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Record W4392353579 · doi:10.1177/17511437241231704

Swallowing during provision of helmet ventilation: Review and provisional multidisciplinary guidance

2024· article· en· W4392353579 on OpenAlexaff
José Vergara, Michael Brenner, Stacey A. Skoretz, Vinciya Pandian, Amy Freeman–Sanderson, Alessandra Dorça, Debra M. Suiter, Martin B. Brodsky

Bibliographic record

VenueJournal of the Intensive Care Society · 2024
Typearticle
Languageen
FieldHealth Professions
TopicDysphagia Assessment and Management
Canadian institutionsSt. Paul's HospitalUniversity of AlbertaUniversity of British Columbia
Fundersnot available
KeywordsSwallowingMedicineIntensive care medicineMultidisciplinary approachIntubationVentilation (architecture)AirwayCritically illAnesthesiaSurgery

Abstract

fetched live from OpenAlex

Use of noninvasive ventilation provided by a helmet increased globally during and after the COVID-19 pandemic. This approach may reduce need for intubation and its associated clinical complications in critically ill patients. Use of helmet interface minimizes virus aerosolization while enabling verbal communication, oral feeding and coughing/expectoration of secretions during its administration. Although improved oral hydration is a recognized benefit of helmet NIV, relatively little is known about the safety and efficiency of swallowing during helmet NIV. Risk of aspiration is a key consideration given the fragile pulmonary status of critically ill patients requiring respiratory support, and therefore the decision to initiate oral intake is best made based on multidisciplinary input. We reviewed the current published evidence on NIV and its effects on upper airway physiology and swallowing function. We then presented a case example demonstrating preservation of swallowing performance with helmet NIV. Last, we offer provisional multidisciplinary guidance for clinical practice, and provide directions for future research.

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: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.525
Threshold uncertainty score0.253

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 integrity0.0000.001
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 head0.027
GPT teacher head0.408
Teacher spread0.381 · 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 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

Citations3
Published2024
Admission routes1
Has abstractyes

Explore more

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