Abstract
Background:
It is important to understand the risk for in-hospital mortality of adults hospitalized with acute COVID-19 infection with a history of HF.
Methods:
We examined patients hospitalized with COVID-19 infection from January 1-July 22, 2020, from 88 centers across the US participating in the American Heart Association’s COVID-19 Cardiovascular Disease registry. The primary exposure was history of HF and the primary outcome was in-hospital mortality. To examine the association between history of HF and in-hospital mortality, we conducted multivariable modified Poisson regression models that included socio-demographics and comorbid conditions. We also examined HF subtypes based on left ventricular ejection fraction (LVEF) in the prior year, when available.
Results:
Among 8,920 patients hospitalized with COVID-19, mean age was 61.4+/−17.5 years and 55.5% were men. History of HF was present in 979 (11%) patients. In-hospital mortality occurred in 31.6% of patients with history of HF, and 16.9% in patients without a history of HF. In a fully-adjusted model, history of HF was associated with increased risk for in-hospital mortality (relative risk [RR]: 1.16; 95% confidence interval [95%CI]:1.03-1.30). Among 335 patients with LVEF, HFrEF was significantly associated with in-hospital mortality in a fully-adjusted model (HFrEF RR: 1.40, 95%CI 1.10-1.79; HFmrEF RR: 1.06, 95%CI 0.65-1.73; HFpEF RR 1.06, 95%CI 0.84-1.33).
Conclusion:
Risk for in-hospital mortality was substantial among adults with history of HF, in large part due to age and comorbid conditions. History of HFrEF may confer especially elevated risk. This population thus merits prioritization for the COVID-19 vaccine.
Keywords: heart failure, COVID-19, mortality, outcomes, Heart Failure and Cardiac Disease
Introduction
As of April 2021, coronavirus disease 2019 (COVID-19) had been diagnosed in more than 140 million people across the world.1 According to the Centers for Disease Control and Prevention (CDC), factors associated with severe illness include “heart conditions such as heart failure (HF), coronary artery disease, or cardiomyopathies.2” While there are over 6 million people across the United States with HF,3 the characteristics of adults with HF hospitalized for COVID-19 and their outcomes have not been well-elucidated. A study from a single health system suggested that adults with a history of HF regardless of ejection fraction had worse outcomes compared with persons without HF.4 However, the sample size was relatively small, including 422 patients with a history of HF, and generalizability was limited as it only included patients from New York City (NYC)—a specific geographic region where the number of cases during the surge in spring 2020 overwhelmed many hospitals.5 This study sought to leverage the American Heart Association (AHA) national COVID-19 Cardiovascular Disease (CVD) registry powered by Get With the Guidelines (GWTG) to examine risk among patients with established HF who were hospitalized with COVID-19 in the United States.
Methods
Data Sources
In early 2020, the AHA launched the COVID-19 CVD Registry in response to the COVID-19 pandemic given the urgent need to better understand characteristics and sequelae of patients hospitalized with COVID-19. The details of this registry have previously been described.6 Briefly, this registry uses the data infrastructure of the AHA’s GWTG program, which is a hospital-based quality improvement program that has collected data on hospitalized patients with selected cardiovascular conditions from participating hospitals for the past two decades.7,8 Similar to other GWTG registries, hospitals voluntarily choose to participate in this registry, and provide data through the use of structured online interactive case report forms in the Patient Management Tool™ (PMT™), powered by IQVIA (Parsippany, New Jersey). Trained personnel populate registry data using standardized definitions for patient demographic characteristics, clinical comorbidities, inpatient laboratory data, treatment therapies at admission and discharge, and in-hospital outcomes.
For the COVID-19 CVD registry, hospitals reported over 200 data elements on consecutive patients hospitalized with COVID-19. The case report form is available at: https://www.heart.org/-/media/files/professional/quality-improvement/covid-19-cvd-registry/ahacovidcvdcrf428-fillable-pdf.pdf?la=en. As of July 22, 2020, 88 hospitals from 31 states across the United States were participating (Supplemental Figure 1). The AHA COVID-19 CVD Registry data were patient-and hospital-de-identified and made available to investigators through the AHA’s Precision Medicine Platform (https://precision.heart.org/); requests to access the data after submitting a proposal should be made through the AHA COVID-19 CVD Registry: https://www.heart.org/en/professional/quality-improvement/covid-19-cvd-registry/covid-19-cvd-registry-research-opportunities.
Each site participating in the registry obtained institutional review board approval or exemption and were granted a waiver of informed consent under the common rule, according to local regulations. The Institutional Review Board at Weill Cornell Medicine confirmed exempt status for this analysis.
Study Population
We examined all completed records (age≥18 years) from the 88 sites participating in the AHA COVID-19 CVD Registry between January 1, 2020 and July 22, 2020. Inclusion in the registry required confirmation with an RT-PCR test, either prior to or during the hospitalization, a positive IgM antibody test, or a clinical diagnosis using hospital specific criteria; and also required one of the following three scenarios: diagnosis prior to hospitalization but still symptomatic during the hospitalization; or a positive test or diagnosis during hospital admission; or symptomatic during the hospitalization and a confirmed test available after hospital discharge.
Exposure
The primary exposure was history of HF (present/absent), which is systematically recorded through the AHA’s COVID-19 CVD Registry case report form. We additionally examined HF subtypes (heart failure with reduced ejection fraction [HFrEF], heart failure with mid-range ejection fraction [HFmrEF], and heart failure with preserved ejection fraction [HFpEF]) based on left ventricular ejection fraction (LVEF) recorded in the previous year, when available. In accordance with the AHA’s Heart Failure Clinical Practice Guidelines, HFrEF was defined as <40%, HFmrEF was defined as EF 40-49.9%, and HFpEF was defined as ≥50%.9,10 We defined “unspecified subtype” as those who were recorded as having history of HF but did not have a LVEF from the prior year available.
Outcome
The primary outcome was in-hospital mortality, which was systematically recorded through the AHA’s COVID-19 CVD Registry case report form. As patients discharged to hospice are likely to die soon after discharge and excluding these patients from the primary outcome could lead to bias, we planned a priori to conduct a sensitivity analysis whereby we examined a composite endpoint of death or discharge to hospice.
