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Record W4413735907 · doi:10.33137/utmj.v102i2.43726

Anesthetic Protocol For Patients With Hereditary Hemorrhagic Telangiectasia Undergoing Enteroscopy For Angiodysplastic Lesions: A Case Report

2025· article· en· W4413735907 on OpenAlexaffvenue
Brian Yang, Michael J. Ricci, Vetri Thangavelu, Wesla Pfeifer

Bibliographic record

VenueUniversity of Toronto Medical Journal · 2025
Typearticle
Languageen
FieldMedicine
TopicVascular Anomalies and Treatments
Canadian institutionsSt. Michael's HospitalUniversity of Toronto
Fundersnot available
KeywordsTelangiectasiaMedicineProtocol (science)AnesthesiaEnteroscopyAnestheticSurgeryDermatologyPathologyEndoscopy

Abstract

fetched live from OpenAlex

Hereditary hemorrhagic telangiectasia (HHT), also known as Osler-Weber-Rendu syndrome, is a rare genetic disorder that poses significant perioperative challenges due to the risk of bleeding. We report the case of a 47-year-old male with HHT undergoing double-balloon enteroscopy (DBE) for gastrointestinal angiodysplastic lesions. Preoperative preparation included detailed screening for anemia, coagulation status, and arteriovenous malformations (AVMs). Anesthetic considerations included airway management strategies to prevent and detect telangiectasia rupture, maintenance of hemodynamic stability, and post-procedural bleeding management. Intraoperative measures included careful intubation, hemodynamic monitoring, and mitigation of embolic risks. The procedure was completed successfully, managing over 100 lesions without incident. This case highlights the importance of personalized perioperative protocols, intraoperative vigilance, and post-operative care which are crucial for the successful management of patients with HHT. We present our HHT-specific anesthetic protocol from a hematology center to address the unique challenges of HHT in endoscopic clinics, contributing to safer outcomes for patients with this rare genetic disorder.

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: Case report · Consensus signal: Case report
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.251
Threshold uncertainty score0.378

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 head0.271
Teacher spread0.263 · 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 designCase report
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

Citations1
Published2025
Admission routes2
Has abstractyes

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