Evidence map›Paper›PMID 38500962›Full record

ArticleLancet regional health. Americas2024

Real-world use of nirmatrelvir-ritonavir in COVID-19 outpatients during BQ.1, BQ.1.1., and XBB.1.5 predominant omicron variants in three U.S. health systems: a retrospective cohort study.

Neil R Aggarwal, Laurel E Beaty, Tellen D Bennett, Lindsey E Fish, Jason R Jacobs, David A Mayer, Kyle C Molina, Jennifer L Peers, Douglas B Richardson, Seth Russell and 6 more

Open access · goldAbstract read
In one paragraph

Article in Lancet regional health. Americas, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
8citing papers in PubMed, 2 pooled it
3.1field-weighted citation impact, top 9% 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

8 citing papers in PubMed, 2 syntheses or guidelines pooled it, 8 citations in OpenAlex.

  1. Pooled it
  2. Pooled it
  3. Article
  4. Review
  5. Article
  6. Article
  7. Article
  8. Review
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

16 authors at 5 institutions in 1 country.

Neil R AggarwalDepartment of Medicine, Division of Pulmonary Sciences and Critical Care, University of Colorado School of Medicine, Aurora, CO, 80045, USA.
Laurel E BeatyDepartment of Biostatistics and Informatics, Colorado School of Public Health, Aurora, CO, 80045, USA.
Tellen D BennettDepartments of Biomedical Informatics and Pediatrics, University of Colorado School of Medicine, Colorado Clinical and Translational Sciences Institute, University of Colorado Anschutz Medical Campus, Aurora, 80045, USA.
Lindsey E FishDivision of General Internal Medicine, Denver Health and Hospital and University of Colorado School of Medicine, Denver, CO, 80204, USA.
Jason R JacobsPulmonology and Critical Care Medicine Research, Intermountain Health, Murray, UT, 84107, USA.
David A MayerDepartment of Biostatistics and Informatics, Colorado School of Public Health, Aurora, CO, 80045, USA.
Kyle C MolinaDepartment of Emergency Medicine, University of Colorado School of Medicine, Aurora, CO, 80045, USA.
Jennifer L PeersDepartment of Emergency Medicine, University of Colorado School of Medicine, Aurora, CO, 80045, USA.
Douglas B RichardsonDivision of General Internal Medicine, Denver Health and Hospital and University of Colorado School of Medicine, Denver, CO, 80204, USA.
Seth RussellDepartments of Biomedical Informatics and Pediatrics, University of Colorado School of Medicine, Colorado Clinical and Translational Sciences Institute, University of Colorado Anschutz Medical Campus, Aurora, 80045, USA.
Alejandro VarelaDepartment of Biostatistics and Informatics, Colorado School of Public Health, Aurora, CO, 80045, USA.
Brandon J WebbDivision of Infectious Diseases and Clinical Epidemiology, Intermountain Health, Salt Lake City, UT, 84107, USA.
Matthew K WyniaDepartment of Medicine, Division of Pulmonary Sciences and Critical Care, University of Colorado School of Medicine, Aurora, CO, 80045, USA.
Mengli XiaoDepartment of Biostatistics and Informatics, Colorado School of Public Health, Aurora, CO, 80045, USA.
Nichole E CarlsonDepartment of Biostatistics and Informatics, Colorado School of Public Health, Aurora, CO, 80045, USA.
Adit A GindeDepartment of Emergency Medicine, University of Colorado School of Medicine, Aurora, CO, 80045, USA.
Colorado School of Public Health · USUniversity of Colorado Denver · USDenver Health Medical Center · USIntermountain Healthcare · USUniversity of Colorado Anschutz Medical Campus · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Ritonavir-boosted Nirmatrelvir (NMV-r), a protease inhibitor with Methods: We conducted a retrospective observational cohort study of non-hospitalised adult patients with SARS-CoV-2 infection using real-world data from three health systems in Colorado and Utah, and compared hospitalisation rates in NMV-r-treated patients in a BA.2/BA.2.12.1/BA.4/BA.5 variant-predominant (first) phase (April 3, 2022-November 12, 2022), with a BQ.1/BQ.1.1/XBB.1.5 variant-predominant (second) phase (November 13, 2022-March 7, 2023). In the primary analysis, we used Firth logistic regression with a two-segment (phase) linear time model, and pre-specified non-inferiority bounds for the mean change between segments. In a pre-specified secondary analysis, we inferred NMV-r effectiveness in a cohort of treated and untreated patients infected during the second phase. For both analyses, the primary outcome was 28-day all-cause hospitalisation. Subgroup analyses assessed treatment effect heterogeneity. Findings: In the primary analysis, 28-day all-cause hospitalisation rates in NMV-r treated patients in the second phase (n = 12,061) were non-inferior compared to the first phase (n = 25,075) (198 [1.6%] vs. 345 [1.4%], adjusted odds ratio (aOR): 0.76 [95% CI 0.54-1.06]), with consistent results among secondary endpoints and key subgroups. Secondary cohort analyses revealed additional evidence for NMV-r effectiveness, with reduced 28-day hospitalisation rates among treated patients compared to untreated patients during a BQ.1/BQ.1.1/XBB.1.5 predominant phase (198/12,061 [1.6%] vs. 376/10,031 [3.7%], aOR 0.34 [95% CI 0.30-0.38), findings robust to additional sensitivity analyses. Interpretation: Real-world evidence from major US healthcare systems suggests ongoing NMV-r effectiveness in preventing hospitalisation during a BQ.1/BQ.1.1/XBB.1.5-predominant phase in the U.S, supporting its continued use in similar patient populations. Funding: U.S. National Institutes of Health.

Indexed as

COVID-19 omicron variantsNirmatrelvir-ritonavir

Identifiers

PMID38500962
PMCPMC10945426
OpenAlexW4391679453

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.