Experience With Hydroxychloroquine and Azithromycin in the Coronavirus Disease 2019 Pandemic: Implications for QT Interval Monitoring.

Background Despite a lack of clinical evidence, hydroxychloroquine and azithromycin are being administered widely to patients with verified or suspected coronavirus disease 2019 (COVID-19). Both drugs may increase risk of lethal arrhythmias associated with QT interval prolongation. Methods and Results We analyzed a case series of COVID-19-positive/suspected patients admitted between February 1, 2020, and April 4, 2020, who were treated with azithromycin, hydroxychloroquine, or a combination of both drugs. We evaluated baseline and postmedication QT interval (corrected QT interval [QTc]; Bazett) using 12-lead ECGs. Critical QTc prolongation was defined as follows: (1) maximum QTc ≥500 ms (if QRS <120 ms) or QTc ≥550 ms (if QRS ≥120 ms) and (2) QTc increase of ≥60 ms. Tisdale score and Elixhauser comorbidity index were calculated. Of 490 COVID-19-positive/suspected patients, 314 (64%) received either/both drugs and 98 (73 COVID-19 positive and 25 suspected) met study criteria (age, 62±17 years; 61% men). Azithromycin was prescribed in 28%, hydroxychloroquine in 10%, and both in 62%. Baseline mean QTc was 448±29 ms and increased to 459±36 ms (P=0.005) with medications. Significant prolongation was observed only in men (18±43 ms versus -0.2±28 ms in women; P=0.02). A total of 12% of patients reached critical QTc prolongation. Changes in QTc were highest with the combination compared with either drug, with much greater prolongation with combination versus azithromycin (17±39 ms versus 0.5±40 ms; P=0.07). No patients manifested torsades de pointes. Conclusions Overall, 12% of patients manifested critical QTc prolongation, and the combination caused greater prolongation than either drug alone. The balance between uncertain benefit and potential risk when treating COVID-19 patients should be carefully assessed.

Guidance for Rebooting Electrophysiology Through the COVID-19 Pandemic From the Heart Rhythm Society and the American Heart Association Electrocardiography and Arrhythmias Committee of the Council on Clinical Cardiology: Endorsed by the American College of Cardiology.

Coronavirus disease 2019 (COVID-19) has presented substantial challenges to patient care and impacted health care delivery, including cardiac electrophysiology practice throughout the globe. Based upon the undetermined course and regional variability of the pandemic, there is uncertainty as to how and when to resume and deliver electrophysiology services for arrhythmia patients. This joint document from representatives of the Heart Rhythm Society, American Heart Association, and American College of Cardiology seeks to provide guidance for clinicians and institutions reestablishing safe electrophysiological care. To achieve this aim, we address regional and local COVID-19 disease status, the role of viral screening and serologic testing, return-to-work considerations for exposed or infected health care workers, risk stratification and management strategies based on COVID-19 disease burden, institutional preparedness for resumption of elective procedures, patient preparation and communication, prioritization of procedures, and development of outpatient and periprocedural care pathways.

Seroprevalence of antibodies to SARS-CoV-2 in healthcare workers: a cross-sectional study.

OBJECTIVE: We sought to determine the extent of SARS-CoV-2 seroprevalence and the factors associated with seroprevalence across a diverse cohort of healthcare workers. DESIGN: Observational cohort study of healthcare workers, including SARS-CoV-2 serology testing and participant questionnaires. SETTINGS: A multisite healthcare delivery system located in Los Angeles County. PARTICIPANTS: A diverse and unselected population of adults (n=6062) employed in a multisite healthcare delivery system located in Los Angeles County, including individuals with direct patient contact and others with non-patient-oriented work functions. MAIN OUTCOMES: Using Bayesian and multivariate analyses, we estimated seroprevalence and factors associated with seropositivity and antibody levels, including pre-existing demographic and clinical characteristics; potential COVID-19 illness-related exposures; and symptoms consistent with COVID-19 infection. RESULTS: We observed a seroprevalence rate of 4.1%, with anosmia as the most prominently associated self-reported symptom (OR 11.04, p<0.001) in addition to fever (OR 2.02, p=0.002) and myalgias (OR 1.65, p=0.035). After adjusting for potential confounders, seroprevalence was also associated with Hispanic ethnicity (OR 1.98, p=0.001) and African-American race (OR 2.02, p=0.027) as well as contact with a COVID-19-diagnosed individual in the household (OR 5.73, p<0.001) or clinical work setting (OR 1.76, p=0.002). Importantly, African-American race and Hispanic ethnicity were associated with antibody positivity even after adjusting for personal COVID-19 diagnosis status, suggesting the contribution of unmeasured structural or societal factors. CONCLUSION AND RELEVANCE: The demographic factors associated with SARS-CoV-2 seroprevalence among our healthcare workers underscore the importance of exposure sources beyond the workplace. The size and diversity of our study population, combined with robust survey and modelling techniques, provide a vibrant picture of the demographic factors, exposures and symptoms that can identify individuals with susceptibility as well as potential to mount an immune response to COVID-19.

