Abstract
Background
COVID‐19 has been linked to cardiovascular complications, but its long‐term impact on left ventricular (LV) function is unclear. We investigated whether SARS‐CoV‐2 infection is associated with increased risk of LV ejection fraction (LVEF) decline and whether vaccination mitigates this risk.
Methods
In this retrospective study, we included patients with COVID‐19, normal baseline LVEF (≥50%), and at least one follow‐up echocardiogram from 2016 to 2024. Outcomes were LVEF dropping <50%, 40%, and 30%. Multivariable Cox models adjusted for demographics, comorbidities, vaccination status, and baseline LVEF. Associations with acute‐phase blood biomarkers were examined.
Results
Among 2853 patients who were COVID+ and 3963 patients who were COVID− (baseline LVEF ≥50%), patients with COVID‐19 had lower mean follow‐up LVEF (60.65% versus 61.53%, P<0.005) and higher rates of LVEF decline <50%, 40%, and 30%. Both hospitalized (adjusted hazard ratio [aHR], 1.57 [1.30–1.91]) and non‐hospitalized (aHR, 1.48 [1.18–1.85]) patients with COVID‐19 had greater risk of LVEF <50% versus controls; only hospitalized patients had significantly increased risk of LVEF<40% (aHR, 1.81 [1.35–2.43]) and <30% (aHR, 2.79 [1.72–4.54]). Vaccination was not significantly associated with LVEF decline. Baseline LVEF, older age, male sex, history of heart failure, myocardial infarction, and chronic kidney disease were associated with greater risk. Elevated troponin, B‐type natriuretic peptide, D‐dimer, and thrombocytopenia predicted greater risk in hospitalized patients with COVID‐19.
Conclusions
SARS‐CoV‐2 infection is associated with long‐term LVEF declines, especially in hospitalized patients. Vigilant cardiac surveillance may be needed in survivors of COVID‐19 to mitigate progressive dysfunction.
Keywords: acute cardiac injury, echocardiogram, heart failure, long COVID, myocardial infarction
Subject Categories: Echocardiography, Imaging, Ultrasound, Risk Factors
CLINICAL PERSPECTIVE.
What Is New?
SARS‐CoV‐2 infection, particularly when requiring hospitalization, is associated with a greater adjusted risk of subsequent decline in left ventricular ejection fraction compared with those tested negative for SARS‐CoV‐2.
What Are the Clinical Implications?
Survivors of COVID‐19, especially those who were hospitalized, should be considered at increased risk for progressive left ventricular dysfunction and may benefit from ongoing echocardiographic surveillance.
Left ventricular ejection fraction (LVEF) is a key marker of cardiac function and the most important echocardiographic parameter in predicting morbidity, mortality, and heart failure progression. 1 Historically, viral infections, including influenza and coronaviruses, could cause myocardial injury and myocarditis, which can manifest as cardiac dysfunction and reduced LVEF. 2 , 3 Emerging evidence suggests that SARS‐CoV‐2 infection induces similar injury to the myocardium through mechanisms such as viral infiltration of cardiomyocytes, endothelial injury, hyperinflammatory states, and thrombotic events. 4 , 5 , 6 , 7 , 8 COVID‐19 could contribute to not only acute but also chronic LV dysfunction. 9
A few studies have reported the emergence or worsening of LV dysfunction in patients with SARS‐CoV‐2 infection, particularly among those requiring hospitalization. 9 Elevated cardiac biomarkers such as troponin and B‐type natriuretic peptide have been associated with acute myocardial injury in COVID‐19 and serve as important indicators of disease severity and prognosis. 8 , 10 , 11 However, the long‐term impact of COVID‐19 on LVEF remains insufficiently characterized, especially across diverse clinical subpopulations. In particular, it is unclear whether SARS‐CoV‐2 infection contributes to progressive LVEF decline independently of established cardiovascular risk factors, including prior congestive heart failure (CHF) or myocardial infarction (MI). Additionally, whether COVID‐19 vaccination reduces LVEF decline has not been delineated. Understanding the longitudinal trajectory of LVEF following COVID‐19, across different age groups, comorbidity profiles, vaccination status, and sociodemographic strata, is important to identifying at‐risk populations and informing long‐term cardiovascular management. Given the global burden of SARS‐CoV‐2 infection, even modest decrements in LVEF among survivors may translate into substantial population‐level morbidity and health care resource use.
The goal of this study was to determine whether COVID‐19 is associated with increased risk of LVEF reduction below clinically significant thresholds in patients with preserved LVEF at baseline. Whether patients with preserved baseline LVEF (≥50%) showed LVEF decline <50%, 40%, and 30% after testing positive or negative for SARS‐CoV‐2 up to 46 months post‐index date was analyzed. We also examined whether an initial reduction in LVEF to <50% was subsequently followed by worsening, stabilization, or recovery of function. The outcomes with respect to COVID‐19 hospitalization and blood biomarkers obtained during acute COVID‐19 were analyzed. These analyses used the electronic health records (EHR) of a large academic urban health system in the Bronx, New York City, an epicenter of early COVID‐19 pandemic and subsequent waves of infections.
METHODS
Study Cohort
This retrospective study was approved by the Einstein‐Montefiore Institutional Review Board with an exemption for informed consent (IRB#2021–13 658). The data that support the findings of this study are available from the corresponding author upon reasonable request. Data were extracted from the Montefiore Health System's EHR from January 1, 2016, to January 12, 2024 as previously described. 12 , 13 , 14 , 15 , 16 , 17 , 18 , 19 , 20 , 21 , 22 , 23 , 24 , 25 , 26 , 27 , 28 , 29 A large team of data scientists and engineers created, maintained, and validated data extraction. To ensure data quality, this team routinely performed manual chart review of all relevant variables on subsets of patients over the past few years. Patients who were COVID+ consisted of those who tested positive by polymerase chain reaction (≥21 years old) at least once, and the index date was defined as the date of first positive test. Patients who were COVID− (≥21 years old) consisted of those who always tested negative and never tested positive, and the index date was defined as the date of first negative test. To ensure adequate follow‐up time, patients who died or were lost to follow‐up within the first 30 days of index date were excluded. To capture pre‐ and post‐index date measurements that were not transiently affected by acute SARS‐CoV‐2 infection, patients were included only if they had at least 1 pre‐index date (>7 days before index date) and at least 1 post‐index date (>30 days after index date) echocardiography‐derived LVEF measurement. Only individuals with a normal LVEF (≥50%) pre‐index date were analyzed and thus those with a pre‐index date LVEF <50% were excluded.
Variables
Demographic data included age at the index date, sex, race, and ethnicity. Data on vaccination for COVID‐19 were collected and patients vaccinated if they had received at least 1 dose before index date were included. Vaccination data were sourced from the New York State Immunization Information System (including New York City data), patient self‐report, Care Everywhere data shared across Epic organizations, and vaccinations administered within the Montefiore Health System. This allowed for capture of both in‐system and external COVID‐19 vaccinations. Insurance and median household income of each patient's ZIP code were collected. Pre‐existing comorbidities, defined by International Classification of Diseases, Tenth Revision (ICD‐10) codes, at index date included hypertension, type 2 diabetes, CHF, MI, coronary artery disease, chronic obstructive pulmonary disease, asthma, chronic kidney disease (CKD), liver disease, and self‐reported tobacco use. To assess the severity of COVID‐19, patients who were COVID+ were stratified based on hospitalization during the acute phase of the infection. Among the hospitalized cohort who were COVID+, the peak and minimum of the following biomarkers at time of infection were collected: neutrophil‐to‐lymphocyte ratio, hemoglobin (g/dL), platelets (110×109 cells/L), C‐reactive protein (mg/dL), lactate dehydrogenase (U/L), aspartate aminotransferase (U/L), temperature (°C), ferritin (μg/L), D‐dimer (μg/mL), creatinine (mg/dL), troponin (TnT [troponin T] was in use until June 2020 when a switch was made to TnI [troponin I], ng/mL), and BNP (B‐type natriuretic peptide, pg/mL).
