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Awake videolaryngoscopy‐assisted tracheal intubation of the morbidly obese

2012· article· en· W1527612638 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueAnaesthesia · 2012
Typearticle
Languageen
FieldMedicine
TopicAirway Management and Intubation Techniques
Canadian institutionsMcGill University Health CentreMcGill University
Fundersnot available
KeywordsMedicineTracheal intubationIntubationAnesthesiaTracheal tubeSedationAirwayLarynxLaryngoscopySurgeryLaryngeal MasksAirway managementMorbidly obeseBronchoscopyLaryngeal mask airwayInternal medicine

Abstract

fetched live from OpenAlex

Awake videolaryngoscopy may be useful for the tracheal intubation of the morbidly obese. This prospective, observational study enrolled 50 patients undergoing bariatric surgery. After sedation and topical anaesthesia of the airway, awake tracheal intubation was attempted, assisted by videolaryngoscopy, and terminated if there was severe gagging, coughing, or inadequate laryngeal view. After three attempts the procedure was considered a failure. Twenty-seven intubations were successful on the first attempt, fifteen on the second, six on the third and two were not successful, giving a success rate of 96% (95% CI 86-100%). In one failure, inserting the tracheal tube caused severe gagging in spite of an adequate view of the larynx, and the trachea was intubated with the videolaryngoscope after induction of anaesthesia. The second failure was due to gagging, with subsequent tracheal intubation successful using fibreoptic bronchoscopy. When managing the morbidly obese airway, awake tracheal intubation using videolaryngoscopy may be considered.

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.

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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.344
Threshold uncertainty score0.453

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 head0.023
GPT teacher head0.282
Teacher spread0.260 · 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