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Record W3129589084 · doi:10.1093/cdn/nzab016

Effect of High-Protein Diet on Postprandial Energy Expenditure in Children with Prader-Willi Syndrome: A Pilot and Feasibility Study

2021· article· en· W3129589084 on OpenAlexafffund
Maha Alsaif, Lucila Triador, Eloisa Colin-Ramírez, Sarah A. Elliott, Michelle Mackenzie, Catherine J. Field, Carla M. Prado, Andrea M. Haqq

Bibliographic record

VenueCurrent Developments in Nutrition · 2021
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicGenetic Syndromes and Imprinting
Canadian institutionsUniversity of Alberta
FundersSaudi Arabian Cultural BureauSaudi Arabian Cultural MissionWomen and Children's Health Research InstituteChildren's Health Research Institute
KeywordsPostprandialEnergy expenditureMedicineInternal medicineEndocrinologyPediatricsGerontologyInsulin

Abstract

fetched live from OpenAlex

The aim of this study was to explore the feasibility of measuring a postprandial increase in energy expenditure (ΔEE) using a state-of-the-art whole-body calorimetry unit (WBCU) in children and youth with Prader-Willi syndrome (PWS). Five participants (aged 10–25 y) received both a standard and a high-protein diet in a random order (crossover design). Resting energy expenditure, postprandial ΔEE 6 h after intake of a standard [15% of total energy (TE)] and a high-protein (30% TE) meal, and respiratory exchange ratio (RER) were measured in a WBCU. No differences were observed in ΔEE comparing the 2 meals. Mean RER was lower following the high-protein meal (0.80 ± 0.01) compared with the standard meal (0.87 ± 0.02) ( P = 0.009). Despite the high participant burden, it was feasible to conduct this metabolic test in children and youth with PWS. This study paves the way for further studies targeting EE in this patient population.

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.019
Threshold uncertainty score0.640

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 head0.013
GPT teacher head0.271
Teacher spread0.259 · 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 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

Citations2
Published2021
Admission routes2
Has abstractyes

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