Lead Investigator: Malathi Ram, Johns Hopkins University
Title of Proposal Research: ACEi/ARB medications for hospitalized patients with COVID-19 – an individual patient data (IPD) based pooled analysis
Vivli Data Request: 7520
Funding Source: Funding is via an administrative supplement mechanism of an existing NCATS award
Potential Conflicts of Interest: None
Summary of the Proposed Research:
ACEi/ARB medications might be beneficial in COVID-19 due to inhibition of viral entry into pneumocytes and alteration of local inflammatory and vasoconstriction/vasodilation balance. The current preclinical and clinical database, albeit limited, suggests equipoise or potential benefit for these medications in hospitalized patients with COVID-19.
This study is designed to confirm our hypothesis that treatment of hospitalized patients with SARS-CoV-2 infection with ACEi/ARB medications will improve clinical outcome in comparison with control treatments.
The necessity of this research is urgent given that over 650,000 Americans have died of COVID-19, daily deaths again surpassed 2,000 at the peak of the delta variant surge, and thus there is a continued need for effective therapeutics.
Currently, starting ACEi/ARB for COVID-19 de novo is not standard because supportive data is weak and evolving. If administration of simple and inexpensive ACEi/ARB medications in COVID-19 will decrease morbidity and mortality, the drugs can have an important effect on outcome of many thousands of hospitalized patients internationally.
This study will be the first IPD-meta analysis of ACEi/ARB medications in COVID-19 and only the third IPD-meta analysis in COVID-19 more broadly.
After down selection of targeted RCTs, finalization of data harmonization spreadsheets and deidentification/anonymization processes, completion of data sharing agreements, trialists will collate IPD data per supplied data harmonization spreadsheets, and upload the data to Vivil. Data will be transferred to JHU where analysis per our prespecified SAP will occur using Bayesian statistical methods. The study, including its SAP, were registered on PROSPERO (CRD42021254261).
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