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Record W4320028607 · doi:10.1016/j.rpth.2022.100032

Exploring the Villalta scale to capture postthrombotic syndrome using alternative approaches: A subanalysis of the ATTRACT trial

2023· article· en· W4320028607 on OpenAlexafffund
Cristina Pop, Chu‐Shu Gu, Suresh Vedantham, J.‐P. Galanaud, Susan R. Kahn

Bibliographic record

VenueResearch and Practice in Thrombosis and Haemostasis · 2023
Typearticle
Languageen
FieldMedicine
TopicVenous Thromboembolism Diagnosis and Management
Canadian institutionsUniversity of TorontoMcGill University
FundersFonds de Recherche du Québec - SantéUniversity of WashingtonCanadian Institutes of Health ResearchCovidienNational Institutes of HealthCanada Research ChairsNational Heart, Lung, and Blood InstituteHeart and Stroke Foundation of CanadaSociety of Interventional Radiology FoundationMcMaster UniversityWashington University in St. LouisBoston Scientific CorporationInstitute of Clinical and Translational Sciences
KeywordsScale (ratio)Computer scienceGeographyCartography

Abstract

fetched live from OpenAlex

Background Clinical trials that evaluated interventions to prevent postthrombotic syndrome (PTS) used the Villalta scale (VS) to define PTS, but there is a lack of consistency in its use. Objectives This study aimed to improve the ability to identify patients with clinically meaningful PTS after DVT in participants of the ATTRACT trial. Methods We conducted a post hoc exploratory analysis of 691 patients from the ATTRACT study, a randomized trial evaluating the effectiveness of pharmacomechanical thrombolysis to prevent PTS in proximal deep vein thrombosis. We compared 8 VS approaches to classify patients with or without PTS in terms of their ability to discriminate between those with poorer vs better venous disease-specific quality of life (Venous Insufficiency Epidemiological and Economic Study Quality of Life [VEINES-QOL]) between 6- and 24-months follow-up. The difference in the average area under the fitted curve of VEINES-QOL scores between PTS and no PTS ( Δ A U C ¯ ) were compared among approaches. Results For any PTS (a single VS score ≥5), approaches 1 to 3 had similar Δ A U C ¯ (−21.2, −23.7, −22.0, respectively). Adjusting the VS for contralateral chronic venous insufficiency (CVI) or restricting to patients without baseline CVI (approaches 7 and 8) did not improve Δ A U C ¯ (−13.6, −19.9, respectively; P >.01). For moderate-to-severe PTS (a single VS score ≥10), approaches 5 and 6 requiring 2 positive assessments had greater but not statistically significant Δ A U C ¯ than approach 4, using one single positive assessment (−31.7, −31.0, −25.5, respectively; P >.01). Conclusion A single VS score of ≥ 5 reliably distinguishes patients with clinically meaningful PTS as assessed by impact on QOL and is preferred because of greater convenience (only one assessment needed). Alternative methods to define PTS (ie, adjusting for CVI) do not improve the scale's ability to identify clinically meaningful PTS.

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)0.018
metaresearch head score (Gemma)0.015
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.018
Threshold uncertainty score0.094

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0180.015
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0030.006
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.002
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 head0.614
GPT teacher head0.467
Teacher spread0.148 · 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 designObservational
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

Citations8
Published2023
Admission routes2
Has abstractyes

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