Literature DB >> 33012341

The Prognostic Value of Electrocardiogram at Presentation to Emergency Department in Patients With COVID-19.

Pierre Elias1, Timothy J Poterucha2, Sneha S Jain3, Gabriel Sayer2, Jayant Raikhelkar2, Justin Fried2, Kevin Clerkin2, Jan Griffin2, Ersilia M DeFilippis2, Aakriti Gupta4, Matthew Lawlor2, Mahesh Madhavan2, Hannah Rosenblum2, Zachary B Roth5, Karthik Natarajan6, George Hripcsak6, Adler Perotte6, Elaine Y Wan2, Amardeep Saluja2, Jose Dizon2, Frederick Ehlert2, John P Morrow2, Hirad Yarmohammadi2, Deepa Kumaraiah2, Bjorn Redfors7, Nicholas Gavin8, Ajay Kirtane9, Leroy Rabbani2, Dan Burkhoff2, Jeffrey Moses2, Allan Schwartz2, Martin Leon4, Nir Uriel10.   

Abstract

OBJECTIVE: To study whether combining vital signs and electrocardiogram (ECG) analysis can improve early prognostication.
METHODS: This study analyzed 1258 adults with coronavirus disease 2019 who were seen at three hospitals in New York in March and April 2020. Electrocardiograms at presentation to the emergency department were systematically read by electrophysiologists. The primary outcome was a composite of mechanical ventilation or death 48 hours from diagnosis. The prognostic value of ECG abnormalities was assessed in a model adjusted for demographics, comorbidities, and vital signs.
RESULTS: At 48 hours, 73 of 1258 patients (5.8%) had died and 174 of 1258 (13.8%) were alive but receiving mechanical ventilation with 277 of 1258 (22.0%) patients dying by 30 days. Early development of respiratory failure was common, with 53% of all intubations occurring within 48 hours of presentation. In a multivariable logistic regression, atrial fibrillation/flutter (odds ratio [OR], 2.5; 95% CI, 1.1 to 6.2), right ventricular strain (OR, 2.7; 95% CI, 1.3 to 6.1), and ST segment abnormalities (OR, 2.4; 95% CI, 1.5 to 3.8) were associated with death or mechanical ventilation at 48 hours. In 108 patients without these ECG abnormalities and with normal respiratory vitals (rate <20 breaths/min and saturation >95%), only 5 (4.6%) died or required mechanical ventilation by 48 hours versus 68 of 216 patients (31.5%) having both ECG and respiratory vital sign abnormalities.
CONCLUSION: The combination of abnormal respiratory vital signs and ECG findings of atrial fibrillation/flutter, right ventricular strain, or ST segment abnormalities accurately prognosticates early deterioration in patients with coronavirus disease 2019 and may assist with patient triage.
Copyright © 2020 Mayo Foundation for Medical Education and Research. Published by Elsevier Inc. All rights reserved.

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Mesh:

Year:  2020        PMID: 33012341      PMCID: PMC7428764          DOI: 10.1016/j.mayocp.2020.07.028

Source DB:  PubMed          Journal:  Mayo Clin Proc        ISSN: 0025-6196            Impact factor:   7.616


The global pandemic of coronavirus disease 2019 (COVID-19) is caused by infection with severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2). In the United States, COVID-19 has infected more than 3.4 million people, leading to more than 138,000 deaths. , Severe cases can result in respiratory failure with acute respiratory distress syndrome, shock, and death. Some patients remain stable with mild symptoms, and others develop rapid deterioration after a period of stability lasting up to a week or more. , , Known markers of poor prognosis include age, comorbidities, and high sequential organ failure assessment score. In patients with severe infection, numerous laboratory findings have been associated with adverse outcomes including hematologic disturbances and inflammatory biomarkers. However, there is a limited understanding of how presenting vital signs relate to final outcome from COVID-19, hampering the development of effective approaches for triaging patients early in their clinical course. Additionally, there is increasing evidence of the prognostic capacity of cardiac involvement in COVID-19. , Electrocardiographic (ECG) abnormalities have been described, but there have been no large studies of ECG abnormalities in COVID-19 patients nor their correlation with clinical outcomes. , Early triage of patients who will require higher levels of care is crucial because of the high volume of patients admitted with the disease. In this study, we sought to determine if data available early in a patient’s emergency department (ED) presentation (demographics, comorbidities, vital signs, and ECG) could prognosticate the composite outcome of mechanical ventilation or death by 48 hours after COVID-19 diagnosis. We hypothesized that abnormalities found on ECGs performed at presentation would add additional prognostic capacity after adjusting for the above data in a multivariable logistic regression model. Lastly, we explored time from presentation to mechanical ventilation or death to better understand the disease course.

