Analgesics
Antiandrogens
Antihistamines
Azvudine
Bromhexine
Budesonide
Colchicine
Conv. Plasma
Curcumin
Famotidine
Favipiravir
Fluvoxamine
Hydroxychlor..
Ivermectin
Lifestyle
Melatonin
Metformin
Minerals
Molnupiravir
Monoclonals
Naso/orophar..
Nigella Sativa
Nitazoxanide
PPIs
Paxlovid
Quercetin
Remdesivir
Thermotherapy
Vitamins
More

Other
Feedback
Home
Top
 
Feedback
Home
c19early.org COVID-19 treatment researchSelect treatment..Select..
Melatonin Meta
Metformin Meta
Antihistamines Meta
Azvudine Meta Molnupiravir Meta
Bromhexine Meta
Budesonide Meta
Colchicine Meta Nigella Sativa Meta
Conv. Plasma Meta Nitazoxanide Meta
Curcumin Meta PPIs Meta
Famotidine Meta Paxlovid Meta
Favipiravir Meta Quercetin Meta
Fluvoxamine Meta Remdesivir Meta
Hydroxychlor.. Meta Thermotherapy Meta
Ivermectin Meta

Pravastatin for COVID-19

Pravastatin has been reported as potentially beneficial for treatment of COVID-19. We have not reviewed these studies. See all other treatments.
Sperry et al., Different HMGCR-inhibiting statins vary in their association with increased survival in patients with COVID-19, medRxiv, doi:10.1101/2022.04.12.22273802
Background In response to the challenge to rapidly identify treatment options for COVID-19, several studies reported that statins, as a drug class, reduce mortality in these patients. Here we explored the possibility that different statins might differ in their ability to exert protective effects based on computational predictions. Methods A Bayesian network tool was used to predict drugs that shift the host transcriptomic response to SARS-CoV-2 infection towards a healthy state. Drugs were predicted using 14 RNA-sequencing datasets from 72 autopsy tissues and 465 COVID-19 patient samples or from cultured human cells and organoids infected with SARS-CoV-2, with a total of 2,436 drugs investigated. Top drug predictions included statins, which were tested in Vero E6 cells infected with SARS-CoV-2 and human endothelial cells infected with a related OC43 coronavirus. A database containing over 4,000 COVID-19 patients on statins was also analyzed to determine mortality risk in patients prescribed specific statins versus untreated matched controls. Findings Simvastatin was among the most highly predicted compounds (14/14 datasets) and five other statins were predicted to be active in > 50% of analyses. In vitro testing of SARS-CoV-2 infected cells revealed simvastatin to be a potent inhibitor whereas most other statins were less effective. Simvastatin also inhibited OC43 infection and reduced cytokine production in endothelial cells. Analysis of the clinical database revealed that reduced mortality risk was only observed in COVID-19 patients prescribed a subset of statins, including simvastatin and atorvastatin. Interpretation Different statins may differ in their ability to sustain the lives of COVID-19 patients despite having a shared target and lipid-modifying mechanism of action. These findings highlight the value of target-agnostic drug prediction coupled with patient databases to identify and validate non-obvious mechanisms and drug repurposing opportunities. Funding DARPA, Wyss Institute, Hess Research Fund, UCSF Program for Breakthrough Biomedical Research, and NIH
MacFadden et al., Screening Large Population Health Databases for Potential COVID-19 Therapeutics: A Pharmacopeia-Wide Association Study (PWAS) of Commonly Prescribed Medications, Open Forum Infectious Diseases, doi:10.1093/ofid/ofac156
Abstract Background For both the current and future pandemics, there is a need for high-throughput drug screening methods to identify existing drugs with potential preventative and/or therapeutic activity. Epidemiologic studies could complement lab-focused efforts to identify possible therapeutic agents. Methods We performed a pharmacopeia-wide association study (PWAS) to identify commonly prescribed medications and medication classes that are associated with the detection of SARS-CoV-2 in older individuals (>65 years) in long-term care homes (LTCH) and the community, between January 15 th, 2020 and December 31 st, 2020, across the province of Ontario, Canada. Results 26,121 cases and 2,369,020 controls from LTCH and the community were included in this analysis. Many of the drugs and drug classes evaluated did not yield significant associations with SARS-CoV-2 detection. However, some drugs and drug classes appeared significantly associated with reduced SARS-CoV-2 detection, including cardioprotective drug classes such as statins (weighted OR 0.91, standard p-value <0.01, adjusted p-value <0.01) and beta-blockers (weighted OR 0.87, standard p-value <0.01, adjusted p-value 0.01), along with individual agents ranging from levetiracetam (weighted OR 0.70, standard p-value <0.01, adjusted p-value <0.01) to fluoxetine (weighted OR 0.86, standard p-value 0.013, adjusted p-value 0.198) to digoxin (weighted OR 0.89, standard p-value <0.01, adjusted p-value 0.02). Conclusions Using this epidemiologic approach which can be applied to current and future pandemics we have identified a variety of target drugs and drug classes that could offer therapeutic benefit in COVID-19 and may warrant further validation. Some of these agents (e.g. fluoxetine) have already been identified for their therapeutic potential.
Please send us corrections, updates, or comments. c19early involves the extraction of 100,000+ datapoints from thousands of papers. Community updates help ensure high accuracy. Treatments and other interventions are complementary. All practical, effective, and safe means should be used based on risk/benefit analysis. No treatment or intervention is 100% available and effective for all current and future variants. We do not provide medical advice. Before taking any medication, consult a qualified physician who can provide personalized advice and details of risks and benefits based on your medical history and situation. FLCCC and WCH provide treatment protocols.
  or use drag and drop   
Thanks for your feedback! Please search before submitting papers and note that studies are listed under the date they were first available, which may be the date of an earlier preprint.
Submit