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Record W4391529664 · doi:10.1136/bmjpo-2023-002262

Developing a core outcome set for the health outcomes for children and adults with congenital oesophageal atresia and/or tracheo-oesophageal fistula: OCELOT task group study protocol

2024· article· en· W4391529664 on OpenAlexaff
Jonathan Ducey, Nick Lansdale, Sarah L. Gorst, Lucy Bray, Nadine M. Teunissen, Paul Cullis, Julia Faulkner, Victoria Gray, Lucía Gutierrez Gammino, Graham Slater, Laura Baird, Alex Adams, Julia Brendel, Adam J. Donne, Eniola Folaranmi, Laura Hopwood, Anna‐May Long, Paul D. Losty, Dan Benscoter, Corné de Vos, Sebastian K. King, Usha Krishnan, Shireen Anne Nah, Lin Yin Ong, Mike Rutter, Warwick J. Teague, Aaron M. Zorn, Nigel Hall, Rebecca Thursfield

Bibliographic record

VenueBMJ Paediatrics Open · 2024
Typearticle
Languageen
FieldSocial Sciences
TopicDelphi Technique in Research
Canadian institutionsChildren's Hospital of Eastern OntarioUniversity of Ottawa
FundersEunice Kennedy Shriver National Institute of Child Health and Human DevelopmentAlder Hey Children's NHS Foundation Trust
KeywordsDelphi methodMedicineFocus groupStakeholderFamily medicineOutcome (game theory)Likert scalePediatricsPsychologyDevelopmental psychologyPublic relations

Abstract

fetched live from OpenAlex

INTRODUCTION: Heterogeneity in reported outcomes of infants with oesophageal atresia (OA) with or without tracheo-oesophageal fistula (TOF) prevents effective data pooling. Core outcome sets (COS) have been developed for many conditions to standardise outcome reporting, facilitate meta-analysis and improve the relevance of research for patients and families. Our aim is to develop an internationally-agreed, comprehensive COS for OA-TOF, relevant from birth through to transition and adulthood. METHODS AND ANALYSIS: A long list of outcomes will be generated using (1) a systematic review of existing studies on OA-TOF and (2) qualitative research with children (patients), adults (patients) and families involving focus groups, semistructured interviews and self-reported outcome activity packs. A two-phase Delphi survey will then be completed by four key stakeholder groups: (1) patients (paediatric and adult); (2) families; (3) healthcare professionals; and (4) researchers. Phase I will include stakeholders individually rating the importance and relevance of each long-listed outcome using a 9-point Likert scale, with the option to suggest additional outcomes not already included. During phase II, stakeholders will review summarised results from phase I relative to their own initial score and then will be asked to rescore the outcome based on this information. Responses from phase II will be summarised using descriptive statistics and a predefined definition of consensus for inclusion or exclusion of outcomes. Following the Delphi process, stakeholder experts will be invited to review data at a consensus meeting and agree on a COS for OA-TOF. ETHICS AND DISSEMINATION: Ethical approval was sought through the Health Research Authority via the Integrated Research Application System, registration no. 297026. However, approval was deemed not to be required, so study sponsorship and oversight were provided by Alder Hey Children's NHS Foundation Trust. The study has been prospectively registered with the COMET Initiative. The study will be published in an open access forum.

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)0.134
metaresearch head score (Gemma)0.108
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: Methods · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Protocol · Consensus signal: Protocol
Teacher disagreement score0.866
Threshold uncertainty score0.706

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.1340.108
Meta-epidemiology (narrow)0.0030.003
Meta-epidemiology (broad)0.0050.007
Bibliometrics0.0050.004
Science and technology studies0.0040.003
Scholarly communication0.0040.004
Open science0.0040.006
Research integrity0.0050.005
Insufficient payload (model declined to judge)0.0390.013

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 head0.212
GPT teacher head0.520
Teacher spread0.308 · 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.

Study designNot applicable
DomainMethods
GenreProtocol

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

Citations3
Published2024
Admission routes1
Has abstractyes

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