Outcomes
Outcome events were defined as ≥1 LVEF measurements <50%, 40%, or 30% recorded in the EHR >30 days after index date. A 30‐day window after index date was chosen to avoid acute COVID‐19 effects. Thresholds of LVEF decline based on established clinical significance were selected: <50% indicates mildly reduced systolic function, <40% represents moderate dysfunction often prompting heart failure therapy, and <30% reflects severe impairment associated with poor prognosis and need for intensified management. 30 , 31 , 32 Follow‐up time was calculated in months from the index date to the date of the first echocardiogram in which LVEF was measured below threshold (for patients who developed the outcome) or to the date of last normal echocardiogram measurement (for patients who never developed the outcome), up to January 12, 2024. Among hospitalized patients who were COVID+, biomarkers at time of hospitalization for infection were assessed according to thresholds set by previous studies and analyzed with respect to future risk of drop in LVEF. 33 , 34 Among patients with an initial post‐index date LVEF drop <50%, the average of all subsequent LVEF measurements was calculated. Three statuses after the initial LVEF <50% were defined: (1) stable: subsequent LVEF measurements remained within ±5% of the initial drop, (2) recovering: subsequent LVEF >5% higher than the initial drop, and (3) worsening: subsequent LVEF >5% lower than the initial drop.
Statistical Analysis
Python (v3.10.12) was used for data processing and statistical analyses. P values <0.05 were considered statistically significant. For group comparison of categorical variables, the chi‐square test was used and for group comparison of continuous variables, the independent t test was used. Risk of outcomes was assessed using multivariable cause‐specific Cox proportional hazards models to account for all‐cause mortality as a competing risk. Covariates adjusted for included vaccination for SARS‐CoV‐2 (at least 1 dose, time‐varying covariate), age, sex, race, ethnicity, average of all preindex date LVEF measurements, and pre‐existing hypertension, type 2 diabetes, CHF, MI, coronary artery disease, chronic obstructive pulmonary disease, asthma, CKD, liver disease, and tobacco use. To confirm results, the same covariates were also adjusted for using inverse probability weighting. In that analysis, vaccination status could not be handled in a time‐varying manner and was instead a binary variable denoting vaccination at any time before last LVEF follow‐up.
RESULTS
Figure 1 shows the patient selection flow chart. From February 1, 2020 to January 12, 2024, there were 212 590 adults with a SARS‐CoV‐2 polymerase chain reaction test. After including only patients with pre‐ and post‐index date echocardiography, 3646 patients who were COVID+ and 4773 patients who were COVID− were identified. Patients with a pre‐index date echocardiogram measuring LVEF <50% were excluded to yield a cohort of 2853 patients who were COVID+ and 3963 patients who were COVID−.
Figure 1. Patient selection flow chart.
LVEF indicates left ventricular ejection fraction; and PCR, polymerase chain reaction.
Baseline Data
The entire cohort included 6816 patients, including 2853 patients who were COVID+ and 3963 patients who were COVID−. Table 1 describes the characteristics of patients who were COVID+ and COVID− with all preindex date LVEF measurements ≥50%. Patients who were COVID+ (n=2853) had a lower proportion of women (P=0.01), higher prevalence of all preexisting comorbidities (P<0.05), were more likely to be on Medicaid (30.11% versus 27.66%, P=0.030), and less likely to have private insurance (29.30% versus 33.96%, P<0.005) compared with patients who were COVID−. There were 1430 (50.12%) patients hospitalized for COVID‐19. There were 34.21% of patients who were COVID+ and 24.80% of patients who were COVID− with at least 1 dose of COVID‐19 vaccination before index date. Time from the first dose to index date was shorter in patients who were COVID−.
Table 1.
Characteristics of Patients With and Without COVID‐19 With Pre‐ and Post‐index Date Left Ventricular Ejection Fraction Measurement
| COVID+ (n=2853) | COVID− (n=3963) | P value | |
|---|---|---|---|
| Age at index date, y, mean±SD | 64.94±14.83 | 65.15±13.13 | 0.53 |
| Female, n (%) | 1755 (61.51%) | 2556 (64.50%) | 0.010* |
| Race and ethnicity, n (%) | |||
| Non‐Hispanic White | 311 (10.90%) | 469 (11.83%) | 0.25 |
| Black | 1059 (37.12%) | 1413 (35.65%) | 0.22 |
| Asian | 94 (3.29%) | 142 (3.58%) | 0.57 |
| Other race | 1389 (48.69%) | 1939 (48.93%) | 0.86 |
| Hispanic | 1220 (42.76%) | 1614 (40.73%) | 0.10 |
| Preexisting comorbidities, n (%) | |||
| Hypertension | 2582 (90.50%) | 3459 (87.28%) | <0.005* |
| Type 2 diabetes | 1725 (60.46%) | 1963 (49.53%) | <0.005* |
| Congestive heart failure | 1139 (39.92%) | 989 (24.96%) | <0.005* |
| Myocardial infarction | 325 (11.39%) | 233 (5.88%) | <0.005* |
| Coronary artery disease | 1520 (53.28%) | 1759 (44.39%) | <0.005* |
| Chronic obstructive pulmonary disease | 362 (12.69%) | 234 (5.90%) | <0.005* |
| Asthma | 926 (32.46%) | 1115 (28.14%) | <0.005* |
| Chronic kidney disease | 1351 (47.35%) | 1230 (31.04%) | <0.005* |
| Liver disease | 977 (34.24%) | 1018 (25.69%) | <0.005* |
| Tobacco use | 1610 (56.43%) | 2171 (54.78%) | 0.18 |
| Insurance, n (%) | |||
| Medicaid | 859 (30.11%) | 1096 (27.66%) | 0.030* |
| Medicare | 1071 (37.54%) | 1415 (35.71%) | 0.13 |
| Private | 836 (29.30%) | 1346 (33.96%) | <0.005* |
| Self‐pay | 87 (3.05%) | 106 (2.67%) | 0.40 |
| Median income quartile of ZIP code, n (%) | |||
| Lower 25% (<$38 768) | 837 (29.34%) | 1154 (29.12%) | 0.87 |
| 25%–50% ($36 730–$56 327) | 810 (28.39%) | 1092 (27.55%) | 0.46 |
| 50%–75% ($56 327–$63 048) | 684 (23.97%) | 929 (23.44%) | 0.63 |
| Top 25% (≥$63 048) | 522 (18.30%) | 788 (19.88%) | 0.11 |
| Hospitalized due to COVID‐19, n (%) | 1430 (50.12%) | − | − |
| Vaccinated for SARS‐CoV‐2, n (%) | 976 (34.21%) | 983 (24.80%) | <0.005* |
| Moderna | |||
| At least 1 dose | 194 (6.80%) | 180 (4.54%) | <0.005* |
| Number of doses (median [IQR]) | 2.0 [1.0–2.0] | 2.0 [1.0–2.0] | 0.58 |
| First dose to index date (mo, mean±SD) | 13.06±7.49 | 8.55±7.29 | <0.005* |
| Pfizer‐BioNTech | |||
| At least 1 dose | 820 (28.74%) | 837 (21.12%) | <0.005* |
| Number of doses (median [IQR]) | 2.0 [2.0–3.0] | 2.0 [2.0–3.0] | <0.005* |
| First dose to index date (mo, mean±SD) | 13.54±7.31 | 9.5±7.31 | <0.005* |
| Johnson & Johnson | |||
| At least 1 dose | 22 (0.77%) | 2 (0.050%) | <0.005* |
| Number of doses (median [IQR]) | 2.0 [1.0–2.0] | 1.5 [1.25–1.75] | 0.94 |
| First dose to index date (mo, mean±SD) | 12.99±7.38 | 4.42±5.65 | 0.24 |
| Average of all pre‐index date left ventricular ejection fractions, mean±SD | 63.05%±5.30 | 62.97% ±5.47 | 0.57 |
| All‐cause mortality, n (%) | 256 (8.97%) | 197 (4.97%) | <0.005* |
IQR indicates interquartile range.
