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. 2022 Dec 14;76:25–30. doi: 10.1016/j.pcad.2022.12.002

Impact of COVID-19 in patients hospitalized with stress cardiomyopathy: A nationwide analysis

Adrija Hajra a, Aaqib Malik b, Dhrubajyoti Bandyopadhyay b,⁎, Akshay Goel b, Ameesh Isath b, Rahul Gupta c, Suraj Krishnan d, Devesh Rai e, Chayakrit Krittanawong f, Salim S Virani g, Gregg C Fonarow h, Carl J Lavie i
PMCID: PMC9749379  PMID: 36528166

Abstract

Stress cardiomyopathy was noted to occur at a higher incidence during coronavirus disease of 2019 (COVID-19) pandemic. This database analysis has been done to compare the in-hospital outcomes in patients with stress cardiomyopathy and concurrent COVID-19 infection with those without COVID-19 infection. The National Inpatient Sample database for the year 2020 was queried to identify all admissions diagnosed with stress cardiomyopathy. These patients were then stratified based on whether they had concomitant COVID-19 infection or not. A 1:1 propensity score matching was performed. Multivariate logistic regression analysis was done to identify predictors of mortality. We identified 41,290 hospitalizations for stress cardiomyopathy, including 1665 patients with concurrent diagnosis of COVID-19. The female preponderance was significantly lower in patients with stress cardiomyopathy and COVID-19. Patients with concomitant COVID-19 were more likely to be African American, diabetic and have chronic kidney disease. After propensity matching, the incidence of complications, including acute kidney injury (AKI), AKI requiring dialysis, coagulopathy, sepsis, cardiogenic shock, cases with prolonged intubation of >24 h, requirement of vasopressor and inpatient mortality, were noted to be significantly higher in patients with COVID-19. Concomitant COVID-19 infection was independently associated with worse outcomes and increased mortality in patients hospitalized with stress cardiomyopathy.

Keywords: Covid, Acute coronary syndrome, Stress cardiomyopathy, Congestive heart failure

List of abbreviations

AKI Acute kidney injury
aOR Adjusted odds ratio
COVID 19 Coronavirus disease of 2019
CV Cardiovascular
CKD Chronic kidney disease
COPD Chronic obstructive pulmonary disease
CABG Coronary artery bypass graft
CI Confidence interval
CHF Congestive heart failure
DVT Deep vein thrombosis
ECMO Extracorporeal membrane oxygenation
HCUP Healthcare Cost and Utilization Project
HMO Health Maintenance Organization
HD Hemodialysis
HTN Hypertension
ICD-10-CM International Classification of Diseases, Tenth Revision, Clinical Modification
IABP Intra-aortic balloon pump
IFNγ Interferon-gamma
IL1B Interleukin 1B
IQR Interquartile range
LOS Length of hospital stay
MI Myocardial infarction
NIS Nationwide Inpatient Sample
PE Pulmonary embolism
PCI Percutaneous coronary intervention
SNF/NH/IC Skilled nursing facility/nursing home/ intermediate care
TNFα Tissue necrosis factor alpha
USD United States dollar
UTI Urinary tract infection
VT Ventricular tachycardia
VF Ventricular fibrillation
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Introduction

The coronavirus disease of 2019 (COVID-19) pandemic has various cardiovascular (CV) manifestations, including myocardial injury, arrhythmias, cardiac arrests, heart failure, and coagulation abnormality.1 , 2 Cases of stress cardiomyopathy have also been reported in COVID-19 patients. The incidence of stress cardiomyopathy has drawn attention among clinicians for its significant effects on patient management and treatment.3 Since its clinical discovery, the pathogenesis of stress cardiomyopathy remains unclear. Systemic viral illnesses, including influenza, have been noted to be associated with stress cardiomyopathy, and cases have been reported in COVID-19-affected individuals, particularly patients with severe disease.4 But data are sparse regarding the baseline characteristics, risk factors associated with inpatient morbidity, and mortality in stress cardiomyopathy patients affected with COVID-19. We have conducted a population-based analysis using a large nationally representative database to compare the characteristics and outcomes of adult patients hospitalized with stress cardiomyopathy with and without concomitant COVID-19 in the United States (US). We also aimed to determine the clinical predictors of adverse outcomes in stress cardiomyopathy patients with COVID-19.

