Abstract
The Coronavirus disease 2019 (COVID-19) infection predisposes patients to develop deep vein thrombosis (DVT) and pulmonary embolism (PE). In this study, we compared the in-hospital outcomes of patients with DVT and/or PE with concurrent COVID-19 infection vs those with concurrent flu infection. The National Inpatient Sample from 2019 to 2020 was analyzed to identify all adult admissions diagnosed with DVT and PE. These patients were then stratified based on whether they had concomitant COVID-19 or flu. We identified 62,895 hospitalizations with the diagnosis of DVT and/or PE with concomitant COVID-19, and 8155 hospitalizations with DVT and/or PE with concomitant flu infection. After 1:1 propensity score match, the incidence of cardiac arrest and inpatient mortality were higher in the COVID-19 group. The incidence of cardiogenic shock was higher in the flu group. Increased age, Hispanic race, diabetes, chronic kidney disease, arrhythmia, liver disease, coagulopathy, and rheumatologic diseases were the independent predictors of mortality in patients with DVT and/or PE with concomitant COVID-19.
Introduction
The incidence of thrombotic events in patients with coronavirus disease 2019 (COVID-19) is significantly higher than the incidence in patients without COVID-19.1 Influenza or flu infection has also been found to be associated with deep vein thrombosis (DVT).2 Various studies have been done to identify the characteristics of patients affected with COVID-19 or flu infection who developed thrombotic complications, including DVT or pulmonary embolism (PE).3 , 4 Studies have been conducted to show the difference in the occurrence of thrombotic events between patients with COVID-19 and patients with non-COVID-19 viral infections, including flu.5 , 6 But there is no large-scale study comparing the in-hospital outcomes in patients admitted with a diagnosis of DVT and/or PE who have concurrent COVID-19 vs flu infection. We have analyzed National Inpatient Sample (NIS) database to compare the demographic data, co-morbidities, in-hospital complications, and mortality in patients with DVT and/or PE who had concomitant COVID-19 infection vs patients admitted with DVT/PE with concomitant flu infection. Also, we demonstrated the clinical predictors of adverse outcomes in DVT/PE patients with COVID-19 infection.
Methods
Data Source
The HCUP NIS database is the largest all-payer in-hospital database in the US (United States) and is available publicly. We have used the NIS database from 2019 to 2020 for our study. The NIS represents 95% of US hospitalizations from 44 states participating in HCUP and provides a stratified sample of 20% of discharges, including up to 8 million hospital discharges per year. The NIS database has been previously demonstrated to correlate well with other discharge databases in the US. In addition, it has been validated in various studies to provide reliable estimates of admissions within the US.7
Study Population
We included hospitalizations with DVT and/or PE and stratified them based on concurrent COVID-19 and influenza infection diagnosis by International Classification of Diseases 10th Revision clinical modification (ICD-10-CM) codes. Studies have shown overall positive predictive value for COVID-19 diagnosis with ICD-10-CM is 99%.8
Outcomes
The primary outcome of interest was in-hospital mortality in patients with DVT and/or PE with COVID-19 compared with those with DVT and/or PE with influenza infection. Secondary outcomes included acute kidney injury (AKI) as well as, AKI requiring hemodialysis, sepsis, stroke, cardiogenic shock, the requirement of vasopressors, acute respiratory failure as well as, respiratory failure requiring intubation, need for mechanical circulatory support such as intra-aortic balloon pump , extracorporeal membrane oxygenation , length of stay , and hospitalization costs.
Statistical Analysis
Statistical analyses were performed using Stata 16.0 (StataCorp. 2019. Stata Statistical Software: Release 16. College Station, TX: StataCorp LLC). The discharge weights provided by the Agency for Healthcare Research and Quality were applied to obtain weighted numbers to calculate national estimates.
A 1:1 propensity score matching (nearest-neighbor matching with a caliper width of 0.1 of the estimated propensity scores) was performed to compare outcomes for patients with DVT and/or PE and concomitant COVID-19 vs patients with DVT/PE with concurrent influenza infection. Multivariate logistic regression models were generated to identify the independent predictors of mortality and reported as adjusted odds ratio (aOR) with a 95% confidence interval (CI). Categorical variables were expressed as percentages. Continuous variables were expressed as median and interquartile range. Categorical variables were compared using the Pearson chi-square test, while continuous variables were compared using the student's t-test. All reported P values are 2-sided, with a value of < 0.05 considered significant.
