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Record W2789052237 · doi:10.4103/ija.ija_724_17

Jet insufflation options for the cannot intubate–cannot ventilate situation

2018· article· en· W2789052237 on OpenAlexaff
HilaryP Grocott

Bibliographic record

VenueIndian Journal of Anaesthesia · 2018
Typearticle
Languageen
FieldMedicine
TopicAirway Management and Intubation Techniques
Canadian institutionsUniversity of Manitoba
Fundersnot available
KeywordsMedicineIngenuityInsufflationJet (fluid)Jet ventilationSurgeryAirwayEngineering

Abstract

fetched live from OpenAlex

Sir, The recent letter by Kulkarni et al.[1] outlining the jet insufflation jugaad that was derived from a Jackson-Rees circuit, a 4 mm ID endotracheal tube connector, and Luer-lock venous extension tubing, offers a potentially viable alternative to commercially available jet ventilation devices such as the Enk Oxygen Flow Modulator (Cook Inc., Bloomington, IN, USA), the Rapid O2™ Insufflator (Meditech Systems Ltd, Shaftesbury, UK) and the Manujet III™ (VBM, Medizintechnik GmBH, Sula and Neckar, Germany) for use in cannot intubate–cannot ventilate situations in paediatric patients. Indeed, the authors' improvised insufflator solution that offers both jet inspiration and active expiration exploits the Hagen–Poiseuille law in a very similar fashion to another relatively new commercially available device, the Ventrain® (Ventinova Medical B. V., Eindhoven, Netherlands).[2] This device has similarly been shown to allow both inspiration and active expiration when used with both short and long small-bore airway cannulae.[3] The Ventrain device is a portable, easy to use, light weight, stand-alone high-pressure injector that uses up to 15 L/min in oxygen flow. Importantly, it has also withstood the evaluative rigor of medical equipment regulatory agencies making it potentially safer than the improvised device suggested by Kulkarni et al. That said, I congratulate these authors on their improvisation and ingenuity, as they appear to have independently validated and partially replicated the work that had been accomplished with the Ventrain. Financial support and sponsorship Nil. Conflicts of interest There are no conflicts of interest.

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)0.002
metaresearch head score (Gemma)0.005
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: Empirical · Consensus signal: none
Teacher disagreement score0.005
Threshold uncertainty score0.013

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.000
Science and technology studies0.0010.002
Scholarly communication0.0020.003
Open science0.0010.001
Research integrity0.0050.008
Insufficient payload (model declined to judge)0.0040.002

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 head0.298
Teacher spread0.275 · 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
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

Citations0
Published2018
Admission routes1
Has abstractyes

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