MétaCan
Menu
Back to cohort
Record W3134262970 · doi:10.1093/jcag/gwab002.075

A77 A REUSABLE POLYCARBONATE BOX TO DECREASE DROPLET CONTAMINATION DURING UPPER ENDOSCOPY: A SIMULATION-BASED STUDY FOR THE COVID-19 PANDEMIC

2021· article· en· W3134262970 on OpenAlexaff
Nikko Gimpaya, Rishad Khan, Zane Gallinger, Michael A. Scaffidi, Abdulrhman Khaled Al Abdulqader, Maria Zahid Ahmed, Reza Gholami, Antonio Ramkissoon, Philip James, J. Mosko, Nadia Griller, Rishi Bansal, Samir C. Grover

Bibliographic record

VenueJournal of the Canadian Association of Gastroenterology · 2021
Typearticle
Languageen
FieldMedicine
TopicInfection Control and Ventilation
Canadian institutionsSunnybrook Health Science CentreHealth Sciences CentreUniversity Health NetworkUniversity of TorontoSt. Michael's Hospital
Fundersnot available
KeywordsSupine positionContaminationEndoscopyPersonal protective equipmentMedicineSurgeryCoronavirus disease 2019 (COVID-19)Internal medicineDisease

Abstract

fetched live from OpenAlex

Abstract Background Upper gastrointestinal (GI) endoscopic procedures are aerosol-generating, increasing the risk of healthcare workers (HCW) contracting Coronavirus disease 2019 (COVID-19). Aims To present a polycarbonate box (EndoBox) designed for use in upper GI endoscopy and evaluate its impact on the contamination of endoscopy staff during simulated procedures. Methods Simulated gastroscopies were performed using an upper body simulator placed in left lateral decubitus (LLD) and supine positions. The endoscopist and assistant wore personal protective equipment. Droplet exposure was measured using fluorescent abiotic surrogate particles. Two blinded observers independently viewed images from each scenario to qualitatively evaluate contamination levels. The primary outcome was the level of HCW contamination by droplets generated from a simulated cough with and without the EndoBox on the upper body simulator. The endoscopist’s ergonomic behaviour was also assessed using the Rapid Upper Limb Assessment (RULA) tool. Results Without the EndoBox, there was a higher level of contamination on the endoscopist when the upper body simulator is in the LLD position. A higher level of contamination was observed on the assistant when the simulator is in supine position. With the EndoBox, the contamination levels on the endoscopy staff were lower in both LLD and supine scenarios. The endoscopist’s ergonomics were rated 2 to 3 on the RULA tool when using the EndoBox. Conclusions The EndoBox reduces macroscopic droplet contamination during simulated gastroscopy. The endoscopist’s risk of musculoskeletal injury remained in the low risk categories as assessed by the RULA tool. Another advantage of the EndoBox design is the arch extending from the bottom that allows for removal of the box without withdrawing the endoscope. This enables rapid access to the patient’s airway if they experience respiratory distress. This study was limited by an inability to assess microscopic contamination and contamination at the level of the port or buttons when suction is applied. Within these limitations, the EndoBox may be a useful adjunct to traditional personal protective equipment. Funding Agencies SMHA AFP COVID-Related Innovation Funds

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)0.002
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.003
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
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 head0.018
GPT teacher head0.293
Teacher spread0.275 · 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 designSimulation or modeling
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

Citations0
Published2021
Admission routes1
Has abstractyes

Explore more

Same venueJournal of the Canadian Association of GastroenterologySame topicInfection Control and VentilationFrench-language works237,207