Results
We identified 62,895 hospitalizations with DVT and/or PE with a concurrent diagnosis of COVID-19 infection. The number of hospitalizations with DVT and/or PE with a concurrent diagnosis of influenza was 8155. Propensity score matching was performed to create a more balanced population, with 8110 hospitalizations in each group.
Table 1 describes the baseline characteristics of patients admitted with DVT and/or PE with concomitant COVID-19 vs concomitant influenza infection. The mean age of DVT and/or PE patients with COVID-19 was 66 years [standard deviation (SD): 55-77] vs 63 years (SD: 51-74) in DVT/PE with flu group. The percentage of female patients (43.4% vs 41.1%, P < 0.001) and the Caucasian population (62% vs 50.2%, P < 0.001) were significantly higher in the flu group compared to the COVID-19 group. The Hispanic population was higher in the COVID-19 group (10.4% vs 17.1%). The number of patients with a history of congestive heart failure (34% vs 18%, P < 0.001) and valvular heart disease (8% vs 4%, P < 0.001) was higher in the flu group compared to the COVID-19 (Table 1).
TABLE 1.
Baseline characteristics of patients with DVT and/or PE with concurrent Flu and COVID-19 before and after propensity match with complications of hospitalized patients.
| Characteristics | ||||||
|---|---|---|---|---|---|---|
| Before matching |
After matching |
|||||
| With Flu | With COVID-19 | P value | With Flu | With COVID-19 | P value | |
| Total number of patients | 8155 | 62,895 | 8110 | 8110 | ||
| Age, median IQR, years | 63 (51-74) | 66 (55-77) | <0.001 | 63 (51-74) | 63 (52-73) | 0.693 |
| Age groups (%) | <0.001 | 0.873 | ||||
| 18-59 | 41.3 | 33.8 | 430 | 420 | ||
| 60-69 | 24.8 | 24.5 | 85 | 75 | ||
| 70-79 | 19.5 | 23.2 | 95 | 115 | ||
| >79 y | 14.4 | 18.5 | 70 | 70 | ||
| Female (%) | 47.4 | 41.1 | <0.001 | 47.5 | 49 | 0.0385 |
| Caucasian race (%) | 61.2 | 50.2 | <0.001 | 61.8 | 62.9 | 0.534 |
| African American race (%) | 19.9 | 22.5 | 0.021 | 20 | 19 | 0.49 |
| Hispanics (%) | 10.4 | 17.1 | <0.001 | 10.4 | 11 | 0.588 |
| Atrial fibrillation (%) | 17.5 | 12.9 | <0.001 | 17.3 | 18.4 | 0.407 |
| Diabetes mellitus (%) | 30.1 | 37.9 | <0.001 | 30.1 | 27.8 | 0.13 |
| Hypertension (%) | 64.4 | 63.6 | 0.539 | 64.4 | 63.6 | 0.667 |
| Chronic kidney disease (%) | 19.8 | 18.8 | 0.348 | 19.9 | 19.3 | 0.695 |
| CHF (%) | 34 | 18.3 | <0.001 | 34.1 | 21 | <0.001 |
| Peripheral vascular disease (%) | 8.1 | 5.4 | <0.001 | 8 | 8.1 | 0.949 |
| Dementia (%) | 7.1 | 11.2 | <0.001 | 7.2 | 7.5 | 0.734 |
| COPD (%) | 39.4 | 21.1 | <0.001 | 39.1 | 39.4 | 0.887 |
| Valvular heart disease (%) | 8.1 | 4.1 | <0.001 | 8.1 | 5.1 | <0.001 |
| Arrhythmias (%) | 33.3 | 28.5 | <0.001 | 33.1 | 31.9 | 0.456 |
| Liver disease (%) | 9.6 | 7.1 | <0.001 | 9.6 | 7.6 | 0.048 |
| Hypothyroidism (%) | 10.7 | 11.6 | 0.247 | 10.7 | 13.8 | 0.005 |
| Anemia (%) | 7.4 | 5.3 | 0.001 | 7.5 | 7.6 | 0.895 |
| Cancer (%) | 13.1 | 5.8 | <0.001 | 12.8 | 13.9 | 0.372 |
| Rheumatological disorders (%) | 5.2 | 3 | <0.001 | 5.2 | 4.7 | 0.563 |
| Weight loss (%) | 17 | 13.1 | <0.001 | 16.9 | 16.8 | 0.927 |
| Coagulopathy (%) | 19.4 | 22.7 | 0.003 | 19.5 | 19.1 | 0.793 |
| Obesity (%) | 25.2 | 27.2 | 0.096 | 25.3 | 24 | 0.377 |