Other indicates all other races.
Indicates p < 0.05.
Patients who were COVID+ had similar pre‐index date LVEF values as patients who were COVID− (63.05% versus 62.97%, P=0.57). Patients who were COVID+ showed higher unadjusted all‐cause mortality compared with patients who were COVID− (8.97% versus 4.97%, P<0.005).
Outcomes
The median follow‐up time was 2.32 [1.49–3.03] years for the entire cohort. Post‐index date outcomes between patients with and without COVID‐19 are shown in Table 2. The average of all post‐index date LVEF values was lower in patients who were COVID+ compared with patients who were COVID− (60.65% versus 61.53%, P<0.005), with average pre‐ to post‐index changes in LVEF of −2.40% versus −1.44%, respectively (P<0.005). Most patients did not experience LVEF reduction below clinically significant thresholds post‐index date. However, more patients who were COVID+ had a post‐index date LVEF <50% compared with controls (10.62% versus 7.24%, P<0.005).
Table 2.
Post‐index Date Outcomes for Left Ventricular Ejection Fraction Dropping <50%, 40%, and 30% for Patients With and Without COVID‐19
| Outcomes | COVID+ (n=2853) | COVID− (n=3963) | P value |
|---|---|---|---|
| Longest echocardiogram follow‐up y, mean±SD | 2.01±0.99 | 2.41±0.87 | <0.005* |
| Longest echocardiogram follow‐up y, median [IQR] | 1.96 [1.22–2.87] | 2.62 [1.85–3.14] | <0.005* |
| Average of all post‐index date LVEFs, mean±SD | 60.65%±8.34 | 61.53%±7.68 | <0.005* |
| Average change in LVEF, mean±SD | −2.40%±8.14 | −1.44%±7.49 | <0.005* |
| Follow‐up LVEF outcomes, n (%) | |||
| Lowest follow‐up LVEF <50% | 303 (10.62%) | 287 (7.24%) | <0.005* |
| Lowest follow‐up LVEF 49%–40% | 179 (6.27%) | 170 (4.29%) | <0.005* |
| Lowest follow‐up LVEF 39%–30% | 74 (2.59%) | 81 (2.04%) | 0.16 |
| Lowest follow‐up LVEF <30% | 50 (1.75%) | 36 (0.91%) | <0.005* |
LVEF indicates left ventricular ejection fraction.
Indicates p < 0.05.
Persistency of LVEF Decline
The median time from index date to first LVEF <50% was shorter in patients who were COVID+ compared with patients who were COVID− (11.66 versus 14.26 months, P<0.005). Subsequent trajectory of patients with an initial decline <50% was analyzed (Table 3). Approximately half of patients who experienced an initial drop <50% had subsequent echocardiograms. Of those, approximately 43% recovered, half remained unchanged, and <10% worsened, with no differences between groups who were COVID+ and COVID− (P>0.05). Tables S1 and S2 show the demographics of those lost to follow‐up after initial drop and those worsened, were stable, or recovered. Based on the available demographics and comorbidities, those who were lost to follow‐up did not systematically differ from those who had follow‐up LVEF measurements.
Table 3.
LVEF Decline, Recovery or No Change After the First Drop in LVEF <50%
| Patients with post‐index date EF drop <50% | COVID+ (n=303) | COVID− (n=287) | P value |
|---|---|---|---|
| Mo from index date to drop, mean±SD | 13.50±9.82 | 15.75±11.07 | <0.005* |
| Mo from index date to drop, median [IQR] | 11.66 [5.83, 18.72] | 14.26 [6.24, 24.86] | <0.005* |
| Without subsequent post‐initial drop follow‐up | 138 (45.54%) | 143 (49.83%) | 0.34 |
| With subsequent post‐initial drop follow‐up | COVID+ (n=165) | COVID− (n=144) | P value |
|---|---|---|---|
| Recovering | 71 (43.03%) | 62 (43.06%) | 1.00 |
| Stable | 79 (47.88%) | 73 (50.69%) | 0.70 |
| Worsening | 15 (9.09%) | 9 (6.25%) | 0.47 |
IQR indicates interquartile range; and LVEF, left ventricular ejection fraction.
Indicates p < 0.05.
Temporal Progression of LVEF Decline
To evaluate the temporal progression of LVEF, the distribution of LVEF values at different time points post‐index date was analyzed (Figure 2A). Throughout all time points post‐index date, there were higher proportions of patients who were COVID+ with an LVEF measurement <30%, 40%, and 50% compared with patients who were COVID−. Cumulative incidence of LVEF declines below thresholds of 30%, 40%, and 50% is shown in Figure 2B. For all thresholds, hospitalized patients who were COVID+ exhibited the highest cumulative incidence, followed by non‐hospitalized patients who were COVID+ and patients who were COVID–. These results presented in Figure 2, including the cumulative incidence curves, are not adjusted for confounders.
Figure 2. Distribution of LVEF throughout time and cumulative incidence of drops in LVEF.
A, Distribution of LVEF relative to index date in patients who were COVID+ and COVID− with all pre‐index date measurements ≥50%. y‐axis scale begins at 85%. B, Cumulative incidence curve of drop in LVEF <50%, <40%, and <30% among hospitalized patients who were COVID+, non‐hospitalized patients who were COVID+, and patients who were COVID–. Results were not adjusted for confounders. LVEF indicates left ventricular ejection fraction.
Multivariable Regression
We assessed the adjusted risk associated with COVID‐19 of LVEF dropping <50%, 40%, and 30% post‐index date (Table 4). Patients hospitalized for COVID‐19 had a higher risk of LVEF dropping <50% (adjusted hazard ratio [aHR], 1.57 [1.30–1.91]), 40% (aHR, 1.81 [1.35–2.43]) and 30% (aHR, 2.79 [1.72–4.54]) compared with patients who were COVID–. Non‐hospitalized patients with COVID‐19 had a higher risk of having LVEF dropping <50% (aHR, 1.48 [1.18–1.85]) compared with patients who were COVID–. The same set of covariates were adjusted for using inverse probability weighting and the results were similar (see Tables S3 and S4 for cohort characteristics and Table S5 for inverse probability weighting‐adjusted HRs).
Table 4.
