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Record W2910418368 · doi:10.1186/s13023-018-0950-z

Development of national consensus statements on food labelling interpretation and protein allocation in a low phenylalanine diet for PKU

2019· article· en· W2910418368 on OpenAlexfundno aff
Sharon Evans, Suzanne Ford, Sarah Adam, Sandra Adams, Jane Ash, Catherine Ashmore, G. Caine, Rachel Carruthers, Sarah Cawtherley, S. Chahal, Anne Clark, Barbara Cochrane, Anne Daly, Karen Dines, Marjorie Dixon, Carolyn Dunlop, Charlotte Ellerton, Moira French, Lisa Gaff, C. Gingell, Diane Green, Joanna Gribben, Anne Grimsley, Paula Hallam, Una Hendroff, Melanie Hill, Rachel Hoban, Sarah Howe, Inderdip Hunjan, Kit Kaalund, Eimear Kelleher, Farzana Khan, Steve Kitchen, Karen A. Lang, Sharan Lowry, Jo Males, Georgina Martin, Nicola McStravick, Camille Newby, Claire Nicol, Rachel Pereira, Louise Robertson, Kathleen Ross, Emma Simpson, Kath Singleton, Rachel Skeath, Jacqueline Stafford, Allyson Terry, Ruth Thom, Alison Tooke, Karen vanWyk, F. White, Lucy White, Anita MacDonald

Bibliographic record

VenueOrphanet Journal of Rare Diseases · 2019
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicMetabolism and Genetic Disorders
Canadian institutionsnot available
FundersHospital for Sick ChildrenUniversity Hospitals Birmingham NHS Foundation TrustCambridge University HospitalsNottingham University Hospitals NHS TrustUniversity of NottinghamUniversity of Cambridge
KeywordsMedicineFacilitatorStatement (logic)Family medicineInterpretation (philosophy)Delphi methodPhenylketonuriasPediatricsPsychologyPhenylalanineSocial psychologyPolitical science

Abstract

fetched live from OpenAlex

BACKGROUND: In the treatment of phenylketonuria (PKU), there was disparity between UK dietitians regarding interpretation of how different foods should be allocated in a low phenylalanine diet (allowed without measurement, not allowed, or allowed as part of phenylalanine exchanges). This led to variable advice being given to patients. METHODOLOGY: In 2015, British Inherited Metabolic Disease Group (BIMDG) dietitians (n = 70) were sent a multiple-choice questionnaire on the interpretation of protein from food-labels and the allocation of different foods. Based on majority responses, 16 statements were developed. Over 18-months, using Delphi methodology, these statements were systematically reviewed and refined with a facilitator recording discussion until a clear majority was attained for each statement. In Phase 2 and 3 a further 7 statements were added. RESULTS: The statements incorporated controversial dietary topics including: a practical 'scale' for guiding calculation of protein from food-labels; a general definition for exchange-free foods; and guidance for specific foods. Responses were divided into paediatric and adult groups. Initially, there was majority consensus (≥86%) by paediatric dietitians (n = 29) for 14 of 16 statements; a further 2 structured discussions were required for 2 statements, with a final majority consensus of 72% (n = 26/36) and 64% (n = 16/25). In adult practice, 75% of dietitians agreed with all initial statements for adult patients and 40% advocated separate maternal-PKU guidelines. In Phase 2, 5 of 6 statements were agreed by ≥76% of respondents with one statement requiring a further round of discussion resulting in 2 agreed statements with a consensus of ≥71% by dietitians in both paediatric and adult practice. In Phase 3 one statement was added to elaborate further on an initial statement, and this received 94% acceptance by respondents. Statements were endorsed by the UK National Society for PKU. CONCLUSIONS: The BIMDG dietitians group have developed consensus dietetic statements that aim to harmonise dietary advice given to patients with PKU across the UK, but monitoring of statement adherence by health professionals and patients is required.

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)0.000
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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.087
Threshold uncertainty score0.254

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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)0.0000.000

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 head0.011
GPT teacher head0.275
Teacher spread0.264 · 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 designBench or experimental
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

Citations17
Published2019
Admission routes1
Has abstractyes

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