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Record W2965278998 · doi:10.1097/aco.0000000000000771

Awake videolaryngoscopy versus fiberoptic bronchoscopy

2019· review· en· W2965278998 on OpenAlexaff
Albert Moore, Thomas Schricker

Bibliographic record

VenueCurrent Opinion in Anaesthesiology · 2019
Typereview
Languageen
FieldMedicine
TopicAirway Management and Intubation Techniques
Canadian institutionsMcGill UniversityRoyal Victoria HospitalRoyal Victoria Regional Health Centre
Fundersnot available
KeywordsMedicineIntubationTracheal intubationAirway managementAirwayAnesthesiaBronchoscopyLaryngoscopesIntensive care medicineSurgery

Abstract

fetched live from OpenAlex

PURPOSE OF REVIEW: The difficult airway remains an ongoing concern in daily anesthesia practice, with awake intubation being an important component of its management. Classically, fiberoptic bronchoscope-assisted tracheal intubation was the method of choice in the awake patient. The development of new generation videolaryngoscopes has revolutionized the approach to tracheal intubation in the anesthetized patient. The question whether videolaryngoscopes have a place in the intubation of the difficult airway in the awake patient is currently being addressed. RECENT FINDINGS: Randomized controlled trials and their meta-analysis have shown that videolaryngoscopes provide similar success rates and faster intubation times when compared with fiberoptic bronchoscope intubation in awake patients with difficult airways. SUMMARY: Videolaryngoscopy is a valid technique that should be considered for difficult airway management in the awake patient.

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)0.001
metaresearch head score (Gemma)0.005
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.006
Threshold uncertainty score0.021

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.005
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0030.002
Bibliometrics0.0020.003
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0060.001

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 head0.236
GPT teacher head0.470
Teacher spread0.235 · 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 designNot applicable
Domainnot available
GenreReview

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

Citations36
Published2019
Admission routes1
Has abstractyes

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