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Objectives: The purpose of this study was to examine treatment practices for cancer therapy-associated decreased left ventricular ejection fraction (LVEF) detected on echocardiography and whether management was consistent with American College of Cardiology/American Heart Association guidelines.Background: Patients treated with anthracyclines or trastuzumab are at risk of cardiotoxicity. Decreased LVEF represents a Class I indication for drug intervention according to American College of Cardiology/American Heart Association guidelines.Methods: Patients receiving anthracycline or trastuzumab at Stanford University from October 2005 to October 2007 and who had undergone echocardiography before and after receiving an anthracycline or trastuzumab were identified. Chart review examined chemotherapy regimens, cardiac risk factors, imaging results, concomitant medications, and cardiology consultations.Results: Eighty-eight patients received therapy with an anthracycline or trastuzumab and had a pre-treatment and follow-up echocardiogram. Ninety-two percent were treated with anthracyclines, 17% with trastuzumab after an anthracycline, and 8% with trastuzumab without previous treatment with anthracycline. Mean baseline LVEF was 60%, with 14% having a baseline <55%. Forty percent had decreased LVEF (<55%) after anthracycline and/or trastuzumab treatment. Of these patients, 40% received angiotensin-converting enzyme inhibitor or angiotensin receptor blocker therapy, 51% beta-blocker therapy, and 54% cardiology consultation. Of patients with asymptomatic decreased LVEF, 31% received angiotensin-converting enzyme inhibitor or angiotensin receptor blocker therapy, 35% beta-blocker therapy, and 42% cardiology consultation. Of those with symptomatic decreased LVEF, 67% received angiotensin-converting enzyme inhibitor or angiotensin receptor blocker therapy, 100% beta-blocker therapy, and 89% cardiology consultation.Conclusions: Many cancer survivors are not receiving treatment consistent with heart failure guidelines. There is substantial opportunity for collaboration between oncologists and cardiologists to improve the care of oncology patients receiving cardiotoxic therapy. [ABSTRACT FROM AUTHOR]

Background: Remote patient monitoring (RPM) clinical trials have reported mixed results in improving outcomes for patients with chronic heart failure (HF). The impact of clinical workflows that could impact RPM effectiveness is often overlooked. We sought to characterize workflows and response protocols that could impact outcomes in studies of non-invasive RPM in HF., Methods: We reviewed studies (1999-2024) assessing non-invasive RPM interventions for adults with HF. We collected 24 aspects of workflows describing education, physiological and symptomatic data collection, transmission and review, clinical escalation protocols, and response time. We attempted to perform a meta-analysis to identify associations between workflow components and outcomes of death and hospitalization., Results: We identified 63 studies (57.1% randomized controlled, 23.8% pilot/feasibility, 19.1% other) comprising 16,699 subjects. Despite a large number of studies and subjects, workflow reporting was insufficient to perform our intended meta-analysis regarding key workflow components. RPM clinical workflows were diverse in configuration, with high variability in component description ranging from always- to never-reported. Specifics of monitoring devices and related training were well-reported as expected based on most trial hypotheses. However, elements of clinical data response such as frequency of data review, clinical escalation criteria, and provider response time were often underreported or not reported at all (48%, 24%, and 97%, respectively), hindering study replication and evidence-based implementation., Conclusions: Clinical workflows are poorly described in non-invasive RPM studies, preventing systematic assessment, device comparison, and replication. A standardized approach to reporting HF RPM workflows is vital to evaluate effectiveness and guide evidence-based clinical implementation., (Copyright © 2024. Published by Elsevier Inc.)

Introduction: Diabetes mellitus (DM) is increasingly recognized as a possible consequence of statin therapy. Secondary analysis of randomized clinical trials and limited observational cohort analyses have suggested that women may be more likely than men to experience statin-associated DM. No analyses of real-world drug safety data addressing this question have been published., Research Design and Methods: This was a retrospective pharmacovigilance analysis of spontaneously reported adverse drug events (ADEs) submitted to the Food and Drug Administration Adverse Event Reporting System between January 1997 through December 2023. We analyzed cases that mentioned atorvastatin, fluvastatin, lovastatin, pitavastatin, pravastatin, rosuvastatin, or simvastatin in aggregate as well as cases reporting atorvastatin, pravastatin, rosuvastatin, simvastatin individually. DM events were identified using the Medical Dictionary for Regulatory Activities. We used the proportional reporting ratio to identify increased rates of statin-associated DM events in women and men compared with all other medications, and the reporting OR to compare reporting rates in women versus men., Results: A total of 18,294,814 ADEs were reported during the study period. Among statin-associated ADEs, 14,874/519,209 (2.9%) reports mentioned DM in women compared with 7,411/489,453 (1.5%) in men, which were both significantly higher than background (0.6%). Statins were the primary-suspected or secondary-suspected cause of the ADE significantly more often in women than men (60 vs 30%), and reporting rates were disproportionately higher in women than in men for all statins. (reporting OR 1.9 (95% CI 1.9 to 2.0)). The largest difference in reporting of statin-associated DM between women and women was observed with atorvastatin., Conclusions: Analysis of post-marketing spontaneous ADE reports demonstrated a higher reporting rate of DM-associated with statin use compared with other medications with a significantly higher reporting rate in women compared with men. Future studies should consider mechanisms of statin-associated DM moderated by sex., Competing Interests: Competing interests: None declared., (© Author(s) (or their employer(s)) 2024. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ.)

Background: Seasonal variations have been observed in heart failure (HF) hospitalization. Numerous explanatory mechanisms have been proposed, but no prior studies have examined potential contributors directly. Our objective was to identify specific factors that could contribute to seasonal variability using a large longitudinal dataset of HF hospitalizations., Methods: Hospital discharge data were obtained for all hospitals in the state of New York from 1994 to 2007. Records with a primary diagnosis of HF by the International Classification of Diseases-9 Clinical Modification (ICD-9-CM) code (428.xx and 425.xx) were included. Year and month of admission were used as predictors to evaluate outcomes of in-hospital mortality, population-adjusted daily rate of hospital admissions and length of stay (LOS) using univariable regression including a sinusoidal model to assess the seasonality of HF outcomes. Observations were then adjusted for multiple medical covariables as well as the average local monthly temperature and humidity at each hospital using data from the Global Historical Climate Network to identify potential modifiers of seasonal variability., Results: Among 949 907 records, the median age was 76 [inter-quartile range (IQR) 65-84 years old], and the cohort was 54% female (510 945 records). The population-adjusted rate of HF admissions per day increased by 1.1 admissions/day/year between 1994 and 2007, whereas in-hospital mortality and LOS decreased by -0.3%/year and -0.3 days/year, respectively (P < 0.001 for all). Seasonal trends were identified for daily HF admissions (February peak, P < 0.0001), mortality (January peak, P < 0.001) and LOS (January peak, P < 0.01). Cosinor analysis revealed significant periodicity for HF admission rate (amplitude = ±0.9 admissions/day/100 000 people, P < 0.001), in-hospital mortality (amplitude = ±0.47%, P < 0.001) and LOS (amplitude = ±0.23 days, P < 0.01). No other patient characteristics were significant modifiers of seasonality. Odds of mortality were highest in July rather than January when adjusted for average local temperature but not humidity., Conclusions: Adverse outcomes in patients hospitalized with HF were significantly worse in the winter months even when adjusted for patient characteristics and concurrent acute diagnoses such as pneumonia. Local ambient temperature was the strongest modifier of the observed seasonality. Given the increasing frequency of extreme weather events, additional work to determine the mechanisms of this and other environmental risk factors is urgently needed., (© 2024 The Author(s). ESC Heart Failure published by John Wiley & Sons Ltd on behalf of European Society of Cardiology.)

Objective: Understand perceived barriers to and facilitators of using clinical informatics applications for pharmacogenomic (PGx) implementation in resource-limited settings., Materials and Methods: We conducted a qualitative research study using a semi-structured interview guide informed by the Consolidated Framework for Implementation Research (CFIR). Interview questions assessed CFIR contextual determinants related to: electronic health record (EHR) infrastructure; clinical informatics personnel and resources; EHR integration of PGx test results; PGx clinical decision support (CDS) tools; institutional resources; and partner receptivity. Transcripts were coded and analyzed to identify themes., Results: We interviewed 24 clinical informaticists and executive leaders working in rural or underserved health care settings in Montana ( n  = 15) and Colorado ( n  = 9) and identified three major themes: (1) EHR infrastructure limitations, (2) insufficient supporting resources, and (3) unique contextual considerations for resource-limited settings. EHR infrastructure limitations included limited agency related to EHR build and interoperability concerns. Theme 1 highlighted challenges associated with integrating structured data into the EHR and inadequate vendor support. Theme 2 included limited familiarity with PGx across the care team, cost concerns, and allocation of non-financial resources. Theme 3 highlighted perceptions about the clinical utility of PGx within rural and underrepresented populations. Potential facilitators, such as being able to act nimbly, were found to coexist among the reported barriers., Discussion and Conclusion: Our results provide insight into the clinical informatics infrastructure in resource-limited settings and identify unique considerations for clinical informatics-facilitated PGx implementation. Future efforts in these settings should consider innovative partnerships and strategies to leverage facilitators and minimize barriers associated with integrating PGx CDS applications., Competing Interests: The authors have no competing interests to declare., (© The Author(s) 2024. Published by Oxford University Press on behalf of the American Medical Informatics Association.)

