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Measurement of forces applied during Macintosh direct laryngoscopy compared with GlideScope <sup>®</sup> videolaryngoscopy*

2012· article· en· W1483115676 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 institutionsUniversity of TorontoToronto General Hospital
Fundersnot available
KeywordsLaryngoscopyMedicineIntubationAnesthesiaTracheal intubationLaryngoscopesTongue

Abstract

fetched live from OpenAlex

Laryngoscopy can induce stress responses that may be harmful in susceptible patients. We directly measured the force applied to the base of the tongue as a surrogate for the stress response. Force measurements were obtained using three FlexiForce Sensors(®) (Tekscan Inc, Boston, MA, USA) attached along the concave surface of each laryngoscope blade. Twenty-four 24 adult patients of ASA physical status 1-2 were studied. After induction of anaesthesia and neuromuscular blockade, laryngoscopy and tracheal intubation was performed using either a Macintosh or a GlideScope(®) (Verathon, Bothell, WA, USA) laryngoscope. Complete data were available for 23 patients. Compared with the Macintosh, we observed lower median (IQR [range]) peak force (9 (5-13 [3-25]) N vs 20 (14-28 [4-41]) N; p = 0.0001), average force (5 (3-7 [2-19]) N vs 11 (6-16 [1-24]) N; p = 0.0003) and impulse force (98 (42-151 [26-444]) Ns vs 150 (93-207 [17-509]) Ns; p = 0.017) with the GlideScope. Our study shows that the peak lifting force on the base of the tongue during laryngoscopy is less with the GlideScope videolaryngoscope compared with the Macintosh laryngoscope.

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)0.001
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.742
Threshold uncertainty score0.864

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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 head0.017
GPT teacher head0.245
Teacher spread0.227 · 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