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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

ObjectiveTo explore trends in blood pressure (BP) control before and during the COVID-19 pandemic.Patients and methodsHealth systems participating in the National Patient-Centered Clinical Research Network (PCORnet) Blood Pressure Control Laboratory Surveillance System responded to data queries, producing 9 BP control metrics. Averages of the BP control metrics (weighted by numbers of observations in each health system) were calculated and compared between two 1-year measurement periods (January 1, 2019, through December 31, 2019, and January 1, 2020, through December 31, 2020).ResultsAmong 1,770,547 hypertensive persons in 2019, BP control to

Social determinants of health and sociodemographic differences place some individuals at higher risk for hypertension leading to persisting disparities. While mobile health (mHealth) offers a promising approach to facilitate blood pressure (BP) management, it remains unclear which interventions are most effective for addressing disparities in hypertension control. We reviewed the current literature to examine whether mHealth interventions for BP control are effective in improving BP control in populations vulnerable to disparities in hypertension. We conducted a systematic review using multiple databases from January 1, 2009 through December 31, 2020. For inclusion, participants must have elevated blood pressure and belong to a sociodemographic group with known disparities in hypertension. We also tracked specific characteristics of each intervention. Out of the eight articles that met our eligibility criteria for inclusion, five were published in 2018 to 2020. Only four demonstrated a significant reduction in BP and all those interventions incorporated care teams. Despite some evidence of the effectiveness of mHealth interventions for improving BP control among vulnerable groups, more effective interventions are needed, and the quality of studies is overall low. Further research is needed to find the most effective ways to engage diverse communities with mHealth solutions to improve BP control.

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.

BackgroundLiver transplantation (LT) is a treatment for acute-on-chronic liver failure (ACLF) but up to 40% mortality post-LT has been reported. Existing post-LT models in ACLF have been limited by small samples. In this study, we developed a novel Expert-Augmented Machine Learning (EAML) model to predict post-LT outcomes.MethodsWe identified ACLF patients in the University of California Health Data Warehouse (UCHDW). We used EAML, which uses the RuleFit machine learning (ML) algorithm to extract rules from decision-trees that are then evaluated by human experts, to predict post-LT outcomes. We compared EAML/RuleFit’s performances versus other popular models.ResultsWe identified 1,384 ACLF patients. For death at one-year: areas-under-the-receiver-operating characteristic curve (AUROCs) were 0.707 (Confidence Interval [CI] 0.625-0.793) for EAML and 0.719 (CI 0.640-0.800) for RuleFit. For death at 90-days: AUROCs were 0.678 (CI 0.581-0.776) for EAML and 0.707 (CI 0.615-0.800) for RuleFit. In pairwise comparisons, EAML/RuleFit models outperformed cross-sectional models. Divergences between experts and ML in rankings revealed biases and artifacts in the underlying data.ConclusionsEAML/RuleFit outperformed cross-sectional models. Significant discrepancies between experts and ML occurred in rankings of biomarkers used in clinical practice. EAML may serve as a method for ML-guided hypothesis generation in further ACLF research.

BackgroundOral nirmatrelvir/ritonavir is a treatment for COVID-19, but whether treatment during the acute phase reduces the risk of developing Long COVID is unknown.MethodsUsing the Covid Citizen Science (CCS) online cohort, we surveyed individuals who reported their first SARS-CoV-2 positive test between March and August 2022 regarding Long COVID symptoms. We excluded those who were pregnant, unvaccinated, hospitalized for COVID-19, or received other antiviral therapy. The primary exposure was oral nirmatrelvir/ritonavir. The primary outcome was the presence of any Long COVID symptoms reported on cross-sectional surveys in November and December 2022. We used propensity-score models and inverse probability of treatment weighting to adjust for differences in treatment propensity. Our secondary question was whether symptom or test positivity rebound were associated with Long COVID.Results4684 individuals met the eligibility criteria, of whom 988 (21.1%) were treated and 3696 (78.9%) were untreated; 353/988 (35.7%) treated and 1258/3696 (34.0%) untreated responded to the survey. Median age was 55 years and 66% were female. We did not identify an association between nirmatrelvir/ritonavir treatment and Long COVID symptoms (OR 1.15; 95%CI 0.80-1.64). Among n=666 treated with nirmatrelvir/ritonavir who responded who responded to questions about rebound, rebound symptoms or test positivity were not associated with Long COVID symptoms (OR 1.34; 95%CI 0.74-2.41; p=0.33).ConclusionsWithin this cohort, treatment with nirmatrelvir/ritonavir among vaccinated, non-hospitalized individuals was not associated with lower prevalence of Long COVID symptoms or severity of Long COVID. Experiencing rebound symptoms or test positivity is not strongly associated with developing Long COVID.

