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Record W1972646275 · doi:10.1002/hed.21410

Percutaneous treatment of facial venous malformations: A matched comparison of alcohol and bleomycin sclerotherapy

2010· article· en· W1972646275 on OpenAlexaff
Jessica Spence, Timo Krings, Karel G. terBrugge, Ronit Agid

Bibliographic record

VenueHead & Neck · 2010
Typearticle
Languageen
FieldMedicine
TopicVascular Malformations and Hemangiomas
Canadian institutionsToronto Western HospitalUniversity of Manitoba
Fundersnot available
KeywordsSclerotherapyBleomycinMedicinePercutaneousAdverse effectSurgeryVenous malformationAlcoholAnesthesiaRadiologyChemotherapyInternal medicine

Abstract

fetched live from OpenAlex

BACKGROUND: Venous malformations (VMs) are common vascular anomalies; 40% are found in the head and neck. Percutaneous sclerotherapy is 1 treatment of choice. METHODS: In all, 17 patients with facial VMs were treated by percutaneous sclerotherapy using alcohol and individually matched to lesions treated with bleomycin. Treatment details and outcomes were compared. The average numbers of sessions were 1.7 for alcohol and 3.4 for bleomycin. Average dose administered was 8.1 cm³ alcohol and 9.1 units bleomycin. RESULTS: Of those treated with alcohol, 2 developed adverse effects and 7 developed complications. None treated with bleomycin developed adverse effects or complications. All patients treated with alcohol improved clinically. In all, 15 patients treated with bleomycin improved after treatment and 2 were unchanged. CONCLUSIONS: Alcohol has a slightly higher success rate and requires fewer treatment sessions. Bleomycin has a lower complication rate and less postprocedural swelling. Bleomycin treatment may be better tolerated and is thus preferred over alcohol sclerotherapy.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.520
Threshold uncertainty score0.354

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 head0.037
GPT teacher head0.330
Teacher spread0.293 · 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

Citations78
Published2010
Admission routes1
Has abstractyes

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