| Smoking history (%) | 16.7 | 5.3 | <0.001 | 16.3 | 14.7 | 0.22 |
| Coronary artery disease (%) | 16.5 | 15.4 | 0.248 | 16.4 | 16.5 | 0.961 |
| Prior stroke (%) | 6.7 | 7.2 | 0.552 | 6.7 | 7 | 0.783 |
| Prior PCI (%) | 3.3 | 3.2 | 0.886 | 3.3 | 3.1 | 0.761 |
| Prior CABG (%) | 2.7 | 2.5 | 0.619 | 2.7 | 2.4 | 0.578 |
| Alcohol (%) | 3.7 | 1.7 | <0.001 | 3.6 | 4.1 | 0.469 |
| Prior MI (%) | 4.1 | 3.3 | 0.084 | 4.1 | 4 | 0.856 |
| Discharge (%) | ||||||
| Routine | 38.4 | 34.9 | <0.001 | 38.5 | 34.8 | <0.001 |
| SNF/NH/IC | 28.5 | 23.3 | 28.5 | 24.8 | ||
| Home healthcare | 16.3 | 14.8 | 16.2 | 14 | ||
| Length of stay, median (IQR), days | 8 (4-18) | 9 (4-18) | 0.83 | 8 (4-18) | 9 (4-18) | 0.6222 |
| Hospital location and teaching status (%) | ||||||
| Rural | 7.1 | 7.9 | 0.4911 | 7 | 7.5 | 0.627 |
| Urban nonteaching | 16.7 | 17.3 | 16.7 | 17.8 | ||
| Urban teaching | 76.2 | 74.8 | 76.3 | 74.7 | ||
| Hospital region (%) | 0.042 | 0.888 | ||||
| Northeast | 16.2 | 18.9 | 16.3 | 17.1 | ||
| Midwest | 24.7 | 25.1 | 24.5 | 25.3 | ||
| South | 39.2 | 39.4 | 39.3 | 38.1 | ||
| West | 19.9 | 16.7 | 19.9 | 19.5 | ||
| Insurance (%) | <0.001 | <0.001 | ||||
| Medicare | 51 | 51 | 50.9 | 47.2 | ||
| Medicaid | 17.7 | 12.6 | 17.7 | 14 | ||
| Private including HMO | 24.7 | 28 | 24.8 | 29.7 | ||
| Self-pay | 4.1 | 3.6 | 4.1 | 4.1 | ||
| Median household income (%) | 0.032 | 0.875 | ||||
| 0-25th percentile | 32.8 | 32.8 | 32.7 | 31.7 | ||
| 26-50th percentile | 24.9 | 27.5 | 25 | 26.1 | ||
| 51-75th percentile | 21.2 | 22 | 21.2 | 21.1 | ||
| 76-100th percentile | 19 | 16.3 | 19 | 19.3 | ||
| Total hospital cost USD median IQR | 27,491 (11224-66827) | 21,304 (10381-49243) | <0.001 | 27,435 (11158-66872) | 21,153 (10584-50103) | <0.001 |
| Hospital bed size (%) | 0.002 | 0.760 | ||||
| Small | 18.9 | 21 | 19 | 19.5 | ||
| Intermediate | 25.4 | 29.1 | 25.5 | 26.4 | ||
| Large | 55.7 | 50 | 55.6 | 54.1 | ||
CABG- coronary artery bypass graft, CHF- congestive heart failure, COVID 19- coronavirus disease of 2019, CKD- chronic kidney disease, COPD- chronic obstructive pulmonary disease, HMO- health maintenance organization, MI- myocardial infarction, PCI- percutaneous coronary intervention, SNF/NH/IC- skilled nursing facility/nursing home/ intermediate care.
Table 2 describes the in-hospital complications and outcomes of the admitted patients. Patients with DVT and/or PE with flu had more incidences of sepsis (43.2% vs 37.2%), in-hospital stroke (2.3% vs 1.5%), and cardiogenic shock (3.8% vs 1.8%). The use of Impella and the incidence of coronary artery bypass graft were higher in the flu group. Even after the propensity matching, the number of patients with the above-mentioned complications was significantly higher in the flu group. Cardiac arrest (3.1% vs 5.5%) and in-hospital mortality (11.2% vs 23.1%) were significantly higher in patients with DVT and/or PE with concurrent COVID-19 infection before and after propensity matching (P < 0.001). (Table 2) There was no significant difference in the length of stay between these two groups, but the cost of hospitalization was significantly higher in the flu group before and after propensity matching (P < 0.001) (Table 1).