Background Uncontrolled blood pressure (BP) remains a leading cause of death in the United States. The American Medical Association developed a quality improvement program to improve BP control, but it is unclear how to efficiently implement this program at scale across multiple health systems. Methods and Results We conducted BP MAP (Blood Pressure Measure Accurately, Act Rapidly, and Partner With Patients), a comparative effectiveness trial with clinic‐level randomization to compare 2 scalable versions of the quality improvement program: Full Support (with support from quality improvement expert) and Self‐Guided (using only online materials). Outcomes were clinic‐level BP control (P =0.59; Full Support versus Usual Care=+3.2% [−0.5% to 6.9%], P =0.09; Self‐Guided versus Usual Care=+2.0% [−0.4% to 4.5%], P =0.10). Conclusions In this randomized trial, 2 methods of implementing a quality improvement intervention in 24 safety net clinics led to modest improvements in BP control that were not statistically significant. Registration URL: https://www.clinicaltrials.gov ; Unique identifier: NCT03818659.

INTRODUCTION AND OBJECTIVES Data are scarce on outcomes of transvenous lead removal (TLR) in adult congenital heart disease (CHD). We evaluated the safety of the TLR procedure in adult CHD patients from a 10-year national database. METHODS We used the Healthcare Cost and Utilization Project Nationwide Inpatient Sample to identify TLR procedures in adult patients with and without CHD from 2005 to 2014. Outcomes included in-hospital mortality and complications. RESULTS Of 132 068 adult patients undergoing TLR, 1939 had simple CHD, 657 had complex CHD, and 626 had unclassified CHD. The number of TLR procedures in adult CHD slightly increased from 236 in 2005 to 445 in 2014, with fluctuations over the study period. The overall rate of any complications in the TLR procedure was 16.6% in patients with CHD vs 10.1% in patients without CHD (P

Resumen Introduccion y objetivos Hay poca informacion sobre los resultados de la extraccion transvenosa de electrodos (ETE) en adultos con cardiopatias congenitas ( CC ). Nuestro objetivo fue evaluar la seguridad del procedimiento de la ETE en pacientes con CC a partir del analisis de bases de datos nacionales de series de pacientes durante 10 anos. Metodos Se analizaron las bases de datos Healthcare Cost y Utilization Project Nationwide Inpatient Sample para identificar los procedimientos de la ETE en pacientes adultos con y sin CC entre los anos 2005 y 2014, centrandose en los numeros sobre mortalidad hospitalaria y complicaciones. Resultados Se encontro que 132.068 pacientes adultos se sometieron a ETE, 1.939 con CC simple, 657 con CC compleja y 626 con CC no especificada. El numero de procedimientos de ETE en adultos con CC aumento ligeramente de 236 casos en 2005 a 445 casos en 2014, con fluctuaciones durante el periodo de estudio. La tasa general de cualquier complicacion en el procedimiento de ETE fue del 16,6% en el grupo de CC frente al 10,1% en el de pacientes sin CC (p Conclusiones Los pacientes adultos con CC simples y complejas sometidos a ETE fueron mas propensos a sufrir complicaciones, sin que ello supusiera un aumento de la mortalidad en comparacion con los pacientes sin CC.

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

Background: Remote activity monitoring has the potential to evaluate real-world, motor function, and disability at home. The relationships of daily physical activity with spinal cord white matter and gray matter (GM) areas, multiple sclerosis (MS) disability and leg function, are unknown. Objective: Evaluate the association of structural central nervous system pathology with ambulatory disability. Methods: Fifty adults with progressive or relapsing MS with motor disability who could walk >2 minutes were assessed using clinician-evaluated, patient-reported outcomes, and quantitative brain and spinal cord magnetic resonance imaging (MRI) measures. Fitbit Flex2, worn on the non-dominant wrist, remotely assessed activity over 30 days. Univariate and multivariate analyses were performed to assess correlations between physical activity and other disability metrics. Results: Mean age was 53.3 years and median Expanded Disability Status Scale (EDSS) was 4.0. Average daily step counts (STEPS) were highly correlated with EDSS and walking measures. Greater STEPS were significantly correlated with greater C2-C3 spinal cord GM areas (ρ = 0.39, p = 0.04), total cord area (TCA; ρ = 0.35, p = 0.04), and cortical GM volume (ρ = 0.32, p = 0.04). Conclusion These results provide preliminary evidence that spinal cord GM area is a neuroanatomical substrate associated with STEPS. STEPS could serve as a proxy to alert clinicians and researchers to possible changes in structural nervous system pathology.