Changes in the digital health landscape in cardiac electrophysiology: A pre-and peri-pandemic COVID-19 era survey.

Background: Digital health is transforming healthcare delivery. Objective: To compare the current digital health landscape in select groups of cardiac electrophysiology (EP) professionals prior to and during the COVID-19 era. Methods: Two online surveys were emailed to 4 Heart Rhythm Society communities and tweeted out to Twitter EP, 1 before and 1 during the pandemic. Categorical variables were analyzed using the χ 2 test and reported as absolute numbers and percentages. Results: There were 253 pre-pandemic (S1) and 273 follow-up surveys (S2) completed. The majority of respondents to both surveys were male, aged <55 years (70.6% vs 75.1%), university-affiliated (52.6% vs 55%), and physicians (83.3% vs 87.9%). Between S1 and S2, routine use of video-telehealth increased (5.9% vs 58.6%; P < .001) for all types of consultations (P < .001 for all). Wireless electrocardiogram prescribing was prevalent and similar (80.2% vs 81.0%), whereas wireless blood pressure monitoring (9.9% vs 18.3%) and wireless oximetry (1.6% vs 8.1%; P = .006 for both) prescribing both increased. For smartphone mobile applications (mApps), prescriptions for heart rate mApps decreased (50.6% vs 40.7%; P = .022), while vital sign (28.9% vs 37%; P = .04) and symptom trackers (15.8% vs 24.9%; P = .01) prescribing increased. A majority in both surveys (84.6% vs 75.5%) reported no workplace infrastructure or support for digital health with concerns for lack of parity in reimbursement. Conclusion: Our results show an increase in adoption of digital health by EP during the COVID-19 pandemic. Concerns regarding a lack of supportive infrastructure persisted. Development of professional society guidelines on optimal clinical workflow, infrastructure, and reimbursement may help advance and sustain digital health integration in EP.

Pre-existing traits associated with Covid-19 illness severity.

IMPORTANCE: Certain individuals, when infected by SARS-CoV-2, tend to develop the more severe forms of Covid-19 illness for reasons that remain unclear. OBJECTIVE: To determine the demographic and clinical characteristics associated with increased severity of Covid-19 infection. DESIGN: Retrospective observational study. We curated data from the electronic health record, and used multivariable logistic regression to examine the association of pre-existing traits with a Covid-19 illness severity defined by level of required care: need for hospital admission, need for intensive care, and need for intubation. SETTING: A large, multihospital healthcare system in Southern California. PARTICIPANTS: All patients with confirmed Covid-19 infection (N = 442). RESULTS: Of all patients studied, 48% required hospitalization, 17% required intensive care, and 12% required intubation. In multivariable-adjusted analyses, patients requiring a higher levels of care were more likely to be older (OR 1.5 per 10 years, P<0.001), male (OR 2.0, P = 0.001), African American (OR 2.1, P = 0.011), obese (OR 2.0, P = 0.021), with diabetes mellitus (OR 1.8, P = 0.037), and with a higher comorbidity index (OR 1.8 per SD, P<0.001). Several clinical associations were more pronounced in younger compared to older patients (Pinteraction<0.05). Of all hospitalized patients, males required higher levels of care (OR 2.5, P = 0.003) irrespective of age, race, or morbidity profile. CONCLUSIONS AND RELEVANCE: In our healthcare system, greater Covid-19 illness severity is seen in patients who are older, male, African American, obese, with diabetes, and with greater overall comorbidity burden. Certain comorbidities paradoxically augment risk to a greater extent in younger patients. In hospitalized patients, male sex is the main determinant of needing more intensive care. Further investigation is needed to understand the mechanisms underlying these findings.

The COronavirus Pandemic Epidemiology (COPE) Consortium: A Call to Action.

The rapid pace of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2; COVID-19) pandemic presents challenges to the real-time collection of population-scale data to inform near-term public health needs as well as future investigations. We established the COronavirus Pandemic Epidemiology (COPE) consortium to address this unprecedented crisis on behalf of the epidemiology research community. As a central component of this initiative, we have developed a COVID Symptom Study (previously known as the COVID Symptom Tracker) mobile application as a common data collection tool for epidemiologic cohort studies with active study participants. This mobile application collects information on risk factors, daily symptoms, and outcomes through a user-friendly interface that minimizes participant burden. Combined with our efforts within the general population, data collected from nearly 3 million participants in the United States and United Kingdom are being used to address critical needs in the emergency response, including identifying potential hot spots of disease and clinically actionable risk factors. The linkage of symptom data collected in the app with information and biospecimens already collected in epidemiology cohorts will position us to address key questions related to diet, lifestyle, environmental, and socioeconomic factors on susceptibility to COVID-19, clinical outcomes related to infection, and long-term physical, mental health, and financial sequalae. We call upon additional epidemiology cohorts to join this collective effort to strengthen our impact on the current health crisis and generate a new model for a collaborative and nimble research infrastructure that will lead to more rapid translation of our work for the betterment of public health.