Abstract
Background
The information on electrocardiographic features of patients with coronavirus disease 2019 (COVID-19) is limited. Our aim was to determine if baseline electrocardiographic features of hospitalized COVID-19 patients are associated with markers of myocardial injury and clinical outcomes.
Methods
In this retrospective, single center cohort study, we included 223 hospitalized patients with laboratory-confirmed COVID-19. Clinical, electrocardiographic and laboratory data were collected and analyzed. Primary composite endpoint of mortality, need for invasive mechanical ventilation, or admission to the intensive care unit was assessed.
Results
Forty patients (17.9%) reached the primary composite endpoint. Patients with the primary composite endpoint were more likely to have wide QRS complex (>120 ms) and lateral ST-T segment abnormality. The multivariable Cox regression showed increasing odds of the primary composite endpoint associated with acute respiratory distress syndrome (odds ratio 7.76, 95% CI 2.67–22.59; p < 0.001), acute cardiac injury (odds ratio 3.14, 95% CI 1.26–7.99; p = 0.016), high flow oxygen therapy (odds ratio 2.43, 95% CI 1.05–5.62; p = 0.037) and QRS duration longer than >120 ms (odds ratio 3.62, 95% CI 1.39–9.380; p = 0.008) Patients with a wide QRS complex (>120 ms) had significantly higher median level of troponin T and pro-BNP than those without it. Patients with abnormality of lateral ST-T segment had significantly higher median level of troponin T and pro-BNP than patients without.
Conclusions
The presence of QRS duration longer than 120 ms and lateral ST-T segment abnormality were associated with worse clinical outcomes and higher levels of myocardial injury biomarkers.
Keywords: COVID-19, Electrocardiogram, Mortality, Myocardial injury, Wide QRS complex
Introduction
Novel coronavirus disease 2019 (COVID-19) has resulted in the deaths of more than 764 000 people worldwide as of August 15, 2020.1 Recently, cases of severe COVID-19 pneumonia have been independently associated with risk of mortality, and substantial evidence has demonstrated the presence of cardiac injury in patients with COVID-19.2 , 3 A recent study showed that 20% of COVID-19 patients with acute cardiac injury have higher mortality than COVID-19 patients without cardiac injury.4 However, electrocardiography (ECG) data were lacking from clinical examinations of patients in isolation wards or the intensive care units, which hinders the determination of the exact mechanisms of cardiac injury and the potential prediction of clinical outcome. Therefore, the present study retrospectively analyzed data from a tertiary referral university hospital in Istanbul, Turkey, to examine the potential association between baseline electrocardiographic findings and in-hospital outcome among patients with COVID-19 pneumonia.
Methods
Study design
The study was approved by the Ethics Committee of Istanbul Faculty of Medicine, Istanbul University and the Turkish Ministry of Health. The requirement of written informed consent was waived by the ethics committee of the designated hospital for patients with emerging infectious diseases. This retrospective cohort study included adult inpatients (≥18 years old) from Istanbul Faculty of Medicine, Istanbul University (Istanbul, Turkey). All adult patients who were diagnosed with having COVID-19 pneumonia according to the World Health Organization's (WHO's) interim guidance were screened, and those who died or were discharged between March 10, 2020, and June 10, 2020, were included in the study. Patients were excluded if they were suspected of having COVID-19 pneumonia but had a negative nasopharyngeal swab for SARS-CoV-2 were excluded from the study.
Data collection
SARS-CoV-2 nucleic acid was detected in all patients by real-time PCR to confirm the viral infection. Computed tomography was performed for the diagnosis of pneumonia. Patients’ medical records were carefully reviewed and analyzed by two trained physicians (A.N. and Z.G.D.). The patient data obtained included demographic information, comorbidities, signs and symptoms, laboratory results and complications. Patients’ comorbidities were extracted from the electronic health records, including hypertension, diabetes, coronary artery disease, cerebrovascular disease, chronic kidney disease, chronic obstructive pulmonary disease (COPD) and malignancy.