Statistical Analysis
We calculated means and standard deviations, or medians and interquartile ranges (IQR) where appropriate for continuous variables; and calculated proportions for categorical variables. To examine the association between history of HF and in-hospital mortality, we conducted a modified Poisson regression analysis that adjusted for demographics (age, sex, and race/ethnicity11) and comorbid conditions (coronary artery disease [CAD], diabetes, obesity [body mass index12 ≥30 kg/m2], smoking, chronic obstructive pulmonary disease [COPD], chronic kidney disease [CKD], cancer, and solid organ transplant) (Model 3). The specific comorbid conditions chosen are established risk factors for severe COVID-19 according to the CDC.2 We reported relative risks (RR) and their 95% confidence intervals (95%CI). We chose to conduct a modified Poisson model, which generates relative risk, instead of a logistic regression because the outcome was common; when an outcome is common, odds ratios from a logistic regression tend to overestimate risk.13
We also examined for effect modification by age (based on threshold of 65 years since age ≥65 years is a major risk factor for mortality),14 sex, and race/ethnicity by testing the significance of interaction terms.
We additionally explored the association between HF subtypes (HFrEF, HFmrEF, HFpEF, and unspecified subtype) and in-hospital mortality using a multivariable modified Poisson regression analysis, again adjusted for demographics and comorbid conditions.
To determine statistical significance, we performed 2-sided hypothesis testing with an alpha error of 0.05. To minimize bias due to missing data, we performed multiple imputations by chained equations.15 Statistical analyses were performed using R version 3.5.1 software (R Foundation, Vienna, Austria).
Results
Clinical Parameters at Presentation
We examined 8,920 patients hospitalized with COVID-19 from 88 different facilities, among whom 979 (11%) had history of HF. The mean age was 61.4 +/− 17.5 years and 55.5% were men. Clinical characteristics for patients with history of HF and without HF are shown in Table 1. Patients with HF were older, more frequently non-Hispanic White, and more frequently Medicare beneficiaries compared to patients without HF. In addition, patients with HF more frequently had several comorbid conditions including: CAD, diabetes, COPD, CKD, cancer, solid organ transplant, atrial fibrillation, cerebrovascular disease, peripheral arterial disease, dyslipidemia, asthma, interstitial lung disease, and prior deep vein thrombosis or pulmonary embolism. As shown in Table 2, patients with HF were more likely to take several different cardiovascular medications.
Table 1.
Baseline Characteristics according to Prior History of Heart Failure
| All (n=8920) | Patients with HF (n=979) | Patients without HF (n=7941) | P-value | |
|---|---|---|---|---|
| SOCIODEMOGRAPHICS, N (%) | ||||
| Age, mean (SD) | 61.4 (17.5) | 71.5 (14.2) | 60.2 (17.5) | <0.001 |
| Age ≥ 65 years | 4060 (45.5) | 694 (70.9) | 3366 (42.4) | <0.001 |
| Male | 4949 (55.5) | 523 (53.4) | 4426 (55.7) | 0.18 |
| Race/Ethnicity | ||||
| White, non-Hispanic | 2869 (32.2) | 424 (43.3) | 2445 (30.8) | <0.001 |
| Black, non-Hispanic | 2100 (23.5) | 282 (28.8) | 1818 (22.9) | <0.001 |
| Hispanic | 2713 (30.4) | 195 (19.9) | 2518 (31.7) | <0.001 |
| Asian or Pacific Islander | 510 (5.7) | 34 (3.5) | 476 (6.0) | 0.002 |
| Native American | 35 (0.4) | 4 (0.4) | 31 (0.4) | 0.99 |
| Undetermined | 693 (7.8) | 40 (4.1) | 653 (8.2) | <0.001 |
| Insurance | ||||
| Medicare | 1993 (22.9) | 394 (42.0) | 1599 (20.6) | <0.001 |
| Medicaid | 1493 (17.2) | 179 (19.1) | 1314 (16.9) | 0.11 |
| Private | 2831 (32.6) | 145 (15.4) | 2686 (34.6) | <0.001 |
| Self | 834 (9.6) | 22 (2.3) | 812 (10.5) | <0.001 |
| Other/Undetermined | 281 (3.2) | 18 (1.9) | 263 (3.4) | 0.02 |
| HIGH RISK CO-MORBID CONDITIONS (%) | ||||
| Coronary artery disease | ||||
| Prior myocardial infarction | 387 (4.3) | 157 (16.0) | 230 (2.9) | <0.001 |
| Prior percutaneous coronary intervention | 414 (4.6) | 151 (15.4) | 263 (3.3) | <0.001 |
| Prior Coronary artery bypass graft | 267 (3.0) | 113 (11.5) | 154 (1.9) | <0.001 |
| Diabetes | 3222 (36.1) | 537 (54.9) | 2685 (33.8) | <0.001 |
| Mild to moderate obesity (BMI 30-39.9) | 2515 (28.2) | 275 (28.1) | 2240 (28.2) | 0.97 |
| Morbid obesity (BMI≥40) | 852 (9.6) | 119 (12.2) | 733 (9.2) | 0.004 |
| Smoking | 551 (6.2) | 94 (9.6) | 457 (5.8) | <0.001 |
| Chronic obstructive pulmonary disease | 708 (7.9) | 234 (23.9) | 474 (6.0) | <0.001 |
| Chronic kidney disease | 1139 (12.8) | 400 (40.9) | 739 (9.3) | <0.001 |
| End-stage renal disease | 346 (3.9) | 120 (12.3) | 226 (2.8) | <0.001 |
| Cancer | 1079 (12.1) | 160 (16.3) | 919 (11.6) | <0.001 |
| Solid organ transplant | 147 (1.6) | 31 (3.2) | 116 (1.5) | <0.001 |
| OTHER COMORBID CONDITIONS (%) | ||||
| Atrial fibrillation/flutter | 819 (9.2) | 321 (32.8) | 498 (6.3) | <0.001 |
| Cerebrovascular disease | 976 (10.9) | 198 (20.2) | 778 (9.8) | <0.001 |
| Peripheral arterial disease | 236 (2.6) | 82 (8.4) | 154 (1.9) | <0.001 |
| Dyslipidemia | 3069 (34.4) | 554 (56.6) | 2515 (31.7) | <0.001 |
| Asthma | 843 (9.5) | 117 (12.0) | 726 (9.1) | 0.01 |
| Interstitial lung disease | 40 (0.4) | 9 (0.9) | 31 (0.4) | 0.04 |
| Other pulmonary disorder | 182 (2.0) | 45 (4.6) | 137 (1.7) | <0.001 |
| Prior deep vein thrombosis or pulmonary embolism | 393 (4.4) | 106 (10.8) | 287 (3.6) | <0.001 |
| Lupus or rheumatoid Arthritis | 146 (1.6) | 21 (2.1) | 125 (1.6) | 0.23 |
| HOSPITAL CHARACTERISTICS (%) | ||||
| U.S. Geographic region | 0.001 | |||
| Northeast | 4595 (51.5) | 484 (49.4) | 4111 (51.8) | |
| Midwest | 514 (5.8) | 50 (5.1) | 464 (5.8) | |
| South | 2800 (31.4) | 297 (30.3) | 2503 (31.5) | |
| West | 1011 (11.3) | 148 (15.1) | 863 (10.9) | |
| Urban location | 6752 (75.7) | 770 (78.7) | 5982 (75.3) | 0.06 |
| Teaching hospital | 6265 (70.2) | 719 (73.4) | 5546 (69.8) | 0.04 |
| Bed size ≥ 200 | 6506 (73.5) | 756 (77.2) | 5750 (72.4) | 0.001 |
Abbreviations: BMI Body mass index; SD Standard deviation
Table 2.
