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Record W3146591236 · doi:10.12701/yujm.2021.00948

Serotonin syndrome in a patient with chronic pain taking analgesic drugs mistaken for psychogenic nonepileptic seizure: a case report

2021· article· en· W3146591236 on OpenAlexaff
Mathieu Boudier‐Revéret, Min Cheol Chang

Bibliographic record

VenueYeungnam university journal of medicine · 2021
Typearticle
Languageen
FieldMedicine
TopicElectroconvulsive Therapy Studies
Canadian institutionsCentre Hospitalier de l’Université de Montréal
Fundersnot available
KeywordsMedicineDuloxetineSerotonergicTramadolTrazodoneAnesthesiaAnalgesicDiscontinuationPregabalinSerotonin syndromeChronic painPsychogenic diseaseTopiramateSerotoninAntidepressantEpilepsyInternal medicinePhysical therapyAnxietyPsychiatry

Abstract

fetched live from OpenAlex

Serotonin syndrome (SS) is a potentially life-threatening condition that is caused by the administration of drugs that increase serotonergic activity in the central nervous system. We report a case of serotonin syndrome in a patient with chronic pain who was taking analgesic drugs. A 36-year-old female with chronic pain in the lower back and right buttock area had been taking tramadol hydrochloride 187.5 mg, acetaminophen 325 mg, pregabalin 150 mg, duloxetine 60 mg, and triazolam 0.25 mg daily for several months. After amitriptyline 10 mg was added to achieve better pain control, the patient developed SS, which was mistaken for psychogenic nonepileptic seizure. However, her symptoms completely disappeared after discontinuation of the drugs that were thought to trigger SS and subsequent hydration with normal saline. Various drugs that can increase serotonergic activity are being widely prescribed for patients with chronic pain. Clinicians should be aware of the potential for the occurrence of SS when prescribing pain medications to patients with chronic pain.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.047
Threshold uncertainty score0.806

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.013
GPT teacher head0.254
Teacher spread0.241 · 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 teacher head, 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

Citations2
Published2021
Admission routes1
Has abstractyes

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