-cigarette only use, 1,693 (4.3%) reported cigarette only use, and 514 (1.3%) dual use. Dual users, compared to cigarette only users, reported a greater median (IQR) number of cigarettes per day, 10.0 (4.0-20.0) vs. 9.0 (3.0-15.0) (p < .0001), a lower (worse) median (IQR) SF-12 general health score, 3.3 (2.8-3.8) vs. 3.5 (2.8-3.9) (p = .0014), and a higher (worse) median (IQR) breathing difficulty score in the past month, 2.0 (1.0-2.0) vs. 1.0 (1.0-2.0) (p = .001). Of the 19 cardiopulmonary symptoms/ conditions, having a history of arrhythmia was significantly different between cigarette only users (14.2%) and dual users (17.8%) (p = .02). In this sample, dual use was not associated with reduced exposure to either (i) cigarettes, compared to cigarette only users or (ii) e-cigarettes, compared to e-cigarette only users. E-cigarette only use, compared to no product use, was associated with lower general health scores, higher breathing difficulty scores (typically and past month), and greater proportions of those who responded 'yes' to having chest pain, palpitations, coronary heart disease, arrhythmia, COPD, and asthma. These data suggest the added use of e-cigarettes alone may have contributed to cardiopulmonary health risks particularly respiratory health risks.

Aims/hypothesisThe impact of marijuana use on metabolic health is largely unknown. This study sought to clarify the cross-sectional and longitudinal associations between self-reported marijuana use, and prediabetes (defined as fasting glucose 5.6-6.9 mmol/l, 2 h glucose post OGTT 7.8-11.0 mmol/l or HbA1c 5.7-6.4% [39-47 mmol/mol]) and diabetes.MethodsData from the community-based Coronary Artery Risk Development in Young Adults (CARDIA) study were used to determine marijuana use and the presence of prediabetes and diabetes among participants. The association between marijuana use and the prevalence of prediabetes and diabetes was examined in 3,034 participants at CARDIA examination year 25 (2010-2011), while the incidence of prediabetes and diabetes according to previous marijuana use was assessed in 3,151 individuals who were free from prediabetes/diabetes at year 7 (1992-1993) and who returned for at least one of the four subsequent follow-up examinations over 18 years.ResultsThe percentage of individuals who self-reported current use of marijuana declined over the course of the study's follow-up. After multivariable adjustment, higher odds of prediabetes were found for individuals who reported current use of marijuana (OR 1.65 [95% CI 1.15, 2.38]) and a lifetime use of 100 times or more (OR 1.49 [95% CI 1.06, 2.11]), compared with individuals who reported never using marijuana. There was no association between marijuana use and diabetes at CARDIA examination year 25. Over 18 years of follow-up, a greater risk of prediabetes (but not diabetes) was found for individuals who reported a lifetime use of marijuana of 100 times or more (HR 1.39 [95% CI 1.13, 1.71]), compared with individuals who had never used marijuana.Conclusions/interpretationMarijuana use in young adulthood is associated with an increased risk of prediabetes by middle adulthood, but not with the development of diabetes by this age.

Despite the equipoise regarding alcohol’s cardiovascular effects and absence of relevant rigorous controlled trials, the lay press frequently portrays alcohol as “heart healthy.” The public perception of alcohol’s heart effects, the sources of those perceptions, and how they may affect behavior are unknown. We performed a cross-sectional analysis of data obtained between March, 2013 and September, 2014 from consecutive participants enrolled in the Health eHeart Study. Of 5,582 participants, 1,707 (30%) viewed alcohol as heart healthy, 2,157 (39%) viewed it as unhealthy, and 1,718 (31%) were unsure. Of those reporting alcohol as heart healthy, 80% cited lay press as a source of their knowledge. After adjustment, older age (odds ratio 1.11), higher education (odds ratio, 1.37), higher income (odds ratio 1.07), US residence (odds ratio 1.63) and coronary artery disease (CAD) (odds ratio 1.51) were associated with perception of alcohol as heart healthy (all p < 0.003). Ever smokers (odds ratio 0.76, p = 0.004) and those with heart failure (HF) (odds ratio 0.5, p = 0.01) were less likely to cite alcohol as heart healthy. Those perceiving alcohol as heart healthy consumed on average 47% more alcohol on a regular basis (95% confidence interval 27–66%, p < 0.001). In conclusion, among more than 5,000 consecutive Health eHeart participants, approximately one third believed alcohol to be heart healthy, and the majority cited the lay press as the origin of that perception. Those with a perception of alcohol as heart healthy drink substantially more alcohol.

Background Cardiac sarcoidosis (CS) is a life-threatening disease that is frequently under-diagnosed.Methods and Results:We used a nationwide inpatient sample to identify CS patients from 2005 to 2011 in the USA. The annual admissions of CS increased from 1,108 in 2005 to 2,182 in 2011, representing a 2-fold rise over a short time. The proportions of CS patients with severe comorbidities, ventricular tachycardia, ventricular fibrillation and heart failure all increased from 2005 to 2011. However, the in-hospital mortality rate declined. Conclusions An increasing trend of CS was observed. Cardiologists should notice that CS is not as rare as thought.