Baseline Medication Patterns according to Prior History of Heart Failure
| All (n=8920) | Patients with HF (n=979) | Patients without HF (n=7941) | P-value | |
|---|---|---|---|---|
| MEDICATION (%) | ||||
| Angiotensin receptor-neprilysin inhibitor | 32 (0.4) | 19 (2.1) | 13 (0.2) | <0.001 |
| ACEI or ARB | 2280 (26.9) | 350 (38.9) | 1930 (25.4) | <0.001 |
| Beta blockers | 2051 (24.2) | 539 (59.9) | 1512 (19.9) | <0.001 |
| Calcium channel blockers | 1721 (20.3) | 249 (27.7) | 1472 (19.4) | <0.001 |
| Diuretics | 1343 (15.8) | 398 (44.2) | 945 (12.5) | <0.001 |
| Mineralocorticoid antagonists | 46 (0.5) | 23 (2.6) | 23 (0.3) | <0.001 |
| SGLT2 inhibitor | 129 (1.5) | 14 (1.6) | 115 (1.5) | 0.89 |
| Statin | 3013 (35.9) | 548 (62.5) | 2465 (32.8) | <0.001 |
| Aspirin | 2030 (23.1) | 445 (46.6) | 1585 (20.2) | <0.001 |
| P2Y12 inhibitors | 347 (3.9) | 105 (11.0) | 242 (3.1) | <0.001 |
| Factor Xa inhibitor | 518 (6.1) | 183 (20.4) | 335 (4.4) | <0.001 |
| Warfarin | 192 (2.3) | 71 (7.9) | 121 (1.6) | <0.001 |
| DPP-4 inhibitors | 274 (3.2) | 41 (4.6) | 233 (3.1) | 0.02 |
| GLP-1 receptor agonist | 145 (1.7) | 23 (2.6) | 122 (1.6) | 0.05 |
| Sulfonylurea | 399 (4.7) | 62 (6.9) | 337 (4.4) | 0.001 |
| Insulin | 1097 (12.9) | 241 (26.8) | 856 (11.3) | <0.001 |
| Thiazolidinedione | 76 (0.9) | 5 (0.6) | 71 (0.9) | 0.35 |
| Metformin | 1297 (15.3) | 132 (14.7) | 1165 (15.4) | 0.63 |
| Corticosteroid | 1069 (12.1) | 183 (19.0) | 886 (11.2) | <0.001 |
| Other immunosuppressive agents | 281 (3.2) | 36 (3.7) | 245 (3.1) | 0.33 |
| Chemotherapy or biological agent for cancer | 144 (1.6) | 12 (1.2) | 132 (1.7) | 0.42 |
| Hydroxychloroquine | 425 (4.8) | 24 (2.5) | 401 (5.1) | <0.001 |
Abbreviations: ACEI: angiotensin-converting enzyme inhibitor, ARB: angiotensin receptor blocker, SGLT2: sodium-glucose co-transporter 2, DPP-4, dipeptidyl peptidase-4, GLP-1: glucose-like protein-1
With regard to indices upon presentation, the most common symptoms in patients with and without HF were shortness of breath, cough, and fever/chills (Table 3). Altered mental status was more frequent among adults with HF compared to those without HF (19.9% vs. 9.4%, p<0.001). Although rare overall, those with HF were more likely to present with systolic blood pressure <90 mmHg than those without HF. Patients with HF had higher levels of troponin, B-type natriuretic peptide (BNP), NT-proBNP, D-dimer, and procalcitonin (Table 3).
Table 3.
Symptoms, Vital signs, and Laboratory values upon presentation according to prior history of HF
| All (n=8920) | Patients with HF (n=979) | Patients without HF (n=7941) | P-value | |
|---|---|---|---|---|
| SYMPTOMS (%) | ||||
| Fever/Chills | 5402 (62.0) | 471 (50.0) | 4931 (63.5) | <0.001 |
| Cough | 5428 (62.3) | 497 (52.8) | 4931 (63.5) | <0.001 |
| Shortness of breath | 5093 (58.5) | 581 (61.7) | 4512 (58.1) | 0.04 |
| Fatigue | 2085 (23.9) | 200 (21.2) | 1885 (24.3) | 0.04 |
| Headache | 772 (8.9) | 41 (4.4) | 731 (9.4) | <0.001 |
| Myalgia | 1774 (20.4) | 131 (13.9) | 1643 (21.2) | <0.001 |
| Sore throat | 561 (6.4) | 32 (3.4) | 529 (6.8) | <0.001 |
| Nasal congestion | 428 (4.9) | 41 (4.4) | 387 (5.0) | 0.44 |
| Gastrointestinal symptoms | 2335 (26.8) | 199 (21.1) | 2136 (27.5) | <0.001 |
| Loss of smell/taste | 347 (4.0) | 15 (1.6) | 332 (4.3) | <0.001 |
| Altered mental status | 917 (10.5) | 187 (19.9) | 730 (9.4) | <0.001 |
| Other | 2084 (23.9) | 220 (23.4) | 1864 (24.0) | 0.69 |
| VITAL SIGNS | ||||
| Fever (>38 °C) | 1857 (21.7) | 167 (17.4) | 1690 (22.3) | 0.001 |
| Median [IQR] heart rate in beats per minute | 94 [81-107] | 88 [75-102] | 94 [82-107] | <0.001 |
| Heart rate ≥125 beats per minute | 546 (6.3) | 47 (4.8) | 499 (6.5) | 0.05 |
| Median [IQR] systolic blood pressure in mm Hg | 129 [115-144] | 128 [112-147] | 129 [115-144] | 0.65 |
| Systolic blood pressure <90 mm Hg | 217 (2.5) | 44 (4.6) | 173 (2.3) | <0.001 |
