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Record W4411965618 · doi:10.1016/j.jscai.2025.103730

SCAI Technical Review on Management of Chronic Venous Disease

2025· article· en· W4411965618 on OpenAlexaff
Robert Attaran, Matthew Edwards, Matthew C. Bunte, Yulanka Castro‐Dominguez, Eri Fukaya, Karem Harth, Pamela Kim, Scott Firestone, Emily Senerth, Rebecca L. Morgan

Bibliographic record

VenueJournal of the Society for Cardiovascular Angiography & Interventions · 2025
Typearticle
Languageen
FieldMedicine
TopicDiagnosis and Treatment of Venous Diseases
Canadian institutionsMcMaster University
FundersMedtronicBoston Scientific Corporation
KeywordsMedicineIntensive care medicine

Abstract

fetched live from OpenAlex

Background: Chronic venous disease (CVD) impacts more than 25 million adults in the United States and is associated with a host of symptoms that can adversely affect quality of life (QoL), such as leg discomfort, edema, and ulceration. Treatments for CVD range from conservative therapy centered around use of compression to more invasive approaches, such as ablation, sclerotherapy, phlebectomy, venoplasty, and stenting. Methods: A systematic review was conducted to address 8 questions on the management of CVD that were formulated by the Society for Cardiovascular Angiography & Interventions (SCAI) Guideline Panel using the patient, intervention, comparator, outcome (PICO) format. Medical literature from January 1, 2008, through May 15, 2023, was searched using PubMed, Embase, and the Cochrane Central Register of Controlled Trials, except where an existing systematic review on compression therapy versus no intervention was updated with evidence from May 1, 2020, to May 15, 2023. Study selection was performed in duplicate; data extraction and risk of bias assessment were performed by 1 reviewer and reviewed by a second reviewer. Pooled effect estimates were calculated when applicable, and overall certainty in the evidence was assessed using the Grading of Recommendations Assessment, Development, and Evaluation (GRADE) approach. Results: Our combined searches identified 3648 titles and abstracts, of which 19 met eligibility criteria and informed the technical review. Studies reported on healing rate and time to healing, disease recurrence, symptom severity, and QoL among patients who were treated with compression therapy, ablation, sclerotherapy, phlebectomy, and venoplasty or stenting. Compression therapy probably results in slightly faster and more complete venous ulcer healing compared with no compression. Ablation of the great saphenous vein ± small saphenous vein may improve healing rate and symptoms over conservative therapy alone, particularly for ulcer disease. Evidence is very uncertain for any effect on healing rate, symptom score, QoL, and disease recurrence associated with perforator vein ablation, venoplasty, and stenting for iliocaval obstruction, sclerotherapy, and phlebectomy of symptomatic varicose veins. Conclusions: Data from this technical review will inform the Society for Cardiovascular Angiography and Interventions Guideline on Management of Chronic Venous Disease. The panel also identified research priorities based on areas where evidence to guide clinical practice is lacking or very uncertain.

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)0.013
metaresearch head score (Gemma)0.045
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.020
Threshold uncertainty score0.071

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0130.045
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0070.007
Bibliometrics0.0200.015
Science and technology studies0.0010.001
Scholarly communication0.0040.003
Open science0.0030.003
Research integrity0.0030.002
Insufficient payload (model declined to judge)0.0170.003

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 head0.018
GPT teacher head0.314
Teacher spread0.296 · 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 designNot applicable
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

Citations3
Published2025
Admission routes1
Has abstractyes

Explore more

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