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Record W2790187504 · doi:10.1177/2292550317716123

Ivy Loop Wiring: A Useful Form of Endotracheal Tube Stabilization in Burn Patients

2017· article· en· W2790187504 on OpenAlexaff
Matthew W.T. Curran, Edward E. Tredget

Bibliographic record

VenuePlastic Surgery · 2017
Typearticle
Languageen
FieldMedicine
TopicBurn Injury Management and Outcomes
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsEndotracheal tubeLoop (graph theory)Tube (container)MedicineMedical emergencyAnesthesiaEngineeringMechanical engineeringMathematicsIntubation

Abstract

fetched live from OpenAlex

The stabilization of endotracheal tubes in the burn population presents many problems. Access to the face for dressings, debridements, and the use of topical antimicrobials prevent adequate stabilization of the endotracheal tube with commonly used methods. Conventional methods have an increased risk of shifting, which can lead to injury to the friable burned tissue or unplanned extubation. To prevent these complications, alternative methods using the dentition to stabilize the endotracheal tube have been described. Here, we present our technique of using Ivy loops to secure the endotracheal tube. It is a simple method with low complications that provides a strong stabilization of the tube while giving access to the face.

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)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Case report · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.000
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.001

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 head0.043
GPT teacher head0.280
Teacher spread0.237 · 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 designCase report
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

Citations2
Published2017
Admission routes1
Has abstractyes

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