Associations of comorbidities and medications with COVID-19 outcome: A retrospective analysis of real-world evidence data

  1. Basel Abu-Jamous
  2. Arseni Anisimovich
  3. Janie Baxter
  4. Lucy Mackillop
  5. Marcela P. Vizcaychipi
  6. Alex McCarthy
  7. Rabia T. Khan

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Abstract

Background

Hundreds of thousands of deaths have already been recorded for patients with the severe acute respiratory syndrome coronavirus (SARS-CoV-2; aka COVID-19). Understanding whether there is a relationship between comorbidities and COVID-19 positivity will not only impact clinical decisions, it will also allow an understanding of how better to define the long-term complications in the groups at risk. In turn informing national policy on who may benefit from more stringent social distancing and shielding strategies. Furthermore, understanding the associations between medications and certain outcomes may also further our understanding of indicators of vulnerability in people with COVID-19 and co-morbidities.

Methods

Electronic healthcare records (EHR) from two London hospitals were analysed between 1 st January and 27 th May 2020. 5294 patients presented to the hospitals in whom COVID status was formally assessed; 1253 were positive for COVID-19 and 4041 were negative. This dataset was analysed to identify associations between comorbidities and medications, separately and two outcomes: (1) presentation with a COVID-19 positive diagnosis, and (2) inpatient death following COVID-19 positive diagnosis. Medications were analysed in different time windows of prescription to differentiate between short-term and long-term medications. All analyses were done with controls (without co-morbidity) matched for age, sex, and number of admissions, and a robustness approach was conducted to only accept results that consistently appear when the analysis is repeated with different proportions of the data.

Results

We observed higher COVID-19 positive presentation for patients with hypertension (1.7 [1.3-2.1]) and diabetes (1.6 [1.2-2.1]). We observed higher inpatient COVID-19 mortality for patients with hypertension (odds ratio 2.7 [95% CI 1.9-3.9]), diabetes (2.2 [1.4-3.5]), congestive heart failure (3.1 [1.5-6.4]), and renal disease (2.6 [1.4-5.1]). We also observed an association with reduced COVID-19 mortality for diabetic patients for whom anticoagulants (0.11 [0.03-0.50]), lipid-regulating drugs (0.15 [0.04-0.58]), penicillins (0.20 [0.06-0.63]), or biguanides (0.19 [0.05-0.70]) were administered within 21 days after their positive COVID-19 test with no evidence that they were on them before, and for hypertensive patients for whom anticoagulants (0.08 [0.02-0.35]), antiplatelet drugs (0.10 [0.02-0.59]), lipid-regulating drugs (0.15 [0.05-0.46]), penicillins (0.14 [0.05-0.45]), or angiotensin-converting enzyme inhibitors (ARBs) (0.06 [0.01-0.53]) were administered within 21 days post-COVID-19-positive testing with no evidence that they were on them before. Moreover, long-term antidiabetic drugs were associated with reduced COVID-19 mortality in diabetic patients (0.26 [0.10-0.67]).

Conclusions

We provided real-world evidence for observed associations between COVID-19 outcomes and a number of comorbidities and medications. These results require further investigation and replication in other data sets.

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    SciScore for 10.1101/2020.08.20.20174169: (What is this?)

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

    Table 1: Rigor

    Institutional Review Board Statementnot detected.
    RandomizationFurthermore, a robustness analysis was carried out by running the same test experiment once with 100% of the available data and 20 more times with randomly selected proportions (60%, 70%, 80%, or 90%) of the data.
    Blindingnot detected.
    Power Analysisnot detected.
    Sex as a biological variablenot detected.

    Table 2: Resources

    No key resources detected.

    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:
    Limitations: Observed associations should be interpreted with care as they might be attributable to confounding factors. For example, we did not use measures of functional status, e.g. clinical fragility scale, which may have been over-represented in one arm of our analysis. Furthermore, we have not considered interactions between multiple co-morbidities and their association with outcomes. Severity of COVID-19 infection at presentation was not incorporated and no distinction is being made in this analysis between those who have been admitted for an acute episode of some comorbidity in their most recent admission and those who have not despite having that condition chronically. Also, length of symptoms at point of presentation to hospital were not assessed neither was the frailty scale. Observations in this study are based on a population of patients presenting to hospitals and for whom COVID-19 status has been assessed to be positive or negative. This may cause a bias as it is not comparing individuals belonging to the general community population. Also, this population of patients comes from two London metropolitan hospitals that may not have a similar distribution of comorbidities and features as hospitals in other metropolitan cities or hospitals away from large cities. Generalisability is therefore not assured without further confirmatory studies. Additionally, our data does not include medications prescribed in primary care, resulting in a potentially inaccurate represe...

    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.
    • No protocol registration statement was detected.

    About SciScore

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  2. Version published to 10.1101/2020.08.20.20174169v1 on medRxiv