Purpose: To describe our experiences implementing and iterating CYP2C19 genotype-guided clopidogrel pharmacogenetic clinical decision support (CDS) tools over time in the setting of a large health system-wide, preemptive pharmacogenomics program., Summary: Clopidogrel-treated patients who are genetically predicted cytochrome P450 isozyme 2C19 (CYP2C19) intermediate or poor metabolizers have an increased risk of atherothrombotic events, some of which can be life-threatening. The Clinical Pharmacogenetics Implementation Consortium provides guidance for the use of clopidogrel based on CYP2C19 genotype in patients with cardiovascular and cerebrovascular diseases. Our multidisciplinary team implemented an automated, interruptive alert that fires when clopidogrel is ordered or refilled for biobank participants with structured CYP2C19 intermediate or poor metabolizer genomic indicators in the electronic health record. The implementation began with a narrow cardiovascular indication and setting and was then scaled in 4 primary dimensions: (1) clinical indication; (2) availability across health-system locations; (3) care venue (e.g., inpatient vs outpatient); and (4) provider groups (eg, cardiology and neurology). We iterated our approach over time based on evolving clinical evidence and proactive strategies to optimize CDS maintenance and sustainability. A key facilitator of expansion was socialization of the broader pharmacogenomics initiative among our academic medical center community, accompanied by clinician acceptance of pharmacogenetic alerts in practice., Conclusion: A multidisciplinary collaboration is recommended to facilitate the use of CYP2C19 genotype-guided antiplatelet therapy in patients with cardiovascular and cerebrovascular diseases. Evolving clopidogrel pharmacogenetic evidence necessitates thoughtful iteration of implementation efforts and strategies to optimize long-term maintenance and sustainability., (© American Society of Health-System Pharmacists 2024. All rights reserved. For commercial re-use, please contact reprints@oup.com for reprints and translation rights for reprints. All other permissions can be obtained through our RightsLink service via the Permissions link on the article page on our site—for further information please contact journals.permissions@oup.com.)

Background: The prevalence of exposure to pharmacogenomic medications is well established but little is known about how long patients are exposed to these medications., Aim: Our objective was to describe the amount of exposure to actionable pharmacogenomic medications using patient-level measures among a large nationally representative population using an insurance claims database., Methods: Our retrospective cohort study included adults (18+ years) from the IQVIA PharMetrics ® Plus for Academics claims database with incident fills of 72 Clinical Pharmacogenetics Implementation Consortium level A, A/B, or B medications from January 2012 through September 2018. Patient-level outcomes included the proportion of days covered (PDC), number of fills, and average days supplied per fill over a 12-month period., Results: Over 1 million fills of pharmacogenetic medications were identified for 605,355 unique patients. The mean PDC for all medications was 0.21 (SD 0.3), suggesting patients were exposed 21% (77 days) of the year. Medications with the highest PDC (0.55-0.89) included ivacaftor, tamoxifen, clopidogrel, HIV medications, transplant medications, and statins; with the exception of statins, these medications were initiated by fewer patients. Pharmacogenomic medications were filled an average of 2.8 times (SD 3.0, range 1-81) during the year following the medication's initiation, and the average days supplied for each fill was 22.3 days (SD 22.4, range 1-180 days)., Conclusion: Patient characteristics associated with more medication exposure were male sex, older age, and comorbid chronic conditions. Prescription fill data provide patient-level exposure metrics that can further our understanding of pharmacogenomic medication utilization and help inform opportunities for pharmacogenomic testing.

Objectives: In a randomized controlled trial, we found that applying implementation science (IS) methods and best practices in clinical decision support (CDS) design to create a locally customized, "enhanced" CDS significantly improved evidence-based prescribing of β blockers (BB) for heart failure compared with an unmodified commercially available CDS. At trial conclusion, the enhanced CDS was expanded to all sites. The purpose of this study was to evaluate the real-world sustained effect of the enhanced CDS compared with the commercial CDS., Methods: In this natural experiment of 28 primary care clinics, we compared clinics exposed to the commercial CDS (preperiod) to clinics exposed to the enhanced CDS (both periods). The primary effectiveness outcome was the proportion of alerts resulting in a BB prescription. Secondary outcomes included patient reach and clinician adoption (dismissals)., Results: There were 367 alerts for 183 unique patients and 171 unique clinicians (pre: March 2019-August 2019; post: October 2019-March 2020). The enhanced CDS increased prescribing by 26.1% compared with the commercial (95% confidence interval [CI]: 17.0-35.1%), which is consistent with the 24% increase in the previous study. The odds of adopting the enhanced CDS was 81% compared with 29% with the commercial (odds ratio: 4.17, 95% CI: 1.96-8.85). The enhanced CDS adoption and effectiveness rates were 62 and 14% in the preperiod and 92 and 10% in the postperiod., Conclusion: Applying IS methods with CDS best practices was associated with improved and sustained clinician adoption and effectiveness compared with a commercially available CDS tool., Competing Interests: None declared., (Thieme. All rights reserved.)

We investigated the extent, biologic characterization, phenotypic specificity, and possible regulation of a β1-adrenergic receptor-linked (β1-AR-linked) gene signaling network (β1-GSN) involved in left ventricular (LV) eccentric pathologic remodeling. A 430-member β1-GSN was identified by mRNA expression in transgenic mice overexpressing human β1-ARs or from literature curation, which exhibited opposite directional behavior in interventricular septum endomyocardial biopsies taken from patients with beta-blocker-treated, reverse remodeled dilated cardiomyopathies. With reverse remodeling, the major biologic categories and percentage of the dominant directional change were as follows: metabolic (19.3%, 81% upregulated); gene regulation (14.9%, 78% upregulated); extracellular matrix/fibrosis (9.1%, 92% downregulated); and cell homeostasis (13.3%, 60% upregulated). Regarding the comparison of β1-GSN categories with expression from 19,243 nonnetwork genes, phenotypic selection for major β1-GSN categories was exhibited for LV end systolic volume (contractility measure), ejection fraction (remodeling index), and pulmonary wedge pressure (wall tension surrogate), beginning at 3 months and persisting to study completion at 12 months. In addition, 121 lncRNAs were identified as possibly involved in cis-acting regulation of β1-GSN members. We conclude that an extensive 430-member gene network downstream from the β1-AR is involved in pathologic ventricular remodeling, with metabolic genes as the most prevalent category.

Introduction/background: Patients with heart failure and reduced ejection fraction (HFrEF) are consistently underprescribed guideline-directed medications. Although many barriers to prescribing are known, identification of these barriers has relied on traditional a priori hypotheses or qualitative methods. Machine learning can overcome many limitations of traditional methods to capture complex relationships in data and lead to a more comprehensive understanding of the underpinnings driving underprescribing. Here, we used machine learning methods and routinely available electronic health record data to identify predictors of prescribing., Methods: We evaluated the predictive performance of machine learning algorithms to predict prescription of four types of medications for adults with HFrEF: angiotensin converting enzyme inhibitor/angiotensin receptor blocker (ACE/ARB), angiotensin receptor-neprilysin inhibitor (ARNI), evidence-based beta blocker (BB), or mineralocorticoid receptor antagonist (MRA). The models with the best predictive performance were used to identify the top 20 characteristics associated with prescribing each medication type. Shapley values were used to provide insight into the importance and direction of the predictor relationships with medication prescribing., Results: For 3,832 patients meeting the inclusion criteria, 70% were prescribed an ACE/ARB, 8% an ARNI, 75% a BB, and 40% an MRA. The best-predicting model for each medication type was a random forest (area under the curve: 0.788-0.821; Brier score: 0.063-0.185). Across all medications, top predictors of prescribing included prescription of other evidence-based medications and younger age. Unique to prescribing an ARNI, the top predictors included lack of diagnoses of chronic kidney disease, chronic obstructive pulmonary disease, or hypotension, as well as being in a relationship, nontobacco use, and alcohol use., Discussion/conclusions: We identified multiple predictors of prescribing for HFrEF medications that are being used to strategically design interventions to address barriers to prescribing and to inform further investigations. The machine learning approach used in this study to identify predictors of suboptimal prescribing can also be used by other health systems to identify and address locally relevant gaps and solutions to prescribing., Competing Interests: DCM reports consulting fees from Biomarin, Abbott/Pharmacylics, Novartis, Pear Therapeutics, Seres, and Sarepta. LAA reports consulting fees from Abbott, ACI Clinical, Amgen, Boston Scientific, Cytokinetics, and Novartis. The remaining authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (© 2023 Kim, Suresh, Rosenberg, Tan, Malone, Allen, Kao, Anderson, Tiwari and Trinkley.)

