Delayed cardiac repolarisation as a predictor of in-hospital mortality in patients with COVID-19.

OBJECTIVE: With 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. METHODS: This 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. RESULTS: All-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). CONCLUSION: In 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.

Increased Inpatient Mortality for Cardiovascular Patients During the First Wave of the COVID-19 Epidemic in New York.

Background The acuity and magnitude of the first wave of the COVID-19 epidemic in New York mandated a drastic change in healthcare access and delivery of care. Methods and Results We retrospectively studied patients admitted with an acute cardiovascular syndrome as their principal diagnosis to 13 hospitals across Northwell Health during March 11 through May 26, 2020 (first COVID-19 epidemic wave) and the same period in 2019. Three thousand sixteen patients (242 COVID-19 positive) were admitted for an acute cardiovascular syndrome during the first COVID-19 wave compared with 9422 patients 1 year prior (decrease of 68.0%, P<0.001). During this time, patients with cardiovascular disease presented later to the hospital (360 versus 120 minutes for acute myocardial infarction), underwent fewer procedures (34.6% versus 45.6%, P<0.001), were less likely to be treated in an intensive care unit setting (8.7% versus 10.8%, P<0.001), and had a longer hospital stay (2.91 [1.71-6.05] versus 2.87 [1.82-4.95] days, P=0.033). Inpatient cardiovascular mortality during the first epidemic outbreak increased by 111.1% (3.8 versus 1.8, P<0.001) and was not related to COVID-19-related admissions, all cause in-hospital mortality, or incidence of out-of-hospital cardiac deaths in New York. Admission during the first COVID-19 surge along with age and positive COVID-19 test independently predicted mortality for cardiovascular admissions (odds ratios, 1.30, 1.05, and 5.09, respectively, P<0.0001). Conclusions A lower rate and later presentation of patients with cardiovascular pathology, coupled with deviation from common clinical practice mandated by the first wave of the COVID-19 pandemic, might have accounted for higher in-hospital cardiovascular mortality during that period.

Association between regional distributions of SARS-CoV-2 seroconversion and out-of-hospital sudden death during the first epidemic outbreak in New York.

BACKGROUND: Increased incidence of out-of-hospital sudden death (OHSD) has been reported during the coronavirus 2019 (COVID-19) pandemic. New York City (NYC) represents a unique opportunity to examine the epidemiologic association between the two given the variable regional distribution of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in its highly diverse neighborhoods. OBJECTIVE: The purpose of this study was to examine the association between OHSD and SARS-CoV-2 epidemiologic burden during the first COVID-19 pandemic across the highly diverse neighborhoods of NYC. METHODS: The incidences of OHSD between March 20 and April 22, 2019, and between March 20 and April 22, 2020, as reported by the Fire Department of New York were obtained. As a surrogate for viral epidemiologic burden, we used percentage of positive SARS-CoV-2 antibody tests performed between March 3 and August 20, 2020. Data were reported separately for the 176 zip codes of NYC. Correlation analysis and regression analysis were performed between the 2 measures to examine association. RESULTS: Incidence of OHSD per 10,000 inhabitants and percentage of SARS-CoV-2 seroconversion were highly variable across NYC neighborhoods, varying from 0.0 to 22.9 and 12.4% to 50.9%, respectively. Correlation analysis showed a moderate positive correlation between neighborhood data on OHSD and percentage of positive antibody tests to SARS-CoV-2 (Spearman ρ 0.506; P <.001). Regression analysis showed that seroconversion to SARS-CoV-2 and OHSD in 2019 were independent predictors for OHSD during the first epidemic surge in NYC (R2 = 0.645). CONCLUSION: The association in geographic distribution between OHSD and SARS-CoV-2 epidemiologic burden suggests either a causality between the 2 syndromes or the presence of local determinants affecting both measures in a similar fashion.