Implementation of clopidogrel pharmacogenetic clinical decision support for a preemptive return of results program.

DISCLAIMER: In an effort to expedite the publication of articles, AJHP is posting manuscripts online as soon as possible after acceptance. Accepted manuscripts have been peer-reviewed and copyedited, but are posted online before technical formatting and author proofing. These manuscripts are not the final version of record and will be replaced with the final article (formatted per AJHP style and proofed by the authors) at a later time. 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 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.

Building a vertically integrated genomic learning health system: The biobank at the Colorado Center for Personalized Medicine.

Precision medicine initiatives across the globe have led to a revolution of repositories linking large-scale genomic data with electronic health records, enabling genomic analyses across the entire phenome. Many of these initiatives focus solely on research insights, leading to limited direct benefit to patients. We describe the biobank at the Colorado Center for Personalized Medicine (CCPM Biobank) that was jointly developed by the University of Colorado Anschutz Medical Campus and UCHealth to serve as a unique, dual-purpose research and clinical resource accelerating personalized medicine. This living resource currently has more than 200,000 participants with ongoing recruitment. We highlight the clinical, laboratory, regulatory, and HIPAA-compliant informatics infrastructure along with our stakeholder engagement, consent, recontact, and participant engagement strategies. We characterize aspects of genetic and geographic diversity unique to the Rocky Mountain region, the primary catchment area for CCPM Biobank participants. We leverage linked health and demographic information of the CCPM Biobank participant population to demonstrate the utility of the CCPM Biobank to replicate complex trait associations in the first 33,674 genotyped individuals across multiple disease domains. Finally, we describe our current efforts toward return of clinical genetic test results, including high-impact pathogenic variants and pharmacogenetic information, and our broader goals as the CCPM Biobank continues to grow. Bringing clinical and research interests together fosters unique clinical and translational questions that can be addressed from the large EHR-linked CCPM Biobank resource within a HIPAA- and CLIA-certified environment.

Patient-Level Exposure to Actionable Pharmacogenomic Medications in a Nationally Representative Insurance Claims Database.

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.

Sustained Effect of Clinical Decision Support for Heart Failure: A Natural Experiment Using Implementation Science.

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 ß 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.

An extensive ß1-adrenergic receptor gene signaling network regulates molecular remodeling in dilated cardiomyopathies.

We investigated the extent, biologic characterization, phenotypic specificity, and possible regulation of a ß1-adrenergic receptor-linked (ß1-AR-linked) gene signaling network (ß1-GSN) involved in left ventricular (LV) eccentric pathologic remodeling. A 430-member ß1-GSN was identified by mRNA expression in transgenic mice overexpressing human ß1-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 ß1-GSN categories with expression from 19,243 nonnetwork genes, phenotypic selection for major ß1-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 ß1-GSN members. We conclude that an extensive 430-member gene network downstream from the ß1-AR is involved in pathologic ventricular remodeling, with metabolic genes as the most prevalent category.

A machine learning evaluation of patient characteristics associated with prescribing of guideline-directed medical therapy for heart failure.

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.

Ventricular Arrhythmias Associated With Over-the-Counter and Recreational Opioids.

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.

Clinical outcomes of cemented vs. uncemented reverse total shoulder arthroplasty for proximal humerus fractures: a systematic review.

