Evidence mapPaperPMID 36829115Full record

ArticleBMC infectious diseases2023

Association of statin use with outcomes of patients admitted with COVID-19: an analysis of electronic health records using superlearner.

Adovich S Rivera, Omar Al-Heeti, Lucia C Petito, Mathew J Feinstein, Chad J Achenbach, Janna Williams, Babafemi Taiwo

Abstract read
In one paragraph

Article in BMC infectious diseases, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
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

6 citing papers in PubMed.

  1. Article
  2. Article
  3. Review
  4. Observational
  5. Article
  6. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

7 authors.

Adovich S Rivera *Institute for Public Health and Management, Feinberg School of Medicine, Chicago, IL, 60611, USA.
Omar Al-Heeti *Division of Infectious Diseases, Department of Medicine, Northwestern University Feinberg School of Medicine, 645 N. Michigan Ave, Suite 900, Chicago, IL, 60611, USA.
Lucia C PetitoDivision of Biostatistics, Department of Preventive Medicine, Feinberg School of Medicine, Chicago, IL, 60611, USA.
Mathew J FeinsteinDivision of Cardiology, Department of Medicine, Feinberg School of Medicine, Chicago, IL, 60611, USA.
Chad J AchenbachDivision of Infectious Diseases, Department of Medicine, Northwestern University Feinberg School of Medicine, 645 N. Michigan Ave, Suite 900, Chicago, IL, 60611, USA.
Janna WilliamsDivision of Infectious Diseases, Department of Medicine, Northwestern University Feinberg School of Medicine, 645 N. Michigan Ave, Suite 900, Chicago, IL, 60611, USA.
Babafemi TaiwoDivision of Infectious Diseases, Department of Medicine, Northwestern University Feinberg School of Medicine, 645 N. Michigan Ave, Suite 900, Chicago, IL, 60611, USA. b-taiwo@northwestern.edu.

Funding

NCATS NIH HHS UL1 TR001422NIH HHS Number UL1TR001422
6 · The paper itself

Abstract

importanceStatin use prior to hospitalization for Coronavirus Disease 2019 (COVID-19) is hypothesized to improve inpatient outcomes including mortality, but prior findings from large observational studies have been inconsistent, due in part to confounding. Recent advances in statistics, including incorporation of machine learning techniques into augmented inverse probability weighting with targeted maximum likelihood estimation, address baseline covariate imbalance while maximizing statistical efficiency.

objectiveTo estimate the association of antecedent statin use with progression to severe inpatient outcomes among patients admitted for COVD-19. DESIGN, SETTING AND

participantsWe retrospectively analyzed electronic health records (EHR) from individuals ≥ 40-years-old who were admitted between March 2020 and September 2022 for ≥ 24 h and tested positive for SARS-CoV-2 infection in the 30 days before to 7 days after admission. EXPOSURE: Antecedent statin use-statin prescription ≥ 30 days prior to COVID-19 admission. MAIN OUTCOME: Composite end point of in-hospital death, intubation, and intensive care unit (ICU) admission.

resultsOf 15,524 eligible COVID-19 patients, 4412 (20%) were antecedent statin users. Compared with non-users, statin users were older (72.9 (SD: 12.6) versus 65.6 (SD: 14.5) years) and more likely to be male (54% vs. 51%), White (76% vs. 71%), and have ≥ 1 medical comorbidity (99% vs. 86%). Unadjusted analysis demonstrated that a lower proportion of antecedent users experienced the composite outcome (14.8% vs 19.3%), ICU admission (13.9% vs 18.3%), intubation (5.1% vs 8.3%) and inpatient deaths (4.4% vs 5.2%) compared with non-users. Risk differences adjusted for labs and demographics were estimated using augmented inverse probability weighting with targeted maximum likelihood estimation using Super Learner. Statin users still had lower rates of the composite outcome (adjusted risk difference: - 3.4%; 95% CI: - 4.6% to - 2.1%), ICU admissions (- 3.3%; - 4.5% to - 2.1%), and intubation (- 1.9%; - 2.8% to - 1.0%) but comparable inpatient deaths (0.6%; - 1.3% to 0.1%). CONCLUSIONS AND RELEVANCE: After controlling for confounding using doubly robust methods, antecedent statin use was associated with minimally lower risk of severe COVID-19-related outcomes, ICU admission and intubation, however, we were not able to corroborate a statin-associated mortality benefit.

Indexed as

COVID-19Hydroxymethylglutaryl-CoA Reductase InhibitorsAdultElectronic Health RecordsFemaleHospitalizationHospital MortalityHumansIntensive Care UnitsMaleRetrospective StudiesSARS-CoV-2Hydroxymethylglutaryl-CoA Reductase InhibitorsCOVID-19Critical careMortalityObservational studiesStatinTargeted maximum likelihood estimation

Identifiers

PMID36829115
PMCPMC9951166

What Socratic holds

Textmetadata
LicenceCC BY
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 Socratic graph.