Background: Epidemic increases in opioid deaths prompted policies limiting access to prescription opioids in North America. Consequently, the over-the-counter opioids loperamide (Imodium A-D) and mitragynine, the herbal ingredient in kratom, are increasingly used to avert withdrawal or induce euphoria. Arrhythmia events related to these nonscheduled drugs have not been systematically studied., Objectives: In this study, we sought to explore opioid-associated arrhythmia reporting in North America., Methods: The U.S. Food and Drug Administration Adverse Event Reporting System (FAERS), Center for Food Safety and Applied Nutrition Adverse Event Reporting System (CAERS), and Canada Vigilance Adverse Reaction (CVAR) databases were searched (2015-2021). Reports involving nonprescription drugs (loperamide, mitragynine) and diphenoxylate/atropine (Lomotil) were identified. Methadone, a prescription opioid (full agonist), served as a positive control owing to its established arrhythmia risk. Buprenorphine (partial agonist) and naltrexone (pure antagonist), served as negative controls. Reports were classified according to Medical Dictionary for Regulatory Activities terminology. Significant disproportionate reporting required a proportional reporting ratio (PRR) of ≥2, ≥3 cases, and chi-square ≥4. Primary analysis used FAERS data, whereas CAERS and CVAR data were confirmatory., Results: Methadone was disproportionately associated with ventricular arrhythmia reports (PRR: 6.6; 95% CI: 6.2-7.0; n = 1,163; chi-square = 5,456), including 852 (73%) fatalities. Loperamide was also significantly associated with arrhythmia (PRR: 3.2; 95% CI: 3.0-3.4; n = 1,008; chi-square = 1,537), including 371 (37%) deaths. Mitragynine demonstrated the highest signal (PRR: 8.9; 95% CI: 6.7-11.7; n = 46; chi-square = 315), with 42 (91%) deaths. Buprenorphine, diphenoxylate, and naltrexone were not associated with arrhythmia. Signals were similar in CVAR and CAERS., Conclusions: The nonprescription drugs loperamide and mitragynine are associated with disproportionate reports of life-threatening ventricular arrhythmia in North America., Competing Interests: Funding Support and Author Disclosures This publication reflects independent work of the authors and is not a representation of official policies or positions of the American College of Cardiology or any U.S. governmental agency, including the Department of Defense, Veterans Medical Affairs Medical Center, or the Food and Drug Administration. Dr Kao was supported by K08 HL125725. All other authors have reported that they have no relationships relevant to the contents of this paper to disclose., (Copyright © 2023 American College of Cardiology Foundation. Published by Elsevier Inc. All rights reserved.)

Actionable drug-gene pairs relevant to depression treatment include CYP2D6 and CYP2C19 with specific antidepressants. While clinical use of pharmacogenetic testing is growing, little is known about pharmacogenetic testing for depression treatment in managed care. We determined the incidence of single-gene CYP2D6 and CYP2C19 testing following a new depression episode among US managed care patients, and described characteristics and antidepressant use of patients receiving tests. We used paid medical and pharmacy claims for patients from commercial health plans in the US. For adult patients with a new depression episode from January 1, 2013 to June 30, 2018, we identified covered claims for single-gene CYP2D6 and CYP2C19 pharmacogenetic tests and antidepressant fills. Fewer than 1% (n = 1795) of the depressed cohort (n = 438,534) received a single-gene CYP2D6 or CYP2C19 test through their insurance within 365 days of their earliest depression episode. The percentage of patients who received a test nearly tripled from 0.2% in 2013 to 0.5% in 2014 before plateauing at 0.4% from 2014 to 2017. Among the patients who received a single-gene CYP2D6 or CYP2C19 test and filled an antidepressant within 365 days of their depression diagnosis, up to 30% may have had their initial antidepressant informed by the test result. Our findings describe the use of antidepressants before and after pharmacogenetic testing, which is clinically relevant as pharmacogenomic testing becomes more common in clinical practice. Our study also emphasizes the need for procedure and billing codes that capture multiple-gene panel tests to be more widely implemented in administrative databases., (© 2022 The Authors. Clinical and Translational Science published by Wiley Periodicals LLC on behalf of American Society for Clinical Pharmacology and Therapeutics.)

Increasing the global adoption of electronic health records (EHRs) is transforming the delivery of clinical care. EHRs offer tools that are useful in the care of heart failure ranging from individualized risk stratification and decision support to population management. EHR tools can be combined to target specific areas of need such as the standardization of care, improved quality of care, and resource management. Leveraging EHR functionality has been shown to improve select outcomes including guideline-based therapies, reduction in adverse clinical outcomes, and improved cost-efficiency. Central to success is participation by clinicians and patients in the design and feedback of EHR tools., Competing Interests: Disclosure statement Dr Kao is supported by National Heart, Lung, and Blood Institute award K08HL125275, as well as L30 HL110124. Dr Kao is an advisor and has received stock options from Codex Health, Inc., (Copyright © 2021 Elsevier Inc. All rights reserved.)

Background: Delays in diagnosis of peripartum cardiomyopathy (PPCM) are common and are associated with worse outcomes; however, few studies have addressed methods for improving early detection., Hypothesis: We hypothesized that easily accessible data (heart rate [HR] and electrocardiograms [ECGs]) could identify women with more severe PPCM and at increased risk of adverse outcomes., Methods: Clinical data, including HR and ECG, from patients diagnosed with PPCM between January 1998 and July 2016 at our institution were collected and analyzed. Linear and logistic regression were used to analyze the relationship between HR at diagnosis and the left ventricular ejection fraction (LVEF) at diagnosis. Outcomes included overall mortality, recovery status, and major adverse cardiac events., Results: Among 82 patients meeting inclusion criteria, the overall mean LVEF at diagnosis was 26 ± 11.1%. Sinus tachycardia (HR > 100) was present in a total of 50 patients (60.9%) at the time of diagnosis. In linear regression, HR significantly predicted lower LVEF (F = 30.00, p < .0001). With age-adjusted logistic regression, elevated HR at diagnosis was associated with a fivefold higher risk of overall mortality when initial HR was >110 beats per minute (adjusted odds ratio 5.35, confidence interval 1.23-23.28), p = .025)., Conclusion: In this study, sinus tachycardia in women with PPCM was associated with lower LVEF at the time of diagnosis. Tachycardia in the peripartum period should raise concern for cardiomyopathy and may be an early indicator of adverse prognosis., (© 2022 The Authors. Clinical Cardiology published by Wiley Periodicals, LLC.)

Background: Since the onset of the SARS-CoV-2 pandemic, most clinical testing has focused on RT-PCR 1 . Host epigenome manipulation post coronavirus infection 2-4 suggests that DNA methylation signatures may differentiate patients with SARS-CoV-2 infection from uninfected individuals, and help predict COVID-19 disease severity, even at initial presentation., Methods: We customized Illumina's Infinium MethylationEPIC array to enhance immune response detection and profiled peripheral blood samples from 164 COVID-19 patients with longitudinal measurements of disease severity and 296 patient controls., Results: Epigenome-wide association analysis revealed 13,033 genome-wide significant methylation sites for case-vs-control status. Genes and pathways involved in interferon signaling and viral response were significantly enriched among differentially methylated sites. We observe highly significant associations at genes previously reported in genetic association studies (e.g. IRF7, OAS1). Using machine learning techniques, models built using sparse regression yielded highly predictive findings: cross-validated best fit AUC was 93.6% for case-vs-control status, and 79.1%, 80.8%, and 84.4% for hospitalization, ICU admission, and progression to death, respectively., Conclusions: In summary, the strong COVID-19-specific epigenetic signature in peripheral blood driven by key immune-related pathways related to infection status, disease severity, and clinical deterioration provides insights useful for diagnosis and prognosis of patients with viral infections., (© 2021. The Author(s).)

Objective: To rapidly develop, validate, and implement a novel real-time mortality score for the COVID-19 pandemic that improves upon sequential organ failure assessment (SOFA) for decision support for a Crisis Standards of Care team., Materials and Methods: We developed, verified, and deployed a stacked generalization model to predict mortality using data available in the electronic health record (EHR) by combining 5 previously validated scores and additional novel variables reported to be associated with COVID-19-specific mortality. We verified the model with prospectively collected data from 12 hospitals in Colorado between March 2020 and July 2020. We compared the area under the receiver operator curve (AUROC) for the new model to the SOFA score and the Charlson Comorbidity Index., Results: The prospective cohort included 27 296 encounters, of which 1358 (5.0%) were positive for SARS-CoV-2, 4494 (16.5%) required intensive care unit care, 1480 (5.4%) required mechanical ventilation, and 717 (2.6%) ended in death. The Charlson Comorbidity Index and SOFA scores predicted mortality with an AUROC of 0.72 and 0.90, respectively. Our novel score predicted mortality with AUROC 0.94. In the subset of patients with COVID-19, the stacked model predicted mortality with AUROC 0.90, whereas SOFA had AUROC of 0.85., Discussion: Stacked regression allows a flexible, updatable, live-implementable, ethically defensible predictive analytics tool for decision support that begins with validated models and includes only novel information that improves prediction., Conclusion: We developed and validated an accurate in-hospital mortality prediction score in a live EHR for automatic and continuous calculation using a novel model that improved upon SOFA., (© The Author(s) 2021. Published by Oxford University Press on behalf of the American Medical Informatics Association. All rights reserved. For permissions, please email: journals.permissions@oup.com.)