Methods

Data source

The Healthcare Cost and Utilization Project (HCUP) Nationwide Inpatient Sample (NIS) database is the largest all-payer inpatient dataset in the US and is available publicly. The NIS represents 95% of US hospitalizations from 44 states participating in HCUP and provides a stratified sample of 20% of discharges, including up to 8 million hospital discharges per year. The NIS database has been previously demonstrated to correlate well with other discharge databases in the US. In addition, it has been validated in various studies to provide reliable estimates of admissions within the US.5

Study population

We included hospitalizations with a diagnosis of stress cardiomyopathy based on the International Classification of Diseases, Tenth Revision, Clinical Modification (ICD-10-CM) code (I51. 81) which has positive predictive value of 98% and identified patients with and without a concurrent diagnosis of COVID-19 based on ICD-10-CM code U07.1.6

Outcomes

The primary outcome of interest was in-hospital mortality in patients with stress cardiomyopathy with concurrent COVID-19 infection compared with those with stress cardiomyopathy without concurrent COVID-19 infection. Secondary outcomes included AKI as well as, AKI requiring dialysis, acute respiratory failure as well as, respiratory failure requiring intubation, need for mechanical circulatory support such as intra-aortic balloon pump (IABP) (and/or impella), extracorporeal membrane oxygenation (ECMO), length of stay (LOS) and hospitalization costs.

Statistical analysis

Statistical analyses were performed using Stata 16.0 (StataCorp. 2019. Stata Statistical Software: Release 16. College Station, TX: StataCorp LLC). The discharge weights provided by the Agency for Healthcare Research and Quality were applied to obtain weighted numbers to calculate national estimates.

A 1:1 propensity score matching was performed to compare outcomes for patients with concomitant stress cardiomyopathy and COVID-19 and patients with stress cardiomyopathy without concomitant COVID-19 using a propensity score calculated based on a multivariable logistic regression model. Propensity score matching without a replacement was performed in a 1:1 nearest-neighbor fashion with a caliper width of 0.1 of the estimated propensity scores. Multivariate logistic regression models were generated to identify the independent predictors and were reported as adjusted odds ratio (aOR) with 95% confidence interval (CI). Categorical variables were expressed as percentages. Continuous variables were expressed as median and interquartile range. Categorical variables were compared using the Pearson chi-square test, while continuous variables were compared using the student's t-test. All reported P values are 2-sided, with a value of <0.05 considered significant.

Results

A total of 41,290 hospitalizations for stress cardiomyopathy were identified, of which 1665 patients (4%) had a concurrent diagnosis of COVID-19. Table 1 describes the baseline characteristics of patients admitted with COVID-19. Stress cardiomyopathy patients with COVID-19 had a mean age of 71 years compared to a mean age of 68 years in stress cardiomyopathy patients without COVID-19. Approximately, 12.3% of patients in the COVID-19 group were African American vs. 8.2% of patients without COVID-19. Before propensity matching, stress cardiomyopathy hospitalizations with COVID-19 had higher prevalence of diabetes mellitus (39.0 vs. 24.5%, p-value <0.001), chronic kidney disease (CKD) (23.1% vs. 15%, p-value <0.001), coagulopathy (22.2% vs. 9.5%, p-value <0.001). Around 5.4% of stress cardiomyopathy patients with COVID-19 had a smoking history (18.6% in patients without COVID-19, p-value <0.001). Approximately, 44.2% of stress cardiomyopathy patients with COVID-19 had a history of coronary artery disease (31.2% in patients without COVID-19, p-value <0.001). The cost of hospitalization was higher, and the LOS was longer in patients with COVID-19, with statistical significance. Table 2 shows the complications and outcomes of stress cardiomyopathy patients with and without COVID-19 infection. Inpatient mortality was higher in COVID-19 affected patients than patients without COVID-19 (33.9% vs. 7.3%, p-value <0.001). Incidence of acute kidney injury (AKI) (48.1% vs. 25.2%) and AKI leading to hemodialysis (6.6% vs. 2.2%), myocarditis (5.7% vs. 0.4%), respiratory failure with intubation of >24 h (25.5% vs. 15.8%), cardiogenic shock (16.5% vs. 7.0%), requirement of vasopressors (12.3% vs. 5.6%), sepsis (44.4% vs. 18.7%) is more in patients with COVID-19 compared to patients without COVID-19 with p-value of <0.001 (Table 2).

