MétaCan
Menu
Back to cohort
Record W3176138926 · doi:10.3390/children8070553

In Newborn Infants a New Intubation Method May Reduce the Number of Intubation Attempts: A Randomized Pilot Study

2021· article· en· W3176138926 on OpenAlexaff
Marlies Bruckner, Nicholas Mark Morris, Gerhard Pichler, Christina H. Wolfsberger, Stefan Heschl, Lukas P. Mileder, Bernhard Schwaberger, Georg M. Schmölzer, Berndt Urlesberger

Bibliographic record

VenueChildren · 2021
Typearticle
Languageen
FieldMedicine
TopicAirway Management and Intubation Techniques
Canadian institutionsRoyal Alexandra HospitalUniversity of Alberta
Fundersnot available
KeywordsIntubationMedicineAnesthesiaInterquartile rangeNasotracheal intubationBradycardiaEndotracheal tubeEndotracheal intubationSurgeryHeart rateInternal medicine

Abstract

fetched live from OpenAlex

Severe desaturation or bradycardia often occur during neonatal endotracheal intubation. Using continuous gas flow through the endotracheal tube might reduce the incidence of these events. We hypothesized that continuous gas flow through the endotracheal tube during nasotracheal intubation compared to standard nasotracheal intubation will reduce the number of intubation attempts in newborn infants. In a randomized controlled pilot study, neonates were either intubated with continuous gas flow through the endotracheal tube during intubation (intervention group) or no gas flow during intubation (control group). Recruitment was stopped early due to financial and organizational issues. A total of 16 infants and 39 intubation attempts were analyzed. The median (interquartile range) number of intubation attempts and number of abandoned intubations due to desaturation and/or bradycardia were 1 (1–2) and 4 (2–5), (p = 0.056) and n = 3 versus n = 20, (p = 0.060) in the intervention group and control group, respectively. Continuous gas flow through the endotracheal tube during intubation seems to be favorable and there are no major unexpected adverse consequences of attempting this methodology.

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.524
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.026
GPT teacher head0.362
Teacher spread0.335 · 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.

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

Citations7
Published2021
Admission routes1
Has abstractyes

Explore more

Same venueChildrenSame topicAirway Management and Intubation TechniquesFrench-language works237,207