Cox‐Proportional Hazards Models Assessing Risk of LVEF Dropping <50%, 40%, and 30% From Pre‐ to Post‐index Date
| Outcome | LVEF drop <50% | LVEF drop <40% | LVEF drop <30% | |||
|---|---|---|---|---|---|---|
| Covariate | aHR [95% CI] | P value | aHR [95% CI] | P value | aHR [95% CI] | P value |
| COVID+ hospitalized vs COVID– | 1.57 [1.30–1.91] | <0.005* | 1.81 [1.35–2.43] | <0.005* | 2.79 [1.72–4.54] | <0.005* |
| COVID+ nonhospitalized vs COVID– | 1.48 [1.18–1.85] | <0.005* | 1.30 [0.90–1.88] | 0.17 | 1.51 [0.79–2.87] | 0.21 |
| Vaccination for SARS‐CoV‐2 | 0.93 [0.79–1.10] | 0.41 | 0.96 [0.74–1.24] | 0.74 | 1.32 [0.84–2.05] | 0.23 |
| Pre‐index date LVEF (5% increments) | 0.56 [0.50–0.59] | <0.005* | 0.59 [0.53–0.70] | <0.005* | 0.59 [0.50–0.74] | <0.005* |
| Age and sex | ||||||
| Age at index date (every 5 y) | 1.10 [1.05–1.10] | <0.005* | 1.10 [1.05–1.16] | <0.005* | 1.16 [1.05–1.28] | <0.005* |
| Male vs female sex | 1.40 [1.17–1.67] | <0.005* | 1.26 [0.96–1.66] | 0.10 | 1.37 [0.86–2.17] | 0.19 |
| Race and ethnicity | ||||||
| Black vs Non‐Hispanic White | 0.88 [0.68–1.13] | 0.32 | 0.94 [0.62–1.42] | 0.77 | 1.22 [0.59–2.56] | 0.59 |
| Other race vs Non‐Hispanic White | 0.89 [0.63–1.24] | 0.49 | 1.11 [0.66–1.89] | 0.69 | 1.25 [0.48–3.28] | 0.65 |
| Hispanic vs Non‐Hispanic | 1.06 [0.80–1.42] | 0.68 | 0.97 [0.62–1.52] | 0.90 | 1.20 [0.55–2.63] | 0.64 |
| Comorbidities | ||||||
| Congestive heart failure | 1.39 [1.16–1.66] | <0.005* | 1.29 [0.98–1.71] | 0.072 | 1.03 [0.64–1.65] | 0.91 |
| Myocardial infarction | 1.39 [1.09–1.76] | 0.0070* | 1.10 [0.73–1.65] | 0.66 | 1.18 [0.59–2.36] | 0.63 |
| Coronary artery disease | 1.04 [0.87–1.25] | 0.64 | 1.11 [0.84–1.46] | 0.47 | 0.77 [0.49–1.22] | 0.27 |
| Hypertension | 0.96 [0.70–1.32] | 0.81 | 1.18 [0.70–1.99] | 0.55 | 0.58 [0.27–1.25] | 0.16 |
| Type‐2 diabetes | 1.09 [0.91–1.30] | 0.38 | 1.06 [0.80–1.41] | 0.68 | 1.45 [0.89–2.36] | 0.14 |
| Chronic obstructive pulmonary disease | 0.95 [0.70–1.29] | 0.73 | 0.95 [0.58–1.53] | 0.82 | 0.77 [0.34–1.76] | 0.54 |
| Chronic kidney disease | 1.64 [1.36–1.97] | <0.005* | 1.44 [1.09–1.92] | 0.012 | 1.44 [0.89–2.34] | 0.14 |
| Asthma | 0.84 [0.68–1.03] | 0.092 | 0.82 [0.60–1.14] | 0.24 | 0.95 [0.56–1.61] | 0.85 |
| Liver disease | 0.86 [0.72–1.04] | 0.13 | 0.73 [0.54–1.00] | 0.047* | 0.77 [0.47–1.28] | 0.31 |
| Tobacco use | 1.02 [0.86–1.21] | 0.80 | 1.11 [0.85–1.46] | 0.44 | 1.43 [0.90–2.27] | 0.13 |
Vaccination was modeled as a time‐varying covariate. aHR indicates adjusted hazard ratio; and LVEF, left ventricular ejection fraction.
Indicates p < 0.05.
The aHR for covariates are also shown. Across all thresholds, baseline LVEF was associated with outcomes, namely, every 5% LVEF increase at baseline was associated with 41% to 44% reduced risk of future LVEF decline. Older age was associated with higher risk of future LVEF decline. Other significant predictors of LVEF decline included male sex for LVEF dropping <50% (aHR, [1.17–1.67]), CHF for LVEF dropping <50% (1.39 [1.16–1.66]), MI for dropping <50% (1.39 [1.09–1.76]), CKD for dropping <50% (1.64 [1.36–1.97]), and 40% (1.44 [1.09–1.92]), and liver disease for dropping <40% (0.73 [0.54–1.00]). Race and ethnicity and having received at least 1 dose of vaccination for SARS‐CoV‐2 did not significantly contribute to outcomes.
Blood Biomarkers
We also investigated the association between commonly measured biomarkers during acute COVID‐19 and post‐COVID‐19 LVEF decline. Table 5 shows the aHRs of LVEF dropping <50%, 40%, and 30% among patients who were COVID+ who had abnormal biomarker measurements during COVID‐19 hospitalization. Individuals with TnT >0.05 ng/mL or TnI >0.20 ng/mL were at higher risk of dropping below all 3 thresholds as well as those with BNP ≥100 pg/mL (P<0.05). Those with platelets ≤110×109 cells/L were more likely to experience a drop <40% (aHR, 1.96 [1.03–3.76]). Those with D‐dimer ≥1.5 μg/mL were more likely to experience a drop <50% (1.39 [1.00–1.93]) and 40% (1.97 [1.21–3.22]).
Table 5.
Association of Maximum or Minimum (Depending on the Thresholds) of Biomarkers at Time of COVID‐19 Hospitalization With Subsequent Risk of Drop in LVEF
| Outcome | LVEF drop <50% | LVEF drop <40% | LVEF drop <30% | |||
|---|---|---|---|---|---|---|
| Covariate | aHR [95% CI] | P value | aHR [95% CI] | P value | aHR [95% CI] | P value |
| Troponin I >0.20 ng/mL or Troponin T >0.05 ng/mL | 2.68 [1.56–4.63] | <0.005* | 4.26 [2.51–7.25] | <0.005* | 4.46 [1.95–10.19] | <0.005* |
| B‐type natriuretic peptide ≥100 pg/mL | 2.13 [1.37–3.31] | <0.005* | 3.22 [1.55–6.67] | <0.005* | 3.21 [1.07–9.62] | 0.037 |
| Platelets ≤110×109 cells/L | 1.30 [0.80–2.14] | 0.29 | 1.96 [1.03–3.76] | 0.040* | 1.27 [0.38–4.23] | 0.70 |
| D‐dimer ≥1.5 μg/mL | 1.39 [1.00–1.93] | 0.048* | 1.97 [1.21–3.22] | 0.0060* | 1.89 [0.91–3.96] | 0.090 |
| Neutrophil/lymphocyte ratio ≥10 | 0.89 [0.59–1.34] | 0.59 | 1.10 [0.63–1.94] | 0.73 | 1.37 [0.62–3.04] | 0.44 |
| Hemoglobin ≤9.2 g/dL | 1.22 [0.82–1.81] | 0.33 | 1.30 [0.72–2.34] | 0.38 | 1.10 [0.41–2.96] | 0.85 |
| C‐reactive protein ≥15 mg/dL | 0.93 [0.64–1.36] | 0.71 | 1.01 [0.58–1.76] | 0.98 | 1.12 [0.49–2.54] | 0.79 |
| Lactate dehydrogenase ≥400 U/L | 0.85 [0.55–1.30] | 0.45 | 1.38 [0.78–2.43] | 0.27 | 1.13 [0.48–2.67] | 0.77 |
| Aspartate aminotransferase ≥100 U/L | 1.72 [0.85–3.45] | 0.13 | 1.32 [0.41–4.31] | 0.64 | 0.00 [0.00–inf] | 1.00 |
| Temperature ≥38.0 °C | 0.94 [0.57–1.56] | 0.81 | 0.79 [0.36–1.74] | 0.56 | 0.47 [0.11–1.98] | 0.31 |
| Ferritin ≥700 μg/L | 1.38 [0.97–1.98] | 0.076 | 1.02 [0.60–1.75] | 0.93 | 0.89 [0.38–2.10] | 0.79 |
| Creatinine ≥1.1 mg/dL | 1.36 [0.92–2.03] | 0.12 | 1.20 [0.67–2.13] | 0.54 | 1.11 [0.47–2.61] | 0.81 |
Each model adjusted for age, sex, race, ethnicity, pre‐existing comorbidities, and average of all pre‐index date LVEF measurements. Each echocardiogram was treated as an observation and the event was defined as the LVEF measuring below the threshold. aHR indicates adjusted hazard ratio; and LVEF, left ventricular ejection fraction.
Indicates p < 0.05.