Methods

Data Collection

All patients 18 years of age or older who tested positive for SARS-CoV-2 using a reverse-transcriptase–polymerase-chain-reaction assay of a nasopharyngeal or oropharyngeal sample at Columbia University Irving Medical Center, Morgan Stanley Children’s Hospital of New York, and New York–Presbyterian Allen Pavilion were enrolled in this study. To ensure all patients had 14-day outcomes, patients must have received a positive diagnosis between March 1, 2020, and April 3, 2020. Data were collected using chart reviews and electronic health records abstraction. This study was conducted with approval from the Columbia University Irving Medical Center Institutional Review Board. Abstracted data included demographics, comorbidities, symptoms, vital signs, laboratory findings, ECGs, and clinical outcomes. Comorbidities were assessed by manual chart review and included hypertension, diabetes, obesity (defined as body mass index ≥30 kg/m2, pulmonary disease (including asthma, chronic obstructive pulmonary disease, interstitial lung disease, or any primary lung disease that required home oxygen therapy or daily treatment), stage 3-5 chronic kidney disease (CKD), heart failure with reduced ejection fraction (HFrEF, defined as ejection fraction <50%), heart failure with preserved ejection fraction (HFpEF, defined as clinical diagnosis found in patient records), obstructive coronary artery disease (CAD; defined as left main disease ≥50% or other vessels ≥70%, treated or untreated), active cancer (defined as metastatic cancer, cancer that required treatment within the last 6 months, or cancer undergoing active observation), or personal history of cancer that did not meet the active cancer definition. Non-metastatic basal cell carcinoma and squamous cell carcinoma of the skin were excluded from the cancer criteria. Abstracted laboratory data included white blood cell count, absolute lymphocyte count, hemoglobin, creatinine, C-reactive protein (CRP), and erythrocyte sedimentation rate. For each lab assay, the first laboratory test that was performed during the encounter was defined as the “initial” test. In addition, the most abnormal result (peak or nadir depending on clinical relevance) of each lab any point during the 14-day period was recorded.

Electrocardiograms

Twelve-lead ECGs were abstracted and analyzed using the MUSE Cardiology Information System (GE Healthcare, Chicago, IL). An “initial ECG” was defined as one obtained within 6 hours of presentation or diagnosis of COVID-19. Ventricularly paced ECGs (n=9) were excluded from analysis. Only the earliest eligible electrocardiogram per patient was used. All ECGs were analyzed by a board-certified electrophysiologist (E.W., J.D., J.M., H.Y., F.E., or D.S.) using a standardized reading protocol which included ECG intervals, rate, rhythm, axis, QRS morphology, voltage, and ST or T wave abnormalities (complete criteria are detailed in the Supplemental Material, available online at http://www.mayoclinicproceedings.org).

Clinical Outcomes

Analysis of clinical outcomes was assessed by chart review. Patients were grouped into one of three mutually exclusive groups: 1) alive, never required mechanical ventilation; 2) alive, required mechanical ventilation; or 3) died of any cause. To ensure disease outcome was adequately captured, all patients were required to have 14 days of follow-up after their initial positive SARS-CoV-2 test to be included in this study. The primary outcome for the study was defined as receiving mechanical ventilation (excluding emergent intubation during unsuccessful resuscitation) or death at any point in the 48 hours after COVID-19 diagnosis.

Statistical Analysis and Multivariable Regression Model

Descriptive statistics including mean, standard deviation, median, interquartile range (IQR), and frequencies were determined for demographics, comorbidities, laboratory findings, ECG parameters, and clinical outcomes. The Shapiro-Wilk test was used to assess normality of key variables, and where applicable nonparametric testing was conducted. Categorical variables were assessed using χ2 analysis. Continuous variable means were compared using Student t tests or the Mann-Whitney U test. Where assumptions of normality were met, mean, standard deviation, and 95% CIs are described. Nonparametric results are described with median and IQRs. All statistical tests were performed in Python 3.4 (Wilmington, DE) and SPSS v26 (Chicago, IL). All variables in Table 1 underwent univariable logistic regression to the primary outcome. Those with a P value nearing .05 were candidates for inclusion in a multivariable logistic regression model. The multivariable logistic regression model was used to determine the odds ratios (ORs) in predicting the primary outcome as a binary event. The variables selected were those regularly available within the first hour of a patient’s presentation to the ED, including demographics, comorbidities, vital signs, and ECG abnormality. Abnormal respiratory vitals were defined as a respiratory rate >20 breaths/min, oxygen saturation <96%, or oxygen therapy via non-rebreather (NRB) or full-face mask (FFM) at presentation. We then evaluated how a simplified algorithm looking at the presence of the most significant risk factors from the multivariable logistic regression model would do in discriminating 48-hour outcome. We also assessed discriminative capacity for 14-day outcome to ensure deaths and intubations occurring after 2 days did not significantly deviate from the 48-hour model’s findings.
Table 1

