Association of Cardiovascular Medications With Adverse Outcomes in a Matched Analysis of a National Cohort of Patients With COVID-19

Background The use of statins, angiotensin-converting enzyme inhibitors (ACEIs)/angiotensin II receptor blockers (ARBs), and anticoagulants may be associated with fewer adverse outcomes in COVID-19 patients. Methods Nested within a cohort of 800,913 patients diagnosed with COVID-19 between April 1, 2020 and June 24, 2021 from the Optum COVID-19 database, three case-control studies were conducted. Cases—defined as persons who: (1) were hospitalized within 30 days of COVID-19 diagnosis (n = 88,405); (2) were admitted to the intensive care unit (ICU)/received mechanical ventilation during COVID-19 hospitalization (n = 22,147); and (3) died during COVID-19 hospitalization (n = 2300)—were matched 1:1 using demographic/clinical factors with controls randomly selected from a pool of patients who did not experience the case definition/event. Medication use was based on prescription ≤90 days before COVID-19 diagnosis. Results Statin use was associated with decreased risk of hospitalization (adjusted odds ratio [aOR], 0.72; 95% confidence interval [95% CI], 0.69, 0.75) and ICU admission/mechanical ventilation (aOR, 0.90; 95% CI, 0.84, 0.97). ACEI/ARB use was associated with decreased risk of hospitalization (aOR, 0.67; 95% CI, 0.65, 0.70), ICU admission/mechanical ventilation (aOR, 0.92; 95% CI, 0.86, 0.99), and death (aOR, 0.60; 95% CI, 0.47, 0.78). Anticoagulant use was associated with decreased risk of hospitalization (aOR, 0.94; 95% CI, 0.89, 0.99) and death (aOR, 0.56; 95% CI, 0.41, 0.77). Interaction effects—in the model predicting hospitalization—were statistically significant for statins and ACEI/ARBs (P < .0001), statins and anticoagulants (P = .003), ACEI/ARBs and anticoagulants (P < .0001). An interaction effect—in the model predicting ventilator use/ICU—was statistically significant for statins and ACEI/ARBs (P = .002). Conclusions Statins, ACEI/ARBs, and anticoagulants were associated with decreased risks of the adverse outcomes under study. These findings may provide clinically relevant information regarding potential treatment for patients with COVID-19.


Background
][14] Angiotensin-converting enzyme inhibitor (ACEI)/angiotensin II receptor blockers (ARBs), used as first-line hypertension therapies, have demonstrated antiinflammatory effects, 15 , 16 specifically by blocking angiotensin-converting enzyme 2 (ACE2) downregulation-induced hyperactivation of the RAAS and attenuating oxidative stress, vasoconstriction, and inflammation. 7 , 17While there were initial theoretical concerns that ACEI/ARBs may increase the expression of the ACE2 receptor -the entry point for COVID-19 infection -thereby exacerbating COVID-19 infection susceptibility and disease progression, 7 , 18 recent data from observational studies, randomized controlled trials, and metaanalyses have demonstrated that ACEI/ARBs do not have an adverse impact on clinical outcomes or prognosis of COVID-19 patients 17 , 19-24 and may, in fact, be associated with protective benefits. 7 , 25 , 26nticoagulants are believed to mitigate the risk of microvascular and macrovascular thrombosis in COVID-19 patients. 27 , 28Anticoagulants such as unfractionated heparin have been shown to be efficacious and suppress the cytokine-mediated inflammatory process that results in endothelial dysfunction caused by COVID-19. 27 , 290][31][32][33] Our purpose was to examine the independent effect of each of these three classes of medication -statins, ACEI/ARBs, and anticoagulants -on COVID-19 outcomes in a large, demographically and clinically diverse cohort of COVID-19 patients.

