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Record W2171095905 · doi:10.1016/j.ymgme.2012.04.004

Recommendations for the use of sapropterin in phenylketonuria

2012· article· en· W2171095905 on OpenAlexaff
Amy Cunningham, Heather Bausell, Mary M. Brown, Maggie Chapman, Kari DeFouw, Sharon L. Ernst, Julie McClure, Helen McCune, Donna O'Steen, Amy Pender, J Skrabal, Ann Wessel, Elaina Jurecki, Renée Shediac, Suyash Prasad, Jane Gillis, Stephen Cederbaum

Bibliographic record

VenueMolecular Genetics and Metabolism · 2012
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicMetabolism and Genetic Disorders
Canadian institutionsMcMaster Children's HospitalDalhousie UniversityIzaak Walton Killam Health Centre
FundersHealth Resources and Services AdministrationUniversity of Utah
KeywordsPhenylalanine hydroxylaseMedicineTetrahydrobiopterinNeurocognitiveDietary managementMetabolic control analysisDietary therapyHyperphenylalaninemiaIntensive care medicinePediatricsPsychiatryPhenylalanineInternal medicineCognition

Abstract

fetched live from OpenAlex

Phenylketonuria (PKU) is an inherited disorder of phenylalanine (Phe) metabolism. Until recently, the only treatment for PKU was a Phe-restricted diet. Increasing evidence of suboptimal outcomes in diet-treated individuals, inconsistent PKU management practices, and the recent availability of tetrahydrobiopterin (BH(4)) therapy have fueled the need for new management and treatment recommendations for this metabolic disorder. BH(4), now available as sapropterin dihydrochloride (sapropterin), may offer the potential for improved metabolic control as well as enhanced dietary Phe tolerance in some PKU patients. A group of metabolic dietitians from North America convened in June 2011 to draft recommendations for the use of sapropterin therapy in PKU. Physicians with extensive experience in PKU management were invited at a later date to contribute to the development of these recommendations. Based on extensive clinical experience and current evidence, the present recommendations provide guidance from patient selection and determination of sapropterin response to the long-term management of patients on sapropterin therapy. Target Phe levels, nutritional adequacy, neurocognitive screening and adherence to treatment are addressed to optimize patient outcomes.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.861
Threshold uncertainty score0.451

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 head0.042
GPT teacher head0.279
Teacher spread0.238 · 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

Citations46
Published2012
Admission routes1
Has abstractyes

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