Evidence map›Paper›PMID 35768681›Full record

Observational studyJournal of general internal medicine2022

Medications Associated with Lower Mortality in a SARS-CoV-2 Positive Cohort of 26,508 Veterans.

Christine M Hunt, Jimmy T Efird, Thomas S Redding, Andrew D Thompson, Ashlyn M Press, Christina D Williams, Christopher J Hostler, Ayako Suzuki

Open access · bronzeAbstract readObservational Study
PubMed Full text at PMC Publisher
In one paragraph

Observational study in Journal of general internal medicine, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed, 1 pooled it
1.1field-weighted citation impact, top 22% of its field
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

7 citing papers in PubMed, 1 synthesis or guideline pooled it, 12 citations in OpenAlex.

  1. Pooled it
  2. Trial
  3. Trial
  4. Review
  5. Review
  6. Statin Therapy in COVID-19: Inhibition of NETosis.Journal of general internal medicine · 2023
    Article
  7. Review
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

8 authors at 3 institutions in 1 country.

Christine M HuntDivision of Gastroenterology, Duke University, Durham, NC, USA.
Jimmy T EfirdVA Cooperative Studies Program Coordinating Center, Boston, MA, USA.
Thomas S ReddingVA Cooperative Studies Program Epidemiology Center, Durham VA Health Care System, Durham, NC, USA.
Andrew D ThompsonVA Cooperative Studies Program Epidemiology Center, Durham VA Health Care System, Durham, NC, USA.
Ashlyn M PressVA Cooperative Studies Program Epidemiology Center, Durham VA Health Care System, Durham, NC, USA.
Christina D WilliamsVA Cooperative Studies Program Epidemiology Center, Durham VA Health Care System, Durham, NC, USA.
Christopher J HostlerDivision of Infectious Diseases, Duke University School of Medicine, Durham, NC, USA.
Ayako SuzukiDivision of Gastroenterology, Duke University, Durham, NC, USA. Ayako.Suzuki@va.gov.ORCID 0000-0003-1824-1067
Duke University · USDurham VA Health Care System · USProgram Support Center · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundMany severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) positive patients take commonly prescribed medications with properties which may affect mortality.

objectiveAssess if common medications postulated to affect clinical outcomes are associated with mortality in SARS-CoV-2 positive patients in the Veterans Health Administration (VHA).

designObservational national cohort analysis.

participantsConsecutive 26,508 SARS-CoV-2 positive Veterans (7% of 399,290 tested from March 1 to September 10, 2020) constitute the study cohort. MAIN MEASURES: The primary outcome was 30-day mortality from the first positive SARS-CoV-2 test date. In patients receiving medications or drug pairs within 2 weeks post-SARS-CoV-2 positive test, 30-day mortality was estimated as relative risk (RR) on the log-binomial scale or using multinomial models with and without adjusting for covariates. KEY

resultsThe 26,508 SARS-CoV-2 positive patients were predominantly male (89%) and White (59%), and 82% were overweight/obese. Medications associated with decreased 30-day mortality risk included the following: metformin (aRR, 0.33; 95% CI, 0.25-0.43), colchicine, angiotensin-converting-enzyme inhibitors (ACEi), angiotensin II receptor blockers, statins, vitamin D, antihistamines, alpha-blockers, anti-androgens, and nonsteroidal anti-inflammatory drugs (aRR, 0.69; 95% CI, 0.61-0.78). The effect of co-prescribed medications on 30-day mortality risk revealed the lowest risk for combined statins and metformin (aRR, 0.21; 95% CI, 0.15-0.31), followed by ACEi and statins (aRR, 0.25; 95% CI, 0.18-0.35), ACEi and metformin (aRR, 0.26; 95% CI, 0.17-0.40), antihistamines and NSAIDs (aRR, 0.41; 95% CI, 0.32-0.52), and in men, combined alpha-blockers and anti-androgens (aRR, 0.51; 95% CI, 0.42-0.64).

conclusionsIn this large national cohort, treatment of SARS-CoV-2 positive patients with individual or co-prescribed metformin and statins, ACEi and statins (or metformin) and other medications was associated with a markedly decreased 30-day mortality and can likely be continued safely. Clinical trials may assess their therapeutic benefit.

Indexed as

COVID-19 Drug TreatmentHydroxymethylglutaryl-CoA Reductase InhibitorsMetforminVeteransAngiotensin-Converting Enzyme InhibitorsAngiotensin Receptor AntagonistsCohort StudiesFemaleHumansMaleSARS-CoV-2Angiotensin-Converting Enzyme InhibitorsAngiotensin Receptor AntagonistsHydroxymethylglutaryl-CoA Reductase InhibitorsMetforminangiotensin-converting enzyme inhibitordrug safetymetforminmortalitysevere acute respiratory syndrome coronavirus-2statins

Identifiers

PMID35768681
PMCPMC9243908
OpenAlexW4283740619

What OpenQuestion holds

Textmetadata
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.