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Portal vein dilation in Klippel-Trenaunay and CLOVES syndromes

2025· article· en· W4410697766 on OpenAlexaff
Asma Maqsood, J. Alonso Sánchez, Gary Peiser, Aisling Carroll-Downey, Maria F Dien Equivel, João Amaral, Laura B. Willis, Manuel Carção, A Gasparetto

Bibliographic record

VenueInternational Angiology · 2025
Typearticle
Languageen
FieldMedicine
TopicVascular Malformations and Hemangiomas
Canadian institutionsHospital for Sick Children
Fundersnot available
KeywordsMedicineKlippel-Trenaunay syndromeDilation (metric space)RadiologySurgeryAnatomyInternal medicine

Abstract

fetched live from OpenAlex

BACKGROUND: Klippel-Trenaunay Syndrome (KTS) and congenital lipomatous overgrowth, vascular anomalies, epidermal nevi and skeletal abnormalities (CLOVES) syndrome are rare conditions associated with overgrowth and vascular anomalies more frequently involving the lower extremities. Although uncommon, these syndromes can be associated with portal vein (PV) abnormalities, including PV thrombosis, and PV hypertension. In this study, we describe additional findings of PV dilation in five patients with KTS or CLOVES. METHODS: A single institution 20 year retrospective review was performed to evaluate PV findings in patients with vascular anomalies and overgrowth of the lower extremities. Two radiologists reviewed the imaging examinations (US, CT and MRI) and recorded type and location of vascular alterations. RESULTS: Of 35 patients (25 females, 24 KTS, 7 CLOVES and 4 other, median age: 8.5 years) with available abdominal imaging, 5 patients had PV dilation and one PV thrombosis. All patients presented additional abdominal vascular anomalies in association. CONCLUSIONS: Systematic evaluation of the abdominopelvic region in patients with KTS and CLOVES can identify vascular anomalies, including PV dilation, which may indicate a prethrombotic state. Early detection and monitoring of these findings could have clinical implications for preventing complications such as portal hypertension and thrombosis.

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 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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.088
Threshold uncertainty score0.205

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
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 head0.008
GPT teacher head0.292
Teacher spread0.285 · 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 teacher head, 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

Citations0
Published2025
Admission routes1
Has abstractyes

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