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Record W4283275613 · doi:10.15420/ver.2021.19

A Clinical Trial of Venous Stent Placement for Post-thrombotic Syndrome: Current Status and Pandemic-related Changes

2022· article· en· W4283275613 on OpenAlexafffund
Suresh Vedantham, Sameer Parpia, Susan R. Kahn

Bibliographic record

VenueVascular and Endovascular Review · 2022
Typearticle
Languageen
FieldMedicine
TopicVenous Thromboembolism Diagnosis and Management
Canadian institutionsMcGill University Health CentreMcMaster UniversityImpact
FundersCanadian Institutes of Health ResearchNational Institutes of HealthAlexion PharmaceuticalsNational Heart, Lung, and Blood InstituteSanofi
KeywordsPost-thrombotic syndromePandemicMedicineClinical trialCardiologyCoronavirus disease 2019 (COVID-19)Intensive care medicineInternal medicineVenous thrombosisThrombosisDisease

Abstract

fetched live from OpenAlex

Patients with post-thrombotic syndrome (PTS) and iliac vein obstruction have lower extremity symptoms, activity limitation and impairment of health-related quality of life. Preliminary studies suggest that iliac vein stent placement, which eliminates venous outflow obstruction, may reduce the clinical severity of PTS. However, stent placement is associated with patient risk, inconvenience and cost. Therefore, the Chronic Venous Thrombosis - Relief with Adjunctive Catheter-directed Therapy (C-TRACT) trial was launched to rigorously assess the risk-benefit ratio of stent placement for the treatment of moderate or severe PTS. In the trial, patients in both treatment groups receive a high quality of multimodality PTS care that includes medical, compressive, and ulcer therapies. Due to the COVID-19 pandemic, the trial protocol and practices were modified to enhance the study feasibility while preserving its ability to answer its primary question. This review summarises the current status of the trial and the potential impact of the pandemic-related adaptations to future venous clinical practice and research.

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)0.005
metaresearch head score (Gemma)0.007
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Randomized trial · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.005
Threshold uncertainty score0.026

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.007
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0030.000

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 head0.054
GPT teacher head0.347
Teacher spread0.293 · 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 designRandomized trial
Domainnot available
GenreEmpirical

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

Citations4
Published2022
Admission routes2
Has abstractyes

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