MétaCan
Menu
Back to cohort
Record W3015333522 · doi:10.1213/ane.0000000000004872

Pediatric Airway Management in COVID-19 Patients: Consensus Guidelines From the Society for Pediatric Anesthesia’s Pediatric Difficult Intubation Collaborative and the Canadian Pediatric Anesthesia Society

2020· review· en· W3015333522 on OpenAlexafffundabout
Clyde Matava, Pete G. Kovatsis, Jennifer K. Lee, Pilar Castro, Simon Denning, Julie Yu, Raymond Park, Justin L. Lockman, Britta S. von Ungern‐Sternberg, Stefano Sabato, Lisa Lee, Ihab Ayad, Sam Mireles, David R. Lardner, Simon D. Whyte, Judit Szolnoki, Narasimhan Jagannathan, Nicole C.P. Thompson, Mary Lyn Stein, Nicholas M. Dalesio, Robert S. Greenberg, John McCloskey, James Peyton, Faye M. Evans, Bishr Haydar, Paul I. Reynolds, Franklin Chiao, Brad M. Taicher, T. Wesley Templeton, Tarun Bhalla, Vidya T. Raman, Annery G. García‐Marcinkiewicz, Jorge A. Gálvez, Jonathan M. Tan, Mohamed Rehman, Christy J. Crockett, Patrick Olomu, Peter Szmuk, Chris D. Glover, Maria Matuszczak, Ignacio Galvez, Agnes I. Hunyady, David M. Polaner, Cheryl K. Gooden, Grace Hsu, Harshad Gumaney, Caroline Pérez-Pradilla, Edgar Kiss, Mary C. Theroux, Jennifer Lau, Saeedah Asaf, Pablo Ingelmo, Thomas Engelhardt, Mónica Hervías, Eric Greenwood, Luv Javia, Nicola Disma, Myron Yaster, John E. Fiadjoe

Bibliographic record

VenueAnesthesia & Analgesia · 2020
Typereview
Languageen
FieldMedicine
TopicInfection Control and Ventilation
Canadian institutionsMcGill UniversityMontreal Children's HospitalBC Children's HospitalAlberta Children's HospitalHospital for Sick Children
FundersNational Center for Advancing Translational SciencesNational Institute of Neurological Disorders and StrokeHospital for Sick Children
KeywordsMedicineIntubationIntensive care medicinePandemicAirway managementTracheal intubationAirwayAsymptomaticHealth careNebulizerAnesthesiaCoronavirus disease 2019 (COVID-19)DiseaseSurgeryInfectious disease (medical specialty)

Abstract

fetched live from OpenAlex

The severe acute respiratory syndrome coronavirus 2 (coronavirus disease 2019 [COVID-19]) pandemic has challenged medical systems and clinicians globally to unforeseen levels. Rapid spread of COVID-19 has forced clinicians to care for patients with a highly contagious disease without evidence-based guidelines. Using a virtual modified nominal group technique, the Pediatric Difficult Intubation Collaborative (PeDI-C), which currently includes 35 hospitals from 6 countries, generated consensus guidelines on airway management in pediatric anesthesia based on expert opinion and early data about the disease. PeDI-C identified overarching goals during care, including minimizing aerosolized respiratory secretions, minimizing the number of clinicians in contact with a patient, and recognizing that undiagnosed asymptomatic patients may shed the virus and infect health care workers. Recommendations include administering anxiolytic medications, intravenous anesthetic inductions, tracheal intubation using video laryngoscopes and cuffed tracheal tubes, use of in-line suction catheters, and modifying workflow to recover patients from anesthesia in the operating room. Importantly, PeDI-C recommends that anesthesiologists consider using appropriate personal protective equipment when performing aerosol-generating medical procedures in asymptomatic children, in addition to known or suspected children with COVID-19. Airway procedures should be done in negative pressure rooms when available. Adequate time should be allowed for operating room cleaning and air filtration between surgical cases. Research using rigorous study designs is urgently needed to inform safe practices during the COVID-19 pandemic. Until further information is available, PeDI-C advises that clinicians consider these guidelines to enhance the safety of health care workers during airway management when performing aerosol-generating medical procedures. These guidelines have been endorsed by the Society for Pediatric Anesthesia and the Canadian Pediatric Anesthesia Society.

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)0.020
metaresearch head score (Gemma)0.044
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: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.020
Threshold uncertainty score0.105

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0200.044
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0030.005
Bibliometrics0.0060.004
Science and technology studies0.0020.001
Scholarly communication0.0030.003
Open science0.0060.004
Research integrity0.0060.007
Insufficient payload (model declined to judge)0.0040.003

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 head0.031
GPT teacher head0.309
Teacher spread0.278 · 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
GenreReview

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

Citations149
Published2020
Admission routes3
Has abstractyes

Explore more

Same venueAnesthesia & AnalgesiaSame topicInfection Control and VentilationFrench-language works237,207