The value of utilizing a multigene pharmacogenetic panel to tailor pharmacotherapy is contingent on the prevalence of prescribed medications with an actionable pharmacogenetic association. The Clinical Pharmacogenetics Implementation Consortium (CPIC) has categorized over 35 gene-drug pairs as "level A," for which there is sufficiently strong evidence to recommend that genetic information be used to guide drug prescribing. The opportunity to use genetic information to tailor pharmacotherapy among adult patients was determined by elucidating the exposure to CPIC level A drugs among 11 Implementing Genomics In Practice Network (IGNITE)-affiliated health systems across the US. Inpatient and/or outpatient electronic-prescribing data were collected between January 1, 2011 and December 31, 2016 for patients ≥ 18 years of age who had at least one medical encounter that was eligible for drug prescribing in a calendar year. A median of ~ 7.2 million adult patients was available for assessment of drug prescribing per year. From 2011 to 2016, the annual estimated prevalence of exposure to at least one CPIC level A drug prescribed to unique patients ranged between 15,719 (95% confidence interval (CI): 15,658-15,781) in 2011 to 17,335 (CI: 17,283-17,386) in 2016 per 100,000 patients. The estimated annual exposure to at least 2 drugs was above 7,200 per 100,000 patients in most years of the study, reaching an apex of 7,660 (CI: 7,632-7,687) per 100,000 patients in 2014. An estimated 4,748 per 100,000 prescribing events were potentially eligible for a genotype-guided intervention. Results from this study show that a significant portion of adults treated at medical institutions across the United States is exposed to medications for which genetic information, if available, should be used to guide prescribing., (© 2021 The Authors. Clinical Pharmacology & Therapeutics © 2021 American Society for Clinical Pharmacology and Therapeutics.)

Objectives: The aim of this study was to determine whether patients with heart failure with reduced ejection fraction (HFrEF) due to nonischemic etiology eligible for cardiac resynchronization therapy (CRT) benefit from an implantable cardioverter-defibrillator (ICD)., Background: It is uncertain whether CRT with an ICD (CRT-D) compared to without an ICD (CRT-P) is associated with a survival benefit in patients with nonischemic etiologies of HFrEF., Methods: Analyses of the COMPANION (Comparison of Medical Therapy, Pacing, and Defibrillation in Heart Failure) trial were performed, using Cox proportional hazards modeling stratified by HFrEF etiology of nonischemic cardiomyopathy (NICM) or ischemic cardiomyopathy (ICM). The primary outcome was all-cause mortality (ACM), and secondary outcomes were the combination of cardiovascular mortality or heart failure hospitalization and sudden cardiac death., Results: Among patients randomized to CRT (n = 1,212), 236 (19.5%) died, 131 and 105 in the CRT-P and CRT-D arms, respectively. The unadjusted and adjusted hazard ratios (HRs) for CRT-D versus CRT-P were both 0.84 (95% confidence interval [CI]: 0.65 to 1.09) for ACM, with a significant device-etiology interaction (p interaction  = 0.015 adjusted; p interaction  = 0.040 unadjusted). In patients with NICM (n = 555), CRT-D versus CRT-P was associated with reduced ACM (adjusted HR: 0.54; 95% CI: 0.34 to 0.86), while patients with ICM (n = 657) did not exhibit a between-device reduction in ACM (adjusted HR: 1.05; 95% CI: 0.77 to 1.44). The effects of CRT-D versus CRT-P on sudden cardiac death (advantage CRT-D) and cardiovascular mortality or heart failure hospitalization (no difference between CRT-P and CRT-D) were similar between the 2 HFrEF etiologies., Conclusions: COMPANION patients with NICM exhibited a decrease in ACM associated with CRT-D but not CRT-P treatment, whereas patients with ICM did not., Competing Interests: Funding Support and Author Disclosures This analysis was supported by the Statistical Data Analysis Center at the University of Wisconsin, by the University of Colorado Division of Cardiology, and by an American Heart Association Strategically Focused Network Grant in Heart Failure awarded to Drs. Bristow and Buttrick. The corporate sponsor of the COMPANION trial, Boston Scientific, provided no funding to the study. Drs. Feldman, Saxon, and Bristow were consultants for Guidant Corporation during the planning and execution of the COMPANION trial. Drs. Doran and Bristow are supported by an American Heart Association Strategically Focused Network Grant in Heart Failure. Dr. DeMets is a founder of the Statistical Data Analysis Center at the University of Wisconsin, where he is an emeritus professor. The Statistical and Data Analysis Center provided biostatistical support for the analyses performed by Mr. Mei in the current study. All other authors have reported that they have no relationships relevant to the contents of this paper to disclose., (Copyright © 2021 The Authors. Published by Elsevier Inc. All rights reserved.)

Background: Limited consideration of clinical decision support (CDS) design best practices, such as a user-centered design, is often cited as a key barrier to CDS adoption and effectiveness. The application of CDS best practices is resource intensive; thus, institutions often rely on commercially available CDS tools that are created to meet the generalized needs of many institutions and are not user centered. Beyond resource availability, insufficient guidance on how to address key aspects of implementation, such as contextual factors, may also limit the application of CDS best practices. An implementation science (IS) framework could provide needed guidance and increase the reproducibility of CDS implementations., Objective: This study aims to compare the effectiveness of an enhanced CDS tool informed by CDS best practices and an IS framework with a generic, commercially available CDS tool., Methods: We conducted an explanatory sequential mixed methods study. An IS-enhanced and commercial CDS alert were compared in a cluster randomized trial across 28 primary care clinics. Both alerts aimed to improve beta-blocker prescribing for heart failure. The enhanced alert was informed by CDS best practices and the Practical, Robust, Implementation, and Sustainability Model (PRISM) IS framework, whereas the commercial alert followed vendor-supplied specifications. Following PRISM, the enhanced alert was informed by iterative, multilevel stakeholder input and the dynamic interactions of the internal and external environment. Outcomes aligned with PRISM's evaluation measures, including patient reach, clinician adoption, and changes in prescribing behavior. Clinicians exposed to each alert were interviewed to identify design features that might influence adoption. The interviews were analyzed using a thematic approach., Results: Between March 15 and August 23, 2019, the enhanced alert fired for 61 patients (106 alerts, 87 clinicians) and the commercial alert fired for 26 patients (59 alerts, 31 clinicians). The adoption and effectiveness of the enhanced alert were significantly higher than those of the commercial alert (62% vs 29% alerts adopted, P<.001; 14% vs 0% changed prescribing, P=.006). Of the 21 clinicians interviewed, most stated that they preferred the enhanced alert., Conclusions: The results of this study suggest that applying CDS best practices with an IS framework to create CDS tools improves implementation success compared with a commercially available tool., Trial Registration: ClinicalTrials.gov NCT04028557; http://clinicaltrials.gov/ct2/show/NCT04028557., (©Katy E Trinkley, Miranda E Kroehl, Michael G Kahn, Larry A Allen, Tellen D Bennett, Gary Hale, Heather Haugen, Simeon Heckman, David P Kao, Janet Kim, Daniel M Matlock, Daniel C Malone, Robert L Page 2nd, Jessica Stine, Krithika Suresh, Lauren Wells, Chen-Tan Lin. Originally published in JMIR Medical Informatics (http://medinform.jmir.org), 22.03.2021.)

Background: Major gaps exist in the routine initiation and dose up-titration of guideline-directed medical therapies (GDMT) for patients with heart failure with reduced ejection fraction. Without novel approaches to improve prescribing, the cumulative benefits of heart failure with reduced ejection fraction treatment will be largely unrealized. Direct-to-consumer marketing and shared decision making reflect a culture where patients are increasingly involved in treatment choices, creating opportunities for prescribing interventions that engage patients., Methods: The EPIC-HF (Electronically Delivered, Patient-Activation Tool for Intensification of Medications for Chronic Heart Failure with Reduced Ejection Fraction) trial randomized patients with heart failure with reduced ejection fraction from a diverse health system to usual care versus patient activation tools-a 3-minute video and 1-page checklist-delivered electronically 1 week before, 3 days before, and 24 hours before a cardiology clinic visit. The tools encouraged patients to work collaboratively with their clinicians to "make one positive change" in heart failure with reduced ejection fraction prescribing. The primary endpoint was the percentage of patients with GDMT medication initiations and dose intensifications from immediately preceding the cardiology clinic visit to 30 days after, compared with usual care during the same period., Results: EPIC-HF enrolled 306 patients, 290 of whom attended a clinic visit during the study period: 145 were sent the patient activation tools and 145 were controls. The median age of patients was 65 years; 29% were female, 11% were Black, 7% were Hispanic, and the median ejection fraction was 32%. Preclinic data revealed significant GDMT opportunities, with no patients on target doses of β-blocker, sacubitril/valsartan, and mineralocorticoid receptor antagonists. From immediately preceding the cardiology clinic visit to 30 days after, 49.0% in the intervention and 29.7% in the control experienced an initiation or intensification of their GDMT ( P =0.001). The majority of these changes were made at the clinician encounter itself and involved dose uptitrations. There were no deaths and no significant differences in hospitalization or emergency department visits at 30 days between groups., Conclusions: A patient activation tool delivered electronically before a cardiology clinic visit improved clinician intensification of GDMT. Registration: URL: https://www.clinicaltrials.gov; Unique identifier: NCT03334188.

