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Record W4403175424 · doi:10.1055/a-2427-3893

Defining standards for fluoroscopy in gastrointestinal endoscopy using Delphi methodology

2024· article· en· W4403175424 on OpenAlex
Kareem Khalaf, Katarzyna M. Pawlak, Douglas G. Adler, Asma Alkandari, Alan Barkun, Todd H. Baron, Robert Bechara, Tyler M. Berzin, Cecilia Binda, Ming‐Yan Cai, Silvia Carrara, Yen‐I Chen, Eduardo Guimarães Hourneaux de Moura, Nauzer Forbes, Alessandro Fugazza, Cesare Hassan, Paul James, Michel Kahaleh, Harry Martin, Roberta Maselli, Gary R. May, Jeffrey D. Mosko, Ganiyat K. Oyeleke, Bret T. Petersen, Alessandro Repici, Payal Saxena, Amrita Sethi, Reem Z. Sharaiha, Marco Spadaccini, Raymond S. Tang, Christopher Teshima, Mariano Villarroel, Jeanin E. van Hooft, Rogier P. Voermans, Daniel von Renteln, Catharine M. Walsh, Tricia Aberin, Dawn Banavage, Jowell Akina Chen, Heather Drake, Melanie Im, Chooi Peng Low, Alexandra Myszko, Krista Navarro, Jessica Redman, Faina Weinstein, Sunil Gupta, Ahmed Mokhtar, Caleb Na, Daniel Tham, Yusuke Fujiyoshi, Tony He, Sharan B. Malipatil, Reza Gholami, Nikko Gimpaya, Arjun Kundra, Samir C. Grover, Natalia Causada Calo

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueEndoscopy International Open · 2024
Typearticle
Languageen
FieldMedicine
TopicEsophageal and GI Pathology
Canadian institutionsThe Wilson CentreSickKids FoundationHospital for Sick ChildrenUniversity of OttawaMcGill University Health CentreMcGill UniversityKingston Health Sciences CentreCentre Hospitalier de l’Université de MontréalUniversity of CalgaryHotel Dieu HospitalMontreal General HospitalOttawa HospitalUniversity Health NetworkUniversity of TorontoSt. Michael's Hospital
FundersAboca S.p.A. Società AgricolaCook MedicalBoston Scientific CorporationSanofiAstraZeneca
KeywordsFluoroscopyMedicineEndoscopyDelphi methodMedical physicsDelphiRadiologyComputer scienceArtificial intelligence

Abstract

fetched live from OpenAlex

Abstract Background and study aims Use of fluoroscopy in gastrointestinal endoscopy is an essential aid in advanced endoscopic interventions. However, it also raises concerns about radiation exposure. This study aimed to develop consensus-based statements for safe and effective use of fluoroscopy in gastrointestinal endoscopy, prioritizing the safety and well-being of healthcare workers and patients. Methods A modified Delphi approach was employed to achieve consensus over three rounds of surveys. Proposed statements were generated in Round 1. In the second round, panelists rated potential statements on a 5-point scale, with consensus defined as ≥80% agreement. Statements were subsequently prioritized in Round 3, using a 1 (lowest priority) to 10 (highest priority) scale. Results Forty-six experts participated, consisting of 34 therapeutic endoscopists and 12 endoscopy nurses from six continents, with an overall 45.6% female representation (n = 21). Forty-three item statements were generated in the first round. Of these, 31 statements achieved consensus after the second round. These statements were categorized into General Considerations (n = 6), Education (n = 10), Pregnancy (n = 4), Family Planning (n = 2), Patient Safety (n = 4), and Staff Safety (n = 5). In the third round, accepted statements received mean priority scores ranging from 7.28 to 9.36, with 87.2% of statements rated as very high priority (mean score ≥ 9). Conclusions This study presents consensus-based statements for safe and effective use of fluoroscopy in gastrointestinal endoscopy, addressing the well-being of healthcare workers and patients. These consensus-based statements aim to mitigate risks associated with radiation exposure while maintaining benefits of fluoroscopy, ultimately promoting a culture of safety in healthcare settings.

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.

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)0.002
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Methods · Consensus signal: Methods
Teacher disagreement score0.205
Threshold uncertainty score0.901

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.102
GPT teacher head0.464
Teacher spread0.362 · 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