| Median [IQR] diastolic blood pressure in mm Hg | 75 [66-84] | 72 [63-84] | 76 [67-84] | <0.001 |
| Respiratory rate >24 breaths per minute | 1640 (19.2) | 208 (21.7) | 1432 (18.8) | 0.04 |
| LABORATORIES | ||||
| Median WBC count (1000 per mm3) | 6.8 [5.1-9.4] | 6.5 [4.9-9.4] | 6.9 [5.2-9.4] | 0.02 |
| WBC count >10,000 per mm3 | 1787 (20.9) | 193 (20.3) | 1594 (21.0) | 0.65 |
| WBC count <4,000 per mm3 | 891 (10.4) | 115 (12.1) | 776 (10.2) | 0.08 |
| Median hemoglobin in g/dL | 13.1 [11.5-14.4] | 11.80 [10.1-13.4] | 13.20 [11.7-14.5] | <0.001 |
| Median platelet count (1000 per mm3) | 199 [154-259] | 184 [139-247] | 201 [156-260] | <0.001 |
| Median serum creatinine mg/dL | 1.01 [0.80-1.48] | 1.47 [1.00-2.75] | 1.00 [0.79-1.38] | <0.001 |
| Serum creatinine ≥1.5 mg/dL | 2101 (24.8) | 463 (49.1) | 1638 (21.8) | <0.001 |
| Median alanine aminotransferase U/L | 30 [19-49] | 22 [15-34] | 31 [20-50] | <0.001 |
| Alanine aminotransferase >40 U/L | 2693 (33.3) | 172 (19.5) | 2521 (35.0) | <0.001 |
| Median aspartate aminotransferase U/L | 39 [27-61] | 35 [23-56] | 40 [27-62] | <0.001 |
| Aspartate aminotransferase >40 U/L | 3797 (48.2) | 358 (40.8) | 3439 (49.1) | <0.001 |
| Median total bilirubin umol/L | 0.5 [0.4-0.7] | 0.5 [0.4-0.8] | 0.5 [0.4-0.7] | <0.001 |
| Total bilirubin >17.1 umol/L | 10 (0.1) | 0 (0.0) | 10 (0.1) | 0.53 |
| Median troponin ng/mL | 0.01 [0.00-0.10] | 0.04 [0.00-0.20] | 0.00 [0.00-0.07] | <0.001 |
| Troponin >0.5 ng/mL | 663 (12.8) | 112 (18.3) | 551 (12.1) | <0.001 |
| Median D-Dimer ug/L | 800 [341, 1500] | 1000 [480, 1700] | 773 [328, 1460] | <0.001 |
| D-Dimer >500 ug/L | 2793 (63.2) | 335 (73.1) | 2458 (62.1) | <0.001 |
| Median BNP ng/L | 58 [22-220] | 333 [102-1045] | 45 [17-154] | <0.001 |
| Median NT-proBNP ng/L | 260 [58-1577] | 2656 [697-12547] | 177[49-828] | <0.001 |
| Median C-Reactive protein mg/dL | 4.90 [1.18-9.99] | 4.65 [1.17-9.99] | 4.98 [1.18-9.99] | 0.73 |
| C-Reactive protein >10 mg/dL | 906 (17.6) | 104 (18.2) | 802 (17.5) | 0.72 |
| Median procalcitonin ng/mL | 0.16 [0.09-0.43] | 0.22 [0.10-0.90] | 0.15 [0.08-0.40] | <0.001 |
| Procalcitonin ≥0.5 ng/mL | 1242 (23.1) | 206 (34.9) | 1036 (21.6) | <0.001 |
| Median IL-6 ng/mL | 0.02 [0.01-0.06] | 0.02 [0.01-0.06] | 0.02 [0.00-0.06] | 0.06 |
| IL-6 ≥0.08 ng/mL | 251 (21.5) | 30 (21.3) | 221 (21.5) | 1 |
In-hospital Events
Figure 1 shows differences in critical illness parameters between patients with and without HF. Adults with HF were more likely to be admitted to the intensive care unit (33.5% vs. 27.6%, p<0.001), with similar prevalence of mechanical ventilation (22.4% vs. 20.5%, p=0.18). Shock was more frequent among individuals with HF (15.7% vs. 11.6%, p<0.001); cardiogenic (2.2% vs. 0.6%), distributive (9.8% vs. 9.0%), and mixed (2.7% vs. 0.7%) shock were all numerically higher among those with HF compared to those without HF. Vasoactive agents were more frequently used for adults with HF (13.5% vs. 10.7%, p=0.01); and mechanical circulatory support strategies such as intra-aortic balloon pumps, percutaneous ventricular assist devices like an Impella, and venoarterial-extracorporeal membranous oxygenation (VA-ECMO) were rare for those with and without HF (Figure 1).
Figure 1. Critical illness parameters according to history of heart failure.
ICU and shock were more common in patients with HF compared to those without HF
Abbreviations: HF Heart failure; ICU Intensive Care Unit; MCS Mechanical Circulatory Support
Atrial fibrillation and sustained ventricular arrhythmias occurred more frequently among patients with HF compared to those without HF; and pulmonary embolism occurred less frequently among those with HF compared to those without HF (Table 4). Corticosteroid use was more common in patients with HF, and hydroxychloroquine and azithromycin use were more common in patients without HF (Table 4). Approximately 3.9% (n=38) of patients with HF and 2.1% (n=167) of patients without HF were discharged to hospice.
Table 4.