ImportanceProlonged symptoms following SARS-CoV-2 infection, or Long COVID, is common, but few prospective studies of Long COVID risk factors have been conducted.ObjectiveTo determine whether sociodemographic factors, lifestyle, or medical history preceding COVID-19 or characteristics of acute SARS-CoV-2 infection are associated with Long COVID.DesignCohort study with longitudinal assessment of symptoms before, during, and after SARS-CoV-2 infection, and cross-sectional assessment of Long COVID symptoms using data from the COVID-19 Citizen Science (CCS) study.SettingCCS is an online cohort study that began enrolling March 26, 2020. We included data collected between March 26, 2020, and May 18, 2022.ParticipantsAdult CCS participants who reported a positive SARS-CoV-2 test result (PCR, Antigen, or Antibody) more than 30 days prior to May 4, 2022, were surveyed.ExposuresAge, sex, race/ethnicity, education, employment, socioeconomic status/financial insecurity, self-reported medical history, vaccination status, time of infection (variant wave), number of acute symptoms, pre-COVID depression, anxiety, alcohol and drug use, sleep, exercise.Main OutcomePresence of at least 1 Long COVID symptom greater than 1 month after acute infection. Sensitivity analyses were performed considering only symptoms beyond 3 months and only severe symptoms.Results13,305 participants reported a SARS-CoV-2 positive test more than 30 days prior, 1480 (11.1% of eligible) responded to a survey about Long COVID symptoms, and 476 (32.2% of respondents) reported Long COVID symptoms (median 360 days after infection).Respondents’ mean age was 53 and 1017 (69%) were female. Common Long COVID symptoms included fatigue, reported by 230/476 (48.3%), shortness of breath (109, 22.9%), confusion/brain fog (108, 22.7%), headache (103, 21.6%), and altered taste or smell (98, 20.6%). In multivariable models, number of acute COVID-19 symptoms (OR 1.30 per symptom, 95%CI 1.20-1.40), lower socioeconomic status/financial insecurity (OR 1.62, 95%CI 1.02-2.63), pre-infection depression (OR 1.08, 95%CI 1.01-1.16), and earlier variants (OR 0.37 for Omicron compared to ancestral strain, 95%CI 0.15-0.90) were associated with Long COVID symptoms.Conclusions and RelevanceVariant wave, severity of acute infection, lower socioeconomic status and pre-existing depression are associated with Long COVID symptoms.Key PointsQuestionWhat are the patterns of symptoms and risk factors for Long COVID among SARS-CoV-2 infected individuals?FindingsPersistent symptoms were highly prevalent, especially fatigue, shortness of breath, headache, brain fog/confusion, and altered taste/smell, which persisted beyond 1 year among 56% of participants with symptoms; a minority of participants reported severe Long COVID symptoms. Number of acute symptoms during acute SARS-CoV-2 infection, financial insecurity, pre-existing depression, and infection with earlier variants are associated with prevalent Long COVID symptoms independent of vaccination, medical history, and other factors.MeaningSeverity of acute infection, SARS-CoV-2 variant, and financial insecurity and depression are associated with Long COVID symptoms.

