MétaCan
Menu
Back to cohort
Record W4404183383 · doi:10.1136/jnnp-2024-abn.225

Reversible subacute chorea caused by nutritional deficiency

2024· article· en· W4404183383 on OpenAlexaboutno aff
Adenan Mohammad Hijaz, Porter Marie-Claire, Savchenko Tetiana, Karatzikou Maria, M Laurà, Stanton Biba, Raftopoulos Rhian

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldMedicine
TopicNeurological and metabolic disorders
Canadian institutionsnot available
Fundersnot available
KeywordsChoreaMedicineInternal medicineDisease

Abstract

fetched live from OpenAlex

We present a case of a 70-year-old lady with a six weeks history of progressive encephalopathy with visual hallucinations and choreiform movements of the right upper and lower limbs. Her past medical history included a longstanding eating disorder, Vitamin B12 deficiency, and several falls resulting in fractures. On examination, there was a right sided hemichorea with orofacial dyskinesia. Her speech was tangential and confabulatory. The remainder of the examination was normal. She scored 18/30 on Montreal Cognitive Assessment (MOCA). Investigations demonstrated a macrocytic anaemia with a low serum folate. Vitamin B12 was at the lower end of normal (287 pg/ml) with a raised homocysteine (indicating functional deficiency). MRI brain and cord was normal. CSF examination was unremarkable with the exception of CSF specific oligoclonal bands (not present on repeat testing). Extended autoantibody screening was negative with a negative CT CAP. She was treated with pabrinex, B12 injections, and folate replacement with complete resolution of her symptoms. On six month follow up, her cognitive improved with a score of 27/30 on MOCA. Although rare, B12 deficiency is a treatable cause of chorea that should not be missed.

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: Case report · Consensus signal: Case report
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.005
Threshold uncertainty score0.012

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0020.001
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)0.0040.001

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 head0.017
GPT teacher head0.264
Teacher spread0.247 · 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
Published2024
Admission routes1
Has abstractyes

Explore more

Same topicNeurological and metabolic disordersFrench-language works237,207