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Record W3120383130 · doi:10.1101/2021.01.04.21249227

Antithrombotic Therapy in COVID-19: Systematic Summary of Ongoing or Completed Randomized Trials

2021· preprint· en· W3120383130 on OpenAlexaff
Azita H. Talasaz, Parham Sadeghipour, Hessam Kakavand, Maryam Aghakouchakzadeh, Elaheh Kordzadeh-Kermani, Benjamín Van Tassell, Azin Gheymati, Hamid Ariannejad, Seyed Hossein Hosseini, Sepehr Jamalkhani, Michelle Sholzberg, Manuel Monréal, David Jiménez, Gregory Piazza, Sahil A. Parikh, Ajay J. Kirtane, John W. Eikelboom, Jean M. Connors, Beverley J. Hunt, Stavros Konstantinides, Mary Cushman, Jeffrey I. Weitz, Gregg W. Stone, Harlan M. Krumholz, Gregory Y.H. Lip, Samuel Z. Goldhaber, Behnood Bikdeli

Bibliographic record

VenuemedRxiv · 2021
Typepreprint
Languageen
FieldMedicine
TopicCOVID-19 Clinical Research Studies
Canadian institutionsSt. Michael's HospitalPopulation Health Research InstituteHamilton Health SciencesUniversity of TorontoMcMaster UniversityThrombosis and Atherosclerosis Research Institute
Fundersnot available
KeywordsAntithromboticMedicineCoronavirus disease 2019 (COVID-19)Randomized controlled trialIntensive care medicineClinical trialSevere acute respiratory syndrome coronavirus 2 (SARS-CoV-2)Perspective (graphical)Thrombosis2019-20 coronavirus outbreakDiseaseInternal medicinePathologyInfectious disease (medical specialty)

Abstract

fetched live from OpenAlex

ABSTRACT Endothelial injury and microvascular/macrovascular thrombosis are common pathophysiologic features of coronavirus disease-2019 (COVID-19). However, the optimal thromboprophylactic regimens remain unknown across the spectrum of illness severity of COVID-19. A variety of antithrombotic agents, doses and durations of therapy are being assessed in ongoing randomized controlled trials (RCTs) that focus on outpatients, hospitalized patients in medical wards, and critically-ill patients with COVID-19. This manuscript provides a perspective of the ongoing or completed RCTs related to antithrombotic strategies used in COVID-19, the opportunities and challenges for the clinical trial enterprise, and areas of existing knowledge, as well as data gaps that may motivate the design of future RCTs.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.041
metaresearch head score (Gemma)0.122
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: Systematic review
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.041
Threshold uncertainty score0.218

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0410.122
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0090.011
Bibliometrics0.0030.004
Science and technology studies0.0000.001
Scholarly communication0.0040.002
Open science0.0010.002
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0070.001

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.280
GPT teacher head0.501
Teacher spread0.222 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSystematic review
Domainnot available
GenreReview

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations10
Published2021
Admission routes1
Has abstractyes

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