BACKGROUND: Reverse total shoulder arthroplasty is an established treatment method for comminuted proximal humerus fractures. Both cemented and uncemented techniques exist, with uncemented reverse total shoulder offering many theoretical advantages, including improved biologic fixation, absence of cement related complications, and ease of revision if necessary. There are few studies comparing the outcomes of the two techniques. METHODS: The study was performed in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) statement. A search for studies assessing clinical outcomes of reverse total shoulder arthroplasty for proximal humerus fractures was performed of PubMed, Embase, Web of Science, and Cochrane Library. Main outcomes included Constant Score (CS), American Shoulder and Elbow Surgeons (ASES) score, and complication rate. Inclusion criteria were as follows: indication for arthroplasty was fracture; minimum one year follow up; article in English. Exclusion criteria were as follows: review articles; biomechanical or cadaver studies. Quality analysis was performed using the Cochrane Risk of Bias tool (RoB 2) and the Risk of Bias in Non-randomized Studies-of Interventions (ROBINS-I) tool. RESULTS: A total of 682 studies were identified through the initial search, with 36 studies meeting all inclusion criteria. There were 24 studies investigating cemented technique, 10 studies examining uncemented technique, and two studies involving both techniques. There was no difference in mean follow up between patients receiving a cemented vs. uncemented rTSA (32.3 months vs. 30.6 months, p = 0.06). Patients who received a cemented rTSA had a significantly higher Constant-Murley score than those who received an uncemented rTSA (59.4 vs 55.9, p < .001). There was no difference between the two groups when comparing ASES Scores (77.5 vs 78.6, p = 0.54) and overall complication rates (11.1% vs 11.8%, p = 0.23). CONCLUSION: Both cemented and uncemented rTSA are both valid options for treating acute proximal humerus fractures. Cemented rTSA may portend slightly improved clinical outcomes with similar overall complication rates compared to uncemented rTSA for proximal humerus fractures.

Clinical Outcomes are Similar Between Graft Types Used in Chronic Patellar Tendon Reconstruction: A Systematic Review.

Purpose: To compare clinical outcomes between graft types and techniques used to repair chronic patellar tendon injuries to help surgeons make evidence-based decisions. Methods: Medline, Embase, and Cochrane libraries were searched through January 2021, according to Preferred Reporting Items for Systematic Reviews and Meta-analysis (PRISMA) guidelines. Inclusion criteria were surgical treatment of chronic patellar tendon injury (defined as >6 weeks old), article available in English, and human subjects, minimum 1-year follow-up, and level of evidence I-IV. Studies describing chronic patellar tendon ruptures in the setting of total knee arthroplasty were excluded. Study quality was assessed using the Joanna Briggs Institute Critical Appraisal tools for case reports and case series. Results: A total of 642 studies were identified through the initial search with 9 studies meeting all inclusion criteria. All studies included were case series encompassing 96 patients with follow-up ranging from 21 months to 7.2 years. Reconstruction techniques included the use of semitendinosus and/or gracilis tendon(s), Achilles tendon, bone-patellar tendon-bone (BTB), or direct repair. The most common graft choice was semitendinosus and/or gracilis tendon(s). Each reconstruction method yielded improvement in respect to range of motion (ROM), extensor lag, quadriceps strength, and patient-reported outcome measures (PROMs). Commonly reported complications were pain and numbness with only one reported instance of graft failure. Conclusions: In this study, we found that all reconstructive methods described in the literature can produce satisfactory outcomes with improved function, strength, and minimal complications after chronic patellar tendon ruptures. Because of study heterogeneity and low levels of evidence, consensus cannot be reached on a single superior reconstruction method. Level of Evidence: Level IV, systematic review of level IV studies.

Machine Learning-Based Models Incorporating Social Determinants of Health vs Traditional Models for Predicting In-Hospital Mortality in Patients With Heart Failure.