Standard 12-lead electrocardiograms were recorded with a speed of 25 mm/s and a gain of 10 mm/mV on the first day of admission and were manually evaluated by cardiologists (M.Y. and H. O.). ECGs were assessed for sinus rhythm or atrial fibrillation, axis deviation, presence of left ventricular hypertrophy, presence of ST segment changes (localized ST elevation or depression) or inverted T wave (deeper than 0.5 mm in leads -DΙ, -DΠ, and V3–V6), and presence of atrioventricular or bundle branch block. Left bundle branch block (LBBB), right bundle branch block (RBBB), and nonspecific intraventricular conduction disturbance (NICD) were defined according to the criteria of the American College of Cardiology Foundation and Heart Rhythm Society.5
Anterior leads were defined as leads V1-V4, the lateral leads were V5, V6, I, aVL and the inferior leads were II, III, and aVF. The QRS duration and QT interval were measured from leads of V1-V6, II, DIII, and aVF in digitized 12 lead ECG recordings using the on-screen digital caliper software Cardio Calipers version 3.3 (Iconico, Inc.). Interobserver correlation for determining QRS duration and QT intervals was assessed using the intraclass correlation coefficient (ICC) test, and a strong correlation between observers was found (ICC:0.94, p < 0.001).
The occurrence of complications was confirmed by three physicians (E.A.G., M.T. and D.D.) according to the following criteria. Sepsis and septic shock were defined according to the 2016 Third International Consensus Definition for Sepsis and Septic Shock.6 Acute kidney injury was defined in accordance with the KDIGO Clinical Practice Guidelines for Acute Kidney Injury as one of the following: an increase in serum creatinine by ≥0.3 mg/dl within 48 h, an increase in serum creatinine to ≥ 1.5 times baseline within the previous 7 days, or urine volume ≤ 0.5 ml/kg/h for 6 hours.7 Cardiac injury was defined by the serum levels of cardiac troponin T (cTnT) above the 99th percentile up of the reference limit. ARDS was defined using the parameters of timing, chest imaging, origin of edema and oxygenation in accordance with the Berlin definition.8 The clinical outcomes in hospital (i.e., discharges, mortality, and length of stay) were monitored up to June 10, 2020 (the final date follow-up date).
Statistical Analysis
Descriptive statistics were obtained for all study variables. All categorical variables were compared for the study outcome by using the Fisher exact test or χ2 test, and continuous variables were compared using the t test or the Mann-Whitney U test, as appropriate. The Kruskal-Wallis test was used to compare continuous variables between three or more groups. Continuous data are expressed as the mean (SD) or median (interquartile range [IQR]) values. Categorical data are expressed as proportions.
The clinical and laboratory variables that differed significantly in the comparative statistical analyses were included in a univariate Cox regression analysis. The models used in the univariate analysis were tested by the Likelihood ratio test, Wald test and score (log-rank) test. Multivariate Cox regressions were then performed for comorbidities, complications, laboratory, and ECG parameters. Multivariate Cox regression models were used to determine the independent risk factors for death during hospitalization. Data were analyzed using SPSS version 26.0 (IBM). For all the statistical analyses, p < 0.05 was considered significant and all testing was 2-sided.
Results
Patient Characteristics
From March 10, 2020, through June 10, 2020, 759 patients were hospitalized due to possible COVID-19 pneumonia. Of these patients, 626 patients underwent an ECG at or near the time of their admission. Among these patients, 225 were confirmed by PCR to have SARS-CoV-2. Two patients were excluded from the study due to the first presentation as being intracranial hemorrhage. Therefore, 223 patients were enrolled in our study.
The clinical characteristics and comorbidities of the patients are shown in Table 1 . The mean age was 57 ± 15 years, 40% were women, 37% of patients had hypertension, 26% had diabetes mellitus, 9% had coronary artery disease 2% had cerebrovascular disease and 2% had chronic heart failure. Other comorbidities were also present among patients: 8% of the patients had a history of malignancy, 6% had chronic renal failure and 5% had chronic obstructive pulmonary disease. The patients’ laboratory and radiological findings at admission are shown in Table 2 .
TABLE 1.
Baseline Characteristics, Symptoms and Comorbidities of Patients on Admission
| Characteristic | Patients, No. (%) |
|||
|---|---|---|---|---|
| All (n = 223) | Primary Composite Endpoint |
p Value | ||
| With (n = 40) | Without (n = 183) | |||
| Age, mean (SD) | 57 (15) | 65 (13) | 55 (15) | <0.001 |
| Female | 90 (40) | 11 (28) | 79 (43) | 0.067 |
| Signs and symptoms at admission | ||||
| Fever | 128 (57) | 25 (63) | 103 (56) | 0.702 |
| Cough | 163 (72) | 23 (58) | 140 (77) | 0.014 |
| Dyspnea | 94 (42) | 26 (65) | 68 (37) | 0.001 |
| Chronic medical illness | ||||
| Hypertension | 83 (37) | 21 (53) | 61 (33) | 0.023 |
| Diabetes mellitus | 58 (26) | 10 (25) | 48 (26) | 0.872 |
| Coronary artery disease | 20 (9) | 7 (18) | 13 (7) | 0.037 |
| Cerebrovascular disease | 5 (2) | 2 (5) | 3 (2) | 0.193 |
| Chronic heart failure | 5 (2) | 3 (8) | 2 (1) | 0.013 |
| Chronic renal failure | 14 (6) | 6 (15) | 8 (4) | 0.012 |
| COPD | 11 (5) | 4 (10) | 7 (4) | 0.102 |
| Malignancy | 18 (8) | 7 (18) | 11 (6) | 0.016 |
TABLE 2.