Background Physical activity can mitigate the risk of cardiovascular diseases, but the presence of mood disorders makes it challenging to follow or develop a regular exercise habit. We conducted an online comparative effectiveness study (Healthy Hearts Healthy Minds) to evaluate whether an online psychosocial intervention adjunctive to an activity monitor (Fitbit) can improve adherence to physical activity among individuals with mood disorders who have or are at-risk for cardiovascular disease (CVD). Methods In this paper, we explore design considerations (including both procedural challenges and achievements) of relevance to our study. Results Challenges of this study included navigating a complex IRB review process, integrating two study platforms, automating study procedures, and optimizing participant engagement. Achievements of this study included building trust with collaborators, leveraging existing online communities, generating daily data reports, and conducting patient-centered research. Limitations These design considerations are based on a single online comparative effectiveness study, and other online intervention studies may be presented with other unique challenges that are specific to their study format or aims. Consistent with some of the generalizability challenges facing other online studies, participants in this study were overall highly educated (most had at least a college degree). Conclusions We successfully conducted a large-scale virtual online intervention to increase physical activity of participants with comorbid mood and cardiovascular disorders by overcoming substantial operational and technical challenges. We hope that this exploration of design considerations in the context of our online study can inform upcoming online intervention studies.

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.

Background Tailored Antiplatelet Initiation to Lessen Outcomes Due to Decreased Clopidogrel Response after Percutaneous Coronary Intervention (TAILOR-PCI) is the largest cardiovascular genotype-based randomized pragmatic trial (NCT#01742117) to evaluate the role of genotype-guided selection of oral P2Y12 inhibitor therapy in improving ischemic outcomes after PCI. The trial has been extended from the original 12- to 24-month follow-up, using study coordinator-initiated telephone visits. TAILOR-PCI Digital Study tests the feasibility of extending the trial follow-up in a subset of patients for up to 24 months using state-of-the-art digital solutions. The rationale, design, and approach of extended digital study of patients recruited into a large, international, multi-center clinical trial has not been previously described. Methods A total of 930 patients from U.S. and Canadian sites previously enrolled in the 5,302 patient TAILOR-PCI trial within 23 months of randomization are invited by mail to the Digital Study website ( http://tailorpci.eurekaplatform.org ) and by up to 2 recruiting telephone calls. Eureka, a direct-to-participant digital research platform, is used to consent and collect prospective data on patients for the digital study. Patients are asked to answer health-related surveys at fixed intervals using the Eureka mobile app and or desktop platform. The likelihood of patients enrolled in a randomized clinical trial transitioning to a registry using digital technology, the reasons for nonparticipation and engagement rates are evaluated. To capture hospitalizations, patients may optionally enable geofencing, a process that allows background location tracking and triggering of surveys if a hospital visit greater than 4 hours is detected. In addition, patients answer digital hospitalization surveys every month. Hospitalization data received from the Digital Study will be compared to data collected from study coordinator telephone visits during the same time frame. Conclusions The TAILOR-PCI Digital Study evaluates the feasibility of transitioning a large multicenter randomized clinical trial to a digital registry. The study could provide evidence for the ability of digital technology to follow clinical trial patients and to ascertain trial-related events thus also building the foundation for conducting digital clinical trials. Such a digital approach may be especially pertinent in the era of COVID-19.

Background: Despite emphasis on efforts to prevent cardiovascular disease (CVD), 13% to 34% of people never fill a prescribed statin (primary nonadherence). This study determined perceptions of adults with primary nonadherence to statins. Methods: Ten focus groups were conducted with 61 adults reporting primary nonadherence to statins (93% without known CVD). Participants were recruited from an academic medical center and nationwide Internet advertisements. Results: Major themes related to primary nonadherence were 1) desire to pursue alternatives before starting a statin (eg, diet and/or exercise, dietary supplements), 2) worry about risks and adverse effects of statins, 3) perceptions of good personal health (suggesting that a statin was not needed), and 4) doubt about the benefits of statins in the absence of disease. Additional themes included mistrust of the pharmaceutical industry, mistrust of prescribing providers, inadequate provider communication about statins, and negative prior experiences with medication. Although rare, a few patients said that high cholesterol does not require treatment if it is genetic. One third noted during focus group discussions that they did not communicate their decision not to take a statin to providers. Conclusions: Adults with primary nonadherence to statins describe seeking alternatives, avoiding perceived risks of statins, poor acceptance/understanding of CVD risk estimates, and doubts about the benefits of statins. Many do not disclose their decisions to providers, thus highlighting the need for provider awareness of the potential for primary nonadherence at the point of prescribing, and the need for future work to develop strategies to identify patients with potential primary nonadherence.