Characteristics of Adult Patients Diagnosed With Coronavirus Disease 2019a

TotalOutcome 48 hours after diagnosis
Alive, never received mechanical ventilationAlive, received mechanical ventilationDied
N (%)1258 (100)1011 (80)174 (14)73 (6)
Demographics
 Age, mean (SD), years61.6 (18.4)60.55 (6)61.32 (35)76.51 (105)
 Male685 (54)532 (53)111 (64)42 (58)
Comorbidities
 No comorbidities209 (17)189 (19)19 (11)1 (1)
 Hypertension715 (57)557 (55)107 (61)53 (73)
 Diabetes461 (37)349 (35)74 (43)40 (55)
 Obesity428 (34)336 (33)78 (45)17 (23)
 Primary lung disease208 (17)161 (16)29 (17)20 (27)
 CKD197 (16)147 (15)29 (17)22 (30)
 HFrEF84 (7)57 (6)14 (8)13 (18)
 HFpEF54 (4)43 (4)6 (3)5 (7)
 CAD144 (11)111 (11)25 (14)9 (12)
 Cancer, active53 (4)47 (5)5 (3)3 (4)
 Cancer, history71 (6)57 (6)11 (6)3 (4)
 Two or more comorbidities691 (55)547 (54)103 (59)45 (62)
Presenting symptoms
 Fever489 (39)408 (40)66 (38)18 (25)
 Cough402 (32)336 (33)55 (32)13 (18)
 Shortness of breath368 (29)263 (26)81 (47)26 (36)
 Gastrointestinal complaints124 (10)117 (12)6 (3)1 (1)
 Weakness84 (7)74 (7)7 (4)3 (4)
 Chest pain40 (3)35 (3)5 (3)0 (0)
Presenting vital signs
 Abnormal temperature (<36° or >38° C)368 (29)292 (29)55 (32)23 (32)
 Heart rate >100 beats/min536 (43)418 (41)81 (47)39 (53)
 Oxygen saturation <96%719 (57)555 (55)127 (73)37 (51)
 Respiratory rate ≥20 breaths/min352 (28)228 (23)90 (52)34 (47)
 Systolic blood pressure <100 mm Hg110 (9)89 (9)9 (5)12 (15)
Presenting electrocardiogram
 Patients with ECGs85067513243
 Normal sinus rhythm557 (66)465 (69)72 (55)20 (47)
 Sinus bradycardia15 (2)13 (2)02 (5)
 Sinus tachycardia220 (26)161 (24)46 (35)13 (30)
 Atrial fibrillation or flutter42 (5)23 (3)11 (10)8 (19)
 Atrial ectopy66 (8)52 (8)7 (6)7 (18)
 PR >240 ms14 (2)12 (2)2 (2)0
 PR depression present8 (1)6 (1)1 (1)1 (2)
 Ventricular ectopy44 (5)34 (5)5 (4)5 (12)
 Pathologic Q Waves72 (8)51 (8)12 (9)9 (21)
 QRS >120 ms70 (8)55 (8)10 (8)5 (12)
 Left ventricular hypertrophy96 (11)71 (11)15 (12)10 (24)
 Low QRS voltage29 (3)22 (3)3 (2)4 (10)
 Right ventricular overloadb34 (4)23 (3)10 (8)1 (2.4)
 Poor R wave progression118 (14)85 (13)24 (18)9 (21)
 Any ST segment Elevation/depression117 (14)78 (12)25 (19)14 (33)
 ST elevation or depression ≥1mm40 (5)27 (4)11 (8)2 (5)
 QTc (Fredericia) ≥500 ms64 (8)43 (6)12 (9)9 (21)

CAD = obstructive coronary artery disease; CKD = stage 3 or greater chronic kidney disease; ECG = electrocardiogram; HFpEF = heart failure with preserved ejection fraction; HFrEF = heart failure with reduced ejection fraction which was defined as a clinical diagnosis of systolic heart failure or a baseline echocardiogram with left ventricular ejection fraction <50%.

Right ventricular overload was defined as the presence of right ventricular hypertrophy or S1Q3T3. Any ST segment elevation/depression includes sub-millimeter changes from baseline, but ST elevations and depressions must have occurred in two contiguous leads to be considered positive.

Characteristics of Adult Patients Diagnosed With Coronavirus Disease 2019a CAD = obstructive coronary artery disease; CKD = stage 3 or greater chronic kidney disease; ECG = electrocardiogram; HFpEF = heart failure with preserved ejection fraction; HFrEF = heart failure with reduced ejection fraction which was defined as a clinical diagnosis of systolic heart failure or a baseline echocardiogram with left ventricular ejection fraction <50%. Right ventricular overload was defined as the presence of right ventricular hypertrophy or S1Q3T3. Any ST segment elevation/depression includes sub-millimeter changes from baseline, but ST elevations and depressions must have occurred in two contiguous leads to be considered positive.

Results

Patient Characteristics, Comorbidities, Laboratory Findings, and Outcomes

From March 1 to April 3, 2020, 5587 individuals were tested for COVID-19 with 2421 (43.3%) having positive results. A total of 1258 patients who were admitted to the hospital were included in the study. Demographics, comorbidities, presentation vital signs, and outcomes are displayed in Table 1. The mean age was 61.6 years (SD, 18.4 years) and 563 (44.8%) patients were female. The most common comorbidities were hypertension (n=753; 56.8%), diabetes (n=461; 36.6%), obesity (n=428; 34.0%), primary lung disease (n=208; 16.5%), and CKD (n=197; 15.7%). Prior known cardiovascular disease included CAD (n=144; 11.4%), HFrEF (n=84; 6.6%), and HFpEF (n=54; 4.3%). The most common symptoms reported at the time of triage were fever (n=489; 38.8%), cough (n=402; 32.0%), shortness of breath (n=368; 29.3%), gastrointestinal complaints (n=124; 9.9%), weakness (n=84; 6.7%), and chest pain (n=40; 3.2%). At 48 hours, 1011 of 1258 patients (80.4%) were alive without receiving mechanical ventilation, 174 (13.8%) received mechanical ventilation but had not died, and 73 (5.8%) had died (Figure 1 ). During the 14-day period, 287 of 1258 patients (22.8%) were intubated, of which 16 (5.8%) were extubated and discharged, 36 (12.5%) were extubated but remained hospitalized, 121 (42.2%) remained intubated, and 115 (40.1%) died. The rate of early clinical decompensation was high, with a median time from hospital arrival to mechanical ventilation of 1 day (IQR, 0 to 4 days) and a median time of hospital arrival to death of 6 days (IQR, 3 to 10 days). Mortality increased from 231 of 1258 (18.4%) patients at 14 days to 277 (22.0%) patients at 30 days.
Figure 1

Patient outcomes at 14 days after coronavirus disease 2019 diagnosis.