Importance: Traditional models for predicting in-hospital mortality for patients with heart failure (HF) have used logistic regression and do not account for social determinants of health (SDOH). Objective: To develop and validate novel machine learning (ML) models for HF mortality that incorporate SDOH. Design, Setting, and Participants: This retrospective study used the data from the Get With The Guidelines-Heart Failure (GWTG-HF) registry to identify HF hospitalizations between January 1, 2010, and December 31, 2020. The study included patients with acute decompensated HF who were hospitalized at the GWTG-HF participating centers during the study period. Data analysis was performed January 6, 2021, to April 26, 2022. External validation was performed in the hospitalization cohort from the Atherosclerosis Risk in Communities (ARIC) study between 2005 and 2014. Main Outcomes and Measures: Random forest-based ML approaches were used to develop race-specific and race-agnostic models for predicting in-hospital mortality. Performance was assessed using C index (discrimination), regression slopes for observed vs predicted mortality rates (calibration), and decision curves for prognostic utility. Results: The training data set included 123 634 hospitalized patients with HF who were enrolled in the GWTG-HF registry (mean [SD] age, 71 [13] years; 58 356 [47.2%] female individuals; 65 278 [52.8%] male individuals. Patients were analyzed in 2 categories: Black (23 453 [19.0%]) and non-Black (2121 [2.1%] Asian; 91 154 [91.0%] White, and 6906 [6.9%] other race and ethnicity). The ML models demonstrated excellent performance in the internal testing subset (n = 82 420) (C statistic, 0.81 for Black patients and 0.82 for non-Black patients) and in the real-world-like cohort with less than 50% missingness on covariates (n = 553 506; C statistic, 0.74 for Black patients and 0.75 for non-Black patients). In the external validation cohort (ARIC registry; n = 1205 Black patients and 2264 non-Black patients), ML models demonstrated high discrimination and adequate calibration (C statistic, 0.79 and 0.80, respectively). Furthermore, the performance of the ML models was superior to the traditional GWTG-HF risk score model (C index, 0.69 for both race groups) and other rederived logistic regression models using race as a covariate. The performance of the ML models was identical using the race-specific and race-agnostic approaches in the GWTG-HF and external validation cohorts. In the GWTG-HF cohort, the addition of zip code-level SDOH parameters to the ML model with clinical covariates only was associated with better discrimination, prognostic utility (assessed using decision curves), and model reclassification metrics in Black patients (net reclassification improvement, 0.22 [95% CI, 0.14-0.30]; P < .001) but not in non-Black patients. Conclusions and Relevance: ML models for HF mortality demonstrated superior performance to the traditional and rederived logistic regressions models using race as a covariate. The addition of SDOH parameters improved the prognostic utility of prediction models in Black patients but not non-Black patients in the GWTG-HF registry.

A Systematic Review on the Effect of Common Medications on Platelet Count and Function: Which Medications Should Be Stopped Before Getting a Platelet-Rich Plasma Injection?

Background: Platelet-rich plasma (PRP) exerts its effect through the release of growth factors and cytokines from the platelet concentrate. Certain medications may affect platelet count or function, resulting in decreased efficacy of PRP injections. Purpose: To systematically review the literature regarding common medications and their effects on platelets to establish guidelines for which medications should be stopped before obtaining a PRP injection. Study Design: Systematic review; Level of evidence, 2. Methods: This review was performed in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) statement. A search for studies assessing the effect of common medications on platelet count or platelet function was performed of the PubMed, Cochrane Library, Web of Science, and OpenGrey databases. Inclusion criteria were as follows: drug studied was aspirin, acetaminophen, a nonsteroidal anti-inflammatory drug (NSAID), a statin, or gabapentin; human participants; and article in the English language. Risk of bias was assessed using the Cochrane Risk of Bias tool and the Risk of Bias in Non-randomised Studies-of Interventions tool. Results: A total of 1711 studies were identified through the initial search, with 20 studies meeting all inclusion criteria. No studies involving gabapentin met all inclusion criteria. Patients treated with aspirin (268 patients) or acetaminophen (13 patients) showed a significant decrease in platelet aggregation. Statin therapy (73 patients) did not result in a significant decrease in platelet aggregation. Patients who took NSAIDs (172 patients) demonstrated significantly decreased platelet aggregation only when treated with nonselective formulations. Those treated with cyclooxygenase (COX)-2-selective NSAIDs showed no significant difference in platelet aggregation. Treatment with aspirin, acetaminophen, statins, or NSAIDs did not lead to a significant decrease in platelet count. Conclusion: Aspirin, acetaminophen, and nonselective NSAIDs should be considered for suspension before a PRP injection because of their potential to diminish the effects of the injection. COX-2-selective NSAIDs and statins do not need to be withheld before a PRP injection.

COVID-19 Surveillance in the Biobank at the Colorado Center for Personalized Medicine: Observational Study.