Background It is increasingly recognized that policies have played a role in both alleviating and exacerbating the health and economic consequences of the COVID-19 pandemic. There has been limited systematic evaluation of variation in U.S. local COVID-19-related policies. This study introduces the U.S. COVID-19 County Policy (UCCP) Database, whose objective is to systematically gather, characterize, and assess variation in U.S. county-level COVID-19-related policies. Methods In January-March 2021, we collected an initial wave of cross-sectional data from government and media websites for 171 counties in 7 states on 22 county-level COVID-19-related policies within 3 policy domains that are likely to affect health: (1) containment/closure, (2) economic support, and (3) public health. We characterized the presence and comprehensiveness of policies using univariate analyses. We also examined the correlation of policies with one another using bivariate Spearman’s correlations. Finally, we examined geographical variation in policies across and within states. Results There was substantial variation in the presence and comprehensiveness of county policies during January-March 2021. For containment and closure policies, the percent of counties with no restrictions ranged from 0% (for public events) to more than half for public transportation (67.8%), hair salons (52.6%), and religious gatherings (52.0%). For economic policies, 76.6% of counties had housing support, while 64.9% had utility relief. For public health policies, most were comprehensive, with 70.8% of counties having coordinated public information campaigns, and 66.7% requiring masks outside the home at all times. Correlations between containment and closure policies tended to be positive and moderate (i.e., coefficients 0.4–0.59). There was variation within and across states in the number and comprehensiveness of policies. Conclusions This study introduces the UCCP Database, presenting granular data on local governments’ responses to the COVID-19 pandemic. We documented substantial variation within and across states on a wide range of policies at a single point in time. By making these data publicly available, this study supports future research that can leverage this database to examine how policies contributed to and continue to influence pandemic-related health and socioeconomic outcomes and disparities. The UCCP database is available online and will include additional time points for 2020–2021 and additional counties nationwide.

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.

BackgroundAmbulatory disability is common in people with multiple sclerosis (MS). Remote monitoring using average daily step count (STEPS) can assess physical activity (activity) and disability in MS. STEPS correlates with conventional metrics such as the expanded disability status scale (Expanded Disability Status Scale; EDSS), Timed-25 Foot walk (T25FW) and timed up and go (TUG). However, while STEPS as a summative measure characterizes the number of steps taken over a day, it does not reflect variability and intensity of activity.ObjectivesNovel analytical methods were developed to describe how individuals spends time in various activity levels (e.g., continuous low versus short bouts of high) and the proportion of time spent at each activity level.Methods94 people with MS spanning the range of ambulatory impairment (unaffected to requiring bilateral assistance) were recruited into FITriMS study and asked to wear a Fitbit continuously for 1-year. Parametric distributions were fit to minute-by-minute step data. Adjusted R2 values for regressions between distributional fit parameters and STEPS with EDSS, TUG, T25FW and the patient-reported 12-item MS Walking scale (MSWS-12) were calculated over the first 4-weeks, adjusting for sex, age and disease duration.ResultsDistributional fits determined that the best statistically-valid model across all subjects was a 3-compartment Gaussian Mixture Model (GMM) that characterizes the step behavior within 3 levels of activity: high, moderate and low. The correlation of GMM parameters for baseline step count measures with clinical assessments was improved when compared with STEPS (adjusted R2 values GMM vs. STEPS: TUG: 0.536 vs. 0.419, T25FW: 0.489 vs. 0.402, MSWS-12: 0.383 vs. 0.378, EDSS: 0.557 vs. 0.465). The GMM correlated more strongly (Kruskal-Wallis: p = 0.0001) than STEPS and gave further information not included in STEPS.ConclusionsIndividuals' step distributions follow a 3-compartment GMM that better correlates with clinic-based performance measures compared with STEPS. These data support the existence of high-moderate-low levels of activity. GMM provides an interpretable framework to better understand the association between different levels of activity and clinical metrics and allows further analysis of walking behavior that takes step distribution and proportion of time at three levels of intensity into account.

