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Record W2172090133 · doi:10.1177/0883073813476140

Can Children With Hyperlipidemia Receive Ketogenic Diet for Medication-Resistant Epilepsy?

2013· article· en· W2172090133 on OpenAlexaff
Yeou-mei Christiana Liu, Helen Lowe, Maria Zak, Jeff Kobayashi, Valerie Chan, Elizabeth Donner

Bibliographic record

VenueJournal of Child Neurology · 2013
Typearticle
Languageen
FieldMedicine
TopicDiet and metabolism studies
Canadian institutionsHospital for Sick Children
FundersAmerican Epilepsy Society
KeywordsKetogenic dietHyperlipidemiaMedicineCholesterolHigh-density lipoproteinLipoproteinInternal medicineEndocrinologyEpilepsyDiabetes mellitus

Abstract

fetched live from OpenAlex

The very-high-fat ketogenic diet can worsen lipid levels in children with pre-existing hyperlipidemia by increasing serum lipoproteins and reducing antiatherogenic high-density lipoproteins. A retrospective chart review of 160 children treated with the ketogenic diet from September 2000 to May 2011 was performed. Twelve children with pre-existing hyperlipidemia were identified. Lipid levels including total cholesterol, low-density lipoprotein, triglycerides, high-density lipoprotein, and total cholesterol/high-density lipoprotein were measured pre-diet and at 3, 6, and 12 months of treatment. During treatment, there was a significant reduction in mean total cholesterol, low-density lipoprotein, and total cholesterol/high-density lipoprotein. Total cholesterol and low-density lipoprotein were normalized in 8 and 7 children at 6 months; and 9 and 9 children at 12 months respectively. At 6 and 12 months, tot cholesterol/HDL ratio was normalized in 5 and 7 children respectively. Diet modifications were made to achieve healthy lipid levels. By extrapolating the data, it suggests lipid levels can be controlled in children and adults with ketogenic diet treatment.

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 score0.209
Threshold uncertainty score0.420

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 science0.0000.000
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 head0.247
Teacher spread0.236 · 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

Citations38
Published2013
Admission routes1
Has abstractyes

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