Data Source
This series of nested case-control studies was based on Optum's longitudinal COVID-19 electronic health record (EHR) database, which was generated from the larger Optum EHR database to specifically study COVID-19.Including more than 90 million patients from 38 hospital networks and 18 nonnetwork hospitals in the United States, the database incorporates clinical and medical administrative data from both inpatient and ambulatory EHRs, practice management systems, and numerous other internal systems.Information was processed from across the continuum of care, including acute inpatient stays and outpatient visits.The database contains structured information, such as diagnosis, procedure codes, laboratory results, and clinical observations, including vital signs, blood pressure, pain, and body mass index (BMI).It also contains unstructured information in the form of clinical notes from office visits; consultation reports; discharge summaries; and reports from nursing records, pathology, radiology, and cardiology.Using a natural language processing (NLP) system, the unstructured data in the clinical notes are scanned to discover, interpret, and extract important clinical information.
The COVID-19 database captures point-of-care diagnostics specific to the COVID-19 patient during initial presentation, acute illness, and convalescence with over 500 mapped labs and bedside observations, including COVID-19-specific testing.The database includes all patients in the EHR database from January 2007 through June 24, 2021.The data were certified as deidentified by an independent statistical expert following Health Insurance Portability and Accountability Act (HIPAA) statistical deidentification rules and managed according to Optum® customer data use agreements.A data use agreement was developed with Optum, and this study was approved by the Institutional Review Board of the University of Texas Medical Branch at Galveston.

COVID-19 Study Cohort
The study cohort is based on a cohort from the Optum COVID-19 database consisting of patients who were diagnosed with COVID-19 (by positive laboratory test (Appendix Table 4 ) or diagnosis [ICD-CM-10: U07.1]) between April 1, 2020, and June 24, 2021, and who received care in above-described health care delivery network, captured in the Optum EHR database, in the 12 months prior to COVID-19 diagnosis.

Case Selection
Three nested case-control studies of COVID-19 outcomes were conducted ( Table 1 ).For study 1, cases ( n = 88,405) were defined as patients who were hospitalized within 30 days of their COVID-19 diagnosis that occurred 0-30 days following the COVID-19 diagnosis date.For study 2, cases ( n = 22,147) were defined as patients who were admitted to the intensive care unit (ICU; had one encounter during the hospitalization that was coded as "Critical Care Unit [CCU]/Intensive Care Unit [ICU] ") or received mechanical ventilation (ICD-10-PCS: 5A09357, 5A09358, 5A09359, 5A0935A, 5A0935B, 5A0935Z, 5A09457, 5A09458, 5A09459, 5A0945A, 5A0945B, 5A0945Z, 5A09557, 5A09558, 5A09559, 5A0955A, 5A0955B, 5A0955Z, 5A19054, 5A1935Z, 5A1945Z, 5A1955Z; CPT: 94,002, 94,003, 94,004) during their COVID-19 hospitalization.For study 3, cases were defined as patients who died during their hospitalization for COVID-19 ( n = 2300).Because the Optum EHR data only has month and year of death, along with a death indicator, patients needed to meet three criteria to be considered to have died during their hospitalization: (1) the patient had a positive death indicator; (2) the patient had a death month and year equal to the month and year of their hospitalization end; and (3) the patient had no encounters of any kind following the hospitalization end date.

Control Selection
The underlying cohort from which controls were selected included patients in the Optum COVID-19 database who met the following criteria: were in an integrated delivery network, had complete demographic data, and had a positive COVID-19 lab test or diagnosis ( Table 1 ).For study 1, controls ( n = 87,758) were randomly selected from patients who were not hospitalized ( n = 712,508).For study 2, controls ( n = 21,625) were randomly selected from patients who were not admitted to the ICU or had mechanical ventilation ( n = 65,611).For study 3, controls ( n = 2300) were randomly selected from patients who did not die during their hospitalization ( n = 85,430).

Exposure to CVD Medications
For each of the three CVD medication groups -statins, ACEI/ARBs, and anticoagulants -patients who received at least one prescription for the medication ≤ 90 days prior to their COVID-19 diagnosis date were defined as exposed.

Covariates
For each case-control study, multivariable analyses were used to adjust for the following unmatched variables: Elixhauser comorbidity index score (with the six matched conditions removed) 34 (0, 1, 2, ≥ 3), ethnicity (non-Hispanic, Hispanic), United States Census Bureau geographic region (Midwest, Northeast, South, West), 35 receipt of remdesivir, and receipt of dexamethasone.

