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Record W2894690803 · doi:10.1515/jbcpp-2018-0075

Review of thiamine deficiency disorders: Wernicke encephalopathy and Korsakoff psychosis

2018· review· en· W2894690803 on OpenAlexaff
Abin Chandrakumar, Aseem Bhardwaj, Geert W. ‘t Jong

Bibliographic record

VenueJournal of Basic and Clinical Physiology and Pharmacology · 2018
Typereview
Languageen
FieldMedicine
TopicAlcoholism and Thiamine Deficiency
Canadian institutionsUniversity of ManitobaChildren's Hospital Research Institute of Manitoba
Fundersnot available
KeywordsThiamineWernicke EncephalopathyThiamine pyrophosphateEncephalopathyPsychosisMedicineEtiologyTransketolaseThiamine deficiencyWernicke's encephalopathyBeriberiPsychiatryPediatricsBioinformaticsInternal medicineBiologyCofactor

Abstract

fetched live from OpenAlex

Wernicke encephalopathy (WE) and Korsakoff psychosis (KP), together termed Wernicke-Korsakoff syndrome (WKS), are distinct yet overlapping neuropsychiatric disorders associated with thiamine deficiency. Thiamine pyrophosphate, the biologically active form of thiamine, is essential for multiple biochemical pathways involved in carbohydrate utilization. Both genetic susceptibilities and acquired deficiencies as a result of alcoholic and non-alcoholic factors are associated with thiamine deficiency or its impaired utilization. WKS is underdiagnosed because of the inconsistent clinical presentation and overlapping of symptoms with other neurological conditions. The identification and individualized treatment of WE based on the etiology is vital to prevent the development of the amnestic state associated with KP in genetically predisposed individuals. Through this review, we bring together the existing data from animal and human models to expound the etiopathogenesis, diagnosis, and therapeutic interventions for WE and KP.

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)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.006
Threshold uncertainty score0.021

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0040.004
Science and technology studies0.0000.000
Scholarly communication0.0010.002
Open science0.0010.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0060.002

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 head0.062
GPT teacher head0.445
Teacher spread0.383 · 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 designNot applicable
Domainnot available
GenreReview

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

Citations173
Published2018
Admission routes1
Has abstractyes

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Same venueJournal of Basic and Clinical Physiology and PharmacologySame topicAlcoholism and Thiamine DeficiencyFrench-language works237,207