Patient outcomes at 14 days after coronavirus disease 2019 diagnosis. Patients who met the primary outcome tended to be older (mean age, 66.3 years vs 60.4 years), male (62.4% vs 52.1%), have hypertension (67.1% vs 54.8%), diabetes (47.2% vs 33.7%), and CKD (19.6% vs 15.1%). On presentation they were more likely to have a respiratory rate greater than 20 breaths/min (50.2% vs 22.1%) and oxygen saturation less than or equal to 95% (67% vs 55%). There were differences noted in earliest creatinine level (median, 1.3 vs 1.0 mg/dL) and CRP (184.7 vs 89.6 mg/L) but differences in erythrocyte sedimentation rate (73 vs 63 mm/h) and absolute lymphocyte count (0.88 vs 1.06 × 103 cells/μL) were less pronounced. Laboratory results are further detailed in the Supplemental Material.

Vital Signs

Vital sign abnormalities on presentation are shown in Table 1. The median temperature was 37.4° C (IQR, 36.8 to 38.2 ° C) and 361 of 1258 patients (29.0%) had a temperature greater than or equal to 38.0 ° C. The median heart rate was 98 beats/min (IQR, 86 to 110 beats/min) and median systolic blood pressure was 124 mm Hg (IQR, 111 to 142 mm Hg). The median respiratory rate was 20 breaths/min (IQR, 18 to 22 breaths/min) and the median oxygen saturation was 94% (IQR, 90% to 97%). Six hundred eighty-two of 1258 (54.2%) patients met criteria for abnormal respiratory vitals (respiratory rate >20 breaths/min, saturation ≤95%, or oxygen therapy via NRB or FFM).

Electrocardiographic Findings

Initial ECGs for 850 patients were available for analysis. The most common rhythm was sinus rhythm (65.6%) followed by sinus tachycardia (25.9%), and atrial fibrillation or flutter (4.9%). Ninety-six of 850 patients (11.3%) met criteria for left ventricular hypertrophy and 29 (3.4%) patients had low QRS voltage. The QTc (Bazett) was prolonged (>460 ms if QRS <120 ms or >500 ms if QRS >120 ms) in 240 patients (28.2%) and markedly prolonged (>500 ms if QRS <120 ms or >550 if QRS >120 ms) in 43 patients (5.1%). Among 812 ECGs with QRS duration less than 120 ms, there was ST elevation or depression in two contiguous leads in 117 patients (13.8%) with 40 (4.7%) being greater than or equal to 1 mm. A full list of ECG findings is detailed in Table 1.

Triage Approach Based on Respiratory Vital Signs and ECG

All variables in Table 1 underwent univariable logistic regression in predicting 48-hour outcome. All variables with P values less than or equal to .05 were included in a multivariable logistic regression model as shown in Table 2 . In our final multivariable model, significant variables included respiratory rate greater than 20 breaths/min (OR, 3.3; 95% CI, 2.2 to 4.7), oxygen saturation less than or equal to 95% or oxygen therapy via NRB or FFM (OR, 2.1; 95% CI, 1.3 to 3.3), presence of atrial fibrillation/flutter (OR, 2.5; 95% CI, 1.1 to 6.2), right ventricular strain (OR, 2.7; 95% CI, 1.3 to 6.1), ST segment abnormality (OR, 2.4; 95% CI, 1.5 to 3.8), and history of diabetes requiring medical therapy (OR, 1.6; 95% CI, 1.0 to 2.4) as detailed in Table 2. No significant collinearity was found among all variables included in the model (highest variance inflation factor = 1.8). The hypothesis that ECG abnormalities had additive prognostic value after adjusting for the presence of demographics, comorbidities, and vital signs was accepted. We then combined the two vital sign abnormalities and three ECG abnormalities into two binary variables (abnormal respiratory vitals and abnormal ECG findings). At 48 hours after diagnosis, 5 (4.6%) of patients with none of the three ECG abnormalities and normal respiratory vital signs received mechanical ventilation or died, compared with 68 (31.5%) of patients with any ECG abnormality and any abnormal respiratory vital sign. The presence of any of the three ECG abnormalities increased the rate of mechanical ventilation or death from 4.6% to 12.3% in patients with normal respiratory vital signs, and from 16.8% to 31.5% in patients with abnormal respiratory vital signs (Figure 2 ). Looking at 14-day and 30-day outcome, these five variables (two respiratory vitals and three ECG abnormalities) continued to all be significant in multivariable regression. The pathway to outcome at 14 days for all patients is detailed in Figure 3 .
Table 2

Multivariable Logistic Regression Model to Predict Mechanical Ventilation or Death at 48 Hoursa

Odds ratio95% CIP
Age (per 10 years)1.080.91-1.2.31
Male1.300.86-1.96.21
Hypertension1.390.85-2.30.19
Diabetes1.561.01-2.40.042
Atrial fibrillation or flutter2.541.05-6.2.39
Right ventricular overload2.71.30-6.12.007
ST segment abnormality2.381.49-3.84<.001
Respiratory rate >20 breaths/min3.262.24-4.73<.001
Oxygen saturation ≤ 95%2.081.32-3.28<.001
Heart rate >100 beats/min1.30.88-1.93.194

Variables from Table 1 with P values less than .05 in univariable logistic regression were included in multivariable logistic regression and reported.