DISCUSSION
This study investigated whether COVID‐19 is significantly associated with elevated risks of LVEF declines compared with patients who were COVID− in a large diverse retrospective clinical cohort with a median echocardiographic follow‐up time of 2.32 years. The major findings are as follows. (1) Patients with COVID‐19 had lower overall post‐index date LVEF measurements and higher proportions of individuals with LVEF dropping <30%, 40%, and 50% at all discrete time points post‐index date compared with patients who were COVID−. (2) SARS‐CoV‐2 infection was associated with increased risks of LVEF declines compared with patients who were COVID−, after adjusting for COVID‐19 vaccination status, baseline LVEF, age, sex, race, ethnicity, and pre‐existing comorbidities. (3) Both hospitalized and non‐hospitalized patients with COVID‐19 were at higher adjusted risk of LVEF dropping <50% compared with controls. However, only hospitalized patients with COVID‐19 were at higher adjusted risks of more pronounced declines (<40% and 30%), indicating LVEF decline scaled with COVID‐19 disease severity. (4) COVID‐19 vaccination was not significantly associated with risk of LVEF decline. (5) Older patients, male patients, and patients with a lower baseline LVEF or a history of CHF, MI, and CKD were at higher risk of post‐index date LVEF decline compared with their counterparts. (6) Elevated troponin and BNP, as well as D‐dimer and platelets, during acute COVID‐19 were significantly associated with LVEF decline. Together, our findings provide evidence that SARS‐CoV‐2 infection is significantly associated with elevated risk of long‐term LV dysfunction compared with controls who were COVID−.
Previous studies investigating post‐COVID‐19 trends in LVEF are sparse. Karagodin et al. followed 153 patients who underwent echocardiography during acute COVID‐19 and 3 to 6 months later. Those with normal baseline LVEF largely maintained normal values at follow‐up, whereas those who started with hyperdynamic (LVEF >70%) or reduced function (<50%) shifted closer to normal ranges. 35 In another study, 27% of 215 patients from March 30 to June 3, 2020 exhibited reduced LVEF at 3‐month follow‐up, compared with 8% at the time of COVID‐19 hospitalization and 16% of controls without COVID. 36 Another study of 443 patients approximately 9.6 months post‐COVID and 1328 matched controls revealed that individuals with prior SARS‐CoV‐2 infection had a slightly lower average LVEF (57.88% versus 59.05%). 37 To our knowledge, this is the first study to longitudinally track LVEF pre and post‐infection and over an extended follow‐up period. In contrast, most existing studies either lacked a control group without COVID‐19 or only performed post‐infection echocardiography. 9 , 35 , 36 , 37
Additional analyses were also performed to further corroborate the above findings. The time from index date to first LVEF <50% was shorter in COVID+ compared with patients who were COVID−, further suggesting that LVEF dysfunction may have been associated with COVID‐19. Following an initial drop <50%, subsequent LVEF trajectory was similar in groups who were COVID+ and COVID−: approximately 43% recovered, half remained stable, and 9.09% of patients who were COVID+ and 6.25% of patients who were COVID− worsened. In the multivariable models, we found that every 5% increment increase in baseline LVEF was associated with 44% to 48% reduced risk of LVEF decline. Older age was associated with a higher risk of LVEF declines for all clinically significant thresholds. Male sex, CHF, MI, and CKD were associated with LVEF declines below some, but not all, clinically significant thresholds. Recapitulating these known risk factors in our multivariable models further corroborated our main conclusions. 38 Race and ethnicity, however, were not associated with outcomes. This could be because of small proportions of non‐Hispanic White and Asian patients in our cohort.
We modeled vaccination for SARS‐CoV‐2 as a time‐varying covariate and found no association with LVEF decline. Some recent work has suggested that individuals who received a complete COVID‐19 vaccination scheme had a significantly lower prevalence of post‐COVID cardiac injury. 39 Simultaneously, several reports have highlighted serious cardiac adverse events following mRNA vaccination, including myocarditis and pericarditis, with spike protein found in the myocardium after vaccination‐related adverse events, particularly in young men. 40 , 41 , 42 , 43 , 44 Although the risk–benefit balance of vaccination may differ across age and risk strata, our findings suggest that among a predominantly older (mean age 65 years old), comorbid adult population, vaccination has little net impact on risk of long‐term LVEF decline.
There are likely multiple interrelated mechanisms contributing to COVID‐19‐related LV dysfunction. Direct myocardial injury is likely a key contributor, as SARS‐CoV‐2 infects cardiomyocytes via the angiotensin‐converting enzyme 2 receptor, which is highly expressed in cardiac tissue. 45 , 46 Viral entry and replication within cardiomyocytes could trigger cellular apoptosis, necrosis, and local inflammation. 47 This direct insult is further exacerbated by systemic inflammation associated with COVID‐19. 48 The cytokine storm, characterized by elevated IL‐6 (interleukin‐6), tumor necrosis factor‐α, and other inflammatory mediators, disrupts calcium homeostasis, impairs myocardial contractility, and if prolonged, promotes adverse remodeling. 49 , 50 , 51 , 52 COVID‐19 has also been associated with endothelial dysfunction and systemic coagulopathy, 53 which could promote formation of microvascular thrombi in coronary vessels that impede myocardial perfusion, inducing ischemia and further worsening LV systolic function. 54 These acute processes can trigger chronic inflammation both locally and systemically, which promote adverse myocardial changes and remodeling. 55 , 56 Cardiac magnetic resonance imaging studies in survivors of COVID‐19 have shown evidence of late gadolinium enhancement, indicative of fibrosis, and T2‐weighted signal abnormalities, suggestive of persistent inflammation. 57 Additionally worsening cardiovascular risk factors such as hypertension, type 2 diabetes, obesity, or sedentary lifestyle can potentially contribute to LV dysfunction. 58 Our biomarker analysis supports proposed mechanisms of cardiac dysfunction, as LVEF decline was associated with elevated troponin and BNP (markers of myocardial injury) and with D‐dimer and thrombocytopenia (markers of systemic stress). 10 , 11
Our findings carry significant clinical implications and underscore the need for vigilant monitoring of cardiac function in survivors of COVID‐19, especially for those with risk factors. Early detection of LVEF decline would allow for timely optimization of guideline‐directed medical therapy, such as angiotensin receptor‐neprilysin inhibitors, beta blockers, mineralocorticoid receptor antagonists, or sodium‐glucose cotransporter 2 inhibitors. 2 , 59 From a therapeutic development perspective, interventions targeting inflammation and myocardial remodeling could be investigated for mitigating the long‐term cardiac sequelae of COVID‐19. Adverse myocardial remodeling weeks to months after severe illness may be in part mediated by inflammatory cytokines like IL‐6. 50 IL‐6 inhibitors have shown promise in reducing circulating levels of N‐terminal proBNP and warrant potential investigation in this context. 60 , 61 , 62 Additionally, studies should focus on identifying more high‐risk subgroups who may benefit from close monitoring of LVEF or early initiation of guideline‐directed medical therapy for reduced LVEF.
Limitations
This study has several limitations. First, we relied on the accuracy of the EHR, which could have inaccuracies or misdocumentation. To mitigate this concern, we have conducted manual chart reviews of key variables in subsets of patients over the past several years. We relied on only COVID‐19 polymerase chain reaction tests, disregarding home COVID‐19 tests because they were not as reliable nor properly documented in our EHR. Moreover, some patients might have been tested positive for COVID‐19 elsewhere such as local pharmacy stores. Such contamination of the COVID− group with patients exposed to COVID‐19 likely underestimated any potential impact of the infection. However, missed cases likely comprised primarily of mild COVID‐19, as patients with severe COVID‐19 would likely have been admitted to our health system, the predominant health system in the Bronx. We did not evaluate the association of COVID‐19 treatments with outcomes due to the heterogeneity of treatment regimens, which were inconsistently applied across the timeline of the pandemic, particularly in its early pandemic. We did not investigate outcomes during acute SARS‐CoV‐2 infection (ie, within 30 days). For patients who were COVID−, the index date was defined as the date of the first negative polymerase chain reaction test. We acknowledge that testing behavior may differ between groups, with patients who were COVID− potentially tested for routine screening or unrelated symptoms. This could bias follow‐up duration or introduce exposure misclassification, though we mitigated this risk by excluding those without follow‐up echocardiography and adjusting for key baseline covariates. Due to the retrospective nature, echocardiograms were obtained at the discretion of clinicians based on clinical indications so the LVEF trends may not strictly reflect changes at the population level. Nearly half of patients with post‐index date LVEF <50% did not have subsequent follow‐up echocardiography, which may bias estimates of recovery, stability, or worsening. As shown in Table S1, patients with and without follow‐up did not differ meaningfully in baseline demographics or comorbidities. However, unmeasured factors, such as severity of symptoms, access to care, or clinical decision‐making, may have influenced follow‐up and could introduce bias. Future research should incorporate multicenter studies to improve generalizability across various populations. Finally, although we adjusted for major confounders using multivariable Cox proportional hazards regression, residual confounding and unintentional patient selection biases are inherent limitations of observational studies. These factors should be considered when interpreting the findings of this study.