Background: Coronary heart disease, heart failure (HF), and stroke are complex diseases with multiple phenotypes. While many risk factors for these diseases are well known, investigation of as-yet unidentified risk factors may improve risk assessment and patient adherence to prevention guidelines. We investigated the diet domain in FHS (Framingham Heart Study), CHS (Cardiovascular Heart Study), and the ARIC study (Atherosclerosis Risk in Communities) to identify potential lifestyle and behavioral factors associated with coronary heart disease, HF, and stroke., Methods: We used machine learning feature selection based on random forest analysis to identify potential risk factors associated with coronary heart disease, stroke, and HF in FHS. We evaluated the significance of selected variables using univariable and multivariable Cox proportional hazards analysis adjusted for known cardiovascular risks. Findings from FHS were then validated using CHS and ARIC., Results: We identified multiple dietary and behavioral risk factors for cardiovascular disease outcomes including marital status, red meat consumption, whole milk consumption, and coffee consumption. Among these dietary variables, increasing coffee consumption was associated with decreasing long-term risk of HF congruently in FHS, ARIC, and CHS., Conclusions: Higher coffee intake was found to be associated with reduced risk of HF in all three studies. Further study is warranted to better define the role, possible causality, and potential mechanism of coffee consumption as a potential modifiable risk factor for HF.

Background: Lisinopril and losartan manufacturer labels recommend twice-daily dosing (BID) if once-daily (QDay) is insufficient to lower blood pressure (BP)., Methods and Results: Retrospective cohort study of patients taking QDay lisinopril and losartan who experienced a dose-doubling (index date). A text-processing tool categorized BID and QDay groups at the index date based on administration instructions. We excluded: pregnant/hospice, regimens other than BID/QDay, and without BP measurements -6 months/+12 months of the index date. The most proximal BP measurements -6 months and +2 weeks to 12 months of the index date were used to evaluate BP differences. Propensity scores were generated, and differences in BP and adverse events (angioedema, acute kidney injury, hyperkalemia) between BID/QDay groups were analyzed within dosing cohorts using inverse propensity of treatment-weighted regression models. Of 11,210 and 6,051 patients who met all criteria for lisinopril and losartan, 784 (7.0%) and 453 (7.5%) were taking BID, respectively. BID patients were older and had higher comorbidity and medication burdens. There were no differences in systolic/diastolic BP between BID and QDay, with absolute differences in mean systolic BP ranging from -1.8 to 0.7 mmHg and diastolic BP ranging from -1.1 to 0.1 mmHg (all 95% confidence intervals [CI] cross 0). Lisinopril 10mg BID was associated with an increased odds of angioedema compared to lisinopril 20mg QDay (odds ratio 2.27, 95%CI 1.13-4.58)., Conclusions: Adjusted models do not support improved effectiveness or safety of BID lisinopril and losartan., Competing Interests: The authors have declared that no competing interests exist.

Importance: Genotype-guided prescribing in pediatrics could prevent adverse drug reactions and improve therapeutic response. Clinical pharmacogenetic implementation guidelines are available for many medications commonly prescribed to children. Frequencies of medication prescription and actionable genotypes (genotypes where a prescribing change may be indicated) inform the potential value of pharmacogenetic implementation., Objective: To assess potential opportunities for genotype-guided prescribing in pediatric populations among multiple health systems by examining the prevalence of prescriptions for each drug with the highest level of evidence (Clinical Pharmacogenetics Implementation Consortium level A) and estimating the prevalence of potential actionable prescribing decisions., Design, Setting, and Participants: This serial cross-sectional study of prescribing prevalences in 16 health systems included electronic health records data from pediatric inpatient and outpatient encounters from January 1, 2011, to December 31, 2017. The health systems included academic medical centers with free-standing children's hospitals and community hospitals that were part of an adult health care system. Participants included approximately 2.9 million patients younger than 21 years observed per year. Data were analyzed from June 5, 2018, to April 14, 2020., Exposures: Prescription of 38 level A medications based on electronic health records., Main Outcomes and Measures: Annual prevalence of level A medication prescribing and estimated actionable exposures, calculated by combining estimated site-year prevalences across sites with each site weighted equally., Results: Data from approximately 2.9 million pediatric patients (median age, 8 [interquartile range, 2-16] years; 50.7% female, 62.3% White) were analyzed for a typical calendar year. The annual prescribing prevalence of at least 1 level A drug ranged from 7987 to 10 629 per 100 000 patients with increasing trends from 2011 to 2014. The most prescribed level A drug was the antiemetic ondansetron (annual prevalence of exposure, 8107 [95% CI, 8077-8137] per 100 000 children). Among commonly prescribed opioids, annual prevalence per 100 000 patients was 295 (95% CI, 273-317) for tramadol, 571 (95% CI, 557-586) for codeine, and 2116 (95% CI, 2097-2135) for oxycodone. The antidepressants citalopram, escitalopram, and amitriptyline were also commonly prescribed (annual prevalence, approximately 250 per 100 000 patients for each). Estimated prevalences of actionable exposures were highest for oxycodone and ondansetron (>300 per 100 000 patients annually). CYP2D6 and CYP2C19 substrates were more frequently prescribed than medications influenced by other genes., Conclusions and Relevance: These findings suggest that opportunities for pharmacogenetic implementation among pediatric patients in the US are abundant. As expected, the greatest opportunity exists with implementing CYP2D6 and CYP2C19 pharmacogenetic guidance for commonly prescribed antiemetics, analgesics, and antidepressants.

Background: Heart failure with reduced ejection fraction (HFrEF) benefits from initiation and intensification of multiple pharmacotherapies. Unfortunately, there are major gaps in the routine use of these drugs. Without novel approaches to improve prescribing, the cumulative benefits of HFrEF treatment will be largely unrealized. Direct-to-consumer marketing and shared decision making reflect a culture where patients are increasingly involved in treatment choices, creating opportunities for prescribing interventions that engage patients., Hypothesis: Encouraging patients to engage providers in HFrEF prescribing decisions will improve the use of guideline-directed medical therapies., Design: The Electronically delivered, Patient-activation tool for Intensification of Chronic medications for Heart Failure with reduced ejection fraction (EPIC-HF) trial randomizes patients with HFrEF to usual care versus patient-activation tools-a 3-minute video and 1-page checklist-delivered prior to cardiology clinic visits that encourage patients to work collaboratively with their clinicians to intensify HFrEF prescribing. The study assesses the effectiveness of the EPIC-HF intervention to improve guideline-directed medical therapy in the month after its delivery while using an implementation design to also understand the reach, adoption, implementation, and maintenance of this approach within the context of real-world care delivery. Study enrollment was completed in January 2020, with a total 305 patients. Baseline data revealed significant opportunities, with <1% of patients on optimal HFrEF medical therapy., Summary: The EPIC-HF trial assesses the implementation, effectiveness, and safety of patient engagement in HFrEF prescribing decisions. If successful, the tool can be easily disseminated and may inform similar interventions for other chronic conditions., (Copyright © 2020 Elsevier Inc. All rights reserved.)

Background: Clinical decision support (CDS) design best practices are intended to provide a narrative representation of factors that influence the success of CDS tools. However, they provide incomplete direction on evidence-based implementation principles., Objective: This study aims to describe an integrated approach toward applying an existing implementation science (IS) framework with CDS design best practices to improve the effectiveness, sustainability, and reproducibility of CDS implementations., Methods: We selected the Practical Robust Implementation and Sustainability Model (PRISM) IS framework. We identified areas where PRISM and CDS design best practices complemented each other and defined methods to address each. Lessons learned from applying these methods were then used to further refine the integrated approach., Results: Our integrated approach to applying PRISM with CDS design best practices consists of 5 key phases that iteratively interact and inform each other: multilevel stakeholder engagement, designing the CDS, design and usability testing, thoughtful deployment, and performance evaluation and maintenance. The approach is led by a dedicated implementation team that includes clinical informatics and analyst builder expertise., Conclusions: Integrating PRISM with CDS design best practices extends user-centered design and accounts for the multilevel, interacting, and dynamic factors that influence CDS implementation in health care. Integrating PRISM with CDS design best practices synthesizes the many known contextual factors that can influence the success of CDS tools, thereby enhancing the reproducibility and sustainability of CDS implementations. Others can adapt this approach to their situation to maximize and sustain CDS implementation success., (©Katy E Trinkley, Michael G Kahn, Tellen D Bennett, Russell E Glasgow, Heather Haugen, David P Kao, Miranda E Kroehl, Chen-Tan Lin, Daniel C Malone, Daniel D Matlock. Originally published in the Journal of Medical Internet Research (http://www.jmir.org), 29.10.2020.)

