Evidence map›Paper›PMID 33083810›Full record

ArticlemedRxiv : the preprint server for health sciences2021

Identification of drugs associated with reduced severity of COVID-19: A case-control study in a large population.

Ariel Israel, Alejandro A Schäffer, Assi Cicurel, Ilan Feldhamer, Ameer Tal, Kuoyuan Cheng, Sanju Sinha, Eyal Schiff, Gil Lavie, Eytan Ruppin

Open access · greenAbstract readPreprint
In one paragraph

Article in medRxiv : the preprint server for health sciences, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed, 1 pooled it
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed, 1 synthesis or guideline pooled it, 21 citations in OpenAlex.

  1. Pooled it
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

10 authors at 5 institutions in 2 countries.

Ariel IsraelDivision of Planning and Strategy, Clalit Health Services, Tel Aviv 62098, Israel.ORCID 0000-0003-4389-8896
Alejandro A SchäfferCancer Data Science Laboratory, National Cancer Institute, National Institutes of Health, Bethesda, MD, USA 20892.ORCID 0000-0002-2147-8033
Assi CicurelDivision of Planning and Strategy, Clalit Health Services, Tel Aviv 62098, Israel.
Ilan FeldhamerDivision of Planning and Strategy, Clalit Health Services, Tel Aviv 62098, Israel.
Ameer TalDivision of Planning and Strategy, Clalit Health Services, Tel Aviv 62098, Israel.
Kuoyuan ChengCancer Data Science Laboratory, National Cancer Institute, National Institutes of Health, Bethesda, MD, USA 20892.ORCID 0000-0001-8118-5243
Sanju SinhaCancer Data Science Laboratory, National Cancer Institute, National Institutes of Health, Bethesda, MD, USA 20892.ORCID 0000-0002-2688-0603
Eyal SchiffSheba Medical Center, Tel-Aviv University, Ramat Gan 52621, Israel.
Gil LavieDivision of Planning and Strategy, Clalit Health Services, Tel Aviv 62098, Israel.
Eytan RuppinCancer Data Science Laboratory, National Cancer Institute, National Institutes of Health, Bethesda, MD, USA 20892.ORCID 0000-0002-7862-3940
National Institutes of Health · USClalit Health Services · ILBen-Gurion University of the Negev · ILTechnion – Israel Institute of Technology · ILTel Aviv University · IL

Funding

Discovering Affective Drug Combinations for Treating Covid-19ZIABC012000 · NCI · DIVISION OF BASIC SCIENCES - NCI · PI RUPPIN, EYTAN · 2020 to 2022
$2.3M
6 · The paper itself

Abstract

backgroundUntil COVID-19 drugs specifically developed to treat COVID-19 become more widely accessible, it is crucial to identify whether existing medications have a protective effect against severe disease. Towards this objective, we conducted a large population study in Clalit Health Services (CHS), the largest healthcare provider in Israel, insuring over 4.7 million members.

methodsTwo case-control matched cohorts were assembled to assess which medications, acquired in the last month, decreased the risk of COVID-19 hospitalization. Case patients were adults aged 18-95 hospitalized for COVID-19. In the first cohort, five control patients, from the general population, were matched to each case (n=6202); in the second cohort, two non-hospitalized SARS-CoV-2 positive control patients were matched to each case (n=6919). The outcome measures for a medication were: odds ratio (OR) for hospitalization, 95% confidence interval (CI), and the p-value, using Fisher's exact test. False discovery rate was used to adjust for multiple testing.

resultsMedications associated with most significantly reduced odds for COVID-19 hospitalization include: ubiquinone (OR=0.185, 95% CI (0.058 to 0.458), p<0.001), ezetimibe (OR=0.488, 95% CI ((0.377 to 0.622)), p<0.001), rosuvastatin (OR=0.673, 95% CI (0.596 to 0.758), p<0.001), flecainide (OR=0.301, 95% CI (0.118 to 0.641), p<0.001), and vitamin D (OR=0.869, 95% CI (0.792 to 0.954), p<0.003). Remarkably, acquisition of artificial tears, eye care wipes, and several ophthalmological products were also associated with decreased risk for hospitalization.

conclusionsUbiquinone, ezetimibe and rosuvastatin, all related to the cholesterol synthesis pathway were associated with reduced hospitalization risk. These findings point to a promising protective effect which should be further investigated in controlled, prospective studies.

fundingThis research was supported in part by the Intramural Research Program of the National Institutes of Health, NCI.

Identifiers

PMID33083810
PMCPMC7574266
OpenAlexW3196597339

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.