Front. Cardiovasc. Med.Frontiers in Cardiovascular MedicineFront. Cardiovasc. Med.2297-055XFrontiers Media S.A.10.3389/fcvm.2022.1039655Cardiovascular MedicineOriginal ResearchMyocardial injury and its correlation to mortality in hospitalized COVID-19 patients: A retrospective cohort studyAbabnehMuhannad J.1*Al-KasasbehAbdullah1JarrahMohamad1MalkawiLujain2SandukaOmar3SmadiAreje M.3SmadiMahmoud M.41Division of Cardiology, Department of Internal Medicine, Faculty of Medicine, Jordan University of Science and Technology, Irbid, Jordan2Department of Internal Medicine, Faculty of Medicine, Jordan University of Science and Technology, Irbid, Jordan3Faculty of Medicine, Jordan University of Science and Technology, Irbid, Jordan4Department of Mathematics and Statistics, Jordan University of Science and Technology, Irbid, Jordan
Edited by: Amit K. Dey, National Institutes of Health (NIH), United States
Reviewed by: Kumar Ashish, CarolinaEast Medical Center, United States; Anubhav Jain, Michigan State University, United States
*Correspondence: Muhannad J. Ababneh, mjababneh@just.edu.jo
This article was submitted to Cardiovascular Epidemiology and Prevention, a section of the journal Frontiers in Cardiovascular Medicine
This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
Purpose
This retrospective observational study was conducted to assess the clinical characteristics and outcomes of hospitalized COVID-19 patients with positive cardiac enzymes in the King Abdullah University Hospital (KAUH) in Irbid, Jordan.
Patients and methods
A total of 676 patients admitted to KAUH for moderate-to-severe COVID-19 were included in the study. Clinical and mortality data were collected from patients’ electronic medical records.
Results
A significant association was found between myocardial injury and In-hospital mortality. Seven comorbidities were identified as risk factors for myocardial injury: Hypertension, diabetes mellitus (DM), previous cerebrovascular accident (CVA), ischemic heart disease (IHD), heart failure, chronic kidney disease (CKD), and cardiac arrhythmias. The need for intensive care unit (ICU) for invasive ventilation was also associated with myocardial injury. Acute kidney injury (AKI) during hospitalization had a significantly higher incidence of myocardial injury and mortality. Acute myocardial infarction (MI) and acute peripheral vascular disease (PVD) were also associated with higher mortality.
Conclusion
Myocardial injury is an important predictor of mortality in patients with moderate-to-severe COVID-19 disease. Patients with a history of hypertension, diabetes mellitus, any vascular diseases, cardiac arrhythmias or heart failure are considered high-risk for adverse outcome. Additionally, COVID-19 patients with myocardial injury and acute kidney injury were recognized with the highest mortality rate.
The COVID-19 pandemic remains to be a global health crisis. Attempts from the scientific community to better understand this disease continue to reveal new characteristics of the novel coronavirus (SARS-CoV-2), ranging from diagnostic challenges to disease mechanisms. Initially thought of as a solely respiratory disease, manifestations of COVID-19 in different organ systems are constantly being reported. While several healthcare professionals and institutions have described vascular thrombotic complications (1), other studies reporting gastrointestinal (2), neurological (3), and cardiac (4) events have emerged. Despite the growing body of literature on the cardiovascular manifestations of moderate-to-severe COVID-19 disease, many questions remain unanswered. More research is needed to better understand the risk, mechanisms, and outcomes of cardiac disease associated with COVID-19 infections.
In the current literature, there has been increasing evidence suggesting cardiovascular involvement in COVID-19 disease. A recent meta-analysis of 35 studies has estimated the frequency of newly developed acute cardiac injury in COVID-19 patients to be more than 25%, in addition to other manifestations such as heart failure and arrhythmias (5). Similar evidence has led other studies to investigate elevation in cardiac biomarkers, such as troponin I, as a potential prognostic factor. A meta-analysis of 10 studies found that 51% of patients with poor outcomes had elevated serum troponin I levels, suggesting that troponin I, and possibly other cardiac biomarkers, could be utilized as a valuable predictor of severe COVID-19 disease (6). Poor outcomes were defined by need for intensive care unit (ICU) admission, oxygen saturation below 90%, invasive mechanical ventilation and in-hospital mortality (6). Another study of 100 patients who had echocardiographic investigations found that 39% of patients had right ventricular dilation and dysfunction and that elevated troponin I levels were associated with worse right ventricular function (7). The mechanisms of myocardial injury in COVID-19 infections remain unclear. There have been a few case reports of COVID-19 infections complicated by myocarditis, though there is no evidence ruling out other pathologies such as supply/demand mismatch and systemic inflammation (8, 9). It is important to note that myocardial injury has been observed in cases of acute respiratory distress syndrome (ARDS) unrelated to the novel coronavirus. A prospective cohort study in 2017 revealed that high-sensitivity troponin I (hsTroponin I) was detectable in 94% of patients with ARDS (10). This suggests that direct cardiotoxicity may not be necessary for myocardial injury in COVID-19 patients, since ARDS in general can cause an elevation in serum hsTroponin I. Despite the increasing evidence of myocardial injury in COVID-19 infections, current understanding of the prognostic value of such findings is quite poor. This calls for further research to assess both the outcomes and initial clinical characteristics of those patients. Additionally, none of the studies assessing cardiac biomarkers in COVID-19 patients was conducted in the MENA region (Middle East and North Africa), which indicates that studies in the region are needed to improve our understanding of this disease and its impacts on this population, and to make similar results obtained from other researcher generalisable.
