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Record W2009730715 · doi:10.1097/ana.0b013e318060d270

Management of the Airway in Patients Undergoing Cervical Spine Surgery

2007· article· en· W2009730715 on OpenAlexaff
Pirjo Manninen, Karolinah Lukitto, Lashmi Venkatraghavan, Hossam El Beheiry

Bibliographic record

VenueJournal of Neurosurgical Anesthesiology · 2007
Typearticle
Languageen
FieldMedicine
TopicSpinal Fractures and Fixation Techniques
Canadian institutionsToronto Western HospitalUniversity of TorontoUniversity Health Network
Fundersnot available
KeywordsMedicineCervical spineAirway managementAirwaySurgery

Abstract

fetched live from OpenAlex

The perioperative management of the airway in patients with cervical spine disease requires careful consideration. In an observational prospective cohort study, we assessed the preoperative factors that may have influenced the anesthesiologists' choice for the technique of intubation and the incidence of postoperative airway complications. We recorded information from 327 patients: mean (+/-SD) age 51+/-15 year, 138 females and 189 males, for anterior surgical approach (n=195) and posterior (n=132). The technique of intubation used was awake fiberoptic bronchoscopy (FOB) in 39% (n=128), asleep FOB 32% (n=103), asleep laryngoscopy 22% (n=72), and other asleep 7% (n=24). Awake FOB was predominately chosen for intubating patients with myelopathy (45%), unstable/fractured spine (73%), and spinal stenosis (55%) but patients with radiculopathy had more asleep FOB (49%) (P<0.001). There was no association between method of intubation and postoperative airway complications. Acute postoperative airway obstruction occurred in 4 (1.2%) patients requiring reintubation. The technique of management of the airway for cervical spine surgery varied considerably among the anesthesiologists, although the choice was not associated with postoperative airway complications.

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 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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.012
Threshold uncertainty score0.195

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 head0.015
GPT teacher head0.269
Teacher spread0.254 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
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

Citations45
Published2007
Admission routes1
Has abstractyes

Explore more

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