CONCLUSIONS
These findings underscore the need for vigilant cardiac surveillance in survivors of COVID‐19 to mitigate progressive LV dysfunction. SARS‐CoV‐2 infection is associated with long‐term LVEF declines. Risk was particularly high in those hospitalized and in those with abnormal cardiac biomarkers during acute infection. Vaccination for COVID‐19 was not associated with LVEF decline risk. These results underscore the need for heightened surveillance of LV function, especially among high‐risk COVID‐19 survivors, to enable timely interventions to address the long‐term cardiovascular burden of COVID‐19 and improve outcomes for affected patients.
Sources of Funding
None.
Disclosures
None.
Supporting information
Data S1
Tables S1–S5
This article was sent to Jacquelyn Y. Taylor, PhD, PNP‐BC, RN, FAHA, FAAN, Associate Editor, for review by expert referees, editorial decision, and final disposition.
Supplemental Material is available at https://www.ahajournals.org/doi/suppl/10.1161/JAHA.125.043976
For Sources of Funding and Disclosures, see page 10.
REFERENCES
- 1. Kosaraju A, Goyal A, Grigorova Y, Makaryus AN. Left Ventricular Ejection Fraction. StatPearls. Treasure Island (FL); 2025. [PubMed] [Google Scholar]
- 2. Bozkurt B, Colvin M, Cook J, Cooper LT, Deswal A, Fonarow GC, Francis GS, Lenihan D, Lewis EF, McNamara DM, et al. Current diagnostic and treatment strategies for specific dilated cardiomyopathies: a scientific statement from the American Heart Association. Circulation. 2016;134:e579–e646. doi: 10.1161/CIR.0000000000000455 [DOI] [PubMed] [Google Scholar]
- 3. Gopal R, Marinelli MA, Alcorn JF. Immune mechanisms in cardiovascular diseases associated with viral infection. Front Immunol. 2020;11:570681. doi: 10.3389/fimmu.2020.570681 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 4. Giustino G, Pinney SP, Lala A, Reddy VY, Johnston‐Cox HA, Mechanick JI, Halperin JL, Fuster V. Coronavirus and cardiovascular disease, myocardial injury, and arrhythmia: JACC focus seminar. J Am Coll Cardiol. 2020;76:2011–2023. doi: 10.1016/j.jacc.2020.08.059 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 5. Hanson PJ, Liu‐Fei F, Ng C, Minato TA, Lai C, Hossain AR, Chan R, Grewal B, Singhera G, Rai H, et al. Characterization of COVID‐19‐associated cardiac injury: evidence for a multifactorial disease in an autopsy cohort. Lab Investig. 2022;102:814–825. doi: 10.1038/s41374-022-00783-x [DOI] [PMC free article] [PubMed] [Google Scholar]
- 6. Tsai EJ, Ci D, Tucker NR. Cell‐Specific Mechanisms in the Heart of COVID‐19 Patients. Circ Res. 2023;132:1290–1301. doi: 10.1161/CIRCRESAHA.123.321876 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 7. Duong KE, Lu JY, Wang S, Duong TQ. Incidence and risk factors of new clinical disorders in patients with COVID‐19 hyperinflammatory syndrome. Sci Rep. 2025;15:19892. doi: 10.1038/s41598-025-04070-9 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 8. Lu JQ, Lu JY, Wang W, Liu Y, Buczek A, Fleysher R, Hoogenboom WS, Zhu W, Hou W, Rodriguez CJ, et al. Clinical predictors of acute cardiac injury and normalization of troponin after hospital discharge from COVID‐19. EBioMedicine. 2022;76:103821. doi: 10.1016/j.ebiom.2022.103821 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 9. Rahmati M, Koyanagi A, Banitalebi E, Yon DK, Lee SW, Shin IJ, Smith L. The effect of SARS‐CoV‐2 infection on cardiac function in post‐COVID‐19 survivors: A systematic review and meta‐analysis. J Med Virol. 2023;95:e28325. doi: 10.1002/jmv.28325 [DOI] [PubMed] [Google Scholar]
- 10. Tawiah K, Jackson L, Omosule C, Ballman C, Shahideh B, Scott MG, Murtagh G, Farnsworth CW. Serial cardiac biomarkers for risk stratification of patients with COVID‐19. Clin Biochem. 2022;107:24–32. doi: 10.1016/j.clinbiochem.2022.06.002 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 11. Sheth A, Modi M, Dawson D, Dominic P. Prognostic value of cardiac biomarkers in COVID‐19 infection. Sci Rep. 2021;11:4930. doi: 10.1038/s41598-021-84643-6 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 12. Lu JY, Buczek A, Fleysher R, Hoogenboom WS, Hou W, Rodriguez CJ, Fisher MC, Duong TQ. Outcomes of hospitalized patients with COVID‐19 with acute kidney injury and acute cardiac injury. Front Cardiovasc Med. 2021;8:798897. doi: 10.3389/fcvm.2021.798897 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 13. Lu JY, Buczek A, Fleysher R, Musheyev B, Henninger EM, Jabbery K, Rangareddy M, Kanawade D, Nelapat C, Soby S, et al. Characteristics of COVID‐19 patients with multiorgan injury across the pandemic in a large academic health system in the Bronx, New York. Heliyon. 2023;9:e15277. doi: 10.1016/j.heliyon.2023.e15277 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 14. Lu JY, Ho SL, Buczek A, Fleysher R, Hou W, Chacko K, Duong TQ. Clinical predictors of recovery of COVID‐19 associated‐abnormal liver function test 2 months after hospital discharge. Sci Rep. 2022;12:17972. doi: 10.1038/s41598-022-22741-9 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 15. Lu JY, Hou W, Duong TQ. Longitudinal prediction of hospital‐acquired acute kidney injury in COVID‐19: a two‐center study. Infection. 2022;50:109–119. doi: 10.1007/s15010-021-01646-1 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 16. Dell'Aquila K, Lee J, Wang SH, Alamuri TT, Jennings R, Tang H, Mahesh S, Leong TJ, Fleysher R, Henninger EM, et al. Incidence, characteristics, risk factors and outcomes of diabetic ketoacidosis in COVID‐19 patients: Comparison with influenza and pre‐pandemic data. Diabetes Obes Metab. 2023;25:2482–2494. doi: 10.1111/dom.15120 [DOI] [PubMed] [Google Scholar]
- 17. Feit A, Gordon M, Alamuri TT, Hou W, Mitchell WB, Manwani D, Duong TQ. Long‐term clinical outcomes and healthcare utilization of sickle cell disease patients with COVID‐19: A 2.5‐year follow‐up study. Eur J Haematol. 2023;111:636–643. doi: 10.1111/ejh.14058 [DOI] [PubMed] [Google Scholar]
- 18. Eligulashvili A, Darrell M, Miller C, Lee J, Congdon S, Lee JS, Hsu K, Yee J, Hou W, Islam M, et al. COVID‐19 patients in the COVID‐19 Recovery and Engagement (CORE) clinics in the Bronx. Diagnostics (Basel). 2022;13:13. doi: 10.3390/diagnostics13010119 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 19. Eligulashvili A, Gordon M, Lee JS, Lee J, Mehrotra‐Varma S, Mehrotra‐Varma J, Hsu K, Hilliard I, Lee K, Li A, et al. Long‐term outcomes of hospitalized patients with SARS‐CoV‐2/COVID‐19 with and without neurological involvement: 3‐year follow‐up assessment. PLoS Med. 2024;21:e1004263. doi: 10.1371/journal.pmed.1004263 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 20. Eligulashvili A, Darrell M, Gordon M, Jerome W, Fiori KP, Congdon S, Duong TQ. Patients with unmet social needs are at higher risks of developing severe long COVID‐19 symptoms and neuropsychiatric sequela. Sci Rep. 2024;14:7743. doi: 10.1038/s41598-024-58430-y [DOI] [PMC free article] [PubMed] [Google Scholar]