Materials and methods
In this work, the retrospective cohort study approach was adopted for analysis of COVID-19 patients hospitalized in King Abdullah University Hospital (KAUH). King Abdullah University Hospital (affiliated with Jordan University of Science and Technology), is a tertiary referral center that serves patients from North of Jordan, the majority of them are Arabs. The indication for admission were the existing of severe hypoxia defined as O2 saturation below 90% or patients with other comorbidities and clinical instability. The targeted group were investigated for elevated troponin I levels and/or electrocardiogram (ECG) abnormalities during the period between 1 September and 31 December 2020. Data were collected from the patients’ electronic medical records. The parameters used in the study included demographic information, hospital admission duration, full medical history including presenting illness, past medical and surgical history, physical exam findings, vital signs, ECG findings, serum troponin I (normal range 0.0–0.02 ng/ml) and other biomarker levels [c reactive protein (CRP), and creatine kinase MB (CK-MB)], intensive care unit (ICU) admission, use of mechanical ventilation, occurrence of acute complications during hospitalization (cardiac infarction, cerebral or peripheral vascular complications, and acute kidney injury), and in-hospital mortality.
Descriptive statistics were used to summarize and determine the sample patients’ characteristics and distribution of patients’ data. Among descriptive statistics, we determined the range, mean, standard deviation (S.D), and median for the continuous variables and counts, percentages, and cross tabulation for the categorical variables. Also, we presented visual examination of data using clustered bar charts and error bar charts. Inferential statistics were also used to assess associations between categorical variables and group comparisons between quantitative variables. Associations between two or more qualitative data variables were assessed using Fishers exact test and Cramer’s V test. Quantitative data between more independent groups were analyzed using two independent samples t-test and One-way ANOVA procedure. Multivariate binary logistic regression was conducted to assess the influence of different qualitative and quantitative risk variables associated with different outcomes. All P-values presented were two-tailed, and P-values < 0.05 were considered as statistically significant. All statistical analyses were performed using statistical package SPSS 21.0 (SPSS Inc., Chicago, IL).
Results and discussionPatients’ characteristics
A total of 676 patients were included in the study, 56.8% of which were males. Their ages ranged between 16 and 96 years, with a mean of 64.50 ± 13.99 years. Analysis of the data showed that 38 patients are smokers (5.7%), including 6 female smokers (2.1%) out of 292 female patients and 32 male smokers (8.4%) out of 384 male patients. The recorded comorbidity rates of hypertension (HTN), diabetes mellitus (DM), pre-diabetes mellitus (pre-DM), pulmonary disease, hypercholesterolemia, ischemic heart disease (IHD), previous cerebrovascular accident (CVA), peripheral vascular disease (PVD), and chronic kidney disease (CKD) are shown in Table 1. Patients with positive cardiac enzymes were 50% of all included patients; 5% were in the myocardial infarction group including STEMI and NSTEMI (infarction group), and 45% were considered as myocardial injury group (injury group), the remaining 50% without elevation in cardiac enzymes were considered as no injury group. The Pie chart in Figure 1 demonstrates the distribution in the three study groups.
Demographic characteristics of patients.
