MétaCan
Menu
Back to cohort
Record W2484253801 · doi:10.1080/15563650.2016.1209769

Extracorporeal treatments in a dapsone overdose: a case report

2016· article· en· W2484253801 on OpenAlexaff
Marc Ghannoum, Monique Cormier, Amélie Bernier-Jean, Dave Brindamour, Clément Déziel, Josée Bouchard

Bibliographic record

VenueClinical Toxicology · 2016
Typearticle
Languageen
FieldMedicine
TopicPoisoning and overdose treatments
Canadian institutionsHôpital du Sacré-Cœur de MontréalUniversité de Montréal
Fundersnot available
KeywordsDapsoneMedicineHemoperfusionMethemoglobinemiaAnesthesiaExtracorporealHemodialysisAsymptomaticToxicitySurgeryPharmacologyInternal medicineDermatology

Abstract

fetched live from OpenAlex

Introduction: Intentional dapsone intoxication can be life-threatening. There is limited data on the clinical effect of extracorporeal treatments (ECTRs) on dapsone elimination. We describe a case of severe dapsone toxicity treated with different ECTRs.Case details: A 23-year-old woman was admitted 2.5 h after ingesting 2.2 g of dapsone. She developed methemoglobinemia (39.9%) and showed signs of toxicity (hemodynamic instability and altered mental status) despite multiple-activated charcoal, methylene blue, vasopressors and endotracheal intubation. Continuous venovenous hemofiltration (CVVH) was then initiated for 5 h, followed by intermittent hemodialysis with hemoperfusion (IHD-HP) for 4 h, and CVVH for another 48 h. The platelet count decreased to 32 × 109/L 3 h after IHD-HP. The elimination half-life of dapsone was 2.0 h during IHD-HP, and 14.2 h during CVVH. Mean dapsone clearance with IHD was 62 mL/min versus 22 mL/min with CVVH. IHD removed 95.3 mg, and CVVH removed 67.8 mg over 3.8 h. No rebound occurred following ECTR cessation. The toxicokinetics of dapsone metabolites were also accelerated during ECTR. The patient was extubated after 3.5 days and discharged without sequelae after 7 days.Discussion: Dapsone clearance was enhanced by ECTR, especially by IHD-HP. However, HP was associated with severe asymptomatic thrombocytopenia.

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)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.285
Threshold uncertainty score0.496

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.099
GPT teacher head0.444
Teacher spread0.345 · 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 designObservational
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

Citations5
Published2016
Admission routes1
Has abstractyes

Explore more

Same venueClinical ToxicologySame topicPoisoning and overdose treatmentsFrench-language works237,207