Evidence map›Paper›PMID 36345824›Full record

Observational studyJournal of hospital medicine2023

The intensity of anticoagulant dosing in hospitalized patients with COVID-19: An observational, comparative effectiveness study.

Laura C Myers, Stanley Xu, Aiyu Chen, John D Greene, Beth Creekmur, Katia Bruxvoort, Gabriel J Escobar, John L Adams, Annette Langer-Gould, Vincent X Liu and 1 more

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

Observational study in Journal of hospital medicine, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed, 1 pooled it
0.2field-weighted citation impact, top 48% 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

2 citing papers in PubMed, 1 synthesis or guideline pooled it, 2 citations in OpenAlex.

  1. Pooled it
  2. Observational
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

11 authors at 1 institution in 1 country.

Laura C MyersDivision of Research and The Permanente Medical Group, Kaiser Permanente Northern California, Oakland, California, USA.
Stanley XuDepartment of Research and Evaluation, Kaiser Permanente Southern California, Pasadena, California, USA.
Aiyu ChenDepartment of Research and Evaluation, Kaiser Permanente Southern California, Pasadena, California, USA.
John D GreeneDivision of Research and The Permanente Medical Group, Kaiser Permanente Northern California, Oakland, California, USA.ORCID 0000-0002-0859-6828
Beth CreekmurDepartment of Research and Evaluation, Kaiser Permanente Southern California, Pasadena, California, USA.ORCID 0000-0001-7802-1125
Katia BruxvoortDepartment of Research and Evaluation, Kaiser Permanente Southern California, Pasadena, California, USA.ORCID 0000-0001-8277-2431
Gabriel J EscobarDivision of Research and The Permanente Medical Group, Kaiser Permanente Northern California, Oakland, California, USA.
John L AdamsKaiser Permanente Center for Effectiveness and Safety Research, Pasadena, California, USA.
Annette Langer-GouldNeurology Department, Southern California Permanente Medical Group, Kaiser Permanente Southern California, Los Angeles, California, USA.
Vincent X LiuDivision of Research and The Permanente Medical Group, Kaiser Permanente Northern California, Oakland, California, USA.
Michael K GouldDepartment of Health Systems Science, Kaiser Permanente Bernard J. Tyson School of Medicine, Pasadena, California, USA.ORCID 0000-0001-6749-8315
Kaiser Permanente · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThe question of anticoagulant dosing in hospitalized patients with coronavirus disease-2019 (COVID-19) is unresolved, with randomized trials showing mixed results and heterogeneity of treatment effects for in-hospital death.

objectiveTo examine the association between the intensity of anticoagulation and clinical outcomes in hospitalized patients with COVID-19. DESIGN, SETTING AND

participantsRetrospective cohort study of patients with COVID-19 and respiratory impairment who were hospitalized between 3/1/2020-12/31/2020 in two Kaiser Permanente regions. EXPOSURE AND MAIN OUTCOME: We fit propensity score models using categorical regression to estimate the probability of receiving standard prophylactic, intermediate, or full-dose anticoagulation beginning on the day of admission or on the day of first respiratory deterioration. Exposure was defined by the highest dose on the day of admission or within 24 hours after deterioration. The primary outcome was in-hospital death.

resultsWe included 17,130 patients in the day of admission analysis and 4,924 patients who experienced respiratory deterioration. There were no differences in propensity score-adjusted odds of in-hospital death for patients who received either intermediate (odds ratio [OR]: 1.00, 95% confidence intervals [CI] 0.89-1.12) or full anticoagulation (OR: 1.00, 95% CI: 0.85-1.17) compared with standard prophylaxis beginning on the day of admission. Similarly, there were no differences in in-hospital death for either intermediate (OR: 1.22, 95% CI: 0.82-1.82) or full anticoagulation (OR: 1.50, 95% CI: 0.90-2.51) compared with standard prophylaxis on the day of deterioration.

conclusionResults of this real-world, comparative effectiveness study showed no differences in in-hospital death among newly admitted or deteriorating patients with COVID-19 who received intermediate-dose or full anticoagulation compared with standard prophylaxis.

Indexed as

COVID-19AnticoagulantsHospital MortalityHumansRetrospective StudiesSARS-CoV-2Anticoagulants

Identifiers

PMID36345824
PMCPMC9877905
OpenAlexW4308553336

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.