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Record W1993443936 · doi:10.4103/0976-3147.120226

Late onset of atypical paroxysmal non-kinesigenic dyskinesia with remote history of Graves’ disease

2013· article· en· W1993443936 on OpenAlexaff
Abdul Qayyum Rana, Ambreen Nadeem, Muhammad Saad Yousuf, Zakerabibi Mohammed Kachhvi

Bibliographic record

VenueJournal of Neurosciences in Rural Practice · 2013
Typearticle
Languageen
FieldMedicine
TopicEpilepsy research and treatment
Canadian institutionsUniversity of TorontoThe Scarborough HospitalParkinson's Clinic of Eastern Toronto & Movement Disorders Centre
Fundersnot available
KeywordsParoxysmal dyskinesiaMedicinePediatricsDyskinesiaClonazepamMovement disordersDystoniaDiseasePsychiatryParkinson's diseaseInternal medicine

Abstract

fetched live from OpenAlex

Paroxysmal non-kinesigenic dyskinesia (PNKD) is a rare hyperkinetic movement disorder and falls under the category of paroxysmal movement disorders. In this condition, episodes are spontaneous, involuntary, and involve dystonic posturing with choreic and ballistic movements. Attacks last for minutes to hours and rarely occur more than once per day. Attacks are not typically triggered by sudden movement, but may be brought on by alcohol, caffeine, stress, fatigue, or chocolate. We report a patient with multiple atypical features of PNKD. She had a 7-year history of this condition with onset at the age of 59, and a remote history of Graves' disease requiring total thyroidectomy. The frequency of attacks in our case ranged from five to six times a day to a minimum of twice per week, and the duration of episode was short, lasting not more than 2 min. Typically, PNKDs occur at a much younger age and have longer attack durations with low frequency. Administering clonazepam worked to reduce her symptoms, although majority of previous research suggests that pharmacological interventions have poor outcomes.

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 score0.002
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.000
Science and technology studies0.0010.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.025
GPT teacher head0.316
Teacher spread0.291 · 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

Citations4
Published2013
Admission routes1
Has abstractyes

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