Figure 2

Electrocardiogram (ECG) abnormalities at time of presentation are prognostic of mechanical ventilation or death at 48 hours. The ability to prognosticate 48-hour outcome was assessed using the first ECG and vital signs recorded in the emergency department. Electrocardiogram abnormality was defined as the presence of atrial fibrillation or flutter, right ventricular hypertrophy or S1Q3T3, or any ST elevation or depression in two contiguous leads. Respiratory vital sign abnormality was defined as a respiratory rate greater than 20 breaths/min, saturation less than or equal to 95%, or requiring oxygen therapy by non-rebreather or full face mask. The absence of any of these ECG abnormalities and any respiratory abnormality made the likelihood of intubation or death at 48 hours less than 5%.

Figure 3

Sankey diagram represents patient flow from 3 days before severe acute respiratory coronavirus 2 diagnosis to 14 days after. All unique patient visits to the emergency department (ED) and inpatient (INPT) were included. On any given day, the patient’s location (home in green, ED in blue, INPT in yellow), if they were currently on a ventilator (No Vent or Vent), and if they were deceased (Died in red) were assessed. An interactive version of this diagram can be found at https://pelias1525.github.io/COVID_1200.html.

Multivariable Logistic Regression Model to Predict Mechanical Ventilation or Death at 48 Hoursa Variables from Table 1 with P values less than .05 in univariable logistic regression were included in multivariable logistic regression and reported. Electrocardiogram (ECG) abnormalities at time of presentation are prognostic of mechanical ventilation or death at 48 hours. The ability to prognosticate 48-hour outcome was assessed using the first ECG and vital signs recorded in the emergency department. Electrocardiogram abnormality was defined as the presence of atrial fibrillation or flutter, right ventricular hypertrophy or S1Q3T3, or any ST elevation or depression in two contiguous leads. Respiratory vital sign abnormality was defined as a respiratory rate greater than 20 breaths/min, saturation less than or equal to 95%, or requiring oxygen therapy by non-rebreather or full face mask. The absence of any of these ECG abnormalities and any respiratory abnormality made the likelihood of intubation or death at 48 hours less than 5%. Sankey diagram represents patient flow from 3 days before severe acute respiratory coronavirus 2 diagnosis to 14 days after. All unique patient visits to the emergency department (ED) and inpatient (INPT) were included. On any given day, the patient’s location (home in green, ED in blue, INPT in yellow), if they were currently on a ventilator (No Vent or Vent), and if they were deceased (Died in red) were assessed. An interactive version of this diagram can be found at https://pelias1525.github.io/COVID_1200.html.

Discussion

We analyzed 1258 patients with COVID-19 seen at three hospitals in New York City during the peak of the COVID-19 pandemic. The principal findings of this study include: 1) rapid clinical deterioration is common in admitted patients, with 53.4% of intubations occurring within 48 hours; 2) 33% of admitted patients either died or required mechanical ventilation within 14 days of COVID-19 diagnosis; and 3) combining abnormal ECG and abnormal respiratory vital signs quickly identifies a group of patients at high risk for mechanical ventilation or death. Myocardial injury is an important marker for severe COVID-19. ECG remains the simplest assessment for myocardial involvement. To our knowledge, no study on COVID-19 has had a majority of patients with ECGs performed at presentation and assessed its prognostic capacity. Although triage and management during a patient’s admission evolves when additional information such as laboratory values and imaging become available, it is important to be able to quickly screen patients upon arrival to the ED to plan for the level of care they may need. Abnormalities in initial vitals and presentation ECG can be detected rapidly in a range of clinical settings. More studies are needed to determine how initial presentation affects outcome beyond the most acute phase of COVID-19.

The Need for Rapid Triage in COVID-19 Patients

Understanding risk factors for COVID-19 severity remains critical because of a need for rapid triage as well as potentially guiding resource allocation. Studies have reported age, hypertension, diabetes, sequential organ failure assessment score, neutrophilia, elevated lactate dehydrogenase, and D-dimer as prognostic factors for patients with COVID-19. , A study from New York described male sex, obesity, elevated liver function tests, ferritin, and CRP as predictors of mechanical ventilation. In addition, cardiac injury, as measured by elevated troponin levels carries a particularly poor prognosis.10, 11, 12 The Brescia-COVID respiratory severity scale is the most easily applied decision tool developed to date, basing risk on presenting vital signs and chest radiograph, but it lacks input variables that point to extrapulmonary involvement which we believe are critical for effective triage. Unfortunately, the majority of risk factors identified so far are laboratory values that will not be immediately available upon presentation. Using data immediately available such as vital signs and ECG provides a quick, simple, and effective assessment of the patient’s prognosis. Herein, we reported a significant increase in event rate when abnormal ECG was incorporated into multivariable regression, with higher prognostic value than every other variable in the model except for abnormal respiratory vitals. We propose that in the setting of triaging COVID-19 patients in the ED, ECG be treated as a sixth vital sign.