Variable
Count (%)
Gender
Male
384 (56.8%)
Female
292 (43.2%)
Smoking status
Yes
38 (5.7%)
No
631 (94.3%)
Hypertension
Yes
433 (64.1%)
No
236 (34.9%)
Diabetes mellitus
Yes
350 (51.8%)
No
319 (47.2%)
Pre-diabetes mellitus
Yes
11 (1.6%)
No
658 (98.4)
Hypercholesterolemia
Yes
31 (4.6%)
No
638 (95.4%)
Pulmonary disease
Yes
46 (6.9%)
No
623 (93.1%)
Previous cerebrovascular accident
Yes
51 (7.6%)
No
618 (92.4%)
Ischemic heart disease
Yes
139 (20.6%)
No
530 (78.4%)
Peripheral vascular disease
Yes
21 (3.1%)
No
648 (96.9%)
Heart failure
Yes
76 (11.4%)
No
593 (88.6%)
Chronic kidney disease
Yes
86 (12.9%)
No
583 (87.1%)
Pie chart of patient groups (no injury, injury, and infarction).
Characteristics of patients with positive cardiac enzymes
The patients were categorized into three groups according to their serial cardiac enzymes levels and clinical history notes. Patients with elevation in their cardiac enzymes without evidence of Myocardial infarction (MI) were categorized into the “injury” group. Patients with elevation in their cardiac enzymes in addition to clinical evidence of MI were classified as the “infarction” group. Clinical evidence of MI is defined as the presence of typical chest pain with ST elevation in ECG, ischemic ECG changes or changes in myocardial function (echocardiography). Patients who did not have elevation in their cardiac enzymes or evidence of infarction were set as the “no injury” group. A univariate analysis was conducted to assess the effect of different predictors on myocardial injury using Fisher exact test; the results are shown in Table 2. The following predictors were found to be statistically significant in predicting myocardial injury: Hypertension (p-value < 0.001), diabetes mellitus (p-value = < 0.001), previous CVA (p-value = 0.008), IHD (p-value < 0.001), HF (p-value < 0.001), CKD (p-value < 0.001), and pre-existing arrhythmia (p-value = 0.005).
Association between patient groups (no injury, injury, and infarction) and patients’ characteristics.
Variable
Patient group
P-value
No injury
Injury
Infarction
Gender
Male
182
185
17
0.11
Female
160
117
15
Hypertension
Yes
192
217
24
<0.001
No
144
84
8
Diabetes mellitus
Yes
149
179
22
<0.001
No
187
122
10
Pre-diabetes mellitus
Yes
8
3
0
0.295
No
328
298
32
Smoking status
Yes
16
21
1
0.394
No
320
280
31
Hypercholesterolemia
Yes
14
14
3
0.408
No
322
287
29
Pulmonary disease
Yes
24
22
0
0.288
No
312
279
32
Previous cerebrovascular accident
Yes
15
33
3
0.008
No
321
268
29
Ischemic heart disease
Yes
46
81
12
<0.001
No
290
220
20
Peripheral vascular disease
Yes
7
11
3
0.061
No
329
290
29
Heart failure
Yes
12
56
8
<0.001
No
324
245
24
Chronic kidney disease
Yes
12
71
3
<0.001
No
324
230
29
Pre-existing arrhythmia
Yes
11
20
5
0.005
No
331
282
27
Multivariate binary logistic regression analysis was performed to assess the significance of a combination of different risk factors on myocardial injury (1: injury, 0: no injury). The candidate risk factors considered in the analysis were: Age, Hypertension (HTN), diabetes mellitus (DM), Smoking status, Hypercholesterolemia, pulmonary disease, previous cerebrovascular accident (CVA), ischemic heart disease (IHD), peripheral vascular disease (PVD), heart failure (HF), chronic kidney injury (CKD), and Pre-existing arrhythmia. A significant logistic regression equation was found using 14 predictors with an Nagelkerke R2 = 39.3%. The significant predictors for myocardial injury were gender, age, HF, DM, and CKD.
A univariate analysis was conducted to assess the effect of different predictors (patient admission for >24 h, ICU admission, and invasive ventilation) on the patient groups (injury, infarction, and no injury) using Cramer’s V test. The results are shown in Table 3. The following variables were found to be statistically significant predictors of myocardial injury: ICU admission and invasive ventilation with p-values < 0.001. Using one-WAY ANOVA procedure, significant differences were found for O2 saturation on admission, while no significant differences for the remaining vital signs on admission (respiratory rate, temperature, systolic blood pressure, and diastolic blood pressure), as depicted in Table 3.
Association and group comparisons between patient groups (injury, infarction, and no injury) and ICU admission, hospital admission for >24 h, invasive ventilation, and vital signs on admission.