SARS-CoV-2 accesses host cells via angiotensin-converting enzyme-2, which is also affected by commonly used angiotensin-converting enzyme inhibitors (ACEIs) and angiotensin receptor blockers (ARBs), raising concerns that ACEI or ARB exposure may portend differential COVID-19 outcomes. In parallel cohort studies of outpatient and inpatient COVID-19-diagnosed adults with hypertension, we assessed associations between antihypertensive exposure (ACEI/ARB vs. non-ACEI/ARB antihypertensives, as well as between ACEI- vs. ARB) at the time of COVID-19 diagnosis, using electronic health record data from PCORnet health systems. The primary outcomes were all-cause hospitalization or death (outpatient cohort) or all-cause death (inpatient), analyzed via Cox regression weighted by inverse probability of treatment weights. From February 2020 through December 9, 2020, 11,246 patients (3477 person-years) and 2200 patients (777 person-years) were included from 17 health systems in outpatient and inpatient cohorts, respectively. There were 1015 all-cause hospitalization or deaths in the outpatient cohort (incidence, 29.2 events per 100 person-years), with no significant difference by ACEI/ARB use (adjusted HR 1.01; 95% CI 0.88, 1.15). In the inpatient cohort, there were 218 all-cause deaths (incidence, 28.1 per 100 person-years) and ACEI/ARB exposure was associated with reduced death (adjusted HR, 0.76; 95% CI, 0.57, 0.99). ACEI, versus ARB exposure, was associated with higher risk of hospitalization in the outpatient cohort, but no difference in all-cause death in either cohort. There was no evidence of effect modification across pre-specified baseline characteristics. Our results suggest ACEI and ARB exposure have no detrimental effect on hospitalizations and may reduce death among hypertensive patients diagnosed with COVID-19.

Depressed individuals are more likely to die from cardiovascular disease (CVD) than those without depression. People with CVD have higher rates of depression than those without and have higher mortality rates if they have comorbid depression. While physical activity (PA) improves both, few people engage in enough. We compared self-guided internet-based cognitive behavior therapy (CBT) + Fitbit or mindfulness-based cognitive therapy (MBCT) + Fitbit, with Fitbit only to increase daily steps for participants with depression who have low PA.Adult participants (N = 340) were recruited from two online patient-powered research networks and randomized to one of three study interventions for 8 weeks with an additional 8 weeks of follow-up. Using linear mixed effects models, we evaluated the effect of the intervention on average daily steps (NCT03373110).Average daily steps increased 2.8 steps per day in MBCT+Fitbit, 2.9 steps/day in CBT + Fitbit, but decreased 8.2 steps/day in Fitbit Only. These changes were not statistically different between the MBCT+Fitbit and CBT + Fitbit groups, but were different from Fitbit Only across the initial 8-week period. Group differences were not maintained across follow-up. Exploratory analyses identified comorbid anxiety disorders, self-reported PA, and employment status as moderators.Changes in daily steps over both 8- and 16-week periods-regardless of intervention group-were minimal. The results emphasize the limits of using self-guided web-based psychotherapy with an activity tracker to increase PA in participants with a history of depression and low PA.

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

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 purpose of this study was to compare standard with brief mindfulness training to improve overall well-being. METHODS Participants were recruited from 17 Patient-Powered Research Networks, online communities of stakeholders interested in a common area of research. Participants were randomized to either a standard 8-session mindfulness based cognitive therapy (MBCT) or a brief 3-session mindfulness training intervention accessed online. Participants were followed for 12 weeks. The primary outcome of the study was well-being as measured by the World Health Organization (WHO)-5 Index. We hypothesized that MBCT would be superior to brief mindfulness training. RESULTS We randomized 4,411 participants, 88% of whom were white and 80% female sex assigned at birth. Baseline WHO-5 score mean was 50.3 (SD = 20.7). Average self-reported well-being in each group increased over the intervention period (baseline to 8 weeks) (model-based slope [95% CI] for MBCT group: 0.78 [0.63, 0.93]; brief mindfulness group: 0.76 [0.60, 0.91]) as well as the full study period (i.e., intervention plus follow-up; baseline to 20 weeks) (model-based slope [95% CI] for MBCT group: 0.41 [0.34, 0.48]; brief mindfulness group: 0.33 [0.26, 0.40]). Change in self-reported well-being was not statistically significantly different between MBCT and brief mindfulness during the intervention period (model-based difference in slopes [95% CI]: -0.02 [-0.24, 0.19], P = .80) or during the intervention period plus 12-week follow-up (-0.08 [-0.18, 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, effects that were stronger for participants in the MBCT condition. CONCLUSIONS Standard MBCT improved well-being but was not superior to a brief mindfulness intervention. Younger patients and those able to complete more training sessions improved the most. CLINICALTRIAL 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