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Record W4310596277 · doi:10.1159/000528071

Fetal Endoscopic Tracheal Intubation: Modification of the Fetal Endoscopic Tracheal Intubation Procedure to Establish an Airway in a Fetus with a Congenital Cervical Teratoma

2022· article· en· W4310596277 on OpenAlexaff
Homero Flores Mendoza, Paolo Campisi, Poorva Deshpande, Nimrah Abbasi, Tim Van Mieghem, Johannes Keunen, Greg Ryan

Bibliographic record

VenueFetal Diagnosis and Therapy · 2022
Typearticle
Languageen
FieldMedicine
TopicTeratomas and Epidermoid Cysts
Canadian institutionsHospital for Sick ChildrenUniversity of TorontoSickKids FoundationMount Sinai Hospital
Fundersnot available
KeywordsMedicineAirwayIntubationFetusTracheal intubationFetoscopySurgeryFetal surgeryAnesthesiaIn uteroPrenatal diagnosisPregnancy

Abstract

fetched live from OpenAlex

INTRODUCTION: FETI is a technique where the fetal airway is secured in-utero via intubation by percutaneous endoscopic fetal tracheoscopy under ultrasound guidance. FETI has been described in large fetal neck masses with anatomical airway compression as a feasible airway management strategy and a potential alternative to an EXIT procedure in select cases. CASE PRESENTATION: This report describes the use of a modified FETI procedure under continuous fetoscopic and ultrasound guidance, in a fetus with a large cervical teratoma causing airway displacement and compression. Following the FETI procedure, an uncomplicated caesarean section was performed. The endotracheal tube was in place at the time of birth, and a patent airway was confirmed. CONCLUSION: The modified FETI procedure described in this report represents another technique that can be used to establish an airway in fetuses with challenging upper airway anatomy, potentially mitigating the risks associated with an EXIT procedure.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.003
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.003
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.000
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0030.002
Insufficient payload (model declined to judge)0.0010.000

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 head0.022
GPT teacher head0.273
Teacher spread0.252 · 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 source (direct Gemma or distilled Codex), 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

Citations4
Published2022
Admission routes1
Has abstractyes

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