Baseline Laboratory and Radiologic Findings of Patients on Admission
| Laboratory findings at admission, median (IQR) | Patients, No. (%) |
|||
|---|---|---|---|---|
| All (n = 223) | Primary Composite Endpoint |
p Value | ||
| With (n = 40) | Without (n = 183) | |||
| Leukocytes/μL | 6100 (4400–7800) | 6795 (5237–9575) | 5800 (4330–7570) | 0.006 |
| Lymphocytes/μL | 1160 (850–1610) | 970 (592–1287) | 1200 (900–1650) | <0.001 |
| Neutrophils/μL | 3780 (2830–5770) | 5360 (3720–8435) | 3470 (2680–5400) | <0.001 |
| Hemoglobin, g/dL | 13.2 (12–14.2) | 12.7 (12.2–14.1) | 13.2 (12.0–14.1) | 0.898 |
| Platelets x103/μL | 194 (154–243) | 194 (152–306) | 193 (155–240) | 0.584 |
| C-reactive protein, mg/dL | 49 (21–91) | 98 (55–167) | 43 (17–77) | <0.001 |
| Procalcitonin, ng/mL | 0.09 (0.05–0.185) | 0.233 (0.115–0.455) | 0.08 (0.05–0.13) | <0.001 |
| High-sensitivity troponin T, pg/mL | 6 (3–14) | 17 (7–48) | 5 (3–11) | <0.001 |
| N-terminal pro-B-type natriuretic peptide, pg/mL | 97 (32–340) | 658 (195–1746) | 67 (25–186) | <0.001 |
| Creatinine, mg/dL | 0.88 (0.76–1.06) | 1.0 (0.8–1.3) | 0.9 (0.7–1.0) | <0.001 |
| Sodium, mEq/L | 138 (136–141) | 137 (135–140) | 138 (136–141) | 0.022 |
| Potassium, mEq/L | 4.2 (3.9–4.6) | 4.3 (3.8–4.7) | 4.2 (3.9–4.6) | 0.579 |
| Calcium, mg/dL | 8.7 (8.4–9.1) | 8.5 (8.1–8.8) | 8.8 (8.4–9.2) | 0.001 |
| Magnesium, mEq/L | 0.86 (0.80–0.92) | 0.83 (0.75–0.96) | 0.87 (0.80–0.91) | 0.540 |
| Alanine aminotransferase, U/L | 24 (15–38) | 28 (15–44) | 24 (15–37) | 0.475 |
| Aspartate aminotransferase, U/L | 28 (21–46) | 37 (24–57) | 27 (20–40) | 0.024 |
| Lactate dehydrogenase, U/L | 255 (212–340) | 364 (243–475) | 248 (209–308) | <0.001 |
| Albumin, g/dL | 3.9 (3.5–4.2) | 3.6 (3.1–4.0) | 4.0 (3.6–4.3) | <0.001 |
| D-dimer, µg/L | 725 (460–1340) | 1530 (775–385) | 660 (435–1070) | <0.001 |
| Ferritin, ng/mL | 322 (147–682) | 643 (222–1198) | 303 (133–584) | 0.001 |
| Chest computed tomography findings | 0.429 | |||
| Consolidation | 21 (9.4) | 2 (5) | 19 (10) | |
| Ground-glass opacity | 109 (48.9) | 23 (55) | 86 (47) | |
| Bilateral pulmonary infiltration | 81 (36.3) | 14 (33) | 67 (37) | |
Abbreviation: COPD, chronic obstructive pulmonary disease; IQR, interquartile range.
Electrocardiographic characteristics
The patients’ baseline electrocardiographic features are shown in Table 3 . The vast majority of patients were in sinus rhythm (99.1%), and only 1.8% of patients had atrial fibrillation. The median QRS duration was 88 ms (IQR, 80–96 ms), and the median corrected QT interval (using the Bazett formula) was 428 ms (IQR, 407–453 ms). A significant proportion (24.2%) had an abnormal axis (23.8% of patients had left axis deviation, and 0.4% had a right axis deviation). Furthermore, 8.4% had premature contractions (4.9% had atrial, and 3.5% had ventricular premature contractions).
