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Measuring functional limitations after venous thromboembolism: Optimization of the Post-VTE Functional Status (PVFS) Scale

2020· article· en· W3014549967 on OpenAlexafffund
Gudula J.A.M. Boon, Stefano Barco, Laurent Bertoletti, Waleed Ghanima, Menno V. Huisman, Susan R. Kahn, Simon Noble, Paolo Prandoni, Rachel Rosovsky, Akhilesh K. Sista, Bob Siegerink, Frederikus A. Klok

Bibliographic record

VenueThrombosis Research · 2020
Typearticle
Languageen
FieldMedicine
TopicVenous Thromboembolism Diagnosis and Management
Canadian institutionsJewish General Hospital
FundersCanadian Institutes of Health ResearchTrombosestichting NederlandSykehuset ØstfoldUniversidad de AlcaláMedizinische Universität WienUniversity of TorontoMedizinischen Hochschule HannoverAmsterdam University Medical CentersUniversitetet i OsloKU LeuvenUniversiteit MaastrichtUniversity of BernUniversität WienChildren’s Hospital of Wisconsin Research InstituteCardiff UniversityInselspital, Universitätsspital BernMaastricht Universitair Medisch CentrumMarie CurieOttawa Hospital Research InstituteMcMaster UniversityFaculté de Médecine, Université de GenèveErasmus Medisch CentrumLeids Universitair Medisch CentrumUniversiteit LeidenMurdoch Children's Research InstituteJewish General HospitalBundesministerium für Bildung und ForschungMassachusetts General HospitalUniversity of Ottawa
KeywordsVenous thromboembolismMedicineScale (ratio)Intensive care medicineInternal medicineThrombosisGeographyCartography

Abstract

fetched live from OpenAlex

INTRODUCTION: We recently proposed a scale for assessment of patient-relevant functional limitations following an episode of venous thromboembolism (VTE). Further development of this post-VTE functional status (PVFS) scale is still needed. METHODS: Guided by the input of VTE experts and patients, we refined the PVFS scale and its accompanying manual, and attempted to acquire broad consensus on its use. RESULTS: A Delphi analysis was performed involving 53 international VTE experts with diverse scientific and clinical backgrounds. In this process, the number of scale grades of the originally proposed PVFS scale was reduced and descriptions of the grades were improved. After these changes, a consensus was reached on the number/definitions of the grades, and method/timing of the scale assessment. The relevance and potential impact of the scale was confirmed in three focus groups totaling 18 VTE patients, who suggested additional changes to the manual, but not to the scale itself. Using the improved manual, the κ-statistics between PVFS scale self-reporting and its assessment via the structured interview was 0.75 (95%CI 0.58-1.0), and 1.0 (95%CI 0.83-1.0) between independent raters of the recorded interview of 16 focus groups members. CONCLUSION: We improved the PVFS scale and demonstrated broad consensus on its relevance, optimal grades, and methods of assessing among international VTE experts and patients. The interobserver agreement of scale grade assignment was shown to be good-to-excellent. The PVFS scale may become an important outcome measure of functional impairment for quality of patient care and in future VTE trials.

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)0.010
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.010
Threshold uncertainty score0.051

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0100.015
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0000.001
Open science0.0010.001
Research integrity0.0000.001
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 head0.212
GPT teacher head0.326
Teacher spread0.114 · 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".

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Citations82
Published2020
Admission routes2
Has abstractyes

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