- 21. Lu JY, Boparai MS, Shi C, Henninger EM, Rangareddy M, Veeraraghavan S, Mirhaji P, Fisher MC, Duong TQ. Long‐term outcomes of COVID‐19 survivors with hospital AKI: association with time to recovery from AKI. Nephrol Dial Transplant. 2023;38:2160–2169. doi: 10.1093/ndt/gfad020 [DOI] [PubMed] [Google Scholar]
- 22. Hadidchi R, Al‐Ani Y, Choi S, Renteria S, Duong KS, Henry S, Wang SH, Duong TQ. Long‐term outcomes of patients with a pre‐existing neurological condition after SARS‐CoV‐2 infection. J Neurol Sci. 2025;473:123477. doi: 10.1016/j.jns.2025.123477 [DOI] [PubMed] [Google Scholar]
- 23. Hadidchi R, Al‐Ani Y, Piskun H, Pakan R, Duong KS, Jamil H, Wang SH, Henry S, Maurer CW, Duong TQ. Impact of COVID‐19 on long‐term outcomes in Parkinson's disease. Eur J Neurol. 2025;32:e70013. doi: 10.1111/ene.70013 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 24. Hadidchi R, Duong KS, Hou J, Maldjian T, Chung J, Hou W, Fineberg S, Lu J, Makower D, Duong TQ. COVID‐19 pandemic interruption of breast cancer screening is linked to clinical upstaging at presentation: the roles of demographics, socioeconomic status and unmet social needs. Breast Cancer Res Treat. 2025;212:205–216. doi: 10.1007/s10549-025-07713-7 [DOI] [PubMed] [Google Scholar]
- 25. Hadidchi R, Pakan R, Alamuri T, Cercizi N, Al‐Ani Y, Wang SH, Henry S, Duong TQ. Long COVID‐19 outcomes of patients with pre‐existing dementia. J Alzheimer's Dis. 2024;103:13872877241303934. doi: 10.1177/13872877241303934 [DOI] [PubMed] [Google Scholar]
- 26. Hadidchi R, Wang SH, Rezko D, Henry S, Coyle PK, Duong TQ. SARS‐CoV‐2 infection increases long‐term multiple sclerosis disease activity and all‐cause mortality in an underserved inner‐city population. Mult Scler Relat Disord. 2024;86:105613. doi: 10.1016/j.msard.2024.105613 [DOI] [PubMed] [Google Scholar]
- 27. Pakan R, Hadidchi R, Al‐Ani Y, Piskun H, Duong KS, Henry S, Wang S, Maurer CW, Duong TQ. Long‐term outcomes of patients with pre‐existing essential tremor after SARS‐CoV‐2 infection. Diagnostics. 2024;14:2774. doi: 10.3390/diagnostics14242774 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 28. Qiu S, Hadidchi R, Vichare A, Lu JY, Hou W, Henry S, Akalin E, Duong TQ. SARS‐CoV‐2 infection is associated with an accelerated eGFR decline in kidney transplant recipients up to four years post infection. Diagnostics. 2025;15:1091. doi: 10.3390/diagnostics15091091 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 29. Hadidchi R, Lee P, Qiu S, Changela S, Henry S, Duong TQ. Long‐term outcomes of patients with pre‐existing coronary artery disease after SARS‐CoV‐2 infection. EBioMedicine. 2025;116:105778. doi: 10.1016/j.ebiom.2025.105778 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 30. Aimo A, Januzzi JL Jr, Vergaro G, Petersen C, Pasanisi EM, Molinaro S, Passino C, Emdin M. Left ventricular ejection fraction for risk stratification in chronic systolic heart failure. Int J Cardiol. 2018;273:136–140. doi: 10.1016/j.ijcard.2018.07.117 [DOI] [PubMed] [Google Scholar]
- 31. Abraham WT, Psotka MA, Fiuzat M, Filippatos G, Lindenfeld J, Mehran R, Ambardekar AV, Carson PE, Jacob R, Januzzi JL Jr, et al. Standardized definitions for evaluation of heart failure therapies: scientific expert panel from the Heart Failure Collaboratory and Academic Research Consortium. Eur J Heart Fail. 2020;22:2175–2186. doi: 10.1002/ejhf.2018 [DOI] [PubMed] [Google Scholar]
- 32. Heidenreich PA, Bozkurt B, Aguilar D, Allen LA, Byun JJ, Colvin MM, Deswal A, Drazner MH, Dunlay SM, Evers LR, et al. 2022 AHA/ACC/HFSA guideline for the management of heart failure: a report of the American College of Cardiology/American Heart Association Joint Committee on Clinical Practice Guidelines. Circulation. 2022;145:e876–e894. doi: 10.1161/CIR.0000000000001062 [DOI] [PubMed] [Google Scholar]
- 33. Russo A, Pisaturo M, Monari C, Ciminelli F, Maggi P, Allegorico E, Gentile I, Sangiovanni V, Esposito V, Gentile V, et al. Prognostic value of creatinine levels at admission on disease progression and mortality in patients with COVID‐19‐an observational retrospective study. Pathogens. 2023;12:12. doi: 10.3390/pathogens12080973 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 34. Webb BJ, Peltan ID, Jensen P, Hoda D, Hunter B, Silver A, Starr N, Buckel W, Grisel N, Hummel E, et al. Clinical criteria for COVID‐19‐associated hyperinflammatory syndrome: a cohort study. Lancet Rheumatol. 2020;2:e754–e763. doi: 10.1016/S2665-9913(20)30343-X [DOI] [PMC free article] [PubMed] [Google Scholar]
- 35. Karagodin I, Singulane CC, Descamps T, Woodward GM, Xie M, Tucay ES, Sarwar R, Vasquez‐Ortiz ZY, Alizadehasl A, Monaghan MJ, et al. Ventricular changes in patients with acute COVID‐19 infection: follow‐up of the World Alliance Societies of Echocardiography (WASE‐COVID) study. J Am Soc Echocardiogr. 2022;35:295–304. doi: 10.1016/j.echo.2021.10.015 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 36. Lassen MCH, Skaarup KG, Lind JN, Alhakak AS, Sengelov M, Nielsen AB, Simonsen JO, Johansen ND, Davidovski FS, Christensen J, et al. Recovery of cardiac function following COVID‐19 ‐ ECHOVID‐19: a prospective longitudinal cohort study. Eur J Heart Fail. 2021;23:1903–1912. doi: 10.1002/ejhf.2347 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 37. Petersen EL, Gossling A, Adam G, Aepfelbacher M, Behrendt CA, Cavus E, Cheng B, Fischer N, Gallinat J, Kuhn S, et al. Multi‐organ assessment in mainly non‐hospitalized individuals after SARS‐CoV‐2 infection: The Hamburg City Health Study COVID programme. Eur Heart J. 2022;43:1124–1137. doi: 10.1093/eurheartj/ehab914 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 38. Milani RV, Drazner MH, Lavie CJ, Morin DP, Ventura HO. Progression from concentric left ventricular hypertrophy and normal ejection fraction to left ventricular dysfunction. Am J Cardiol. 2011;108:992–996. doi: 10.1016/j.amjcard.2011.05.038 [DOI] [PubMed] [Google Scholar]