TABLE 3.
Baseline Electrocardiographic Features, Complications and Clinical Outcomes of COVID-19 Patients
| Parameter | Patients, No. (%) |
|||
|---|---|---|---|---|
| All (n = 223) | Primary Composite Endpoint |
p Value | ||
| With (n = 40) | Without (n = 183) | |||
| PR duration, ms (IQR) | 160 (140–170) | 150 (133–168) | 160 (140–171) | 0.231 |
| QRS duration, ms (IQR) | 88 (80–96) | 90 (84–109) | 85 (80–95) | 0.013 |
| QTc (Bazett), ms (IQR) | 428 (407–453) | 451 (418–490) | 426 (403–449) | <0.001 |
| QTc (Framingham), ms (IQR) | 404 (384–449) | 419 (392–445) | 401 (382–422) | 0.011 |
| Wide QRS complex (>120 ms) | 21 (9.4) | 9 (22) | 12 (6.6) | 0.002 |
| Rhythm | ||||
| Sinus | 221 (99.1) | 39 (98) | 182 (99) | 0.908 |
| Atrial fibrillation | 4 (1.8) | 2 (5) | 2 (1) | 0.092 |
| Intraventricular conduction delay | 0.046 | |||
| RBBB | 13 (5.8) | 5 (13) | 8 (4) | 0.046 |
| LBBB | 3 (1.3) | 1 (3) | 1 (0.5) | 0.230 |
| Nonspecific intraventricular conduction delay | 9 (4) | 3 (8) | 5 (2.7) | 0.134 |
| Abnormal ST-T segment changes | ||||
| Inferior | 5 (2.2) | 1 (3) | 4 (2.2) | 0.920 |
| Anterior | 3 (1.3) | 1 (3) | 2 (1.1) | 0.484 |
| Lateral | 18 (8.1) | 10 (25) | 8 (4.4) | <0.001 |
| Extensive | 7 (3.1) | 2 (5) | 5 (2.7) | 0.424 |
| Pathologic Q wave | 0.690 | |||
| Inferior | 6 (2.7) | 2 (5) | 4 (2.2) | |
| Anterior | 1 (0.4) | 0 (0) | 1 (0.5) | |
| Lateral | 1 (0.4) | 0 (0) | 1 (0.5) | |
| Left ventricular hypertrophy (Cornell voltage) | 8 (3.6) | 4(10) | 4(2.2) | 0.025 |
| Axis | ||||
| Left axis deviation | 53 (23.8) | 14 (36) | 38 (20.8) | 0.046 |
| Right axis deviation | 1 (0.4) | 0 (0) | 1 (0.5) | 0.617 |
| Extrasystole | ||||
| Atrial | 11 (4.9%) | 3 (7.5%) | 7 (3.8%) | 0.317 |
| Ventricular | 8 (3.5%) | 4 (10%) | 4 (2.2%) | 0.016 |
| Complications | ||||
| Sepsis | 55 (24.7) | 30 (75) | 25 (13.7) | <0.001 |
| Septic shock | 22 (9.9) | 22 (55) | 0 (0) | <0.001 |
| ARDS | 32 (14.3) | 31 (78) | 1 (0.5) | <0.001 |
| Need for intensive care unit | 38 (17) | 38 (95) | 0(0) | <0.001 |
| Acute cardiac injury | 64 (28.6) | 32 (80) | 32 (17.5) | <0.001 |
| Arrhythmia | 7 (3.1) | 5(13) | 2 (1.1) | <0.001 |
| Acute heart failure | 16 (7.2) | 12 (30) | 4 (2.2) | <0.001 |
| Acute kidney injury | 21 (9.4) | 15 (38) | 6 (3.3) | <0.001 |
| Clinical outcome | ||||
| Median length of stay, days | 10 (7–14) | 21 (14–26) | 9 (7–12) | <0.001 |
| Discharged | 198 (88.8) | 15 (38) | 183 (100) | <0.001 |
| Died | 25 (11.1) | 25 (63) | 0 (0) | <0.001 |
Abbreviation: ARDS, acute respiratory distress syndrome; LBBB, left bundle branch block; RBBB, right bundle branch block
Abnormal intraventricular conduction was found in 11.1%, with RBBB in 5.8%, left bundle branch block in 1.3%, and nonspecific intraventricular conduction delay in 4%. Evidence of a previous Q-wave myocardial infarction was present in 3.5%. Left ventricular hypertrophy (Cornell voltage) was found in 3.6% of patients. A significant proportion (14.6%) had repolarization abnormality: 8.1% had lateral, 3.1% had extensive, 2.2% had inferior and 1.3% had anterior ST-T segment abnormality.
