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Record W2883388224

The difficult airway with recommendations for management - Part 2 - The anticipated difficult airway Prise en charge des voies aeriennes - 2e partie - Recommandations lorsque des difficultes sont prevues

2013· article· fr· W2883388224 on OpenAlexaboutno aff
J. Adam Law, M. G. Cooper, Laura V. Duggan, E. Griesdale, Rachel Hung, Philip M. Jones, R. Morris, Timothy Mullen, F. Murphy, Nithesh Naik, Jeanette Scott, P. Turkstra, Timothy Wong

Bibliographic record

Venuenot available
Typearticle
Languagefr
FieldMedicine
TopicAirway Management and Intubation Techniques
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineAirway managementAirwayCricothyrotomyLaryngoscopyIntensive care medicineAnesthesiologyIntubationTracheal intubationMedical emergencyAnesthesia
DOInot available

Abstract

fetched live from OpenAlex

Background Appropriate planning is crucial to avoid morbidity and mortality when difficulty is anticipated with airway management. Many guidelines developed by national societies have focused on management of difficulty encountered in the unconscious patient; however, little guidance appears in the literature on how best to approach the patient with an anticipated difficult airway. Methods To review this and other subjects, the Canadian Airway Focus Group (CAFG) was re-formed. With representation from anesthesiology, emergency medicine, and critical care, CAFG members were assigned topics for review. As literature reviews were completed, results were presented and discussed during teleconferences and two face-to-face meetings. When appropriate, evidence- or consensus-based recommendations were made, and levels of evidence were assigned. Principal findings Previously published predictors of difficult direct laryngoscopy are widely known. More recent studies report predictors of difficult face mask ventilation, video laryngoscopy, use of a supraglottic device, and cricothyrotomy. All are important facets of a complete airway evaluation and must be considered when difficulty is anticipated with airway management. Many studies now document the increasing patient morbidity that occurs with multiple attempts at tracheal intubation. Therefore, when difficulty is anticipated, tracheal intubation after induction of general anesthesia should be considered only when success with the chosen device(s) can be predicted in a maximum of three attempts. Concomitant predicted difficulty using oxygenation by face mask or supraglottic device ventilation as a fallback makes an awake approach advisable. Contextual issues, such as patient cooperation, availability of additional skilled help, and the clinician’s experience, must also be considered in deciding the appropriate strategy. Conclusions With an appropriate airway evaluation and consideration of relevant contextual issues, a rational decision can be made on whether an awake approach to tracheal intubation will maximize patient safety or if airway management can safely proceed after induction of general anesthesia. With predicted difficulty, close attention should be paid to details of implementing the chosen approach. This should include having a plan in case of the failure of tracheal intubation or patient oxygenation. (Please see Appendix for all authors’ affiliations, attributions, and disclosures).

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)0.014
metaresearch head score (Gemma)0.038
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: Not applicable
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.050
Threshold uncertainty score0.098

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0140.038
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.002
Bibliometrics0.0040.003
Science and technology studies0.0020.002
Scholarly communication0.0030.002
Open science0.0030.003
Research integrity0.0050.006
Insufficient payload (model declined to judge)0.0060.005

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 head0.028
GPT teacher head0.278
Teacher spread0.250 · 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
GenreMethods

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
Published2013
Admission routes1
Has abstractyes

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