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4-AMINOPYRIDINE TOXICITY WITH UNINTENTIONAL OVERDOSE IN FOUR PATIENTS WITH MULTIPLE SCLEROSIS

2008· article· en· W2048938969 on OpenAlexaffabout
Jodie Burton, Chaim M. Bell, Scott E. Walker, Paul O’Connor

Bibliographic record

VenueNeurology · 2008
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicIon channel regulation and function
Canadian institutionsSt. Michael's Hospital
Fundersnot available
Keywords4-AminopyridineMultiple sclerosisToxicityMedicineDrug overdoseEmergency medicineAnesthesiaInternal medicinePoison controlPsychiatry

Abstract

fetched live from OpenAlex

Aminopyridine has been shown to improve spasticity and ambulatory speed in patients with multiple sclerosis (MS), spinal cord injuries, and neuromuscular diseases.1–4 Four-aminopyridine (4-AP) selectively blocks fast, voltage-gated potassium channels in excitable tissues and increases the influx of calcium at nerve terminals, thereby enhancing neuromuscular transmission.1 It is this mechanism of action, however, that predispose to adverse events, specifically seizures.1,2,5 ### Case reports. In Ontario, Canada, from April 2007 to early May 2007, four patients with secondary progressive MS were admitted to hospital with status epilepticus. Three of the four provided consent for inclusion in this case series. Patients ranged in age from 46 to 54 years with Expanded Disability Status Scale (EDSS) scores of 6.0–6.5 and disease duration of 7–20 years. All had been prescribed 4-AP 10-mg tablets for ambulatory decline at doses between 10 mg BID to TID. All patients experienced unusual sensory and behavioral symptoms that rapidly transitioned into status epilepticus (recurrent seizures without full …

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 score0.015
Threshold uncertainty score0.029

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0020.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
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 head0.020
GPT teacher head0.191
Teacher spread0.171 · 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

Citations39
Published2008
Admission routes2
Has abstractyes

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