In-hospital Medication Use and Complications according to History of Heart Failure
| All (n=8920) | Patients with HF (n=979) | Patients without HF (n=7941) | P-value | |
|---|---|---|---|---|
| MEDICATION (%) | ||||
| Glucocorticoids | 1817 (21.2) | 221 (24.1) | 1596 (20.8) | 0.004 |
| Immunoglobulins | 67 (0.8) | 10 (1.0) | 57 (0.7) | 0.38 |
| Convalescent serum | 230 (2.6) | 30 (3.1) | 200 (2.6) | 0.34 |
| Ritonavir/lopinavir | 85 (1.0) | 6 (0.7) | 79 (1.0) | 0.37 |
| Hydroxychloroquine | 3861 (43.9) | 303 (31.6) | 3558 (45.4) | <0.001 |
| Azithromycin | 4312 (48.9) | 390 (40.7) | 3922 (49.9) | <0.001 |
| Remdesivir | 690 (7.8) | 82 (8.6) | 608 (7.7) | 0.40 |
| Tocilizumab | 609 (6.9) | 65 (6.8) | 544 (6.9) | 0.93 |
| COMPLICATIONS (%) | ||||
| Myocarditis | 28 (0.3) | 4 (0.4) | 24 (0.3) | 0.79 |
| Atrial fibrillation | 718 (8.1) | 189 (19.7) | 529 (6.7) | <0.001 |
| Sustained ventricular tachycardia | 90 (1.0) | 16 (1.7) | 74 (0.9) | 0.05 |
| Heart block | 7 (0.1) | 5 (0.5) | 2 (<0.1) | <0.001 |
| Intracardiac thrombus | 12 (0.1) | 3 (0.3) | 9 (0.1) | 0.27 |
| Stroke | 106 (1.2) | 11 (1.1) | 95 (1.2) | 1 |
| Pulmonary embolism | 124 (1.4) | 5 (0.5) | 119 (1.5) | 0.02 |
| Deep vein thrombosis | 193 (2.2) | 16 (1.7) | 177 (2.2) | 0.30 |
| Significant bleeding | 257 (2.9) | 50 (5.1) | 207 (2.6) | <0.001 |
| New dialysis | 340 (3.9) | 40 (4.2) | 300 (3.8) | 0.64 |
| Length of stay, median days (IQR) | 5.8 [3.5-10.8] | 6.7 [3.8-11.8] | 5.8 [3.5-10.8] | <0.001 |
Mortality
In-hospital mortality was 31.6% for patients with HF and 16.9% for those without HF. In an unadjusted regression model, a history of HF was associated with an increased risk for in-hospital mortality (RR 1.87, 95%CI 1.68-2.07). When adjusting for age, sex, and race/ethnicity, the RR attenuated to 1.30 (95%CI 1.17-1.44). In a fully adjusted model including demographics and comorbid conditions, the RR further attenuated to 1.16 (95%CI 1.03-1.30) (Figure 2). The p-value for interaction for age was <0.01. Adults aged <65 years had a fully-adjusted RR of 1.11 (95%CI 0.81-1.52); and adults aged ≥65 years had a fully-adjusted RR of 1.17 (95%CI 1.04-1.32). We did not find evidence to support an interaction with sex (p=0.21) or race/ethnicity (p=0.69). These observations were similar when examining the composite outcome of in-hospital mortality or hospice (Supplemental Figure 2).
Figure 2. Association between a history of heart failure and in-hospital mortality.
In a fully adjusted model including demographics and comorbid conditions, the relative risk of in-hospital mortality was 1.16 (95%CI 1.03-1.30). The p-for-interaction for age was <0.01. Adults aged <65 years had a fully-adjusted RR of 1.11 (95%CI 0.81-1.52); and adults aged ≥65 years had a fully-adjusted RR of 1.17 (95%CI 1.04-1.32). We did not find evidence to support an interaction with sex (p=0.21) or race/ethnicity (p=0.69). The model controlled for age, sex, race, smoking, diabetes, chronic obstructive pulmonary disease, chronic kidney disease, coronary artery disease, obesity defined as body mass index ≥30 kg/m2, cancer, and solid organ transplant.
Abbreviations: HF Heart failure
HF Subtypes
Among patients with HF, 335 (34.2%) had known LVEF in the past year: 103 (30.7%) had HFrEF, 48 (14.3%) had HFmrEF, and 184 (54.9%) had HFpEF. Patients with HFpEF were older and were more frequently Black non-Hispanic than those with HFrEF or HFmrEF (Supplemental Table 1). Those with HFpEF also had a lower prevalence of known CAD. Calcium channel blockers were the most common medications administered prior to admission among those with HFpEF; and renin-angiotensin system inhibitors, statins, insulin, and corticosteroids were most common in those with HFmrEF (Supplemental Table 2). Symptoms and vital signs upon presentation were similar across HF subtypes; patients with HFrEF most frequently had troponins above 0.5 ng/mL and also had the highest levels of BNP and NT-proBNP (Supplemental Table 3).
Figure 3 shows differences in critical illness parameters across HF subtypes. Adults with HFrEF experienced shock and required vasoactive agents more frequently than other HF subtypes. Those with HFpEF most frequently experienced atrial fibrillation and significant bleeding (Supplemental Table 4). In-hospital medication patterns were similar across HF subtypes (Supplemental Table 4). Three patients with HFrEF, 1 patient with HFmrEF, 10 patients with HFpEF, and 24 patients with unspecified subtype were discharged to hospice.
Figure 3. Critical illness parameters according to heart failure subtype.
Shock was more common in individuals with HFrEF compared to other heart failure subtypes
Abbreviations: ICU Intensive Care Unit; MCS Mechanical Circulatory Support; HFrEF Heart failure with reduced ejection fraction; HFmrEF Heart failure with mid-range ejection fraction; HFpEF Heart failure with preserved ejection fraction
In-hospital mortality was 35% for HFrEF, 27.1%, for HFmrEF, 30.4% for HFpEF, and 31.7% for those with unspecified subtype. In an unadjusted regression model, the RRs for in-hospital mortality were as follows: HFrEF: RR 1.99, 95%CI 1.55-2.56; HFmrEF: RR 1.54, 95%CI 0.99-2.39; HFpEF: RR 1.89, 95%CI 1.55-2.30; unspecified subtype: RR 1.86, 95%CI 1.66-2.09). In a fully-adjusted model, HFrEF remained associated with in-hospital mortality (HFrEF RR: 1.40, 95%CI 1.10-1.79; HFmrEF RR: 1.06, 95%CI 0.65-1.73; HFpEF RR 1.08, 95%CI 0.84-1.33; unspecified subtype RR: 1.16, 95%CI 1.02-1.32) (Figure 4). These findings were similar when examining the composite outcome of in-hospital mortality or hospice (Supplemental Figure 3).
Figure 4. Association between heart failure subtypes and in-hospital mortality.