Table 1.

Baseline characteristics of patients with COVID-19 and stress cardiomyopathy before and after propensity match with complications of hospitalized patients.

Before Matching
 After Matching
Characteristics Without COVID-19 With COVID-19 P Value Without COVID-19 With COVID-19 P Value
39,625 1665 1620 1620
Age, median IQR, years 68 (58–77) 71 (61–78) 0.0391 72 (61–81) 71 (61–78) 0.1094
Age groups
18–59 10,785 380.00 0.1057 345 370 0.0300
60–69 10,355 405.00 375 390
70–79 10,750 540.00 415 525
>79 years 7735 340.00 485 335
Female 32,040 1035 <0.001 1085 1030 0.3584
Caucasian race 3250 205 0.0113 255 200 0.2017
African American race 2425 325 <0.001 305 295 0.8303
Hispanics 2015 125 0.0552 130 115 0.6599
Atrial fibrillation 6535 330 0.1058 340 315 0.5984
Diabetes mellitus 9690 650 <0.001 660 620 0.4938
Hypertension 25,955 1110 0.6534 1070 1075 0.9297
Chronic kidney disease 5930 385 <0.001 390 375 0.7819
CHF 18,590 830 0.2811 845 800 0.4582
Peripheral vascular disease 3375 110 0.2317 110 110 0.9999
Dementia 2310 190 <0.001 220 185 0.3744
COPD 12,480 525 0.9891 480 515 0.5495
Valvular heart disease 1035 145 0.3796 150 145 0.8847
Arrhythmias 14,645 640 0.5790 675 625 0.4128
Liver disease 3520 190 0.1114 205 180 0.5403
Hypothyroidism 7205 245 0.1059 280 240 0.3767
Anemia 2155 115 0.2572 165 110 0.0947
Cancer 3665 75 0.002 60 75 0.5651
Rheumatological disorders 2195 70 0.2954 55 70 0.5174
Weight loss 5910 250 0.9606 280 230 0.2729
Coagulopathy 3770 370 <0.001 300 340 0.4387
Obesity 5155 345 0.0001 260 335 0.1122
Smoking history 7385 90 <0.001 95 90 0.8610
Coronary artery disease 17,510 520 <0.001 540 520 0.7393
Prior stroke 3870 180 0.5245 205 180 0.5230
Prior PCI 1915 80 0.9810 55 80 0.3277
Prior CABG 600 25 0.9850 15 25 0.4742
Alcohol 2420 20 0.0002 20 20 0.9999
Prior MI 4615 135 0.0537 200 135 0.0868



Discharge
Routine 20,380 425 <0.001 655 420 <0.001
SNF/NH/IC 7515 390 380 380
Home healthcare 7375 220 280 210
Length of stay, median (IQR), days 4 (2–8) 8 (4–16) <0.001 5 (2–9) 8 (4–16) <0.001
Weekend admission 9560 470 0.0862 330 460 0.0196
Elective admission 2540 35 0.0049 85 35 0.0468



Hospital location and teaching status
Prior CABG 600 25 0.9850 15 25 0.4742
Alcohol 2420 20 0.0002 20 20 0.9999
Prior MI 4615 135 0.0537 200 135 0.0868



Discharge
Routine 20,380 425 <0.001 655 420 <0.001
SNF/NH/IC 7515 390 380 380
Home healthcare 7375 220 280 210
Length of stay, median (IQR), days 4 (2–8) 8 (4–16) <0.001 5 (2–9) 8 (4–16) <0.001
Weekend admission 9560 470 0.0862 330 460 0.0196
Elective admission 2540 35 0.0049 85 35 0.0468



Hospital location and teaching status
Prior CABG 600 25 0.9850 15 25 0.4742
Alcohol 2420 20 0.0002 20 20 0.9999
Prior MI 4615 135 0.0537 200 135 0.0868



