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Record W4366144492 · doi:10.1016/j.bja.2023.02.035

Difficult or impossible facemask ventilation in children with difficult tracheal intubation: a retrospective analysis of the PeDI registry

2023· article· en· W4366144492 on OpenAlexaff
Annery G. García‐Marcinkiewicz, Lisa Lee, Bishr Haydar, John E. Fiadjoe, Clyde Matava, Pete G. Kovatsis, James Peyton, Mary Lyn Stein, Raymond Park, Brad M. Taicher, T. Wesley Templeton, Benjamin Bruins, Paul A. Stricker, Elizabeth Laverriere, Justin L. Lockman, Brian Struyk, Christopher Ward, Akira Nishisaki, Ramesh Kodavatiganti, Rodrigo J. Daly Guris, Luis Sequera‐Ramos, Mark S. Teen, Ayodele Oke, Grace Hsu, Arul M. Lingappan, Chinyere Egbuta, Stephen G Flynn, Tally Goldfarb, Edgar Kiss, Patrick Olomu, Peter Szmuk, Sam Mireles, Andrea Murray, Simon D. Whyte, Ranu Jain, Maria Matuszczak, Agnes I. Hunyady, Adrian Bösenberg, See Wan Tham, Daniel K. Low, Chris Holmes, Stefan Sabato, Nicholas M. Dalesio, Robert S. Greenberg, Angela Lucero, Paul I. Reynolds, Ian Lewis, Charles Schrock, Sydney Nykiel‐Bailey, Elizabeth Starker, Judit Szolnoki, Melissa Brooks-Peterson, Somaletha Bhattacharya, Nicholas E. Burjek, Narasimhan Jagannathan, David R. Lardner, Scott C. Watkins, Christy J. Crockett, John W. Moore, Sara B. Robertson, Madhankumar Sathyamoorthy, Franklin Chiao, Jasmine Patel, Aarti Sharma, Piedad Echeverry Marín, Carolina Pérez‐Pradilla, Neeta Singh, Britta S. von Ungern‐Sternberg, David Sommerfield, Guelay Bilen-Rosas, Hilana Lewkowitz-Shpuntoff, Pilar Castro, N. Ricardo Riveros Perez, Jurgen C. de Graaff, Eduardo Vega, A. González, Paola Ostermann, Kasia Rubin, C. De Lord, Angela Lee, Eugenie S. Heitmiller, Songyos Valairucha, Priti G. Dalal, Thanh Tran, Ihab Ayad, Mohamed Rehman, Allison Fernandez, Lillian Zamora, Niroop Ravula, Sadiq Shaik

Bibliographic record

VenueBritish Journal of Anaesthesia · 2023
Typearticle
Languageen
FieldMedicine
TopicAirway Management and Intubation Techniques
Canadian institutionsHospital for Sick Children
FundersAnesthesia Patient Safety Foundation
KeywordsMedicineVentilation (architecture)IntubationAnesthesiaAirwayIncidence (geometry)Tracheal intubationSupraglottic airwayAirway managementSurgery

Abstract

fetched live from OpenAlex

BACKGROUND: Difficult facemask ventilation is perilous in children whose tracheas are difficult to intubate. We hypothesised that certain physical characteristics and anaesthetic factors are associated with difficult mask ventilation in paediatric patients who also had difficult tracheal intubation. METHODS: We queried a multicentre registry for children who experienced "difficult" or "impossible" facemask ventilation. Patient and case factors known before mask ventilation attempt were included for consideration in this regularised multivariable regression analysis. Incidence of complications, and frequency and efficacy of rescue placement of a supraglottic airway device were also tabulated. Changes in quality of mask ventilation after injection of a neuromuscular blocking agent were assessed. RESULTS: The incidence of difficult mask ventilation was 9% (483 of 5453 patients). Infants and patients having increased weight, being less than 5th percentile in weight for age, or having Treacher-Collins syndrome, glossoptosis, or limited mouth opening were more likely to have difficult mask ventilation. Anaesthetic induction using facemask and opioids was associated with decreased risk of difficult mask ventilation. The incidence of complications was significantly higher in patients with "difficult" mask ventilation than in patients without. Rescue placement of a supraglottic airway improved ventilation in 71% (96 of 135) of cases. Administration of neuromuscular blocking agents was more frequently associated with improvement or no change in quality of ventilation than with worsening. CONCLUSIONS: Certain abnormalities on physical examination should increase suspicion of possible difficult facemask ventilation. Rescue use of a supraglottic airway device in children with difficult or impossible mask ventilation should be strongly considered.

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)0.000
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 score0.044
Threshold uncertainty score0.294

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.003
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 head0.010
GPT teacher head0.256
Teacher spread0.246 · 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

Citations21
Published2023
Admission routes1
Has abstractyes

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