Treatment, complications and clinical outcome
The patients’ treatment data are summarized in Supplementary Table 1. During follow-up, a total of 40 patients (17.9%) reached the primary composite endpoint of mortality, need for invasive mechanical ventilation or admission to the intensive care unit. The median time to reach the endpoint was 8 days (IQR, 3–11 days). A total of 25 patients (11.1%) died, and 198 patients (88.8%) were discharged. Complications were more common among patients with the primary composite endpoint than those it and included sepsis (30 [75%] vs. 25 [13.7%]; p < 0.001), septic shock (22 [55%] vs. 0 [0%]; p < 0.001), ARDS (31 [78%] vs. 1 [0.5%]; p < 0.001), acute kidney injury (15 [38%] vs. 6 [3.3%]; p < 0.001), acute cardiac injury (32 [80%] vs 32 [17.5%]; p < 0.001), acute heart failure (12 [30%] vs. 4 [2.2%]; p < 0.001) and arrhythmia (5 [13%] vs. 2 [1.1%]; p < 0.001) (Table 3).
The relationship between electrocardiographic parameters and clinical outcomes
ECG findings of a wide QRS complex (>120 ms) and lateral ST-T segment abnormality were more common in patients with the primary composite endpoint than those without it [{9/40 (22%) vs. 12/171 (6.6 %); p = 0.002}, {10/40 (25%) vs. 8/171 (4.4%); p < 0.001}, respectively]. Wide QRS complex was able to predict worse clinical outcomes with a sensitivity of 22.5%, specificity of 93.4%, positive predictive value of 42.8%, and negative predictive value 84.7%. Lateral ST-T segment abnormality was able to predict the primary composite endpoint with a sensitivity of 25%, specificity of 95.5%, positive predict value of 55.6%, and negative predictive value of 85.3%. The multivariable Cox regression showed increasing odds of the primary composite endpoint associated with acute respiratory distress syndrome (odds ratio 7.76, 95% CI 2.67–22.59; p < 0.001), acute cardiac injury (odds ratio 3.14, 95% CI 1.26–7.99; p = 0.016), high flow oxygen therapy (odds ratio 2.43, 95% CI 1.05–5.62; p = 0.037), and QRS duration longer than >120 ms (odds ratio 3.62, 95% CI 1.39–9.380; p = 0.008) (Table 4).
TABLE 4.
Multivariate Cox Regression Analysis on the Risk Factors Associated with the Primary Composite Endpoint in Patients with COVID-19
| Hazard Ratio (95% CI) | p Value | |
|---|---|---|
| Age | 1.018 (0.986–1.050) | 0.270 |
| Cardiovascular diseases | 0.583 (0.192–1.767) | 0.340 |
| Chronic kidney failure | 1.701 (0.480–6.029) | 0.340 |
| Hypertension | 1.395 (0.574–3.389) | 0.463 |
| Acute cardiac injury | 3.141 (1.235–7.991) | 0.016 |
| Acute respiratory distress syndrome | 7.817 (3.175–19.243) | <0.001 |
| High flow oxygen therapy | 2.432 (1.054–5.615) | 0.037 |
| Malignancy | 1.819 (0.632–5.235) | 0.268 |
| Wide QRS complex (>120 ms) | 3.428 (1.401–8.385) | 0.007 |
Patients with a wide QRS complex (>120 ms) had a significantly higher median level of troponin T (14,1 pg/mL [IQR, 7,6–38 pg/mL] vs. 5,8 pg/mL [IQR, 3–12 pg/mL]; p < 0.001) and pro-BNP (346 pg/mL [IQR, 58–1363 pg/mL] vs. 87 pg/mL [IQR, 31–261 pg/mL]; p = 0.033) than patients without it (Table 5 ; Figs. 1 A, B). Patients with abnormality of the lateral ST segment had a significantly higher median level of troponin T (27 pg/mL [9–49 pg/mL] vs. 5,8 pg/mL [3–11.9 pg/mL]; p = 0.003) and pro-BNP (839 pg/mL [237–1720 pg/mL] vs. 73 pg/mL [30–216 pg/mL]; p = 0.001) than patients without it (Table 6 ; Figs. 1C, D).
TABLE 5.