In unadjusted model, all HF subtypes were associated with in-hospital mortality: HFrEF: RR 1.99, 95%CI 1.55-2.56; HFmrEF: RR 1.54, 95%CI 0.99-2.39; HFpEF: RR 1.89, 95%CI 1.55-2.30; unknown subtype: RR 1.86, 95%CI 1.66-2.09). In a fully-adjusted model, HFrEF was associated with in-hospital mortality (HFrEF RR: 1.40, 95%CI 1.10-1.79; HFmrEF RR: 1.06, 95%CI 0.65-1.73; HFpEF RR 1.08, 95%CI 0.84-1.33; unspecified subtype RR: 1.16, 95%CI 1.02-1.32) The model controlled for age, sex, race, smoking, diabetes, chronic obstructive pulmonary disease, chronic kidney disease, coronary artery disease, obesity defined as body mass index ≥30 kg/m2, cancer, and solid organ transplant.
Abbreviations: HFrEF Heart failure with reduced ejection fraction; HFmrEF Heart failure with mid-range ejection fraction; HFpEF Hearrt failure with preserved ejection fraction; RR Relative Risk
Discussion
There were several important findings from this analysis of a national registry of over 8,000 adults hospitalized for COVID-19 infection. First, the prevalence of prior HF was 11%. Second, in-hospital mortality for adults with prior diagnosis of HF exceeded 30%, and was in large part due to risks conferred by socio-demographics and comorbid conditions. Third, we found that adults aged at least 65 years were especially vulnerable to the additive risk of HF. Finally, we found that prior HFrEF was associated with in-hospital mortality but HFpEF and HFmrEF were not.
Prior work has shown that preexisting HF may be present in up to a third of adults hospitalized for respiratory infections.16 A study evaluating adults hospitalized in the United States for a principal diagnosis of influenza reported a 15% prevalence of prior HF17, but this may have been underestimated due to coding practices. Accordingly, the prevalence of 11% from our study was lower than anticipated. This was at least in part due to the relatively young age of patients captured in this registry. Additionally, this could reflect that some patients with HF recognized that they were vulnerable to the negative effects of COVID-19 and therefore followed recommended precautions to protect themselves. Alternatively, our results could reflect patient reluctance to seek care during the ongoing pandemic—observed elevated rates of out-of-hospital cardiac arrest have been partially attributed to this phenomenon.18 Not all patients, even those with history of HF, will need a hospitalization if they contract COVID-19. However, given that patients with history of HF have a reduced physiologic resilience to respiratory viral infections19 and that HF-exacerbations may be triggered by respiratory viral infections,20 increased vigilance is warranted. Our findings should thus prompt increased efforts to educate our patients about contacting a healthcare professional if they develop concerning symptoms.
To our knowledge, this was the first geographically-diverse study in the United States examining the association between HF and in-hospital mortality. Our study showed that in-hospital mortality for adults with a history of HF exceeded 30%, which was almost double the in-hospital mortality for adults without HF. Much of this risk was attributable to socio-demographics and comorbid conditions. Indeed, once adjusted for these other factors, the relative risk for in-hospital mortality was attenuated to 1.16. A prior study by Alvarez-Garcia et al from a hospital system in NYC demonstrated that among 422 adults with COVID-19, a history of HF was independently associated with a two-fold increased odds of in-hospital mortality.4 However, it is important to note that that study was conducted within a single hospital system in a specific region of the country (NYC). In contrast, the current study included patients from 88 different hospitals and 31 states from across the United States. Findings from our study showed that the incremental risk of in-hospital mortality conferred by a history of HF is likely closer to 10-20% as opposed to doubled.
Our findings showed that older adults aged at least 65 years are especially vulnerable to the additive risk of HF. These observations do not negate the notion that younger adults with HF are also vulnerable to adverse events during hospitalization for COVID-19. By virtue of having other conditions that confer risk, adults with HF of any age remain one of the most vulnerable populations for adverse events during a hospitalization for COVID-19. Accordingly, regardless of age, sex, or race/ethnicity, patients with HF should be especially vigilant about following preventive behaviors like handwashing, social distancing, and mask-wearing. The use of virtual visits has previously been endorsed by the Heart Failure Society of America,21 and should continue as a strategy to optimize care with limited unnecessary contact. These data moreover support prioritizing the COVID-19 vaccine for patients with HF, especially those ≥65 years, and creating outreach and educational programs to improve vaccination rates in these patients.
When examining HF subtypes, we found that prior HFrEF conferred an elevated risk for in-hospital mortality but HFpEF and HFmrEF did not. While prior studies have reported in-hospital mortality for each subtype,4 the relatively large number of HF patients in this study allowed the first examination of the association of different HF subtypes with in-hospital mortality after adjusting for other key variables such as socio-demographics and comorbid conditions. Notably, those with HFrEF were more likely to present with hypotension, experience shock, and require vasoactive agents. Mechanisms underlying this observation are not known. As has been shown in other respiratory viruses like influenza, 22, 23 SARS-CoV-2 can cause direct myocardial injury and/or inflammatory processes leading to myocardial dysfunction.24 Our findings suggest that individuals with HFrEF in particular may have lower reserve to handle additional myocardial injury. Those with HFrEF had higher levels of cardiac biomarkers (BNP/NT-proBNP and troponin) possibly suggesting increased wall stress and myocardial injury compared with the other HF subtypes. Since few echocardiograms were performed during hospitalization, we did not know whether a significant drop in LVEF, or changes to the right ventricle (which have been shown to confer risk of mortality in COVID-1925) occurred in the setting of COVID-19. Studies that can characterize COVID-19 illness-related myocardial tissue properties of both the left ventricle and right ventricle over time are warranted.
Some might point to the high use of angiotensin-converting enzyme (ACE) inhibitors or angiotensin receptor blockers (ARBs) as an explanation for our findings, given concerns about increased susceptibility to infection related to the ACE2 receptor.26 However, data have shown that ACE inhibitors and/or ARBs are not associated with increased susceptibility to COVID-19,27, 28 and major HF societies including the AHA have recommended their continuation in patients with HF.29 Observations here regarding outcomes of HF subtypes need to be interpreted with caution, given that baseline LVEF was only available for 1/3 of the patients with HF in this study. However, based on these data, it is reasonable to infer that extra vigilance is needed when caring for adults with HFrEF who are hospitalized with COVID-19.
There are several strengths to this study. First, data were derived from a national registry that included 88 hospitals across 31 states in the United States. Second, to our knowledge, this is the largest study of patients with HF hospitalized for COVID-19 in the US to date. Third, to examine the association of HF with mortality, we included key demographics as well as most comorbid conditions identified by the CDC as conferring increased risk for severe infection. These factors allowed us to draw conclusions about the independent risks conferred by preexisting HF on COVID mortality.
