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Record W4417354217 · doi:10.1136/bcr-2025-265676

Hypnosis as a complementary approach in the anaesthetic management of anterior mediastinal mass biopsy

2025· article· en· W4417354217 on OpenAlexaff
Valérie Zaphiratos, David Ogez, F. Yung

Bibliographic record

VenueBMJ Case Reports · 2025
Typearticle
Languageen
FieldMedicine
TopicPediatric Pain Management Techniques
Canadian institutionsCentre Hospitalier Universitaire Sainte-JustineHôpital Maisonneuve-RosemontUniversité de Montréal
Fundersnot available
KeywordsGeneral anaesthesiaHypnosisSedationBiopsyAirwayGeneral anaestheticMediastinal massLocal anaesthetic

Abstract

fetched live from OpenAlex

Anterior mediastinal masses pose significant anaesthetic challenges, primarily due to the risks of airway compression and haemodynamic instability. We present the case of an adolescent with an anterior mediastinal mass causing severe tracheal and vascular compression, necessitating urgent diagnostic biopsies. Given the high risk associated with general anaesthesia, the procedure was performed under local anaesthesia in conjunction with clinical hypnosis. This approach was well tolerated, successfully avoiding deep sedation and airway manipulation.As the initial biopsies were inconclusive, an excisional lymph node biopsy was subsequently performed using the same anaesthetic strategy, incorporating both the hypnosis protocol and local anaesthesia. This procedure confirmed the diagnosis of Hodgkin lymphoma, enabling the prompt initiation of chemotherapy.This case underscores the potential role of clinical hypnosis as an adjunct to local anaesthesia in enhancing patient comfort and cooperation, particularly when general anaesthesia presents substantial risks.

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)0.002
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 score0.262
Threshold uncertainty score0.542

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.026
GPT teacher head0.335
Teacher spread0.309 · 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

Citations0
Published2025
Admission routes1
Has abstractyes

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