Background: It is unclear whether testing for novel risk factors, such as a cardiovascular genetic risk score (cGRS), improves clinical decision making or health outcomes when used for targeting statin initiation in the primary prevention of atherosclerotic cardiovascular disease (ASCVD). Our objective was to estimate the cost-effectiveness of cGRS testing to inform clinical decision making about statin initiation in individuals with low-to-intermediate (2.5%–7.5%) 10-year predicted risk of ASCVD. Methods and Results: We evaluated the cost-effectiveness of testing for a 27-single-nucleotide polymorphism cGRS comparing 4 test/treat strategies: treat all, treat none, test/treat if cGRS is high, and test/treat if cGRS is intermediate or high. We tested a set of clinical scenarios of men and women, aged 45 to 65 years, with 10-year ASCVD risks between 2.5% and 7.5%. Our primary outcome measure was cost per quality-adjusted life-year gained. Under base case assumptions for statin disutility and cost, the preferred strategy is to treat all patients with ASCVD risk >2.5% without cGRS testing. For certain clinical scenarios, such as a 57-year-old man with a 10-year ASCVD risk of 7.5%, cGRS testing can be cost-effective under a limited set of assumptions; for example, when statins cost $15 per month and statin disutility is 0.013 (ie, willing to trade 3 months of life in perfect health to avoid 20 years of statin therapy), the preferred strategy (using a willingness-to-pay threshold of $50 000 per quality-adjusted life-year gained) is to test and treat if cGRS is intermediate or high. Overall, the results were not sensitive to assumptions about statin efficacy and harms. Conclusions: Testing for a 27-single-nucleotide polymorphism cGRS is generally not a cost-effective approach for targeting statin therapy in the primary prevention of ASCVD for low- to intermediate-risk patients.

Unlike tobacco, the effect of marijuana smoke on subclinical atherosclerosis, a surrogate measure for cardiovascular disease, is not known. This study aimed to determine the association between lifetime exposure to marijuana and measures of subclinical atherosclerosis in mid-life.We used data from the US-based Coronary Artery Risk Development in Young Adults (CARDIA) study, a cohort of black and white men and women aged 18-30 years at baseline in 1985-86, with up to seven follow-up examinations over 25 years. A total of 3498 participants in the CARDIA study were included in this study.Cumulative years of exposure to marijuana (expressed in 'marijuana-years', with 1 marijuana-year equivalent to 365 days of use) using repeated assessments every 2-5 years for 25 years. Abdominal artery calcium (AAC) and coronary artery calcium (CAC) scores were measured by computed tomography at year 25 examination.Among 3117 participants with AAC and CAC measurements, 2627 (84%) reported past marijuana use and 1536 (49%) past daily tobacco smoking. Compared with tobacco smokers, 46% of whom reported 10 or more pack-years of use, only 12% of marijuana users reported 5 or more marijuana-years of use and only 6% reported having used marijuana daily. We found a significant interaction between never and ever tobacco users on the association between cumulative marijuana use and AAC (P = 0.05). Among those who never smoked tobacco, cumulative marijuana-years were not associated with AAC or CAC in models adjusted for demographics, cardiovascular risk factors, licit and illicit drug exposure and depression symptoms. However, among ever tobacco smokers, marijuana exposure was associated with AAC and CAC. At 5 marijuana-years of exposure, using AAC = 0 and CAC = 0 as a reference group, the odds ratio (OR) was 1.97 [95% confidence interval (CI) = 1.21-3.21, P = 0.007] for AAC 0/CAC = 0 and 1.83 (95% CI = 1.02-3.31, P = 0.04) for CAC 0), regardless of AAC. Tobacco smoking was associated strongly with both AAC and CAC.Marijuana use appears to be associated with subclinical atherosclerosis, but only among ever tobacco users.

Direct volunteer “eCohort” recruitment can be an efficient way of recruiting large numbers of participants, but there is potential for volunteer bias. We compared self-selected participants in the Health eHeart Study to participants in the National Health And Nutrition Examination Survey (NHANES) 2013–14, a cross-sectional survey of the US population. Compared with the US population (represented by 5,769 NHANES participants), the 12,280 Health eHeart participants with complete survey data were more likely to be female (adjusted odds ratio (ORadj) = 3.1; 95% confidence interval (CI) 2.9–3.5); less likely to be Black, Hispanic, or Asian versus White/non-Hispanic (ORadj’s = 0.4–0.6, p

Background— Ascertainment of hospitalizations is critical to assess quality of care and the effectiveness and adverse effects of various therapies. Smartphones, mobile geolocators that are ubiquitous, have not been leveraged to ascertain hospitalizations. Therefore, we evaluated the use of smartphone-based geofencing to track hospitalizations. Methods and Results— Participants aged ≥18 years installed a mobile application programmed to geofence all hospitals using global positioning systems and cell phone tower triangulation and to trigger a smartphone-based questionnaire when located in a hospital for ≥4 hours. An in-person study included consecutive consenting patients scheduled for electrophysiology and cardiac catheterization procedures. A remote arm invited Health eHeart Study participants who consented and engaged with the study via the internet only. The accuracy of application-detected hospitalizations was confirmed by medical record review as the reference standard. Of 22 eligible in-person patients, 17 hospitalizations were detected (sensitivity 77%; 95% confidence interval, 55%–92%). The length of stay according to the application was positively correlated with the length of stay ascertained via the electronic medical record ( r =0.53; P =0.03). In the remote arm, the application was downloaded by 3443 participants residing in all 50 US states; 243 hospital visits at 119 different hospitals were detected through the application. The positive predictive value for an application-reported hospitalization was 65% (95% confidence interval, 57%–72%). Conclusions— Mobile application–based ascertainment of hospitalizations can be achieved with modest accuracy. This first proof of concept may ultimately be applicable to geofencing other types of prespecified locations to facilitate healthcare research and patient care.