Several limitations should be noted. This study was observational in nature and thus precluded establishing a causal relationship between HF and mortality. Despite being the largest study of patients with HF and COVID-19 to date, sample size may have precluded definitive inferences about the association between HF and in-hospital mortality. Sample size also limited subgroup analyses—future work examining additional age-stratified analyses to identify the highest risk subpopulations may be warranted. Baseline LVEF was available in only 1/3 of the HF patients, and the small sample raises the possibility for overfitting—accordingly, findings related to HF subtype should be considered hypothesis-generating. In light of the challenges to obtain diagnostic testing such as echocardiograms during the height of the pandemic, it is possible that some cases of clinical HF may have been missed. In our models, we did not account for clinician-level differences such as in-hospital management practices. For example, if patients with a specific HF subtype received increased attention and/or more aggressive therapy, this could have impacted the association with mortality. We also did not have data on New York Heart Association (NYHA) class—if the group with HFrEF had more advanced disease based on NYHA class, this could have had an impact on our findings. The AHA COVID-19 CVD Registry is a voluntary program among hospitals interested in a quality improvement initiative, which may impact generalizability. Finally, these data were collected through July 22, 2020, and do not include cases from the latest surge of COVID-19 infections in the United States.
In conclusion, our study showed that a prior history of HF occurred in 11% of adults hospitalized for COVID-19, most of the risk for in-hospital mortality was explained by socio-demographics and comorbid conditions, adults aged at least 65 years are especially vulnerable to the additive risk of a prior history of HF, and HFrEF may confer especially high risk. These data identify adults with HF as a vulnerable population to the adverse effects of COVID-19.
Supplementary Material
Clinical Implications.
What is new?
History of heart failure was present in 1 out of 9 patients hospitalized with acute COVID-19 infection in this national registry study.
Nearly 1 in 3 patients with a history of heart failure died during hospitalization for acute COVID-19 infection.
Among adults with a history of heart failure, a large proportion of risk for in-hospital mortality was attributable to socio-demographics and comorbid conditions.
History of heart failure with reduced ejection fraction may confer especially high risk for in-hospital mortality among adults hospitalized with COVID-19.
What are the Clinical Implications?
Patients with history of heart failure, especially those older than 65 years, should be considered a group at high risk for COVID-19 related complications.
Patients with history of heart failure with reduced ejection fraction may warrant especially close attention when admitted for COVID-19.
Sources of Funding:
AHA’s suite of Registries is funded by multiple industry sponsors. AHA’s COVID-19 CVD Registry is partially supported by The Gordon and Betty Moore Foundation.
Disclosures:
Dr. Goyal is supported by American Heart Association grant 20CDA35310455 and by National Institute on Aging grant K76AG064428; Dr. Goyal receives personal fees for medicolegal consulting related to heart failure. Dr Weinsaft has received compensation from GE Healthcare for consulting related to cardiac MR. Dr. Safford has received research support from Amgen. Dr. Navi serves as a DSMB member for the PCORI-funded TRAVERSE trial and has received personal fees for medico-legal consulting on stroke. Dr. Elkind serves as an unpaid Officer of the AHA; receives study drug in kind from the BMS-Pfizer Alliance for Eliquis® and ancillary research funding but no personal compensation for an NIH-funded trial of stroke prevention in patients with ESUS; and receives royalties from UpToDate for chapters on COVID-19 and stroke. Dr. Allen is supported by grants from the American Heart Association, the National Institutes of Health, and the Patient-Centered Outcomes Research Institute; and received consulting fees from ACI Clinical, Amgen, Boston Scientific, Cytokinetics, and Novartis. Sadiya Khan is supported by an American Heart Association grant (#19TPA34890060).
References:
- 1.COVID-19 Weekly Epidemiological Update. World Health Organization. URL https://www.who.int/publications/m/item/weekly-epidemiological-update---17-november-2020. Published on November 17, 2020. Accessed on November 23, 2020. [Google Scholar]
- 2.COVID-19. Centers for Disease Control and Prevention. URL https://www.cdc.gov/coronavirus/2019-ncov/need-extra-precautions/people-with-medical-conditions.html Updated May 13, 2021. Accessed November 3, 2020. [Google Scholar]
- 3.Virani SS, Alonso A, Benjamin EJ, Bittencourt MS, Callaway CW, Carson AP, Chamberlain AM, Chang AR, Cheng S, Delling FN, et al. , American Heart Association Council on E, Prevention Statistics C and Stroke Statistics S. Heart Disease and Stroke Statistics-2020 Update: A Report From the American Heart Association. Circulation. 2020;141:e139–e596. [DOI] [PubMed] [Google Scholar]
- 4.Alvarez-Garcia J, Lee S, Gupta A, Cagliostro M, Joshi AA, Rivas-Lasarte M, Contreras J, Mitter SS, LaRocca G, Tlachi P, Brunjes D, Glicksberg BS, et al. Prognostic Impact of Prior Heart Failure in Patients Hospitalized With COVID-19. J Am Coll Cardiol. 2020;76:2334–2348. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 5.Griffin KM, Karas MG, Ivascu NS and Lief L. Hospital Preparedness for COVID-19: A Practical Guide from a Critical Care Perspective. Am J Respir Crit Care Med. 2020; 201:1337–1344. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 6.Alger HM, Rutan C, Williams JHt, Walchok JG, Bolles M, Hall JL, Bradley SM, Elkind MSV, Rodriguez F, Wang TY, et al. American Heart Association COVID-19 CVD Registry Powered by Get With The Guidelines. Circ Cardiovasc Qual Outcomes. 2020;13:e006967. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 7.Smaha LA and American Heart A. The American Heart Association Get With The Guidelines program. Am Heart J. 2004;148:S46–8. [DOI] [PubMed] [Google Scholar]