Comparison of Levels of Myocardial Injury Biomarkers between Patients with a Wide QRS complex and Patients without it
| Patients with Wide QRS Complex (n = 21) | Patients without Wide QRS Complex (n =198) | p Value | |
|---|---|---|---|
| Troponin T, median, pg/mL | 14,1 (7,6–37,9) | 5,8 (3–12) | <0.001 |
| Pro-BNP, median, pg/mL | 346 (58–1363) | 87 (31–261) | 0.033 |
Figure 1.
A. Bar graph demonstrating statistically significant higher level of median high sensitive troponin T in patients with a wide QRS complex (>120 ms) compared to patients without it. B. Bar graph showing statistically significant higher level of median pro-BNP in patients with a wide QRS complex (>120 ms) compared to patients without it. C. Comparison of median high sensitive troponin T levels among patients with various ST-T segment abnormality. D. Comparison of median pro-BNP levels among patients with various ST-T segment abnormality.
TABLE 6.
Comparison of Levels of Myocardial Injury Biomarkers among Patients with Different Repolarization Abnormality
| None (n = 189) | Inferior (n = 5) | Anterior (n = 3) | Lateral (n = 18) | Extensive (n = 7) | p Value | |
|---|---|---|---|---|---|---|
| Troponin T, median, pg/mL | 5,8 (3–11.9) | 6,14 (4,4–7,1) | 10,6 (7,5–25,8) | 27 (9–49) | 13,7 (3,7–49) | 0.003 |
| Pro-BNP, median, pg/mL | 73 (30–216) | 47 (19–185) | 283 (16–550) | 839 (237–1720) | 356 (72–1585) | 0.001 |
Discussion
The present study retrospectively analyzed hospitalized COVID-19 patients in terms of the relationship between baseline ECG parameters and the primary composite endpoint of mortality, need for invasive mechanical ventilation or admission to the intensive care unit. We found out that median corrected QT interval and QRS duration were longer in patients with the primary endpoint than in patients without it. In addition, left axis deviation, left ventricular hypertrophy, ventricular premature contractions and lateral ST-T segment abnormality were more common in patients with the primary endpoint.
Recently, in a study on 756-patient, McCullough et al. reported, that intraventricular conduction block, repolarization abnormalities and RBBB in COVID-19 patients were associated with an increased risk of mortality.9 In comparison, the presence of a wide QRS complex (>120 ms) was associated with 3.43-fold increased odds of worse clinical outcome in our study. Consistently, Ukena et al. reported that a QRS width greater than 120 ms in duration in acute myocarditis is associated with a substantial risk of cardiac death or need for heart transplantation.10 In our study, patients with a wide QRS complex in the baseline ECG had higher levels of troponin T and pro-BNP than patients without it.
Compared to patients without the primary composite endpoint, those with the endpoint were more likely to have acute cardiac injury in our study. Likewise, cardiac involvement was evident in a retrospective cohort study on 191 adult patients in Wuhan, China. Among the non-survivors (54 patients), 59% had acute cardiac injury.11 A prospective cohort study in Wuhan, China, analyzed laboratory findings from 416 hospitalized patients diagnosed with COVID-19. Of this cohort, 19.7% of the patients had cardiac injury, and required both invasive and non-invasive mechanical ventilation more frequently than patients without cardiac injury. Complications and mortality were also more common in patients with cardiac injury.4 It is plausible that cardiac injury related to COVID-19 plays a crucial role in the pathophysiology of the disease.
Another striking finding of our study was that the patients with lateral ST-T segment abnormality had higher levels of troponin T and pro-BNP than patients without. Lateral ST-T segment abnormality was associated with worse clinical outcomes. Shi et al.4 recently reported that ECGs performed during a period of elevated cardiac biomarkers showed ST-T segment changes compatible with myocardial ischemia in COVID-19 patients. They concluded that observed cardiac injury may be a result of type two myocardial infarction, secondary to ischemia triggered by a mismatch between oxygen supply and demand caused by the severe respiratory illness. Furthermore, it is also possible that the virus's direct impact on the cells can lead to myocarditis.4
It has been hypothesized that indirect inflammatory mechanisms are more likely related to the cardiac complications associated with COVID-19.12 However, Tavazzi et al. demonstrated the first case of biopsy-proven myocardial localization of coronavirus in a COVID-19 patient with cardiogenic shock.13 Other possible mechanisms of myocardial injury include myocardial interstitial fibrosis, interferon mediated immune response, increased cytokine response by helper T cells, coronary plaque destabilization, and apoptosis-induced cellular damage.14 , 15
Moreover, Algohbani reported a case of acute myocarditis caused by the Middle East Respiratory Syndrome coronavirus (MERS-CoV), which was characterized by myocardial edema and injury in the apical and lateral segments in cardiac magnetic resonance imaging.16 Therefore, we hypothesize that the similar regional myocardial damage in infections caused by viruses from the same family may contribute to our understanding of the pathophysiology of myocardial injury in COVID-19 patients. Future imaging studies examining the myocardial damage in COVID-19 represent an important and uncharted area for investigation.