Attribute
n (%)
Patient groups
P-value
Injury
Infarction
No injury
Patient admitted for >24 h
Yes
646 (97.14%)
290
32
324
0.401
No
19 (2.86%)
7
0
12
ICU admission
Yes
176 (26.4%)
108
17
51
<0.001
No
485 (73.6%)
185
15
285
Invasive ventilation
Yes
127 (19.33%)
79
10
38
<0.001
No
530 (80.67%)
215
20
295
Respiratory rate on admission
N
266
27
302
0.072
Mean value
21.97
21.22
21.46
S.D
2.79
2.819
2.818
Temperature on admission
N
290
30
330
0.143
Mean value
37.16
37.22
37.28
S.D
0.748
0.646
0.99
Systolic blood pressure on admission
N
297
31
31
0.108
Mean value
130.86
129.14
129.16
S.D
22.316
19.295
19.413
Diastolic blood pressure on admission
N
297
31
330
0.368
Mean value
74.94
75.58
76.1
S.D
11.92
9.605
8.563
O2 saturation on admission
N
258
30
309
<0.001
Mean value
85.2
85.30
89.4
S.D
12.099
11.052
7.051
N, number of patients; S.D, standard deviation.
In the stacked bar chart in Figure 2 we can demonstrate a significant correlation for the need of invasive mechanical ventilation in patients with myocardial involvement (injury of infarction).
Stacked bar chart of invasive ventilation vs. patient groups.
Error bar plot of O2 saturation on admission in the different patient groups is also shown in Figure 3.
Error bar plot of O2 saturation on admission against patient groups.
Mortality and patient groups (injury, no injury, STEMI, and NSTEMI)
The “infarction” patient group was subdivided into two further groups according to their ECG findings: ST segment elevation MI (STEMI) and non-ST segment elevation MI (NSTEMI). A contingency table of mortality vs. patient groups (injury, no injury, STEMI, and NSTEMI) is shown in Table 4. A significant association between mortality and patient groups was detected with p-value < 0.001 using Cramer’s V test.
Contingency table of mortality and patient groups (injury, no injury, STEMI, and NSTEMI).
Counts and %
Patient groups
Total
No injury
Injury
STEMI
NSTEMI
Mortality
Count
58
142
5
13
218
% within patient group
17.0%
47.0%
83.3%
50.0%
32.2%
% of total patients
8.6%
21.0%
0.7%
1.9%
32.2%
% of mortality
26.6%
65%
2.3%
6%
100%
Mortality with intensive care unit admission and invasive ventilation
To study the association between mortality and patients’ clinical findings, a univariate analysis was conducted to assess the effect of different predictors (patient admission for >24 h, ICU admission, and invasive ventilation) on the mortality using Fishers exact test. The results are shown in Table 5. The following predictors were found to be statistically significant in predicting mortality: Patient admission for >24 h (p-value = 0.025), ICU admission, and invasive ventilation with p-values < 0.001.
Association and group comparisons of mortality with hospital admission for >24 h, ICU admission, and invasive ventilation.
Variable
n (%)
Mortality
P-value
No
Yes
Patient admitted for >24 h
Yes
646 (97.14%)
430
216
0.025
No
19 (2.86%)
17
2
Total
665
ICU admission
Yes
176 (26.63%)
19
157
<0.001
No
485 (73.37%)
428
57
Total
661
Invasive ventilation
Yes
127 (19.33%)
5
122
<0.001
No
530 (80.67%)
440
90
Total
657
Multivariate binary logistic regression analysis shows the significance of the risk factors patient admission for >24 h, ICU admission, and invasive ventilation on mortality and yields Nagelkerke measure of R2 = 67.9%.
Mortality and myocardial injury in patients with acute complications
The incidence of acute MI, acute kidney injury (AKI), acute peripheral vascular disease (PVD), and acute CVA was recorded. Table 6 demonstrates the incidence of acute complications and mortality during patients’ hospital stay:
Incidence of acute complications and mortality.
Mortality
Yes
218 (32.2%)
No
458 (67.8%)
Acute MI
Yes
20 (3%)
No
641 (97%)
Acute CVA
Ischemic CVA
5 (0.8%)
Unspecified CVA
3 (0.5%)
No CVA
654 (98.8%)
Acute peripheral vascular disease (PVD)
Yes
11 (1.7%)
No
652 (98.3%)
Acute kidney injury (AKI)a
Yes
102 (15.4%)
No
560 (84.6%)
aAKI as defined by KDIGO—as an increase in baseline serum creatinine of either 1.5 times over 7 days or 26.5 mmol/L over 48 h, or documented oliguria (urine output of <0.5 mL/kg/h).
Statistical analyses were performed to investigate the association between the incidence of acute complications during hospitalization with myocardial injury (described as the three patient groups) (Table 7) and mortality (Table 8). Using Cramer’s V test, the incidence of acute kidney injury (AKI) was significantly associated with myocardial injury (p-value = <0.001).