BACKGROUND: Characterizing the experience and impact of the COVID-19 pandemic among various populations remains challenging due to the limitations inherent in common data sources, such as electronic health records (EHRs) or cross-sectional surveys. OBJECTIVE: This study aims to describe testing behaviors, symptoms, impact, vaccination status, and case ascertainment during the COVID-19 pandemic using integrated data sources. METHODS: In summer 2020 and 2021, we surveyed participants enrolled in the Biobank at the Colorado Center for Personalized Medicine (CCPM; N=180,599) about their experience with COVID-19. The prevalence of testing, symptoms, and impacts of COVID-19 on employment, family life, and physical and mental health were calculated overall and by demographic categories. Survey respondents who reported receiving a positive COVID-19 test result were considered a "confirmed case" of COVID-19. Using EHRs, we compared COVID-19 case ascertainment and characteristics in EHRs versus the survey. Positive cases were identified in EHRs using the International Statistical Classification of Diseases, 10th revision (ICD-10) diagnosis codes, health care encounter types, and encounter primary diagnoses. RESULTS: Of the 25,063 (13.9%) survey respondents, 10,661 (42.5%) had been tested for COVID-19, and of those, 1366 (12.8%) tested positive. Nearly half of those tested had symptoms or had been exposed to someone who was infected. Young adults (18-29 years) and Hispanics were more likely to have positive tests compared to older adults and persons of other racial/ethnic groups. Mental health (n=13,688, 54.6%) and family life (n=12,233, 48.8%) were most negatively affected by the pandemic and more so among younger groups and women; negative impacts on employment were more commonly reported among Black respondents. Of the 10,249 individuals who responded to vaccination questions from version 2 of the survey (summer 2021), 9770 (95.3%) had received the vaccine. After integration with EHR data up to the time of the survey completion, 1006 (4%) of the survey respondents had a discordant COVID-19 case status between EHRs and the survey. Using all longitudinal EHR and survey data, we identified 11,472 (6.4%) COVID-19-positive cases among Biobank participants. In comparison to COVID-19 cases identified through the survey, EHR-identified cases were younger and more likely to be Hispanic. CONCLUSIONS: We found that the COVID-19 pandemic has had far-reaching and varying effects among our Biobank participants. Integrated data assets, such as the Biobank at the CCPM, are key resources for population health monitoring in response to public health emergencies, such as the COVID-19 pandemic.

Pharmacogenetic testing among patients with depression in a US managed care population.

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.

Electronic Health Records and Heart Failure.

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.

Heart rate as an early predictor of severe cardiomyopathy and increased mortality in peripartum cardiomyopathy.

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.

Use of Actigraphy (Wearable Digital Sensors to Monitor Activity) in Heart Failure Randomized Clinical Trials: A Scoping Review.

BACKGROUND: Actigraphy-based measurements of physiologic parameters may enable design of patient-centric heart failure (HF) clinical trials. Recently, the Heart Failure Collaboratory focused on recommendations for meaningful change and use of actigraphy as an end point in HF clinical trials. We aimed to evaluate randomized controlled trials (RCTs) that have quantified the impact of HF interventions using actigraphy. METHODS: Using a scoping review strategy, we evaluated the use of actigraphy in HF RCTs. Studies were identified through electronic searches of Embase, OVID Medline, PubMed, and Cochrane Review. Data on trial characteristics and results were collected. RESULTS: We identified 11 RCTs with a total of 1,455 participants. The risk of bias across the included trials was high overall. All trials had the primary outcomes reflecting measures of either physical activity (n = 8), sleep (n = 2), or both (n = 1). Five trials evaluated response to pharmacologic therapies compared with placebo, 3 evaluated physical activity interventions, 2 evaluated group or cognitive therapy, and 1 evaluated sleep-ventilation strategy. Sample sizes ranged from 30 to 619 participants. There was significant heterogeneity relating to device type, body placement site, and handling of missing actigraphy data. Duration of monitoring ranged from 48 hours to 12 weeks. None of the studies evaluating pharmacologic therapies (n = 5) demonstrated a significant improvement of actigraphy-based primary end point measurements. CONCLUSIONS: There is significant heterogeneity in the use, methodology, and results of actigraphy-based HF RCTs. Our results highlight the need to develop, standardize, and validate actigraphy-specific outcomes for use in HF clinical trials.

The Addition of a Defibrillator to Resynchronization Therapy Decreases Mortality in Patients With Nonischemic Cardiomyopathy.

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 (pinteraction = 0.015 adjusted; pinteraction = 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.

Real-time electronic health record mortality prediction during the COVID-19 pandemic: a prospective cohort study.

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.