TCT CONNECT-217 Hydroxychloroquine and Azithromycin Usage in African American Patients With Coronavirus Disease 2019 (COVID-19) and Their Effects on QT Interval

Background: The novel coronavirus disease-2019 (COVID-19) caused by the severe acute respiratory syndrome coronavirus-2 (SARS CoV-2) has been a major cause of morbidity and mortality around the world Thirteen million cases have been diagnosed with approximately 570,000 deaths worldwide COVID-19 is associated with ischemia, myocarditis and eventual resulting arrhythmia Cases may present as acute thrombotic occlusion, stress cardiomyopathy, or coronary spasm Hydroxychloroquine (HCQ) was temporarily approved by FDA for COVID-19 treatment In this study, we planned to characterize the risk and degree of QTc prolongation in largely African-American population in central Brooklyn, who were hospitalized with COVID-19 infection in association with inpatient administration of HCQ and azithromycin One of the major adverse drug effects of HCQ and chloroquine is the potential prolongation of corrected QT interval (QTc) Methods: In our retrospective study, we included patients, both males and females, 18 years of age and older who were admitted at SUNY Downstate Medical Center, Brooklyn, New York, for COVID-19 infection and were treated with hydroxychloroquine Native baseline RR, QRS, and QT intervals were measured before administering the first dose of hydroxychloroquine and within 24 h of administration The RR interval was measured as a distance between the peak of the R-wave and the peak of the previous R-wave in the same lead in milliseconds and converted to a heart rate by equation, 60,000/RR For correction of the QT, we used common formulas: QTc = QT/√RR [Bazett formula], QTc = QT/∛RR [Fridericia formula], QTc = QT + 0 154 (1-RR) [Framingham formula], QTc = QT + 1 75 (heart rate-60) [Hodges formula] QTc interval prolongation was defined based on the following rules: Male Rules: 1) Baseline 450 ms;2) >15% increase over baseline post HCQ;and 3) baseline >450 ms and 500 ms;Female Rules: 1) Baseline 470 ms;2) >15% increase over baseline post HCQ;and 3) baseline >470 ms and 500 ms Statistics: Means were compared using independent sample t-tests;paired sample t-tests and proportions were compared using Chi square analysis QT correction formulas were compared using 1-way ANOVA and post hoc analysis was done with Tukey correction Binary univariate and multivariate regression were performed to determine risk factor predictors for QTc prolongation Results: We screened 444 consecutive patients with COVID-19 who were admitted to our hospital between March 10 and April 15, 2020, a total of 247 were excluded from this study because they met the exclusion criteria Thus, 197 patients were included in the analysis The mean baseline QTc interval calculated using the Bazett, Hodges, Frederica, Framingham methods were 451 0 ± 34 3, 425 1 ± 28 9, 417 2 ± 34 0, and 413 9 ± 31 ms, respectively Of the 4 correction methods, 35 5% of all patients met the criteria for prolongation using the Bazett method Of all patients included in the study 125 (63 5%) were male and 72 (36 5%) were female Subjects were predominantly African American ancestry, 179 (90 9%) The mean age of all patients was 66 1 ± 13 3 years The most common comorbidities were hypertension (74 6%), diabetes (55 3%), and hyperlipidemia (37 5%) Of all study participants, 91 7% received concomitant azithromycin;31% of patients were on home beta-blocker therapy, while 27 9% were on home calcium-channel blockers Of baseline electrocardiograms, 87 8% were sinus rhythm Total number of patients meeting prolongation criteria was less using the Hodges, Frederica, and Framingham methods Mean QTc values in both genders are presented in (Tables 1, 2, 3, and 4) All 4 methods showed statistically significant increases in QTc Bazett had the relatively largest difference between pre- and post-therapy QT interval with a mean difference of 14 48 ms The increase was present in both men and women The mean difference across sexes was largest using the Bazett method 16 43, bu this was not statistically significant Univariate analysis across all methods found that the concomitant use of azithromycin was not a significant predictor in QT prolongation across the Bazett, Hodges, Frederica, and Framingham methods However, the presence of coronary artery disease was a statistically significant predictor for QT prolongation The presence of congestive heart failure was also a predictor using the Hodges and Framingham methods (Table 5, 6, 7, and 8) (Figure 1) [Formula presented] ANOVA analysis across all subjects showed a significant difference between the four methods There were significant differences between Bazett and 3 methods The largest difference was between Bazett and Framingham, by 37 12 s There was also a smaller difference between the Hodge and Framingham methods The significant difference between the Bazzett method and the others also persisted across both men and women The difference between Hodges and Bazzett was only significant in men (Table 9, 10, and 11) QT prolongation irrespective of the method used for correction did not predict mortality [Formula presented] [Formula presented] [Formula presented] [Formula presented] [Formula presented] [Formula presented] [Formula presented] [Formula presented] [Formula presented] [Formula presented] [Formula presented] Conclusion: It was notable that the longest QTc prolongation seen in this study was only 14 48 ms, using the Bazett formula With other formulas, this prolongation was significantly smaller and so was the proportion of patients meeting QTc prolongation criteria Not surprisingly, the Bazett formula again overestimated extend of QT prolongation We can only speculate that the differences are perhaps related to the fact that our population was nearly exclusively African American Common channels variation has been well documented to be a factor in QT prolongation, including drug-inducted QT prolongation In the African-American ethnic subgroup, Ser1103Tyr-SCN5A is seen in approximately 8 % of population and can certainly explain our data Furthermore, frequency of CAD and CHF was slightly higher than reported in other studies and both entities were associated with QT prolongation on our population Reassuringly, the presence of QT prolongation was not found to be a predictor of mortality in our cohort Categories Other: COVID-19 Lectures