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A Retrospective Chart Review and Infant Feeding Survey in the Irish Phenylketonuria (PKU) Population (2016–2020)

2023· preprint· en· W4382362686 on OpenAlexfundno aff
Jane Rice, Jenny McNulty, Meabh O’Shea, Teresa Gudex, Ina Knerr

Bibliographic record

VenuePreprints.org · 2023
Typepreprint
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicMetabolism and Genetic Disorders
Canadian institutionsnot available
FundersChildren's Health Foundation
KeywordsBreastfeedingMedicinePediatricsPopulationFamily medicineEnvironmental health

Abstract

fetched live from OpenAlex

Phenylketonuria (PKU) is an inherited disorder of protein metabolism. It is generally treated using dietary management with limited intake of phenylalanine (Phe). Partial breastfeeding (BF) is encouraged among mothers of infants with PKU, together with a Phe-free mixture of synthetic amino acids. We aimed to describe our current BF rates and complementary feeding practices, as well as examining parental experiences of infant feeding. The aim was to better understand the challenges faced by families so improvements can be made to clinical care. A chart review was carried out on 39 PKU patients, examining the BF rate and duration, use of second stage synthetic protein (SP) and average complementary feeding age. A parental questionnaire on complementary feeding and BF experience was designed. 26% of babies were partially breastfed at three months. 70% of mums would like to have breastfed for longer and cited PKU as a reason for stop-ping. 52% parents reported challenges during the complementary feeding process including food refusal, protein calculation and anxiety around maintaining good Phe levels. Suggestions to improve BF continuation and duration include active promotion of the benefits and suitability, access to lactation consultant and peer support. The delay in introducing a second stage SP may contribute to long-term bottle use for SP. Improved patient education, written resources and sup-port is necessary to improve food choices and long term acceptance of SP.

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)0.003
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.039
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.001
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 head0.089
GPT teacher head0.349
Teacher spread0.260 · 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.

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

Citations3
Published2023
Admission routes1
Has abstractyes

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Same venuePreprints.orgSame topicMetabolism and Genetic DisordersFrench-language works237,207