Statistical Analysis
Patient demographic and clinical characteristics for the overall COVID-19 cohort and each matched case-control study were summarized using percentages.To compare the baseline covariates between groups, standardized differences were calculated 36 in the cohort of COVID-19-positive patients based on three comparisons: hospitalization status, ventilation use or admission to ICU, and mortality.
For each nested matched case-control study, multivariable conditional logistic regression analysis, adjusting for each of the aforementioned unbalanced covariates, was used to calculate adjusted odds ratios (aORs) and 95% confidence intervals (95% CIs) for the three outcomes: hospitalization within 30 days of COVID-19 diagnosis, ICU admission/mechanical ventilation during COVID-19 hospitalization, and death during COVID-19 hospitalization.
Finally, to assess the robustness of our findings, several sensitivity analyses were conducted.First, for each medication group, analyses using prescription periods of ≤ 60 days and ≤ 120 days before the COVID-19 diagnosis date were assessed (Appendix Tables 1 and 2 ).Second, analyses were conducted in which patients who were in hospital networks with fewer than 100 COVID-19 patients (along with their matched pairs) were removed (Appendix Table 2 ).All analyses were performed using SAS version 9.4 (SAS Institute).

Results
Table 2 presents the demographic and clinical characteristics of the overall COVID-19 study cohort and each of the three primary samples used in the case-control studies.For the ventilation/ICU status group, there were larger standardized differences 37 in in-hospital dexamethasone and remdesivir use.For the hospitalization status group, there was a larger standardized difference 37 in the Elixhauser comorbidity index.
To assess the robustness of our findings, we conducted a number of sensitivity analyses.First, logistic regression models using prescription periods of ≤ 60 days and ≤ 120 days before the COVID-19 diagnosis date were assessed (Appendix Tables 1 and 2 ).Next, logistic regression models in which patients who were in hospital networks with ≤ 100 COVID-19 patients (along with their matched pairs) were removed (Appendix Table 3 ) were conducted.In each of the above sensitivity analyses, the direction and magnitude of the ORs for each of the three medications under study were consistent with the overall study findings.

Discussion
In this matched nested case-control study of a national cohort of patients diagnosed with COVID-19, we found that the use of statins, ACEI/ARBs, and anticoagulants was protective against a number of adverse COVID-19 outcomes.Using matching and multivariable adjustment, we accounted for multiple potentially confounding factors, including sex, age, race, ethnicity, region, and underlying medical conditions and medications.Moreover, our primary findings persisted across multiple sensitivity analyses, using exposure periods that extended to 60 and 120 days before the COVID-19 diagnosis and restricting to a cohort of patients treated in health systems with a high volume of COVID-19 patients.
It is likely that the observed protective effects on COVID-19 by statins are attributable, in some measure, to their antiinflammatory, antithrombotic, and immunomodulatory effects via a reduction in viral replication and suppression of the damaging effects of cytokine storm and microvascular and macrovascular thrombosis. 8 , 11-14 Zhang et al. showed  an association between statin use and decreased risk of mortality and ventilator use, with lower levels of inflammatory markers among statin users. 8However, observational studies, randomized controlled trials, and metaanalyses have produced conflicting data on the utility of statin use for COVID-19 clinical outcomes. 8 , 11 , 38-46While a number of stud-  * * Each case-control study was matched on sex, race, age group, and each of the following medical conditions: COPD, obesity, cardiovascular disease, angina, diabetes, hyperlipidemia, and hypertension.
ies reported that the use of statins was associated with lower mortality rates and decreased inflammatory response in hospitalized COVID-19 patients, 8 , 39 , 41 , 42 , 44 especially critically ill patients, 11 other studies did not support the use of statins for hospitalized COVID-19 patients. 45 , 47ariou et al. found that statin treatment was associated with increased mortality in a cohort of 2449 hospitalized patients with both type 2 diabetes mellitus and COVID-19, 38 and one randomized controlled trial reported that atorvastatin use significantly increased the frequency of ICU admission and length of stay at the hospital for inpatients with COVID-19. 45he protective effects of ACEI/ARBs were possibly driven, to some degree, by antiinflammatory effects in COVID-19 patients, 15 , 16 specifically by inhibiting ACE2 downregulation-induced hyperactivation of the RAAS caused by the SARS-CoV-2 virus. 7By attenuating the deleterious effects of angiotensin II, ACEI/ARBs may reduce oxidative stress, vasoconstriction, and inflammation in the lungs. 17Notably, there is concern that critical biases may have distorted the evidence in past observational research. 48Further, Bauer et al. reported that older, vulnerable patients might benefit from temporary discontinuation of RAAS inhibition for improved recovery from COVID-19. 49iven that coagulopathy -which commonly occurs as a result of COVID-19-related systemic thrombo-inflammation and results in a consequent risk of vascular permeability and hypercoagulation -is associated with increased disease severity and mortality, there has been interest in examining the effect of anticoagulants in COVID-19 patients.Postmortem examinations of COVID-19 patients showed thrombosis in pulmonary vessels and other organs without SARS-CoV-2 penetration. 27 , 50he observed protective effects of anticoagulants in this study were generally consistent with some past studies 28 , 29 , 31 , 51 but inconsistent with others, 6 , 32 , 33 including a randomized controlled trial by Connors et al. that was terminated early. 304][55][56][57] It is important to note that ours is, to our knowledge, the largest matched, national comparative analysis of cardiovascular medications and COVID-19 outcomes thus far.
The results of our study may have been influenced by several limitations.First, medication use was defined by written prescriptions identified in the patient's EHR prior to COVID-19 diagnosis.It is possible that this record did not include information on over-the-counter (OTC) medications and thus contained no information on coadministration of these drugs.Many OTC medications, including aspirin and nonsteroidal antiinflammatory drugs, may influence the study outcomes and these data were not available in our database.Second, reliance on EHR data precluded assessment of a number of potential confounding factors such as diet, alcohol, medication adherence, lifestyle habits, prior state of health, and other health behaviors.Medication adherence to statins in particular has been recognized as a global challenge. 58Using EHR data also leads to a certain degree of misclassification by relying on codes in administrative claims data, but we attempted to minimize this by using standardized categorization algorithms, as well as multiple sensitivity analyses.Third, our data provide information on the date the medication was prescribed but not on the date it was filled, purchased, or picked up by the patient.It is possible, therefore, that some of the drug exposure periods used in this study underestimated the true medication exposure period.Our sensitivity analyses assessing 60-and 120-day exposure windows, however, help to address this issue.
Despite these limitations, this study has a number of strengths, including a large nationally representative sample, matching based on sociodemographic and disease risk factors, simultaneous adjustment for potentially confounding medical conditions and medications, and assessment of multiple exposure windows.This large, national matched comparative analysis of cardiovascular medications and COVID-19 outcomes addresses a critically important clinical and public health issue.
Our findings also suggest the need for a large randomized comparative effectiveness trial of statin, ACEI/ARB, and anticoagulant therapies alone or in combination as potential therapies for COVID-19 patients, regardless of history of ASCVDs.Other areas of study include examining comparative effectiveness of different statins -based on their lipophilic versus hydrophilic property -in COVID-19 patients as well as the effect of dose and duration with statins, ACEI/ARBs, and anticoagulants.