Discharge
Routine 20,380 425 <0.001 655 420 <0.001
SNF/NH/IC 7515 390 380 380
Home healthcare 7375 220 280 210
Length of stay, median (IQR), days 4 (2–8) 8 (4–16) <0.001 5 (2–9) 8 (4–16) <0.001
Weekend admission 9560 470 0.0862 330 460 0.0196
Elective admission 2540 35 0.0049 85 35 0.0468



Hospital location and teaching status
Rural 2380 105 0.3293 100 100 0.9599
Urban non-teaching 6470 220 230 220
Urban teaching 30,775 1340 1290 1300
Hospital region
Northeast 8265 380 0.0235 320 375 0.2712
Midwest 9235 490 570 470
South 13,535 450 385 445
West 8590 345 345 330



Insurance
Medicare 24,610 1040 0.1626 1070 1015 0.1769
Medicaid 4745 175 220 175
Private including HMO 8090 340 260 325
Self-pay 1175 40 30 40



Median household income (%)
0–25th percentile 9830 415 0.6795 405 405 0.8133
26–50th percentile 10,510 475 445 450
51–75th percentile 9770 420 445 415
76–100th percentile 8775 325 275 320
Total hospital cost USD median IQR 14,892 (9152–28,180) 25,887 (11438–56,742) <0.001 18,753 (9396–34,557) 25,864 (11206–56,327) 0.0013



Hospital bed size
Small 7515 315 0.4478 270 295 0.4633
Intermediate 10,770 400 340 390
Large 21,340 950 1010 935
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CABG- coronary artery bypass graft, CHF- congestive heart failure, COVID 19- coronavirus disease 2019, CKD- chronic kidney disease, COPD- chronic obstructive pulmonary disease, HMO- health maintenance organization, MI- myocardial infarction, PCI- percutaneous coronary intervention, SNF/NH/IC- skilled nursing facility/nursing home/ intermediate care.

Table 2.

Complication of hospitalized patients with Takotsubo cardiomyopathy with or without COVID-19.

Before Matching
 After Matching
Complications Without COVID-19 With COVID-19 P Value Without COVID-19 With COVID-19 P Value
AKI 9990 800 <0.001 595 780 0.0042
AKI leading to HD 855 110 <0.001 100 105 0.8667
UTI 4605 235 0.1529 250 225 0.5556
Sepsis 7425 740 <0.001 465 715 <0.001
DVT 910 85 0.0015 65 80 0.5769
PE 735 50 0.1369 45 50 0.8069
Stroke in-hospital 1075 25 0.1786 60 25 0.0678
Cardiogenic shock 2785 275 <0.001 205 265 0.1772
Cardiac arrest 1700 145 0.0002 80 145 0.0364
VT 2340 90 0.6967 110 90 0.5011
VF 765 15 0.1775 25 15 0.4805
Bleeding requiring transfusion 2025 145 0.0029 120 130 0.7442
Death 2895 565 <0.001 220 545 <0.001
Vasopressors 2205 205 <0.001 130 200 0.0572
Prolonged intubations >24 h 5710 625 <0.001 345 600 <0.001
Respiratory failure 13,910 945 <0.001 605 930 <0.001
Resp failure with intubation >24 h 6265 425 <0.001 365 420 <0.001
ECMO utilization 80 5 0.6986 5 5 0.999
Impella 165 10 0.6131 0 10 0.1572
IABP 250 15 0.5480 20 15 0.7055
CABG 100 0 0.3576 NA NA NA
PCI 1140 30 0.2459 35 30 0.7639
Tamponade 105 10 0.2577 5 10 0.5621
Acute heart failure 1335 5 0.0020 40 5 0.0185
Myocarditis 155 95 <0.001 5 90 0.0185
HTN crises 1705 25 0.0122 45 25 0.2767
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AKI- acute kidney injury, COVID 19- coronavirus disease 2019, CABG- coronary artery bypass graft, DVT- deep vein thrombosis, ECMO- extracorporeal membrane oxygenation, HD- hemodialysis, HTN- hypertension, IABP- intra-aortic balloon pump, MI- myocardial infarction, PCI- percutaneous coronary intervention, PE- pulmonary embolism, UTI- urinary tract infection, VT- ventricular tachycardia, VF- ventricular fibrillation,

Propensity score matching was performed to create a more balanced population, with 1620 hospitalizations in each group. In a propensity score-matched population, stress cardiomyopathy patients with COVID-19 had a higher incidence of in-hospital mortality than stress cardiomyopathy patients without COVID-19 (33.6% vs.13.6%, respectively; aOR 3.22, CI 2.19–4.72, p < 0.001). In addition, sepsis, respiratory failure, respiratory failure requiring prolonged intubation for >24 h, cases with prolonged intubation and length of stay were significantly higher in stress cardiomyopathy patients with COVID-19, even after propensity match.

