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Record W2800240446 · doi:10.14740/jmc.v9i5.3044

Anesthetic Management of a Patient With Carnitine-Acylcarnitine Translocase Deficiency

2018· article· en· W2800240446 on OpenAlexvenueno aff
Faizaan Syed, Henry Turner, Faris AlGhamdi, Dmitry Tumin, Joseph D. Tobias, Tariq Wani

Bibliographic record

VenueJournal of Medical Cases · 2018
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicMetabolism and Genetic Disorders
Canadian institutionsnot available
Fundersnot available
KeywordsCarnitineMedicineTranslocaseAnestheticMitochondrionLimitingInternal medicineAnesthesiaBiochemistryChromosomal translocationBiologyGene

Abstract

fetched live from OpenAlex

Carnitine-acylcarnitine translocase (CACT) deficiency is a rare disorder of mitochondrial fatty acid metabolism that results in an acute encephalopathic and/or myopathic disorder. Carnitine and CACT play an essential role in the transport of fatty acids into the mitochondria. The deficiency leads to the reduced transport of long-chain fatty acids into the mitochondria, thereby limiting the use of fatty acids for energy production especially during prolonged fasting, febrile illnesses, increased muscular activity, and other periods of systemic stress. We present the anesthetic management of a 10-year-old girl, diagnosed with CACT deficiency at birth, who presented for multiple osteotomies. The preoperative evaluation of such patients is presented, previous reports of anesthetic care are reviewed, and options for intraoperative care are discussed. J Med Cases. 2018;9(5):127-130 doi: https://doi.org/10.14740/jmc3044w

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Case report · Consensus signal: Case report
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0010.000

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 head0.008
GPT teacher head0.254
Teacher spread0.246 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designCase report
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

Citations0
Published2018
Admission routes1
Has abstractyes

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