Conclusion
Our study suggests that all three medications studied -statins, ACEI/ARBs, and anticoagulants -were associated with decreased risks of the adverse outcomes under study.Even with the increased availability of COVID-19 vaccines and treatments, immunocompromised and elderly patients with COVID-19 remain at risk for severe adverse outcomes.As of February 2023, COVID-19 is still a major contributor to premature deaths in the United States, with an approximately 21-day average of 452 new COVID-19 deaths per day. 59

Table 1
Cohort Flow Chart.

Table 2
Patient Characteristics by Hospitalization, ICU Admission/Mechanical Ventilation, and Hospital Mortality.
36Standardized differences were calculated using SAS version 9.4 (SAS Institute, Cary, North Carolina).36

Table 3
Unadjusted and Adjusted Odds Ratios for Hospitalization, ICU Admission/Mechanical Ventilation, and Hospital Mortality Due to COVID-19.Multivariable analyses were adjusted for all unmatched variables including statin use, ACEI/ARB use, anticoagulant use, ethnicity, region, and Elixhauser score.

Table 2
Our findings may help to guide clinical decision-making on choices of cardiovascular medications to continue or adjust for COVID-19 patients with multimorbidity and ASCVD.Each case-control study was matched on sex, race, age group, and each of the following medical conditions: COPD, obesity, cardiovascular disease, angina, diabetes, hyperlipidemia, and hypertension.Sensitivity Analyses Based on Prescription Period of ≤ 120 Days.

Table 3
Sensitivity Analyses Restricted to Patients From Health Systems With ≥ 100 COVID-19 Patients With Hospitalization and ≥ 100 COVID-19 Patients With ICU Admission/Mechanical Ventilation and Hospital Mortality.Multivariable analyses were adjusted for all unmatched variables including statin use, ACEI/ARB use, anticoagulant use, ethnicity, region, and Elixhauser score.**Each case-control study was matched on sex, race, age group, and each of the following medical conditions: COPD, obesity, cardiovascular disease, angina, diabetes, hyperlipidemia, and hypertension.†OR, odds ratio.‡ 95% CI, 95% confidence interval.