Our study has several strengths. First, we enrolled in only hospitalized patients who had PCR-proven COVID-19 pneumonia. Second, every patient underwent troponin T and pro-BNP level measurements. On the other hand, there were several limitations in the present study. First, because the patients were clinically observed only during hospital stay, so we cannot extrapolate the findings to outpatient settings or longer durations. Second, due to retrospective nature of this study, some parameters were not available for all patients, and in-hospital medications might not have been fully recorded. Third, the information from follow-up ECGs to detect dynamic changes would have increased the power of the study.
Moreover, because we could not obtain prior ECGs for all patients, we were not able to make a comparison between baseline and prior ECGs for detecting dynamic changes. In addition, routine cardiac imaging of every hospitalized COVID-19 patient would have added invaluable information about the correlation with ECG findings. However, this was impossible because of the highly contagious nature of the disease. Nevertheless, our data are consistent with growing data that myocardial involvement has a significant role in the prognosis of COVID-19.17 , 18
Our data demonstrate that ECG may be a useful tool in COVID-19, not only for measuring the QT interval, but also for predicting the prognosis of the hospitalized patients. The presence of a wide QRS complex (>120 ms) and lateral ST-T segment abnormality in the baseline ECG are associated with worse clinical outcomes and elevated levels of myocardial injury biomarkers. Such findings should alert the physicians and warrant closer monitoring of patients.
Acknowledgements
We would like thank all doctors, nurses, and other health providers at Istanbul Faculty of Medicine who were involved in taking care of COVID-19 patients. AO and TT accept full responsibility for the accuracy and the integrity of the data as the guarantor of this work and they contributed equally.
Footnotes
Conflict of Interest: None declared.
Supplementary material associated with this article can be found, in the online version, at https://doi.org/10.1016/j.amjms.2020.12.012.
Appendix. SUPPLEMENTARY MATERIALS
References
- 1.COVID-19 dashboard; 2020. The Center for Systems Science and Engineering at Johns Hopkins University.https://coronavirus.jhu.edu/map.html Available at. Accessed August 15, 2020. [Google Scholar]
- 2.Wang D, Hu B, Hu C, Zhu F, Liu X, Zhang J, Wang B, Xiang H, Cheng Z, Xiong Y, Zhao Y, Li Y, Wang X, Peng Z. JAMA. 2020;323:1061–1069. doi: 10.1001/jama.2020.1585. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 3.Huang C, Wang Y, Li X, Ren L, Zhao J, Hu Y, Zhang L, Fan G, Xu J, Gu X, Cheng Z, Yu T, Xia J, Wei Y, Wu W, Xie X, Yin W, Li H, Liu M, Xiao Y, Gao H, Guo L, Xie J, Wang G, Jiang R, Gao Z, Jin Q, Wang J, Cao B. Clinical features of patients infected with 2019 novel coronavirus in Wuhan. China Lancet. 2020;395:497–506. doi: 10.1016/S0140-6736(20)30183-5. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 4.Shi S, Qin M, Shen B, Cai Y, Liu T, Yang F, Gong W, Liu X, Liang J, Zhao Q, Huang H, Yang B, Huang C. Association of cardiac injury with mortality in hospitalized patients with COVID-19 in Wuhan, China. JAMA Cardiol. 2020;5:802–810. doi: 10.1001/jamacardio.2020.0950. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 5.Surawicz B, Childers R, Deal BJ, Gettes LS, Bailey JJ, Gorgels A, Hancock EW, Josephson M, Kligfield P, Kors JA, Macfarlane P, Mason JW, Mirvis DM, Okin P, Pahlm O, Rautaharju PM, van Herpen G, Wagner GS, Wellens H. AHA/ACCF/HRS recommendations for the standardization and interpretation of the electrocardiogram. Part III: intraventricular conduction disturbances a scientific statement from the American Heart Association Electrocardiography and Arrhythmias Committee. J Am Coll Cardiol. 2009;53:976–981. doi: 10.1016/j.jacc.2008.12.013. [DOI] [PubMed] [Google Scholar]