Late Presentation of COVID-19 Patients

During this study period, the New York Department of Health found 962 deaths at home were from confirmed or suspected COVID-19 accounting for 9.3% of total COVID-19 deaths in New York City. Given these sobering statistics, our analysis of hospitalized patients may underestimate illness severity on presentation and raising concern that some patients may be seeking or receiving medical attention too late in their disease course. In the Wuhan experience, the median time of symptom onset to dyspnea was 5 days, symptom onset to hospital admission 7 days, and symptom onset to acute respiratory distress syndrome 8 days. A study including 655 of our patients found a median of 5 days of symptoms before presentation to the ED. Once respiratory symptoms develop in COVID-19, rapid clinical decline appears to be common. In addition to disease-specific factors, there are patient and medical system features that likely contribute to critical illness of presentation. The news media has highlighted hospital overcrowding and the importance of social distancing, which may make patients more likely to wait before contacting the medical system. When patients call their physicians with possible COVID-19–related symptoms, they are often encouraged to avoid medical attention due to concerns about either disseminating the virus or receiving a nosocomial infection. Considering more intubations occurred within the first 24 hours than any other day, patients who had respiratory symptoms for many days may have benefited from earlier assessment. It remains unclear if earlier presentation would have changed clinical outcome. The American College of Emergency Physicians among others has noted lack of evidence as the key hurdle to devising criteria for safe triage from the ED. Among those patients planned for admission, it remains a challenge to determine who is likely to decompensate requiring intensive care in the following days. Our study found that among a cohort of COVID-19 patients slated for admission, normal respiratory vitals and no evidence of atrial fibrillation/flutter, right ventricular overload, or ST segment deviation meant there was a less than 5% chance of poor outcome in the next 48 hours. Considering this population only included patients who were sick enough for admission, we believe these criteria can quickly and effectively determine who is safe for lower-acuity settings.

Study Limitations

As a retrospective analysis during an ongoing pandemic, this study has multiple limitations. First, at the time of data abstraction many patients remained hospitalized with their final outcomes unclear. To ensure equal exposure time, outcome was assessed at 48 hours and again at 14 days. It is likely that additional adverse outcomes will accumulate in these patients as their course progresses. To mitigate for this, we reassessed mortality 2 weeks past censoring at 30 days. Second, data were abstracted from the medical records, and it is probable that comorbidities were incompletely characterized. Third, this analysis begins at the time of presentation to the hospital. The timing of symptom onset was only captured in approximately half of these patients. Lastly, our institution only tested patients who were planned to be admitted, so this cohort does not reflect all patients presenting to the hospital with symptoms concerning for COVID-19.

Conclusion

Among 1258 patients with COVID-19, 247 (19.6%) met the primary outcome of mechanical ventilation or death 48 hours after diagnosis. Mortality increased to 231 (18.4%) patients at 48 hours and 277 (22.0%) patients when reassessed at 30 days. The combination of abnormal respiratory vital signs and ECG with presence of atrial fibrillation/flutter, right ventricular overload, or ST segment abnormality at presentation is easily obtained, highly prognostic of 48-hour outcome, and should form the basis of early triage for in-hospital level of care. More patients are intubated in the first 24 hours from presentation than any other day, indicating need for rapid triage and raising concerns that some patients are presenting late in their disease course. Further study is needed to clarify the mechanisms of cardiovascular involvement in COVID-19, identify ideal criteria for when patients should seek medical attention, and determine if earlier presentation would improve patient outcomes.
  15 in total

1.  Clinical Characteristics of 138 Hospitalized Patients With 2019 Novel Coronavirus-Infected Pneumonia in Wuhan, China.

Authors:  Dawei Wang; Bo Hu; Chang Hu; Fangfang Zhu; Xing Liu; Jing Zhang; Binbin Wang; Hui Xiang; Zhenshun Cheng; Yong Xiong; Yan Zhao; Yirong Li; Xinghuan Wang; Zhiyong Peng
Journal:  JAMA       Date:  2020-03-17       Impact factor: 56.272

Review 2.  COVID-19 and Cardiovascular Disease.

Authors:  Kevin J Clerkin; Justin A Fried; Jayant Raikhelkar; Gabriel Sayer; Jan M Griffin; Amirali Masoumi; Sneha S Jain; Daniel Burkhoff; Deepa Kumaraiah; LeRoy Rabbani; Allan Schwartz; Nir Uriel
Journal:  Circulation       Date:  2020-03-21       Impact factor: 29.690

3.  Association of Cardiac Injury With Mortality in Hospitalized Patients With COVID-19 in Wuhan, China.

Authors:  Shaobo Shi; Mu Qin; Bo Shen; Yuli Cai; Tao Liu; Fan Yang; Wei Gong; Xu Liu; Jinjun Liang; Qinyan Zhao; He Huang; Bo Yang; Congxin Huang
Journal:  JAMA Cardiol       Date:  2020-07-01       Impact factor: 14.676

4.  Risk Factors Associated With Acute Respiratory Distress Syndrome and Death in Patients With Coronavirus Disease 2019 Pneumonia in Wuhan, China.

