USING OBJECTIVE ELECTROCARDIOGRAPHIC DATA TO BETTER PREDICT MORTALITY IN PATIENTS HOSPITALIZED WITH COVID 19

ABSTRACT

BACKGROUND: The impact of SARS-CoV-2 infection on intrinsic myocardial conduction continues to be an area of focus amongst the medical community. Our objective was to investigate if specific myocardial conduction abnormalities were independently associated with mortality in patients hospitalized with COVID 19. METHODS: Under IRB exemption, the electronic medical records of COVID-19 patients (N=3840) undergoing index hospitalization were reviewed to extract presentation ECG conduction data, demographics, and laboratory results (within 8h). This patient cohort was then separated into two groups based on mortality vs. not (N=520). Logistical regression was used to test association of ECG conduction intervals with mortality. RESULTS: According to our nominal logistic fit for hospital mortality, Heart Rate (HR) >100 (p=0.0007;LW 4.14), QRS duration > 120 ms (p=0.0053;LW 2.27), and QTc prolongation (defined as QTc > 450ms in males;QTc > 460ms in females) (p=0.0089;LW 2.04) were independently associated with higher risk of mortality. LogWorth (LW) calculations were included in an effort to estimate the proportional effect each variable has on overall mortality. LW > 2 were shown to be statistically significant with p< 0.05 with HR > 100 (LW 4.14) having the highest proportional effect on mortality followed by QRSd (LW 2.27) then QTc prolongation (LW 2.04). PR interval> 200ms (p=0.30) and QRS axis (p=0.15) were not associated with higher risk of mortality. CONCLUSIONS: Amongst our patient cohort, HR > 100, QRSd > 120ms, and QTc prolongation (QTc > 450 in males;QTc > 460 in females) were each independently associated with higher risk of mortality in patients hospitalized with COVID 19. These findings support the use of objective ECG data in risk stratifying patients hospitalized with COVID 19.