Acute complications and patient groups (no injury, injury, and infarction).
Acute complication
Incidence
Patient group
P-value
No injury
Injury
Infarction
Acute kidney injury (AKI)a
Yes
20
71
11
<0.001
No
315
224
21
Acute CVA
Ischemic CVA
1
4
0
0.52
Unspecified CVA
1
2
0
No
332
290
32
Acute PVD
Yes
5
6
0
0.656
No
330
290
32
aAKI as defined by KDIGO—as an increase in baseline serum creatinine of either 1.5 times over 7 days or 26.5 mmol/L over 48 h, or documented oliguria (urine output of <0.5 mL/kg/h).
Acute complications and mortality.
Complication
Mortality
P-value
Yes
No
Acute MI
Yes
16
4
<0.001
No
205
446
Acute Kidney Injury (AKI)a
Yes
79
25
<0.001
No
143
425
Acute CVA
Ischemic
3
2
0.194
Unspecified
2
1
No
215
448
Acute PVD
Yes
7
4
0.034
No
214
448
aAKI as defined by KDIGO—as an increase in baseline serum creatinine of either 1.5 times over 7 days or 26.5 mmol/L over 48 h, or documented oliguria (urine output of <0.5 mL/kg/h).
Using Fisher’s exact test, a significant association was found between mortality and the incidence of acute MI, AKI, and acute PVD. No significant association was found between mortality and acute CVA using Cramer’s V test. The results are displayed in Table 8.
Conclusion
The study demonstrates that myocardial injury, represented by elevation in serum troponin I, is an important predictor of mortality in patients with moderate-to-severe COVID-19 disease. Specifically, patients who are expected to suffer myocardial injury according to the findings are those with a medical history of hypertension, DM, CVA, IHD, heart failure, CKD, or cardiac arrhythmias. An early testing for elevated cardiac biomarkers (troponin I) can be used as a predictor for adverse outcome and complications and help in patients triage and need for admission.
The study also suggests that patients who require ICU admission, invasive ventilation, or both should have their serum troponin I levels monitored regularly during their hospital stay, as these readings can be a significant predictor of mortality.
The incidence of AKI during hospitalization was identified as a poor prognostic factor, as it was highly associated with myocardial injury and a higher In-hospital mortality. Other complications that were associated with higher In-hospital mortality were acute MI and acute PVD.
According to the findings of this study and considering the reports of cardiac complications of COVID-19 in the literature, a thorough investigation into the mechanisms of myocardial injury in COVID-19 disease would be recommended. We would also suggest further research of the incidence, pathophysiology, and potential predictors of AKI in COVID-19 patients.
Limitations
The authors believe that the prevalence of smokers in this study (5.7%) was underreported; a 2014 national survey by the World Health Organization found the prevalence of smokers in the Jordanian population to be around 32.3% (11). We hypothesize that this underestimation was due to underreporting, or incomplete documentation in the electronic records. The authors also believe that the prevalence of hypercholesterolemia in the study (4.6%) was below the actual figure due to lack of primary screening in the local community.
Data availability statement
The raw data supporting the conclusions of this article will be made available by the authors, without undue reservation.
Ethics statement
The collection and use of patients’ data was approved by the Institutional Review Board (IRB) of Jordan University of Science and Technology (JUST) and King Abdullah University Hospital (KAUH). Written informed consent for participation was not required for this study in accordance with the national legislation and the institutional requirements.
Author contributions
MA: primary investigator, IRB proposal, supervising data collection and analysis, and manuscript writing and editing. AA-K and MJ: supervising data collection and manuscript preparation. LM: IRB proposal, supervising data collection and manuscript preparation. OS: data collection, and manuscript writing and editing. AS: statistical analysis and manuscript editing. MS: supervising data collection, statistical analysis, and manuscript preparation. All authors contributed to the article and approved the submitted version.
We would like to thank our dedicated colleagues and students for their valuable contribution in data collection: Abdallah M. S. Aljabeiti, Noor A. Qasem, Rama S. K. Alqatarneh, and Qusai A. K. A. Ali (Jordan University of Science and Technology—Graduate Students—School of Medicine).
Conflict of interest
The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.
Publisher’s note
All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.
AbbreviationsKAUH
King Abdullah University Hospital
HTN
hypertension
DM
diabetes mellitus
MI
myocardial infarction
CKD
chronic kidney disease
IHD
ischemic heart disease
PVD
peripheral vascular disease
CVA
cerebrovascular accident
AKI
acute kidney injury
ICU
intensive care unit
STEMI
ST elevation myocardial infarction
NSTEMI
non-ST elevation myocardial infarction.
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