There was an increase in the number of stress cardiomyopathy hospitalizations with concomitant COVID-19 throughout the year. The risk of in-hospital mortality was highest for those admitted earlier in the year, and decreased after the initial months, with another peak in the later part of the year (Fig. 1 ).

Fig. 1.

Fig. 1

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Incidence by month, mortality by month and percentage died of total admissions with COVID-19.

COVID 19- coronavirus disease of 2019.

Predictors of mortality

On multivariable regression analysis, COVID-19 was found to be independently associated with mortality in patients admitted with stress cardiomyopathy (aOR 6.10, 95% CI 4.62–8.05, p-value <0.001). Additionally, arrhythmias (aOR 1.56, CI 1.33–1.84, p-value <0.001), coagulopathy (aOR 2.55, 95% CI 2.06–3.15, p-value <0.001), and liver disease (aOR 2.59, 95% CI 2.086–3.23, p-value <0.001) were found to be independently associated with increased odds of mortality in stress cardiomyopathy patients with concurrent COVID-19 infection (Table 3 ).

Table 3.

Predictors of mortality after multivariate analysis.

Variable Odds Ratio Lower Limit Upper Limit P Value
COVID 19 6.102 4.624 8.054 <0.001
Age 0.659 0.545 0.798 <0.001
CKD 1.237 1.000 1.529 0.0500
Coagulopathy 2.548 2.062 3.149 <0.001
Weight loss 1.435 1.157 1.778 0.0010
Arrhythmias 1.566 1.332 1.841 <0.001
Liver disease 2.597 2.086 3.233 <0.001
Cancer 2.117 1.678 2.67
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COVID 19- coronavirus disease 2019, CKD- chronic kidney disease.

Discussion

To the best of our knowledge, this is the first analysis of nationwide data to report the characteristics and outcomes of patients with stress cardiomyopathy and concomitant COVID-19 infection. Stress cardiomyopathy is known to be more common in female patients.7 Interestingly, we found a lower number of female patients with stress cardiomyopathy in the COVID-19 affected group. Stress cardiomyopathy, previously known as Takotsubo cardiomyopathy, is caused by intense emotional or physical stress leading to rapid deterioration of cardiac function.8 , 9 Various possible mechanisms like sympathetic nervous system stimulation, estrogen deficiency, and excess deposition of extracellular matrix have been found to contribute to the pathogenesis of stress cardiomyopathy. COVID-19, complicated with multiorgan failure, shock, and profound hypoxia with adult respiratory distress syndrome, is hypothesized to trigger stress cardiomyopathy due to catecholamine surge. Direct myocardial injury in COVID-19 is also postulated to contribute to the pathogenesis of stress cardiomyopathy.10 Patients with COVID-19 have elevated levels of proinflammatory cytokines such as interleukin 1B (IL1B), interferon-gamma (IFNγ), and tumor necrosis factor alpha (TNFα). The cytokine storm, and physical and chemical stressors with postmenopausal status, could also contribute to the development of stress cardiomyopathy.4 , 11 , 12 A recent study by Zuin et al. showed an increased incidence of stress cardiomyopathy during the pandemic compared to control groups.13 Generalized increases in psychological distress, cytokine storm, increased sympathetic responses in patients with COVID-19, and microvascular dysfunction may result in this increased incidence.13 , 14 In our study, stress cardiomyopathy patients with COVID-19 had an increased incidence of respiratory failure requiring intubation, indicating that physiological stress is associated with worse outcomes in stress cardiomyopathy patients.

