Abstract
ObjectiveWith the rapid influx of COVID-19 admissions during the first wave of the pandemic, there was an obvious need for an efficient and streamlined risk stratification tool to aid in triaging. To this date, no clinical prediction tool exists for patients presenting to the hospital with COVID-19 infection.MethodsThis is a retrospective cohort study of patients admitted in one of 13 Northwell Health Hospitals, located in the wider New York Metropolitan area between 1 March 2020 and 27 April 2020. Inclusion criteria were a positive SARS-CoV-2 nasal swab, a 12-lead ECG within 48 hours,and a complete basic metabolic panel within 96 hours of presentation.ResultsAll-cause, in-hospital mortality was 27.1% among 7098 patients. Independent predictors of mortality included demographic characteristics (male gender, race and increased age), presenting vitals (oxygen saturation <92% and heart rate >120 bpm), metabolic panel values (serum lactate >2.0 mmol/L, sodium >145, mmol/L, blood urea nitrogen >40 mmol/L, aspartate aminotransferase >40 U/L, Creatinine >1.3 mg/dL and glycose >100 mg/L) and comorbidities (congestive heart failure, chronic obstructive pulmonary disease and coronary artery disease). In addition to those, our analysis showed that delayed cardiac repolarisation (QT corrected for heart rate (QTc) >500 ms) was independently associated with mortality (OR 1.41, 95% CI 1.05 to 1.90). Previously mentioned parameters were incorporated into a risk score that accurately predicted in-hospital mortality (AUC 0.78).ConclusionIn the largest cohort of COVID-19 patients with complete ECG data on presentation, we found that in addition to demographics, presenting vitals, clinical history and basic metabolic panel values, QTc >500 ms is an independent risk factor for in-hospital mortality.
Subject
Cardiology and Cardiovascular Medicine
Cited by
3 articles.
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