Association between oral anticoagulants and COVID-19-related outcomes: a population-based cohort study
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Abstract
Early evidence has shown that anticoagulant reduces the risk of thrombotic events in those infected with COVID-19. However, evidence of the role of routinely prescribed oral anticoagulants (OACs) in COVID-19 outcomes is limited.
Aim
To investigate the association between OACs and COVID-19 outcomes in those with atrial fibrillation and a CHA 2 DS 2 -VASc score of 2.
Design and setting
On behalf of NHS England, a population-based cohort study was conducted.
Method
The study used primary care data and pseudonymously-linked SARS-CoV-2 antigen testing data, hospital admissions, and death records from England. Cox regression was used to estimate hazard ratios (HRs) for COVID-19 outcomes comparing people with current OAC use versus non-use, accounting for age, sex, comorbidities, other medications, deprivation, and general practice.
Results
Of 71 103 people with atrial fibrillation and a CHA 2 DS 2 -VASc score of 2, there were 52 832 current OAC users and 18 271 non-users. No difference in risk of being tested for SARS-CoV-2 was associated with current use (adjusted HR [aHR] 0.99, 95% confidence interval [CI] = 0.95 to 1.04) versus non-use. A lower risk of testing positive for SARS-CoV-2 (aHR 0.77, 95% CI = 0.63 to 0.95) and a marginally lower risk of COVID-19-related death (aHR, 0.74, 95% CI = 0.53 to 1.04) were associated with current use versus non-use.
Conclusion
Among those at low baseline stroke risk, people receiving OACs had a lower risk of testing positive for SARS-CoV-2 and severe COVID-19 outcomes than non-users; this might be explained by a causal effect of OACs in preventing severe COVID-19 outcomes or unmeasured confounding, including more cautious behaviours leading to reduced infection risk.
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SciScore for 10.1101/2021.04.30.21256119: (What is this?)
Please note, not all rigor criteria are appropriate for all manuscripts.
Table 1: Rigor
Ethics IRB: Ethical approval: This study was approved by the Health Research Authority (REC reference 20/LO/0651) and by the LSHTM Ethics Board (reference 21863). Sex as a biological variable not detected. Randomization not detected. Blinding not detected. Power Analysis not detected. Table 2: Resources
Software and Algorithms Sentences Resources Software and Reproducibility: Data management was performed using Python 3.8 and SQL, with analysis carried out using Stata 16.1. Pythonsuggested: (IPython, RRID:SCR_001658)Results from OddPub: We did not detect open data. We also did not detect open code. Researchers are encouraged to share open data when possible (see Nature blog).
Results from LimitationRecognizer: …SciScore for 10.1101/2021.04.30.21256119: (What is this?)
Please note, not all rigor criteria are appropriate for all manuscripts.
Table 1: Rigor
Ethics IRB: Ethical approval: This study was approved by the Health Research Authority (REC reference 20/LO/0651) and by the LSHTM Ethics Board (reference 21863). Sex as a biological variable not detected. Randomization not detected. Blinding not detected. Power Analysis not detected. Table 2: Resources
Software and Algorithms Sentences Resources Software and Reproducibility: Data management was performed using Python 3.8 and SQL, with analysis carried out using Stata 16.1. Pythonsuggested: (IPython, RRID:SCR_001658)Results from OddPub: We did not detect open data. We also did not detect open code. Researchers are encouraged to share open data when possible (see Nature blog).
Results from LimitationRecognizer: We detected the following sentences addressing limitations in the study:Strengths and limitations: The greatest strength of this study was the power enabling us to examine the association between OACs and various COVID-19 related outcomes as our dataset included medical records from 24 million individuals. To our knowledge, this is also the first population-based study comparing risk of COVID-related outcomes and cause-specific deaths between warfarin and DOACs. We also conducted quantitative bias analyses to explore the impact of unmeasured confounding to our observed results, supporting our interpretation. The breadth of data available in primary care allows us to account for a wide range of potential confounders. We pre-specified our analysis plan and have shared all analytical code. We recognise possible limitations. First, we could not eliminate residual confounding. Whilst differences in health behaviours and shielding between groups may partly explain our results, more studies are required to confirm these findings. Second, we do not know whether patients took the medications as prescribed. We are also not able to capture any anticoagulant use during hospitalisation. Low molecular weight heparin or unfractionated heparin might be given during hospitalisation for OAC untreated patients with severe COVID-19 disease to prevent venous thromboembolism, merely leading to an underestimation of the effect without accounting for the anticoagulation use during hospitalisation. Third, there may be misclassification in ascertaining AF using diagnostic...
Results from TrialIdentifier: No clinical trial numbers were referenced.
Results from Barzooka: We did not find any issues relating to the usage of bar graphs.
Results from JetFighter: We did not find any issues relating to colormaps.
Results from rtransparent:- Thank you for including a conflict of interest statement. Authors are encouraged to include this statement when submitting to a journal.
- Thank you for including a funding statement. Authors are encouraged to include this statement when submitting to a journal.
- Thank you for including a protocol registration statement.
Results from scite Reference Check: We found no unreliable references.
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