In this large, national, propensity-matched analysis, we found COVID-19 to be an independent predictor of in-hospital mortality, with a higher rate of adverse clinical outcomes and increased healthcare resource utilization in patients hospitalized with stress cardiomyopathy. In our study, concomitant COVID-19 infection resulted in approximately a two and a half times higher mortality in patients with stress cardiomyopathy. In our study, the inpatient mortality of stress cardiomyopathy patients with concurrent COVID-19 infection was 33.64%. Recent studies have shown that, in general, stress cardiomyopathy has in-hospital mortality of 3.5–10.6%, comparable to that of acute coronary syndromes.15 Undoubtedly, our study has highlighted the significantly worse prognosis of stress cardiomyopathy in the setting of COVID-19 infection.

Studies have also shown an association between the severity of COVID-19 infection with various complications, including AKI, sepsis, and organ failure.16 , 17 In our study, the incidence of complications including AKI, AKI requiring dialysis, respiratory failure with intubation of >24 h, cardiogenic shock, the requirement of vasopressors, and sepsis was higher in patients with stress cardiomyopathy and COVID-19 infection. These findings indicate the possible association of stress cardiomyopathy with the severity of COVID-19 infection. Studies have shown that patients with COVID-19 and stress cardiomyopathy have a higher incidence of CV risk factors, including diabetes, and an increased coagulopathy risk, as our study found.18 A study comparing patients with stress cardiomyopathy before the COVID-19 pandemic and during the pandemic showed increased LOS for affected patients with statistical significance, as noted in our study. This increased burden on the healthcare system is a matter of concern, and clinicians should be aware of this.19 Our findings validate that COVID-19 is associated with significantly increased morbidity and mortality in patients with stress cardiomyopathy. The findings of this analysis will help clinicians to be aware of the importance of early suspicion of deterioration of patients with concurrent stress cardiomyopathy and COVID-19. Early detection and aggressive management may change the outcome of patients suffering both an acute CV condition and viral infection.

Limitations

Our study has its inherent limitations. Firstly, it is a retrospective database analysis based on discharge diagnoses. We also do not have access to patient-level information and, thus, unmeasured confounding may affect these findings. The treatment guidelines and vaccination policy for COVID-19 have emerged with time. We do not have the option to find out if any management guideline or vaccination status would have changed the outcome of patients included in this analysis. Cases are being reported with stress cardiomyopathy after COVID-19 treatment.20 Studies have also shown an association between stress cardiomyopathy with COVID-19 vaccination.21 Also, one case of stress cardiomyopathy with a history of COVID-19 infection has been reported recently.22 More studies are required to understand the disease process better so that preventive measures can be taken in the future. Despite these limitations, NIS is a well-validated representation of the US population and with internal and external quality control measures. The large sample size of NIS data also compensates for residual confounders.

Conclusion

COVID-19 infection among patients hospitalized with stress cardiomyopathy is associated with significantly higher in-hospital mortality, adverse clinical outcomes, and use of in-hospital resources. In addition, advanced age, arrhythmia, liver disease, and coagulopathy were independent predictors of mortality in patients with stress cardiomyopathy hospitalized with concomitant COVID-19.

Author access to data

Publicly available National Inpatient Sample of the US.

Funding

No external funding was used in the preparation of this manuscript.

Ethical approval of studies and informed consent

Not applicable as it is a retrospective analysis of data.

CRediT authorship contribution statement

Adrija Hajra: Writing – original draft. Aaqib Malik: Conceptualization, Methodology, Data curation. Dhrubajyoti Bandyopadhyay: Conceptualization, Methodology, Data curation. Akshay Goel: Conceptualization, Methodology, Data curation. Ameesh Isath: Conceptualization, Methodology, Data curation. Rahul Gupta: Writing – original draft. Devesh Rai: Writing – original draft. Salim S. Virani: Writing – review & editing, Supervision. Gregg C. Fonarow: Writing – review & editing, Supervision. Carl J. Lavie: Writing – review & editing, Supervision.

Declaration of Competing Interest

Dr. Fonarow has served as a consultant for Abbott, Amgen, Bayer, Janssen, Medtronic, and Novartis.

Dr. Virani discloses the following relationships: Research support: Department of Veterans Affairs, World Heart Federation, Tahir and Jooma Family Honorarium: American College of Cardiology (Associate Editor for Innovations, acc.org).

Others: No conflicts of interest.

Acknowledgment

None.

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