Healthcare disparities among anticoagulation therapies for severe COVID‐19 patients in the multi‐site VIRUS registry

  1. Christian Kirkup
  2. Colin Pawlowski
  3. Arjun Puranik
  4. Ian Conrad
  5. John C. O'Horo
  6. Dina Gomaa
  7. Valerie M Banner‐Goodspeed
  8. Jarrod M Mosier
  9. Igor Borisovich Zabolotskikh
  10. Steven K. Daugherty
  11. Michael A. Bernstein
  12. Howard A. Zaren
  13. Vikas Bansal
  14. Brian Pickering
  15. Andrew D. Badley
  16. Rahul Kashyap
  17. A. J. Venkatakrishnan
  18. Venky Soundararajan

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Abstract

Here we analyze hospitalized andintensive care unit coronavirus disease 2019 (COVID‐19) patient outcomes from the international VIRUS registry ( https://clinicaltrials.gov/ct2/show/NCT04323787 ). We find that COVID‐19 patients administered unfractionated heparin but not enoxaparin have a higher mortality‐rate (390 of 1012 = 39%) compared to patients administered enoxaparin but not unfractionated heparin (270 of 1939 = 14%), presenting a risk ratio of 2.79 (95% confidence interval [CI]: [2.42, 3.16]; p  = 4.45e−52). This difference persists even after balancing on a number of covariates including demographics, comorbidities, admission diagnoses, and method of oxygenation, with an increased mortality rate on discharge from the hospital of 37% (268 of 733) for unfractionated heparin versus 22% (154 of 711) for enoxaparin, presenting a risk ratio of 1.69 (95% CI: [1.42, 2.00]; p  = 1.5e−8). In these balanced cohorts, a number of complications occurred at an elevated rate for patients administered unfractionated heparin compared to patients administered enoxaparin, including acute kidney injury, acute cardiac injury, septic shock, and anemia. Furthermore, a higher percentage of Black/African American COVID patients (414 of 1294 [32%]) were noted to receive unfractionated heparin compared to White/Caucasian COVID patients (671 of 2644 [25%]), risk ratio 1.26 (95% CI: [1.14, 1.40]; p  = 7.5e−5). After balancing upon available clinical covariates, this difference in anticoagulant use remained statistically significant (311 of 1047 [30%] for Black/African American vs. 263 of 1047 [25%] for White/Caucasian, p  = .02, risk ratio 1.18; 95% CI: [1.03, 1.36]). While retrospective studies cannot suggest any causality, these findings motivate the need for follow‐up prospective research into the observed racial disparity in anticoagulant use and outcomes for severe COVID‐19 patients.

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  1. Version published to 10.1002/jmv.26918
  2. ScreenIT

    SciScore for 10.1101/2020.11.06.20226035: (What is this?)

    Please note, not all rigor criteria are appropriate for all manuscripts.

    Table 1: Rigor

    NIH rigor criteria are not applicable to paper type.

    Table 2: Resources

    Software and Algorithms
    SentencesResources
    Data for the registry is collected via REDCap and can be automatically filled from a site’s EHR data.
    REDCap
    suggested: (REDCap, RRID:SCR_003445)
    The code to perform the statistical analyses was written in Python v3.7.7, using the scikit-learn package v0.23.2 to train the logistic regression models for the propensity score matching step.
    scikit-learn
    suggested: (scikit-learn, RRID:SCR_002577)
    The function stats.chi2_contingency from the SciPy package in Python was used to compute the Chi-squared p-values.
    SciPy
    suggested: (SciPy, RRID:SCR_008058)
    Python
    suggested: (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:
    There are several limitations of this study. While we have longitudinal data from the registry on daily anticoagulant use, we do not have access to the detailed physician notes for these patients. Therefore, in this dataset we cannot distinguish between prophylactic and therapeutic anticoagulant use. Since we include only patients who received an anticoagulant medication, there is potential for immortal time bias because there may be some patients who died prior to anticoagulant administration in the hospital. Another limitation of this study is the lack of follow-up data for all patients. For many sites, we do not have access to follow-up data for patients to determine 28-day mortality status, so the mortality rates may be skewed towards the sites of the study where this outcome data is most available. Finally, there are differences in the FDA drug labels for unfractionated heparin, enoxaparin, and other forms of low molecular weight heparin, which can lead to differences in real-world patterns of prescription13,14. For example, patients with active kidney disease are contraindicated for higher doses of enoxaparin. However, unfractionated heparin does not require any dose modifications for patients with active kidney disease, so there may be a preference for this medication among this cohort of patients. Although these biases in prescription patterns are partially controlled for by the propensity score matching algorithm, there may be some additional unobserved confounding f...

    Results from TrialIdentifier: We found the following clinical trial numbers in your paper:

    IdentifierStatusTitle
    NCT04323787RecruitingViral Infection and Respiratory Illness Universal Study[VIRU…

    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.

    About SciScore

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  3. Version published to 10.1101/2020.11.06.20226035v1 on medRxiv