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Population-based drug repurposing to treat thrombosis in COVID-19 patients
Stroke ; 52(SUPPL 1), 2021.
Article in English | EMBASE | ID: covidwho-1234371
ABSTRACT

Introduction:

Patients with coronavirus disease 2019 (COVID-19) have an increased risk of thrombosis. Our objective is to obtain population-level treatment effects of drugs on treating thrombosis in COVID-19.

Methods:

We conducted a retrospective analysis of Optum electronic health records (EHRs) with 34,043 hospitalized COVID-19 patients. We identified case-patient with thrombosis (stroke, deep vein thrombosis, pulmonary embolism, and myocardial infarction) using PheWas codes. The propensity score matching was used to select comparable control patients who survived without any thrombosis based on demographics and admission status (temperature and SpO2 level). We computed the average treatment effect (ATT) for medication using advanced inverse propensity score weighting based on pre-treatment conditions (i.e., comorbidities in the last 6 months and medications in the last 2 months before hospitalization).

Results:

We identified 2,446 case-patients with thrombosis and 5,020 comparable control patients. There were a total of 540 drugs that were administered in at least 80 patients. We calculated the 540 drugs' ATT coefficient. As a result, 23 drugs had a positive ATT coefficient with a p-value of less than 0.05. After filtering out commonly prescribed symptomatic drugs (e.g., Acetaminophen, Guaifenesin, and Ondansetron), we highlight the following drugs with statistically significant treatment effects Atorvastatin (ATT=0.34), Ceftriaxone (ATT=0.26), Levothyroxine (ATT=0.26), Albuterol (ATT=0.25), Azithromycin (ATT=0.23), Enoxaparin (ATT=0.20), and Metformin (ATT=0.20).

Conclusions:

In this preliminary work, we identified anti-thrombotic drugs (Enoxaparin) but also anti-inflammatory drugs (Atorvastatin, Metformin) and possibly antibiotics that have a significant treatment effect in COVID-19 patients that could reduce risk of thrombosis. We also observed that several anti-thrombotic drugs (Apixaban and Ticagrelor) had negative treatment effects, which was partly due to an imbalance in pre-treatment conditions. Our future work is to incorporate more extensive data (such as lab tests and vital signs) into the propensity scores to better capture the severity of admission status.

Full text: Available Collection: Databases of international organizations Database: EMBASE Language: English Journal: Stroke Year: 2021 Document Type: Article

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Full text: Available Collection: Databases of international organizations Database: EMBASE Language: English Journal: Stroke Year: 2021 Document Type: Article