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Record W4409919972 · doi:10.1051/mmnp/2025013

Unraveling the Hemodynamic Impact of Persistent Iliac Vein Lesions and Physical Therapy Post-Stenting

2025· article· en· W4409919972 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueMathematical Modelling of Natural Phenomena · 2025
Typearticle
Languageen
FieldMedicine
TopicVenous Thromboembolism Diagnosis and Management
Canadian institutionsCentre hospitalier de l'Université Laval
Fundersnot available
KeywordsHemodynamicsVeinMedicineCardiologyInternal medicine

Abstract

fetched live from OpenAlex

Stent implantation is a standard treatment for iliac vein compression syndrome (IVCS), but persistent lesions in the stented vein can lead to adverse outcomes. This study investigates the hemodynamic impact of these lesions and the effects of therapeutic strategies post-stenting. A patient-specific model simulating flattened, narrow, and tissue adhesion (TA) lesions was used to analyze key hemodynamic parameters, including Wall Shear Stress (WSS), Oscillatory Shear Index (OSI), Relative Residence Time (RRT), and Flow Resistance (RF). The results show that contralateral venous lesions significantly worsen hemodynamic conditions in the iliac vein after stenting. The adhesion model exhibited significantly higher reflux volumes and more extensive regions of low TAWSS, high OSI, and high RRT compared to the other lesion models. Both active ankle exercises (AAE) and intermittent pneumatic compression (IPC) therapies improved the hemodynamic environment in the stented vein. However, these therapies also worsened blood flow disturbances at the contralateral lesion site. These findings highlight the importance of personalized therapeutic strategies to optimize clinical outcomes following stenting.

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.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.609
Threshold uncertainty score0.422

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.027
GPT teacher head0.295
Teacher spread0.268 · 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