TABLE 2.
Complication of hospitalized patients with DVT and/or PE with concurrent Flu and COVID-19
| Complications | ||||||
|---|---|---|---|---|---|---|
| Before matching |
After matching |
|||||
| With flu (%) | With COVID-19 (%) | P value | With flu (%) |
With COVID-19 (%) | P value | |
| Total number of patients | 8155 | 62,895 | 8110 | 8110 | ||
| AKI | 39.2 | 40 | 0.599 | 39.2 | 36.7 | 0.149 |
| AKI leading to HD | 5.9 | 6 | 0.884 | 6 | 5.4 | 0.495 |
| UTI | 14.1 | 12.6 | 0.078 | 14.2 | 12.5 | 0.137 |
| Sepsis | 43.2 | 37.2 | <0.001 | 43.2 | 38 | 0.003 |
| DVT | 56.1 | 46.6 | <0.001 | 56.2 | 46.4 | <0.001 |
| PE | 55.1 | 63.9 | <0.001 | 55.1 | 63.6 | <0.001 |
| Stroke in-hospital | 2.3 | 1.5 | 0.011 | 2.3 | 1.1 | 0.013 |
| Cardiogenic shock | 3.9 | 1.8 | <0.001 | 3.8 | 1.6 | <0.001 |
| Cardiac arrest | 3.1 | 5.6 | <0.001 | 3.1 | 6 | <0.001 |
| VT | 4.3 | 3.4 | 0.064 | 4.2 | 2.7 | 0.025 |
| VF | 0.5 | 0.7 | 0.439 | 0.5 | 0.6 | 0.635 |
| Bleeding requiring transfusion | 10.9 | 8.8 | 0.007 | 11 | 9.2 | 0.113 |
| Death | 11.2 | 23.1 | <0.001 | 11.2 | 21.5 | <0.001 |
| Vasopressors | 5.6 | 6.8 | 0.102 | 5.6 | 5.9 | 0.759 |
| Prolonged intubations >24 hours | 26.5 | 25.3 | 0.299 | 26.5 | 23.2 | 0.037 |
| Respiratory failure | 59.4 | 59.2 | 0.882 | 59.3 | 58.4 | 0.626 |
| ECMO utilization | 0.4 | 0.2 | 0.034 | 0.4 | 0.2 | 0.224 |
| Impella | 0.3 | 0.02 | <0.001 | 0.2 | 0 | 0.045 |
| IABP | 0.1 | 0.04 | 0.689 | 0.1 | 0 | 0.316 |
| CABG | 0.25 | 0.01 | <0.001 | 0.2 | 0 | 0.045 |
| PCI | 0.4 | 0.2 | 0.024 | 0.4 | 15 | 0.205 |
AKI, acute kidney injury; COVID 19, coronavirus disease of 2019; CABG, coronary artery bypass graft; DVT, deep vein thrombosis; ECMO, extracorporeal membrane oxygenation; HD, hemodialysis; HTN, hypertension; IABP, intra-aortic balloon pump; MI, myocardial infarction; PCI, percutaneous coronary intervention; PE, pulmonary embolism; UTI, urinary tract infection; VT, ventricular tachycardia; VF, ventricular fibrillation.
Predictors of Mortality
On multivariable regression analysis, increased age [aOR 1.023, 95% confidence interval (CI) 1.020-1.027, P < 0.001], Hispanic race (aOR 1.196, 95% CI 1.019-1.403, P < 0.05), presence of diabetes (aOR 1.144, 95% CI 1.045-1.251, P < 0.05), chronic kidney disease (aOR 1.309, 95% CI 1.171-1.464, P < 0.001), congestive heart failure (CHF) (aOR 1.180, 95% CI 1.057-1.319, P = 0.003), chronic obstructive pulmonary disease (COPD) (aOR1.125, 95% CI 1.006-1.258, P = 0.038), arrhythmia (aOR 1.777, 95% CI 1.618-1.951, P <0.001), liver disease (aOR 2.639, 95% CI 2.282-3.051, P < 0.001), coagulopathy (aOR 1.822, 95% CI 1.645-2.019, P < 0.001), rheumatologic diseases (aOR 1.398, 95% CI 1.081-1.806, P < 0.011), and weight loss (aOR 1.332, 95% CI 1.169-1.518, P < 0.001) were independent predictors of mortality in patients with DVT and/or PE and concurrent COVID-19 infection (Table 3 ).