Use of machine learning (ML) in clinical research is growing steadily given the increasing availability of complex clinical data sets. ML presents important advantages in terms of predictive performance and identifying undiscovered subpopulations of patients with specific physiology and prognoses. Despite this popularity, many clinicians and researchers are not yet familiar with evaluating and interpreting ML analyses. Consequently, readers and peer-reviewers alike may either overestimate or underestimate the validity and credibility of an ML-based model. Conversely, ML experts without clinical experience may present details of the analysis that are too granular for a clinical readership to assess. Overwhelming evidence has shown poor reproducibility and reporting of ML models in clinical research suggesting the need for ML analyses to be presented in a clear, concise, and comprehensible manner to facilitate understanding and critical evaluation. We present a recommendation for transparent and structured reporting of ML analysis results specifically directed at clinical researchers. Furthermore, we provide a list of key reporting elements with examples that can be used as a template when preparing and submitting ML-based manuscripts for the same audience.

Using serial analysis of myocardial gene expression employing endomyocardial biopsy starting material in a dilated cardiomyopathy cohort, we show that mRNA expression of the severe acute respiratory syndrome-coronavirus-2 (SARS-CoV-2) cardiac myocyte receptor ACE2 is up-regulated with remodeling and with reverse remodeling down-regulates into the normal range. The proteases responsible for virus-cell membrane fusion were expressed but not regulated with remodeling. In addition, a new candidate for SARS-CoV-2 cell binding and entry was identified, the integrin encoded by ITGA5 . Up-regulation in ACE2 in remodeled left ventricles may explain worse outcomes in patients with coronavirus disease 2019 who have underlying myocardial disorders, and counteracting ACE2 up-regulation is a possible therapeutic approach to minimizing cardiac damage., (© 2020 The Authors.)

Purpose: Little is known about how many insured patients receive pharmacogenetic testing. We describe trends of single-gene pharmacogenetic testing in a US managed care population, and demographic and clinical characteristics of patients who received a test., Methods: We leveraged a random sample of nearly 11 million patients from a data set of paid medical and pharmacy claims to identify patients with at least one claim indicating receipt of at least one of these single-gene pharmacogenetic tests: CYP2C19, CYP2D6, CYP2C9, VKORC1, UGT1A1, and HLA class 1 typing., Results: From 1 January 2013 to 30 September 2017, 5712 patients received at least one pharmacogenetic test (55% female; mean age = 43 years). The median number of tests per patient was 3 (mean = 2.7, max = 12); 54% were processed through Managed Medicare/Medicaid, while 45% were processed through commercial insurance. The total number of pharmacogenetic tests received more than doubled from 2013 (n = 1955) to 2015 (n = 4192), then decreased slightly in 2016 (n = 3946). The most common test was CYP2C19 (n = 4719), and "long-term (current) use of other medications" was the most common diagnosis., Conclusion: Pharmacogenetic testing through patients' insurance was low, but more than doubled from 2013 to 2016. This study highlights the need to better understand utilization patterns and insurance coverage for pharmacogenetic tests.

Aims: The aim of this study is to use six previously described heart failure with preserved ejection fraction (HFpEF) phenotypes to describe differences in (i) the biological response to spironolactone, (ii) clinical endpoints, and (iii) patient-reported health status by HFpEF phenotype and treatment arm in the Treatment of Preserved Cardiac Function Heart Failure with an Aldosterone Antagonist Trial (TOPCAT)., Methods and Results: We analysed 1767 patients in TOPCAT from the Americas. Using 11 clinical variables, patients were classified according to six HFpEF phenotypes previously identified in the I-PRESERVE and CHARM-Preserved studies. Kansas City Cardiomyopathy Questionnaire (KCCQ) measured health status. All phenotypes showed increase in potassium with spironolactone, although only three phenotypes showed significant increase in creatinine, and two phenotypes showed significant decrease in systolic blood pressure. Rate of the TOPCAT primary outcome (cardiovascular death, aborted cardiac arrest, or heart failure hospitalization) differed by HFpEF phenotype (P < 0.001) but not by treatment arm within each HFpEF phenotype. Baseline KCCQ score differed by HFpEF phenotype (P < 0.001), although some phenotypes with poor health status had lower rates of the TOPCAT primary outcome, and some phenotypes with better health status had higher rates of the TOPCAT primary outcome. However, within 3/6 phenotypes, higher baseline KCCQ score was associated with lower risk of the TOPCAT primary outcome. Change in KCCQ scores at 4 and 12 months did not differ among HFpEF phenotypes overall or by treatment arm., Conclusions: Complex, data-driven HFpEF phenotypes differ according to biological response to spironolactone, baseline health status, and clinical endpoints. These differences may inform the design of targeted clinical trials focusing on improvement in outcomes most relevant for specific HFpEF phenotypes., (© 2020 The Authors. ESC Heart Failure published by John Wiley & Sons Ltd on behalf of European Society of Cardiology.)

Background: Elective percutaneous coronary interventions (PCI) are difficult to discriminate from non-elective PCI in administrative data due to non-specific encounter codes, limiting the ability to track outcomes, ensure appropriate medical management, and/or perform research on patients who undergo elective PCI. The objective of this study was to assess the abilities of several algorithms to identify elective PCI procedures using administrative data containing diagnostic, utilization, and/or procedural codes., Methods and Results: For this retrospective study, administrative databases in an integrated healthcare delivery system were queried between 1/1/2015 and 6/31/2016 to identify patients who had an encounter for a PCI. Using clinical criteria, each encounter was classified via chart review as a valid PCI, then as elective or non-elective. Cases were tested against nine pre-determined algorithms. Performance statistics (sensitivity, specificity, positive predictive value, and negative predictive value) and associated 95% confidence intervals (CI) were calculated. Of 521 PCI encounters reviewed, 497 were valid PCI, 93 of which were elective. An algorithm that excluded emergency room visit events had the highest sensitivity (97.9%, 95%CI 92.5%-99.7%) while an algorithm that included events occurring within 90 days of a cardiologist visit and coronary angiogram or stress test had the highest positive predictive value (62.2%, 95%CI 50.8%-72.7%)., Conclusions: Without an encounter code specific for elective PCI, an algorithm excluding procedures associated with an emergency room visit had the highest sensitivity to identify elective PCI. This offers a reasonable approach to identify elective PCI from administrative data., Competing Interests: The authors have declared that no competing interests exist.

Patients with congestive heart failure (CHF) require complex medical management across the continuum of care. Electronic health records (EHR) are currently used for traditional tasks of documentation, reviewing and managing test results, computerized order entry, and billing. Unfortunately many clinicians view EHR as merely digitized versions of paper charts, which create additional work and cognitive burden without improving quality or efficiency of care. In fact, EHR are revolutionizing the care of chronic diseases such as CHF. This review describes how appropriate use of technologies offered by EHR can help standardize CHF care, promote adherence to evidence-based guidelines, optimize workflow efficiency, improve performance metrics, and facilitate patient engagement. This review discusses a number of tools including documentation templates, telehealth and telemedicine, health information exchange, order sets, clinical decision support, registries, and analytics. Where available, evidence of their potential utility in management of CHF is presented. Together these EHR tools can also be used to enhance quality improvement, patient management, and clinical research as part of a learning health care system model. This review describes how existing EHR tools can support patients, cardiologists, and care teams to deliver consistent, high-quality, coordinated, patient-centered, and guideline-concordant care of CHF., (Copyright © 2020 American College of Cardiology Foundation. Published by Elsevier Inc. All rights reserved.)

The development of treatments for heart failure (HF) is challenged by burdensome clinical trials. Reducing the need for extensive data collection and increasing opportunities for data compatibility between trials may improve efficiency and reduce resource burden. The Heart Failure Collaboratory (HFC) multi-stakeholder consortium sought to create a lean case report form (CRF) for use in HF clinical trials evaluating cardiac devices. The HFC convened patients, clinicians, clinical researchers, the U.S. Food and Drug Administration (FDA), payers, industry partners, and statisticians to create a consensus core CRF. Eight recent clinical trial CRFs for the treatment of HF from 6 industry partners were analyzed. All CRF elements were systematically reviewed. Those elements deemed critical for data collection in HF clinical trials were used to construct the final, harmonized CRF. The original CRFs included 176 distinct data items covering demographics, vital signs, physical examination, medical history, laboratory and imaging testing, device therapy, medications, functional and quality of life assessment, and outcome events. The resulting, minimally inclusive CRF device contains 75 baseline data items and 6 events, with separate modular additions that can be used depending on the additional detail required for a particular intervention. The consensus electronic form is now freely available for use in clinical trials. Creation of a core CRF is important to improve clinical trial efficiency in HF device development in the United States. This living document intends to reduce clinical trial administrative burden, increase evidence integrity, and improve comparability of clinical data between trials., (Copyright © 2019 The Authors. Published by Elsevier Inc. All rights reserved.)