Authors:  Chaomin Wu; Xiaoyan Chen; Yanping Cai; Jia'an Xia; Xing Zhou; Sha Xu; Hanping Huang; Li Zhang; Xia Zhou; Chunling Du; Yuye Zhang; Juan Song; Sijiao Wang; Yencheng Chao; Zeyong Yang; Jie Xu; Xin Zhou; Dechang Chen; Weining Xiong; Lei Xu; Feng Zhou; Jinjun Jiang; Chunxue Bai; Junhua Zheng; Yuanlin Song
Journal:  JAMA Intern Med       Date:  2020-07-01       Impact factor: 21.873

5.  Clinical features of patients infected with 2019 novel coronavirus in Wuhan, China.

Authors:  Chaolin Huang; Yeming Wang; Xingwang Li; Lili Ren; Jianping Zhao; Yi Hu; Li Zhang; Guohui Fan; Jiuyang Xu; Xiaoying Gu; Zhenshun Cheng; Ting Yu; Jiaan Xia; Yuan Wei; Wenjuan Wu; Xuelei Xie; Wen Yin; Hui Li; Min Liu; Yan Xiao; Hong Gao; Li Guo; Jungang Xie; Guangfa Wang; Rongmeng Jiang; Zhancheng Gao; Qi Jin; Jianwei Wang; Bin Cao
Journal:  Lancet       Date:  2020-01-24       Impact factor: 79.321

6.  Characterization and clinical course of 1000 patients with coronavirus disease 2019 in New York: retrospective case series.

Authors:  Michael G Argenziano; Samuel L Bruce; Cody L Slater; Jonathan R Tiao; Matthew R Baldwin; R Graham Barr; Bernard P Chang; Katherine H Chau; Justin J Choi; Nicholas Gavin; Parag Goyal; Angela M Mills; Ashmi A Patel; Marie-Laure S Romney; Monika M Safford; Neil W Schluger; Soumitra Sengupta; Magdalena E Sobieszczyk; Jason E Zucker; Paul A Asadourian; Fletcher M Bell; Rebekah Boyd; Matthew F Cohen; MacAlistair I Colquhoun; Lucy A Colville; Joseph H de Jonge; Lyle B Dershowitz; Shirin A Dey; Katherine A Eiseman; Zachary P Girvin; Daniella T Goni; Amro A Harb; Nicholas Herzik; Sarah Householder; Lara E Karaaslan; Heather Lee; Evan Lieberman; Andrew Ling; Ree Lu; Arthur Y Shou; Alexander C Sisti; Zachary E Snow; Colin P Sperring; Yuqing Xiong; Henry W Zhou; Karthik Natarajan; George Hripcsak; Ruijun Chen
Journal:  BMJ       Date:  2020-05-29

7.  The Variety of Cardiovascular Presentations of COVID-19.

Authors:  Justin A Fried; Kumudha Ramasubbu; Reema Bhatt; Veli K Topkara; Kevin J Clerkin; Evelyn Horn; LeRoy Rabbani; Daniel Brodie; Sneha S Jain; Ajay J Kirtane; Amirali Masoumi; Koji Takeda; Deepa Kumaraiah; Daniel Burkhoff; Martin Leon; Allan Schwartz; Nir Uriel; Gabriel Sayer
Journal:  Circulation       Date:  2020-04-03       Impact factor: 29.690

8.  Risk Factors of Fatal Outcome in Hospitalized Subjects With Coronavirus Disease 2019 From a Nationwide Analysis in China.

Authors:  Ruchong Chen; Wenhua Liang; Mei Jiang; Weijie Guan; Chen Zhan; Tao Wang; Chunli Tang; Ling Sang; Jiaxing Liu; Zhengyi Ni; Yu Hu; Lei Liu; Hong Shan; Chunliang Lei; Yixiang Peng; Li Wei; Yong Liu; Yahua Hu; Peng Peng; Jianming Wang; Jiyang Liu; Zhong Chen; Gang Li; Zhijian Zheng; Shaoqin Qiu; Jie Luo; Changjiang Ye; Shaoyong Zhu; Xiaoqing Liu; Linling Cheng; Feng Ye; Jinping Zheng; Nuofu Zhang; Yimin Li; Jianxing He; Shiyue Li; Nanshan Zhong
Journal:  Chest       Date:  2020-04-15       Impact factor: 9.410

9.  Covid-19 in Critically Ill Patients in the Seattle Region - Case Series.

Authors:  Pavan K Bhatraju; Bijan J Ghassemieh; Michelle Nichols; Richard Kim; Keith R Jerome; Arun K Nalla; Alexander L Greninger; Sudhakar Pipavath; Mark M Wurfel; Laura Evans; Patricia A Kritek; T Eoin West; Andrew Luks; Anthony Gerbino; Chris R Dale; Jason D Goldman; Shane O'Mahony; Carmen Mikacenic
Journal:  N Engl J Med       Date:  2020-03-30       Impact factor: 91.245

10.  An interactive web-based dashboard to track COVID-19 in real time.

Authors:  Ensheng Dong; Hongru Du; Lauren Gardner
Journal:  Lancet Infect Dis       Date:  2020-02-19       Impact factor: 25.071

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  18 in total

1.  Association of race/ethnicity and socioeconomic status with COVID-19 30-day mortality at a Philadelphia medical center using a retrospective cohort study.