- 6.Singer M, Deutschman CS, Seymour CW, Shankar-Hari M, Annane D, Bauer M, Bellomo R, Bernard GR, Chiche JD, Coopersmith CM, Hotchkiss RS, Levy MM, Marshall JC, Martin GS, Opal SM, Rubenfeld GD, van der Poll T, Vincent JL, Angus DC. The third international consensus definitions for sepsis and septic shock (sepsis-3) JAMA. 2016;315:801–810. doi: 10.1001/jama.2016.0287. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 7.Khwaja A. KDIGO clinical practice guidelines for acute kidney injury. Nephron - Clin Pract. 2012;120:c179–c184. doi: 10.1159/000339789. [DOI] [PubMed] [Google Scholar]
- 8.Definition Task Force ARDS, Ranieri VM, Rubenfeld GD, Thompson BT, Ferguson ND, Caldwell E, Fan E, Camporota L, Slutsky AS. Acute respiratory distress syndrome: The Berlin definition. JAMA. 2012;307:2526–2533. doi: 10.1001/jama.2012.5669. [DOI] [PubMed] [Google Scholar]
- 9.McCullough SA, Goyal P, Krishnan U, Choi JJ, Safford MM, Okin PM. Electrocardiographic Findings in COVID-19: Insights on Mortality and Underlying Myocardial Processes. J Card Fail. 2020;26:626–632. doi: 10.1016/j.cardfail.2020.06.005. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 10.Ukena C, Mahfoud F, Kindermann I, Kandolf R, Kindermann M, Böhm M. Prognostic electrocardiographic parameters in patients with suspected myocarditis. Eur J Heart Fail. 2011;13:398–405. doi: 10.1093/eurjhf/hfq229. [DOI] [PubMed] [Google Scholar]
- 11.Zhou F, Yu T, Du R, Fan G, Liu Y, Liu Z, Xiang J, Wang Y, Song B, Gu X, Guan L, Wei Y, Li H, Wu X, Xu J, Tu S, Zhang Y, Chen H, Cao B. Clinical course and risk factors for mortality of adult inpatients with COVID-19 in Wuhan, China: a retrospective cohort study. Lancet. 2020;395:1054–1062. doi: 10.1016/S0140-6736(20)30566-3. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 12.Atallah B, Mallah SI, AbdelWareth L, AlMahmeed W, Fonarow GC. A marker of systemic inflammation or direct cardiac injury: should cardiac troponin levels be monitored in COVID-19 patients? Eur Heart Journal Qual Care Clin Outcomes. 2020;6:204–207. doi: 10.1093/ehjqcco/qcaa033. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 13.Tavazzi G, Pellegrini C, Maurelli M, Belliato M, Sciutti F, Bottazzi A, Sepe PA, Resasco T, Camporotondo R, Bruno R, Baldanti F, Paolucci S, Pelenghi S, Iotti GA, Mojoli F, Arbustini E. Myocardial localization of coronavirus in COVID-19 cardiogenic shock. Eur J Heart Fail. 2020;22:911–915. doi: 10.1002/ejhf.1828. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 14.Babapoor-Farrokhran S, Gill D, Walker J, Rasekhi RT, Bozorgnia B, Amanullah A. Myocardial injury and COVID-19: Possible mechanisms. Life Sci. 2020;253 doi: 10.1016/j.lfs.2020.117723. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 15.Centurión OA, Scavenius KE, García LB, Torales JM, Miño LM. Potential mechanisms of cardiac injury and common pathways of inflammation in patients with COVID-19. Crit Pathw Cardiol. 2020 doi: 10.1097/HPC.0000000000000227. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 16.Alhogbani T. Acute myocarditis associated with novel Middle East respiratory syndrome coronavirus. Ann Saudi Med. 2016;36:78–80. doi: 10.5144/0256-4947.2016.78. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 17.Guo T, Fan Y, Chen M, Wu X, Zhang L, He T, Wang H, Wan J, Wang X, Lu Z. Cardiovascular implications of fatal outcomes of patients with Coronavirus Disease 2019 (COVID-19) JAMA Cardiol. 2020;5:1–8. doi: 10.1001/jamacardio.2020.1017. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 18.Tersalvi G, Vicenzi M, Calabretta D, Biasco L, Pedrazzini G, Winterton D. Elevated Troponin in patients with Coronavirus Disease 2019: possible mechanisms. J Card Fail. 2020;26:470–475. doi: 10.1016/j.cardfail.2020.04.009. [DOI] [PMC free article] [PubMed] [Google Scholar]
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