TABLE 3.
Predictors of mortality after multivariate analysis
| Variable | Odds ratio | Lower limit | Upper limit | P value |
|---|---|---|---|---|
| Age | 1.023 | 1.020 | 1.027 | <0.001 |
| Hispanic race | 1.196 | 1.019 | 1.403 | 0.028 |
| Diabetes | 1.144 | 1.045 | 1.251 | 0.003 |
| Coagulopathy | 1.822 | 1.645 | 2.019 | <0.001 |
| Weight loss | 1.332 | 1.169 | 1.518 | <0.001 |
| Arrhythmias | 1.777 | 1.618 | 1.951 | <0.001 |
| Liver disease | 2.639 | 2.282 | 3.051 | <0.001 |
| CKD | 1.309 | 1.171 | 1.464 | <0.001 |
| CHF | 1.180 | 1.057 | 1.319 | 0.003 |
| COPD | 1.125 | 1.006 | 1.258 | 0.038 |
| Rheumatologic diseases | 1.398 | 1.081 | 1.806 | 0.011 |
CKD, chronic kidney disease; CHF, congestive heart failure; COPD, chronic obstructive pulmonary disease.
Discussion
To the best of our knowledge, this is the largest nationwide data to report the characteristics and outcomes of patients with DVT and/or PE and concurrent COVID-19 vs. flu infection. Direct endothelial injury, activation of coagulation factors, cytokine storms, and suppression of fibrinolytic associated with severe COVID-19 infection contribute to hypercoagulability and thrombotic complications.1 Studies have shown up to 30% of patients hospitalized with COVID-19 develop arterial or venous thromboembolism.9 Prior studies have shown older age, CKD, COPD, heart failure, and prior venous thrombotic events predispose venous thromboembolism in COVID-19 patients.9 , 10 As found in our study, the predictors of mortality in patients with DVT/ PE with concomitant COVID-19 also include similar risk factors. A study by Lo Re et al. showed that after an inpatient venous thrombotic event, the risk of 30-day mortality was significantly higher in patients with COVID-19 compared to those with influenza.9 We also found inpatient mortality is higher in COVID-19 patients than in the flu. A cohort study from the US showed that COVID-19 was independently associated with a higher 90-day risk for venous thrombosis but not arterial thrombosis, compared with influenza.11 Another study from Europe showed patients with influenza were more often diagnosed with arterial thrombotic complications than patients with COVID-19 infection.12 Our analysis found that in-hospital stroke was higher in flu patients compared to COVID-19 patients. The finding of increased stroke corroborates with the increased risk of arterial thrombosis in influenza patients. The severity of infection has been linked with the incidence of DVT and PE in COVID-19 cohort.13 Our study found that cardiac arrest and inpatient mortality was higher in the COVID-19-affected individuals. This finding indirectly indicates the possible association of DVT and PE with the severity of COVID-19 infection. The COVID-19 patients admitted with DVT and/or PE were possibly affected with severe COVID-19 disease. The severity of the disease contributed to the increased mortality. COVID-19 has already been identified as a significant economic burden in the United States.14 Our data analysis also showed that the hospital cost was significantly higher in the COVID-19-affected patients.
Limitations
NIS study has its inherent limitations. NIS data is a retrospective database analysis with discharge diagnosis and does not have patient-level information. Unmeasured confounding factors may affect these findings. We cannot get any follow-up information from NIS data analysis. As this data is from 2019 to 2020, the impact of COVID-19 vaccination on these outcomes was not available. Despite these limitations, NIS is a well-validated representation of the US population and with internal and external quality control measures. The large sample size of NIS data also compensates for the residual confounders.
Conclusion
COVID-19 infection among patients hospitalized with DVT and/or PE is associated with significantly higher in-hospital mortality. In addition, increased age, Hispanic race, presence of diabetes, CKD, COPD, CHF, arrhythmia, liver disease, coagulopathy, and rheumatologic disease were independent predictors of mortality in patients with DVT and/or PE with concurrent COVID-19.
Acknowledgments
Acknowledgments
None.
Footnotes
The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.
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