Objectives: To investigate the biologic relevance of cross-platform concordant changes in gene expression in intact human failing/hypertrophied ventricular myocardium undergoing reverse remodeling., Background: Information is lacking on genes and networks involved in remodeled human LVs, and in the associated investigative best practices., Methods: We measured mRNA expression in ventricular septal endomyocardial biopsies from 47 idiopathic dilated cardiomyopathy patients, at baseline and after 3-12 months of β-blocker treatment to effect left ventricular (LV) reverse remodeling as measured by ejection fraction (LVEF). Cross-platform gene expression change concordance was investigated in reverse remodeling Responders (R) and Nonresponders (NR) using 3 platforms (RT-qPCR, microarray, and RNA-Seq) and two cohorts (All 47 subjects (A-S) and a 12 patient "Super-Responder" (S-R) subset of A-S)., Results: For 50 prespecified candidate genes, in A-S mRNA expression 2 platform concordance (CcpT), but not single platform change, was directly related to reverse remodeling, indicating CcpT has biologic significance. Candidate genes yielded a CcpT (PCR/microarray) of 62% for Responder vs. Nonresponder (R/NR) change from baseline analysis in A-S, and ranged from 38% to 100% in S-R for PCR/microarray/RNA-Seq 2 platform comparisons. Global gene CcpT measured by microarray/RNA-Seq was less than for candidate genes, in S-R R/NR 17.5% vs. 38% (P = 0.036). For S-R global gene expression changes, both cross-cohort concordance (CccT) and CcpT yielded markedly greater values for an R/NR vs. an R-only analysis (by 22 fold for CccT and 7 fold for CcpT). Pathway analysis of concordant global changes for R/NR in S-R revealed signals for downregulation of multiple phosphoinositide canonical pathways, plus expected evidence of a β1-adrenergic receptor gene network including enhanced Ca2+ signaling., Conclusions: Two-platform concordant change in candidate gene expression is associated with LV biologic effects, and global expression concordant changes are best identified in an R/NR design that can yield novel information., Competing Interests: This work was funded in part by industry sponsored research awards from GlaxoSmithKline, AstraZeneca and ARCA biopharma (awarded to MRB). The industry funding was unrestricted and without any stipulations, other than receipt of reports of the findings in the form of scientific presentations or manuscripts. MRB was but is no longer a consultant for GlaxoSmithKline, and MRB and IAC are fractional employees of ARCA biopharma. MRB is a founder, officer and director of ARCA biopharma, and none of the information in this manuscript is related to any intellectual property licensed to or being developed by ARCA as the study was conceived, executed and analyzed within MRB’s academic functions and responsibilities. This does not alter our adherence to PLOS ONE policies on sharing data and materials.

Objectives: The purpose of this study was to compare the effectiveness of bucindolol with that of metoprolol succinate for the maintenance of sinus rhythm in a genetically defined heart failure (HF) population with atrial fibrillation (AF)., Background: Bucindolol is a beta-blocker whose unique pharmacologic properties provide greater benefit in HF patients with reduced ejection fraction (HFrEF) who have the beta 1 -adrenergic receptor (ADRB1) Arg389Arg genotype., Methods: A total of 267 HFrEF patients with a left ventricular ejection fraction (LVEF) <0.50, symptomatic AF, and the ADRB1 Arg389Arg genotype were randomized 1:1 to receive bucindolol or metoprolol therapy and were up-titrated to target doses. The primary endpoint of AF or atrial flutter (AFL) or all-cause mortality (ACM) was evaluated by electrocardiogram (ECG) during a 24-week period., Results: The hazard ratio (HR) for the primary endpoint was 1.01 (95% confidence interval [CI]: 0.71 to 1.42), but trends for bucindolol benefit were observed in several subgroups. Precision therapeutic phenotyping revealed that a differential response to bucindolol was associated with the interval of time from the initial diagnoses of AF and HF to randomization and with the onset of AF relative to that of the initial HF diagnosis. In a cohort whose first AF and HF diagnoses were <12 years prior to randomization, in which AF onset did not precede HF by more than 2 years (n = 196), the HR was 0.54 (95% CI: 0.33 to 0.87; p = 0.011)., Conclusions: Pharmacogenetically guided bucindolol therapy did not reduce the recurrence of AF/AFL or ACM compared to that of metoprolol therapy in HFrEF patients, but populations were identified who merited further investigation in future phase 3 trials., (Copyright © 2019. Published by Elsevier Inc.)

Background: To improve user-centred design efforts and efficiency; there is a need to disseminate information on modern day clinician preferences for technologies such as computerised clinical decision support (CDS)., Objective: To describe clinician perceptions regarding beneficial features of CDS for chronic medications in primary care., Methods: This study included focus groups and clinicians individually describing their ideal CDS. Three focus groups were conducted including prescribing clinicians from a variety of disciplines. Outcome measures included identification of favourable features and unintended consequences of CDS for chronic medication management in primary care. We transcribed recordings, performed thematic qualitative analysis and generated counts when possible., Results: There were 21 participants who identified four categories of beneficial CDS features during the group discussion: non-interruptive alerts, clinically relevant and customisable support, presentation of pertinent clinical information and optimises workflow. Non-interruptive alerts were broadly defined as passive alerts that a user chooses to review, whereas interruptive were active or disruptive alerts that interrupted workflow and one is forced to review before completing a task. The CDS features identified in the individual descriptions were consistent with the focus group discussion, with the exception of non-interruptive alerts. In the individual descriptions, 12 clinicians preferred interruptive CDS compared with seven clinicians describing non-interruptive CDS., Conclusion: Clinicians identified CDS for chronic medications beneficial when they are clinically relevant and customisable, present pertinent clinical information (eg, labs, vitals) and improve their workflow. Although clinicians preferred passive, non-interruptive alerts, most acknowledged that these may not be widely seen and may be less effective. These features align with literature describing best practices in CDS design and emphasise those features clinicians prioritise, which should be considered when designing CDS for medication management in primary care. These findings highlight the disparity between the current state of CDS design and clinician-stated design features associated with beneficial CDS., (© Author(s) (or their employer(s)) 2019. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ.)

Objectives: This study sought to investigate sex differences in outcomes and responses to spironolactone in patients with heart failure with preserved ejection fraction (HFpEF)., Background: HFpEF affects women more frequently than men. Sex differences in responses to effects of mineralocorticoid antagonists have not been reported., Methods: This was an exploratory, post hoc, non-pre-specified analysis of the TOPCAT (Aldosterone Antagonist Therapy for Adults With Heart Failure and Preserved Systolic Function) trial. Subjects with symptomatic HF and a left ventricular ejection fraction ≥45% were randomized to spironolactone or placebo therapy. Subjects enrolled from the Americas were analyzed. The primary outcome was a composite of cardiovascular (CV) death, cardiac arrest, or HF hospitalization. Secondary outcomes included all-cause mortality, CV, and non-CV mortality and CV, HF, and non-CV hospitalization. Sex differences in outcomes and treatment effects were determined using time-to-event analysis., Results: In total, 882 of 1,767 subjects (49.9%) were women. Women were older with fewer comorbidities but worse patient-reported outcomes. There were no sex differences in outcomes in the placebo arm or in response to spironolactone for the primary outcome or its components. Spironolactone therapy was associated with reduced all-cause mortality in women (hazard ratio: 0.66; p = 0.01) but not in men (p interaction  = 0.02)., Conclusions: In TOPCAT, women and men presented with different clinical profiles and similar clinical outcomes. The interaction between spironolactone and sex in TOPCAT overall and in the present analysis was nonsignificant for the primary outcome, but there was a reduction in all-cause mortality associated with spironolactone therapy in women, with a significant interaction between sex and treatment arm. Prospective evaluation is needed to determine whether spironolactone therapy may be effective for treatment of HFpEF in women. (Aldosterone Antagonist Therapy for Adults With Heart Failure and Preserved Systolic Function [TOPCAT]; NCT00094302)., (Copyright © 2019 American College of Cardiology Foundation. Published by Elsevier Inc. All rights reserved.)

Marijuana use is increasing worldwide, and it is ever more likely that patients presenting with acute myocardial infarctions (AMI) will be marijuana users. However, little is known about the impact of marijuana use on short-term outcomes following AMI. Accordingly, we compared in-hospital outcomes of AMI patients with reported marijuana use to those with no reported marijuana use. We hypothesized that marijuana use would be associated with increased risk of adverse outcomes in AMI patients. Hospital records from 8 states between 1994-2013 were screened for patients with a diagnosis of AMI. Clinical profiles and outcomes in patients with reported use of marijuana were compared to patients without reported marijuana use. Short-term outcomes were defined as adverse events that occurred during hospitalization for an admitting diagnosis of AMI. The composite primary outcome included death, intraaortic balloon pump placement, (IABP), mechanical ventilation, cardiac arrest, and shock. In total, 3,854 of 1,273,897 AMI patients reported use of marijuana. The marijuana cohort was younger than (47.2 vs. 57.2, respectively) and had less coronary artery disease than the non-marijuana cohort. In multivariable analysis including age, race and common cardiac risk factors, there was no association between marijuana use and the primary outcome (p = 0.53), but marijuana users were more likely to be placed on mechanical ventilation (OR (odds ratio) 1.19, p = 0.004). Interestingly, marijuana-using patients were significantly less likely to die (OR 0.79, p = 0.016), experience shock (OR 0.74, p = 0.001), or require an IABP (OR 0.80, p = 0.03) post AMI than patients with no reported marijuana use. These results suggest that, contrary to our hypothesis, marijuana use was not associated with increased risk of adverse short-term outcomes following AMI. Furthermore, marijuana use was associated with decreased in-hospital mortality post-AMI., Competing Interests: The authors have declared that no competing interests exist.

