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Aerosol Box Use in Reducing Health Care Worker Contamination During Airway Procedures (AIRWAY Study)

2023· article· en· W4365135216 on OpenAlexafffund
Adam Cheng, Jonathan Pirie, Yiqun Lin, Carl Lo, Jennifer Davidson, Todd P. Chang, Clyde Matava, Michael Buyck, Dana Singer Harel, Natasha Collia, Guylaine Neveu, Stéphanie Pellerin, Mohsen Madadi, Keya Manshadi, Brandi Wan, Arielle Lévy, Donovan Duncan, Jabeen Fayyaz, Mireille Garhib, Theophilus Tackey

Bibliographic record

VenueJAMA Network Open · 2023
Typearticle
Languageen
FieldMedicine
TopicInfection Control and Ventilation
Canadian institutionsUniversité de MontréalCentre Hospitalier Universitaire Sainte-JustineAlberta Children's HospitalUniversity of TorontoSickKids FoundationHospital for Sick ChildrenUniversity of Calgary
FundersCanadian Institutes of Health Research
KeywordsAirwayContaminationAerosolMedicineEnvironmental scienceEnvironmental healthIntensive care medicineAnesthesiaGeographyMeteorologyBiology

Abstract

fetched live from OpenAlex

Importance: The aerosol box has been used during the management of patients with COVID-19 to reduce health care practitioner (HCP) exposure during aerosol-generating medical procedures (AGMPs). Little is known about the effect of aerosol box use on HCP contamination and AGMP procedure time. Objective: To investigate whether use of an aerosol box during AGMPs reduces HCP contamination or influences the time to successful completion and first-pass success rate for endotracheal intubation (ETI) and laryngeal mask airway (LMA) insertion. Design, Setting, and Participants: This multicenter, simulation-based, randomized clinical trial was conducted from May to December 2021 at tertiary care pediatric hospitals. Participant teams performed 3 simulated patient scenarios: bag-valve-mask ventilation, ETI, and LMA insertion. During the scenarios, aerosols were generated using Glo Germ. Teams of 2 HCPs were randomly assigned to control (no aerosol box) or intervention groups (aerosol box). Statistical analysis was performed from July 2022 to February 2023. Interventions: The aerosol box (or SplashGuard CG) is a transparent, plastic barrier covering the patient's head and shoulders with access ports allowing HCPs to manage the airway. Main Outcomes and Measures: The primary outcome was surface area of contamination (AOC) on participants. Secondary outcomes were time to successful completion and first-pass success rates for ETI and LMA insertion. Results: A total of 64 teams (128 participants) were enrolled, with data from 61 teams (122 participants) analyzed. Among the 122 participants analyzed, 79 (64.8%) were female and 85 (69.7%) were physicians. Use of an aerosol box was associated with a 77.5% overall decreased AOC to the torso (95% CI, -86.3% to -62.9%; P < .001) and a 60.7% overall decreased AOC to the facial area (95% CI, -75.2% to -37.8%; P < .001) in airway HCPs. There was no statistically significant difference in surface contamination after doffing personal protective equipment between groups. Time to completing ETI was longer in the aerosol box group compared with the control group (mean difference: 10.2 seconds; 95% CI, 0.2 to 20.2 seconds; P = .04), but there was no difference between groups for LMA insertion (mean difference: 2.4 seconds; 95% CI, -8.7 to 13.5 seconds; P = .67). Conclusions and Relevance: In this randomized clinical trial of aerosol box use in AGMPs, use of an aerosol box reduced contamination deposition on HCPs' torso and face predoffing; the use of an aerosol box delayed time to successful intubation. These results suggest that the incremental benefits of reduced surface contamination from aerosol box use should be weighed against delayed time to complete intubation, which may negatively affect patient outcome. Trial Registration: ClinicalTrials.gov Identifier: NCT04880668.

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.029
Threshold uncertainty score0.612

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
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 head0.026
GPT teacher head0.318
Teacher spread0.292 · 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

Citations7
Published2023
Admission routes2
Has abstractyes

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