- 8.Ellrodt AG, Fonarow GC, Schwamm LH, Albert N, Bhatt DL, Cannon CP, Hernandez AF, Hlatky MA, Luepker RV, Peterson PN, et al. Synthesizing lessons learned from get with the guidelines: the value of disease-based registries in improving quality and outcomes. Circulation. 2013;128:2447–60. [DOI] [PubMed] [Google Scholar]
- 9.Yancy CW, Jessup M, Bozkurt B, Butler J, Casey DE Jr., Drazner MH, Fonarow GC, Geraci SA, Horwich T, Januzzi JL, et al. 2013 ACCF/AHA guideline for the management of heart failure: executive summary: a report of the American College of Cardiology Foundation/American Heart Association Task Force on practice guidelines. Circulation. 2013;128:1810–52. [DOI] [PubMed] [Google Scholar]
- 10.Yancy CW, Jessup M, Bozkurt B, Butler J, Casey DE Jr., Colvin MM, Drazner MH, Filippatos GS, Fonarow GC, Givertz MM, et al. 2017 ACC/AHA/HFSA Focused Update of the 2013 ACCF/AHA Guideline for the Management of Heart Failure: A Report of the American College of Cardiology/American Heart Association Task Force on Clinical Practice Guidelines and the Heart Failure Society of America. J Am Coll Cardiol. 2017;136:e137–e161. [DOI] [PubMed] [Google Scholar]
- 11.Rodriguez F, Solomon N, de Lemos JA, Das SR, Morrow DA, Bradley SM, Elkind MSV, Williams JH Iv, Holmes D, Matsouaka RA, et al. Racial and Ethnic Differences in Presentation and Outcomes for Patients Hospitalized with COVID-19: Findings from the American Heart Association’s COVID-19 Cardiovascular Disease Registry. Circulation. 2020. ;143:2332–2342. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 12.Hendren NS, de Lemos JA, Ayers C, Das SR, Rao A, Carter S, Rosenblatt A, Walchok JG, Omar W, Khera R, et al. Association of Body Mass Index and Age With Morbidity and Mortality in Patients Hospitalized With COVID-19: Results From the American Heart Association COVID-19 Cardiovascular Disease Registry. Circulation. 2020. ;143:135–144. [DOI] [PubMed] [Google Scholar]
- 13.Knol MJ, Le Cessie S, Algra A, Vandenbroucke JP and Groenwold RH. Overestimation of risk ratios by odds ratios in trials and cohort studies: alternatives to logistic regression. CMAJ. 2012;184:895–9. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 14.COVID-19. Centers for Disease Control and Prevention. URL https://www.cdc.gov/coronavirus/2019-ncov/need-extra-precautions/older-adults.html. Updated June 9, 2021. Accessed November 3, 2020. [Google Scholar]
- 15.Carpenter JRKM. Multiple Imputation and its Application. Hoboken, NJ: John Wiley & Sons, Ltd; 2013. [Google Scholar]
- 16.Perry TW, Pugh MJ, Waterer GW, Nakashima B, Orihuela CJ, Copeland LA, Restrepo MI, Anzueto A and Mortensen EM. Incidence of cardiovascular events after hospital admission for pneumonia. Am J Med. 2011;124:244–51. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 17.Yandrapalli S, Aronow WS and Frishman WH. Readmissions in adult patients following hospitalization for influenza: a nationwide cohort study. Ann Transl Med. 2018;6:318. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 18.Lai PH, Lancet EA, Weiden MD, Webber MP, Zeig-Owens R, Hall CB and Prezant DJ. Characteristics Associated With Out-of-Hospital Cardiac Arrests and Resuscitations During the Novel Coronavirus Disease 2019 Pandemic in New York City. JAMA Cardiol. 2020;5:1154–1163. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 19.Panhwar MS, Kalra A, Gupta T, Kolte D, Khera S, Bhatt DL and Ginwalla M. Effect of Influenza on Outcomes in Patients With Heart Failure. JACC Heart Fail. 2019;7:112–117. [DOI] [PubMed] [Google Scholar]
- 20.Kytomaa S, Hegde S, Claggett B, Udell JA, Rosamond W, Temte J, Nichol K, Wright JD, Solomon SD and Vardeny O. Association of Influenza-like Illness Activity With Hospitalizations for Heart Failure: The Atherosclerosis Risk in Communities Study. JAMA Cardiol. 2019;4:363–369. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 21.Gorodeski EZ, Goyal P, Cox ZL, Thibodeau JT, Reay RE, Rasmusson K, Rogers JG and Starling RC. Virtual Visits for Care of Patients with Heart Failure in the Era of COVID-19: A Statement from the Heart Failure Society of America. J Card Fail. 2020;26:448–456. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 22.Fagnoul D, Pasquier P, Bodson L, Ortiz JA, Vincent JL and De Backer D. Myocardial dysfunction during H1N1 influenza infection. J Crit Care. 2013;28:321–7. [DOI] [PubMed] [Google Scholar]
- 23.Gao C, Wang Y, Gu X, Shen X, Zhou D, Zhou S, Huang JA, Cao B, Guo Q and Community-Acquired Pneumonia-China N. Association Between Cardiac Injury and Mortality in Hospitalized Patients Infected With Avian Influenza A (H7N9) Virus. Crit Care Med. 2020;48:451–458. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 24.Nishiga M, Wang DW, Han Y, Lewis DB and Wu JC. COVID-19 and cardiovascular disease: from basic mechanisms to clinical perspectives. Nat Rev Cardiol. 2020;17:543–558. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 25.Kim J, Volodarskiy A, Sultana R, Pollie MP, Yum B, Nambiar L, Tafreshi R, Mitlak HW, RoyChoudhury A, Horn EM, et al. Prognostic Utility of Right Ventricular Remodeling Over Conventional Risk Stratification in Patients With COVID-19. J Am Coll Cardiol. 2020;76:1965–1977. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 26.Li W, Moore MJ, Vasilieva N, Sui J, Wong SK, Berne MA, Somasundaran M, Sullivan JL, Luzuriaga K, Greenough TC, et al. Angiotensin-converting enzyme 2 is a functional receptor for the SARS coronavirus. Nature. 2003;426:450–4. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 27.Mehta N, Kalra A, Nowacki AS, Anjewierden S, Han Z, Bhat P, Carmona-Rubio AE, Jacob M, Procop GW, Harrington S, et al. Association of Use of Angiotensin-Converting Enzyme Inhibitors and Angiotensin II Receptor Blockers With Testing Positive for Coronavirus Disease 2019 (COVID-19). JAMA Cardiol. 2020;5:1020–1026. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 28.Fosbol EL, Butt JH, Ostergaard L, Andersson C, Selmer C, Kragholm K, Schou M, Phelps M, Gislason GH, Gerds TA, et al. Association of Angiotensin-Converting Enzyme Inhibitor or Angiotensin Receptor Blocker Use With COVID-19 Diagnosis and Mortality. JAMA. 2020;324:168–177. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 29.Bozkurt B, Kovacs R and Harrington B. Joint HFSA/ACC/AHA Statement Addresses Concerns Re: Using RAAS Antagonists in COVID-19. J Card Fail. 2020;26:370. [DOI] [PMC free article] [PubMed] [Google Scholar]
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