Objective: Women with pregnancies complicated by hypertensive disorders of pregnancy (HDP) have increased long-term cardiovascular (CV) risk. We sought to determine if they demonstrate increased short-term CV risk., Methods: Using administrative records, all hospital-based deliveries in Florida from 2004 to 2010 and subsequent readmission to any Florida hospital within 3 years of index delivery were identified. Deliveries and clinical diagnoses were determined using International Classification of Diseases, Ninth Revision, Clinical Modification codes. HDP included pregnancies complicated by gestational hypertension, pre-eclampsia or eclampsia. Outcomes were CV readmission (acute myocardial infarction, stroke or heart failure), non-CV readmission and any readmission within 3 years of delivery excluding subsequent deliveries. Associations were determined using multivariate logistic regression., Results: Among 1 452 926 records from delivering mothers of singleton infants (mean age 27.2±6.2 years; 52% white, 23% African American (AA), 18% Hispanic), there were 4054 CV and 259 252 non-CV readmissions. Women with HDP had higher CV readmission rates (6.4 vs 2.5/1000 deliveries; P<0.001). AA women had higher rates of CV readmission than whites or Hispanics (6.8 vs 1.7 vs 1.0/1000 deliveries, respectively; P<0.001). Women with HDP had higher multivariate risk of CV readmission (OR 2.41; 95% CI 2.08 to 2.80) and any readmission (OR 1.13; 95% CI 1.10 to 1.15). Compared with whites, AA women had higher risk for CV readmission (OR 3.60; 95% CI 3.32 to 3.90) after adjustment for HDP., Conclusion: Women with HDP had twice the risk of CV readmission within 3 years of delivery, with higher rates among AA women. More work is needed to explore preventive strategies for HDP-associated events., Competing Interests: Competing interests: None declared., (© Article author(s) (or their employer(s) unless otherwise stated in the text of the article) 2018. All rights reserved. No commercial use is permitted unless otherwise expressly granted.)

Myocardial H 2 receptor activation contributes to heart failure (HF) in preclinical models, and H 2 receptor antagonists are associated with decreased HF incidence. This study evaluated whether H 2 histamine receptor (HRH2) single nucleotide polymorphisms (SNPs) are associated with HF incidence and whether myocardial transcript abundance is associated with HF recovery. The association of SNPs in HRH2 with incident HF was characterized using Cox proportional hazards regression among participants in the Multi-Ethnic Study of Atherosclerosis. Differences in myocardial HRH2 transcripts were characterized in participants with dilated cardiomyopathy comparing 6 "super-responders" with 6 nonresponders to β blockade in the Beta-Blocker Effect on Remodeling and Gene Expression Trial. In MESA, no candidate SNP was associated with HF in black, Hispanic, or white participants. The rs2241562 minor allele was present only in Chinese participants and the adjusted HF hazard among those with 1 or more copies of this allele was 3.7, 95% confidence interval 1.0 to 13.4. In BORG, super-responders to β blockade had higher levels of myocardial HRH2 transcript at baseline compared with nonresponders (fragments per kilobase per transcript per million mapped reads: Variant 2, 5.5 ± 1.1 compared with 3.2 ± 0.8 in nonresponders, p = 0.002; Variant 1 + 2, 32.1 ± 7.4 compared with 23.3 ± 4.2 in nonresponders, p = 0.04). In conclusion, the presence of a minor allele at rs2241562 was associated with increased HF incidence in Chinese participants. Differences in myocardial HRH2 transcript abundance were seen in participants with dilated cardiomyopathy who responded to β blockade. These observations support the hypothesis that HRH2 is involved in the pathogenesis of HF., (Copyright © 2017 Elsevier Inc. All rights reserved.)

Diagnosis, prognosis, treatment, and development of new therapies for diseases or syndromes depend on a reliable means of identifying phenotypes associated with distinct predictive probabilities for these various objectives. Left ventricular ejection fraction (LVEF) provides the current basis for combined functional and structural phenotyping in heart failure by classifying patients as those with heart failure with reduced ejection fraction (HFrEF) and those with heart failure with preserved ejection fraction (HFpEF). Recently the utility of LVEF as the major phenotypic determinant of heart failure has been challenged based on its load dependency and measurement variability. We review the history of the development and adoption of LVEF as a critical measurement of LV function and structure and demonstrate that, in chronic heart failure, load dependency is not an important practical issue, and we provide hemodynamic and molecular biomarker evidence that LVEF is superior or equal to more unwieldy methods of identifying phenotypes of ventricular remodeling. We conclude that, because it reliably measures both left ventricular function and structure, LVEF remains the best current method of assessing pathologic remodeling in heart failure in both individual clinical and multicenter group settings. Because of the present and future importance of left ventricular phenotyping in heart failure, LVEF should be measured by using the most accurate technology and methodologic refinements available, and improved characterization methods should continue to be sought., (Copyright © 2017 American College of Cardiology Foundation. Published by Elsevier Inc. All rights reserved.)

Little is known about genetics of heart failure with preserved ejection fraction (HFpEF) in part because of the many comorbidities in this population. To identify single-nucleotide polymorphisms (SNPs) associated with HFpEF, we analyzed phenotypic and genotypic data from the Cardiovascular Health Study, which profiled patients using a 50,000 SNP array. Results were explored using novel SNP- and gene-centric tools. We performed analyses to determine whether some SNPs were relevant only in certain phenotypes. Among 3804 patients, 7 clinical factors and 9 SNPs were significantly associated with HFpEF; the most notable of which was rs6996224, a SNP associated with transforming growth factor-beta receptor 3. Most SNPs were associated with HFpEF only in the absence of a clinical predictor. Significant SNPs represented genes involved in myocyte proliferation, transforming growth factor-beta/erbB signaling, and extracellular matrix formation. These findings suggest that genetic factors may be more important in some phenotypes than others.

The learning healthcare system uses health information technology and the health data infrastructure to apply scientific evidence at the point of clinical care while simultaneously collecting insights from that care to promote innovation in optimal healthcare delivery and to fuel new scientific discovery. To achieve these goals, the learning healthcare system requires systematic redesign of the current healthcare system, focusing on 4 major domains: science and informatics, patient-clinician partnerships, incentives, and development of a continuous learning culture. This scientific statement provides an overview of how these learning healthcare system domains can be realized in cardiovascular disease care. Current cardiovascular disease care innovations in informatics, data uses, patient engagement, continuous learning culture, and incentives are profiled. In addition, recommendations for next steps for the development of a learning healthcare system in cardiovascular care are presented., (© 2017 American Heart Association, Inc.)

Background: In dilated cardiomyopathies (DCMs) changes in expression of protein-coding genes are associated with reverse remodeling, and these changes can be regulated by microRNAs (miRs). We tested the general hypothesis that dynamic changes in myocardial miR expression are predictive of β-blocker-associated reverse remodeling., Methods: Forty-three idiopathic DCM patients (mean left ventricular ejection fraction 0.24 ± 0.09) were treated with β-blockers. Serial ventriculography and endomyocardial biopsies were performed at baseline, and after 3 and 12 months of treatment. Changes in RT-PCR (candidate miRs) or array-measured miRs were compared based on the presence (R) or absence (NR) of a reverse-remodeling response, and a miR-mRNA-function pathway analysis (PA) was performed., Results: At 3 months, 2 candidate miRs were selectively changed in Rs, decreases in miR-208a-3p and miR-591. PA revealed changes in miR-mRNA interactions predictive of decreased apoptosis and myocardial cell death. At 12 months, 5 miRs exhibited selective changes in Rs (decreases in miR-208a-3p, -208b-3p, 21-5p, and 199a-5p; increase in miR-1-3p). PA predicted decreases in apoptosis, cardiac myocyte cell death, hypertrophy, and heart failure, with increases in contractile and overall cardiac functions., Conclusions: In DCMs, myocardial miRs predict the time-dependent reverse-remodeling response to β-blocker treatment, and likely regulate the expression of remodeling-associated miRs., Trial Registration: ClinicalTrials.gov NCT01798992., Funding: NIH 2R01 HL48013, 1R01 HL71118 (Bristow, PI); sponsored research agreements from Glaxo-SmithKline and AstraZeneca (Bristow, PI); NIH P20 HL101435 (Lowes, Port multi-PD/PI); sponsored research agreement from Miragen Therapeutics (Port, PI)., Competing Interests: C.C. Sucharov, J.D. Port, and M.R. Bristow have stock (each less than 0.1% of total outstanding shares) in Miragen Therapeutics, and M.R. Bristow is member of the Miragen Scientific Advisory Board.