- 39. Parodi JB, Indavere A, Bobadilla Jacob P, Toledo GC, Micali RG, Waisman G, Masson W, Epstein ED, Huerin MS. Impact of COVID‐19 vaccination in post‐COVID cardiac complications. Vaccine. 2023;41:1524–1528. doi: 10.1016/j.vaccine.2023.01.052 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 40. McCullough PA, Hulscher N. Risk stratification for future cardiac arrest after COVID‐19 vaccination. World J Cardiol. 2025;17:103909. doi: 10.4330/wjc.v17.i2.103909 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 41. Rose J, Hulscher N, McCullough PA. Determinants of COVID‐19 vaccine‐induced myocarditis. Therap Adv Drug Saf. 2024;15:20420986241226566. doi: 10.1177/20420986241226566 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 42. Hulscher N, Hodkinson R, Makis W, McCullough PA. Autopsy findings in cases of fatal COVID‐19 vaccine‐induced myocarditis. ESC Heart Fail. 2024:ehf2.14680. doi: 10.1002/ehf2.14680 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 43. Krauson AJ, Casimero FVC, Siddiquee Z, Stone JR. Duration of SARS‐CoV‐2 mRNA vaccine persistence and factors associated with cardiac involvement in recently vaccinated patients. NPJ Vaccines. 2023;8:141. doi: 10.1038/s41541-023-00742-7 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 44. Yonker LM, Swank Z, Bartsch YC, Burns MD, Kane A, Boribong BP, Davis JP, Loiselle M, Novak T, Senussi Y, et al. Circulating spike protein detected in post‐COVID‐19 mRNA vaccine myocarditis. Circulation. 2023;147:867–876. doi: 10.1161/CIRCULATIONAHA.122.061025 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 45. Navaratnarajah CK, Pease DR, Halfmann PJ, Taye B, Barkhymer A, Howell KG, Charlesworth JE, Christensen TA, Kawaoka Y, Cattaneo R, et al. Highly efficient SARS‐CoV‐2 infection of human cardiomyocytes: spike protein‐mediated cell fusion and its inhibition. J Virol. 2021;95:e0136821. doi: 10.1128/JVI.01368-21 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 46. Bojkova D, Wagner JUG, Shumliakivska M, Aslan GS, Saleem U, Hansen A, Luxan G, Gunther S, Pham MD, Krishnan J, et al. SARS‐CoV‐2 infects and induces cytotoxic effects in human cardiomyocytes. Cardiovasc Res. 2020;116:2207–2215. doi: 10.1093/cvr/cvaa267 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 47. Bavishi C, Bonow RO, Trivedi V, Abbott JD, Messerli FH, Bhatt DL. Special Article ‐ Acute myocardial injury in patients hospitalized with COVID‐19 infection: A review. Prog Cardiovasc Dis. 2020;63:682–689. doi: 10.1016/j.pcad.2020.05.013 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 48. Lee CY, Huang CH, Rastegari E, Rengganaten V, Liu PC, Tsai PH, Chin YF, Wu JR, Chiou SH, Teng YC, et al. Tumor necrosis factor‐alpha exacerbates viral entry in SARS‐CoV2‐infected iPSC‐derived cardiomyocytes. Int J Mol Sci. 2021;22:22. doi: 10.3390/ijms22189869 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 49. Dimai S, Semmler L, Prabhu A, Stachelscheid H, Huettemeister J, Klaucke SC, Lacour P, Blaschke F, Kruse J, Parwani A, et al. COVID19‐associated cardiomyocyte dysfunction, arrhythmias and the effect of Canakinumab. PLoS One. 2021;16:e0255976. doi: 10.1371/journal.pone.0255976 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 50. Colzani M, Bargehr J, Mescia F, Williams EC, Knight‐Schrijver V, Lee J, Summers C, Mohorianu I, Smith KGC, Lyons PA, et al. Proinflammatory cytokines driving cardiotoxicity in COVID‐19. Cardiovasc Res. 2024;120:174–187. doi: 10.1093/cvr/cvad174 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 51. Wu CK, Lee JK, Chiang FT, Yang CH, Huang SW, Hwang JJ, Lin JL, Tseng CD, Chen JJ, Tsai CT. Plasma levels of tumor necrosis factor‐alpha and interleukin‐6 are associated with diastolic heart failure through downregulation of sarcoplasmic reticulum Ca2+ ATPase. Crit Care Med. 2011;39:984–992. doi: 10.1097/CCM.0b013e31820a91b9 [DOI] [PubMed] [Google Scholar]
- 52. Melendez GC, McLarty JL, Levick SP, Du Y, Janicki JS, Brower GL. Interleukin 6 mediates myocardial fibrosis, concentric hypertrophy, and diastolic dysfunction in rats. Hypertension. 2010;56:225–231. doi: 10.1161/HYPERTENSIONAHA.109.148635 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 53. Pellegrini D, Kawakami R, Guagliumi G, Sakamoto A, Kawai K, Gianatti A, Nasr A, Kutys R, Guo L, Cornelissen A, et al. Microthrombi as a major cause of cardiac injury in COVID‐19: a pathologic study. Circulation. 2021;143:1031–1042. doi: 10.1161/CIRCULATIONAHA.120.051828 [DOI] [PubMed] [Google Scholar]
- 54. Becker RC. COVID‐19 update: Covid‐19‐associated coagulopathy. J Thromb Thrombolysis. 2020;50:54–67. doi: 10.1007/s11239-020-02134-3 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 55. Corovic A, Zhao X, Huang Y, Newland SR, Gopalan D, Harrison J, Giakomidi D, Chen S, Yarkoni NS, Wall C, et al. Coronavirus disease 2019‐related myocardial injury is associated with immune dysregulation in symptomatic patients with cardiac magnetic resonance imaging abnormalities. Cardiovasc Res. 2024;120:1752–1767. doi: 10.1093/cvr/cvae159 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 56. Puntmann VO, Martin S, Shchendrygina A, Hoffmann J, Ka MM, Giokoglu E, Vanchin B, Holm N, Karyou A, Laux GS, et al. Long‐term cardiac pathology in individuals with mild initial COVID‐19 illness. Nat Med. 2022;28:2117–2123. doi: 10.1038/s41591-022-02000-0 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 57. Puntmann VO, Carerj ML, Wieters I, Fahim M, Arendt C, Hoffmann J, Shchendrygina A, Escher F, Vasa‐Nicotera M, Zeiher AM, et al. Outcomes of cardiovascular magnetic resonance imaging in patients recently recovered from coronavirus disease 2019 (COVID‐19). JAMA Cardiol. 2020;5:1265–1273. doi: 10.1001/jamacardio.2020.3557 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 58. Lu JY, Lu JY, Wang SH, Duong KS, Hou W, Duong TQ. New‐onset cardiovascular diseases post SARS‐CoV‐2 infection in an urban population in the Bronx. Sci Rep. 2024;14:31451. doi: 10.1038/s41598-024-82983-7 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 59. Maddox TM, Januzzi JL Jr, Allen LA, Breathett K, Brouse S, Butler J, Davis LL, Fonarow GC, Ibrahim NE, Lindenfeld J, et al. 2024 ACC expert consensus decision pathway for treatment of heart failure with reduced ejection fraction: a report of the American College of Cardiology Solution Set Oversight Committee. J Am Coll Cardiol. 2024;83:1444–1488. doi: 10.1016/j.jacc.2023.12.024 [DOI] [PubMed] [Google Scholar]
- 60. Papamichail A, KoureK C, Briasoulis A, Xanthopoulos A, Tsougos E, Farmakis D, Paraskevaidis I. Targeting key inflammatory mechanisms underlying heart failure: a comprehensive review. Int J Mol Sci. 2023;2:510. doi: 10.3390/ijms25010510 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 61. Szabo TM, Frigy A, Nagy EE. Targeting mediators of inflammation in heart failure: a short synthesis of experimental and clinical results. Int J Mol Sci. 2021;22:22. doi: 10.3390/ijms222313053 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 62. Yokoe I, Kobayashi H, Kobayashi Y, Giles JT, Yoneyama K, Kitamura N, Takei M. Impact of tocilizumab on N‐terminal pro‐brain natriuretic peptide levels in patients with active rheumatoid arthritis without cardiac symptoms. Scand J Rheumatol. 2018;47:364–370. doi: 10.1080/03009742.2017.1418424 [DOI] [PubMed] [Google Scholar]
Associated Data
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Supplementary Materials
Data S1
Tables S1–S5