Authors:  Dianna R Cheney-Peters; Crystal Y Lee; Shuji Mitsuhashi; Dina S Zaret; Joshua M Riley; Chantel M Venkataraman; Joseph W Schaefer; Brandon J George; Chris J Li; Christa M Smaltz; Conor G Bradley; Danielle M Fitzpatrick; David B Ney; Divya M Chalikonda; Joshua D Mairose; Kashyap Chauhan; Margaret V Szot; Robert B Jones; Rukaiya Bashir-Hamidu; Alan A Kubey
Journal:  J Med Virol       Date:  2021-10-11       Impact factor: 20.693

2.  Worldwide Survey of COVID-19-Associated Arrhythmias.

Authors:  Ellie J Coromilas; Stephanie Kochav; Isaac Goldenthal; Angelo Biviano; Hasan Garan; Seth Goldbarg; Joon-Hyuk Kim; Ilhwan Yeo; Cynthia Tracy; Shant Ayanian; Joseph Akar; Avinainder Singh; Shashank Jain; Leandro Zimerman; Maurício Pimentel; Stefan Osswald; Raphael Twerenbold; Nicolas Schaerli; Lia Crotti; Daniele Fabbri; Gianfranco Parati; Yi Li; Felipe Atienza; Eduardo Zatarain; Gary Tse; Keith Sai Kit Leung; Milton E Guevara-Valdivia; Carlos A Rivera-Santiago; Kyoko Soejima; Paolo De Filippo; Paola Ferrari; Giovanni Malanchini; Prapa Kanagaratnam; Saud Khawaja; Ghada W Mikhail; Mauricio Scanavacca; Ludhmila Abrahão Hajjar; Brenno Rizerio; Luciana Sacilotto; Reza Mollazadeh; Masoud Eslami; Vahideh Laleh Far; Anna Vittoria Mattioli; Giuseppe Boriani; Federico Migliore; Alberto Cipriani; Filippo Donato; Paolo Compagnucci; Michela Casella; Antonio Dello Russo; James Coromilas; Andrew Aboyme; Connor Galen O'Brien; Fatima Rodriguez; Paul J Wang; Aditi Naniwadekar; Melissa Moey; Chia Siang Kow; Wee Kooi Cheah; Angelo Auricchio; Giulio Conte; Jongmin Hwang; Seongwook Han; Pietro Enea Lazzerini; Federico Franchi; Amato Santoro; Pier Leopoldo Capecchi; Jose A Joglar; Anna G Rosenblatt; Marco Zardini; Serena Bricoli; Rosario Bonura; Julio Echarte-Morales; Tomás Benito-González; Carlos Minguito-Carazo; Felipe Fernández-Vázquez; Elaine Y Wan
Journal:  Circ Arrhythm Electrophysiol       Date:  2021-02-07

Review 3.  Electrocardiographic manifestations of COVID-19.

Authors:  Brit Long; William J Brady; Rachel E Bridwell; Mark Ramzy; Tim Montrief; Manpreet Singh; Michael Gottlieb
Journal:  Am J Emerg Med       Date:  2020-12-29       Impact factor: 2.469

4.  2021 Focused Update Consensus Guidelines of the Asia Pacific Heart Rhythm Society on Stroke Prevention in Atrial Fibrillation: Executive Summary.

Authors:  Tze-Fan Chao; Boyoung Joung; Yoshihide Takahashi; Toon Wei Lim; Eue-Keun Choi; Yi-Hsin Chan; Yutao Guo; Charn Sriratanasathavorn; Seil Oh; Ken Okumura; Gregory Y H Lip
Journal:  Thromb Haemost       Date:  2021-11-13       Impact factor: 5.249

Review 5.  Phenotypic heterogeneity of COVID-19 pneumonia: clinical and pathophysiological relevance of the vascular phenotype.

Authors:  Matteo Bertini; Emanuele D'Aniello; Luca Di Ienno; Federico Gibiino; Guido Tavazzi; Carlo Alberto Volta; Marco Contoli; Alberto Papi; Gianluca Campo; Roberto Ferrari; Claudio Rapezzi
Journal:  ESC Heart Fail       Date:  2021-11-10

6.  Unusual T-wave changes and extreme QTc prolongation in a 71-year-old man with asymptomatic COVID infection.

Authors:  Priyanka Anand; Jacob J Mayfield; Beixin He; Kavita B Khaira
Journal:  HeartRhythm Case Rep       Date:  2021-11-17

7.  Response of the authors regarding article "Electrocardiographic markers of increased risk of sudden cardiac death in patients with COVID-19 pneumonia".

Authors:  Mohammed Alareedh; Hussein Nafakhi; Foaad Shaghee; Ahmed Nafakhi
Journal:  Ann Noninvasive Electrocardiol       Date:  2021-07       Impact factor: 1.468

8.  Mortality Predictors in Patients Diagnosed with COVID-19 in the Emergency Department: ECG, Laboratory and CT.

Authors:  Aslı Türkay Kunt; Nalan Kozaci; Ebru Torun
Journal:  Medicina (Kaunas)       Date:  2021-06-17       Impact factor: 2.430

9.  Atrial fibrillation is related to higher mortality in COVID-19/SARS-CoV-2 pneumonia infection.

Authors:  Andrea Denegri; Marianna Morelli; Giuseppe Pezzuto; Vincenzo Livio Malavasi; Giuseppe Boriani
Journal:  Cardiol J       Date:  2021-09-15       Impact factor: 2.737

10.  Outcomes of atrial fibrillation in patients with COVID-19 pneumonia: A systematic review and meta-analysis.

Authors:  Ming-Yue Chen; Fang-Ping Xiao; Lin Kuai; Hai-Bo Zhou; Zhi-Qiang Jia; Meng Liu; Hao He; Mei Hong
Journal:  Am J Emerg Med       Date:  2021-09-24       Impact factor: 2.469

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