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Record W4393147481 · doi:10.1080/15563650.2024.2328351

Assessing the impact of a new medical toxicology service on the treatment of paracetamol overdose at a large tertiary care hospital

2024· article· en· W4393147481 on OpenAlexaff
E. Z. Bronshteĭn, Or Segev, Dennis Scolnik, Miguel Glatstein

Bibliographic record

VenueClinical Toxicology · 2024
Typearticle
Languageen
FieldPharmacology, Toxicology and Pharmaceutics
TopicDrug-Induced Hepatotoxicity and Protection
Canadian institutionsSickKids FoundationHospital for Sick ChildrenUniversity of Toronto
Fundersnot available
KeywordsMedicineRetrospective cohort studyEmergency medicineDrug overdoseGeneralizability theoryClinical toxicologyMedical emergencyIncidence (geometry)Intensive care medicineToxicologyPoison controlSurgeryPsychology

Abstract

fetched live from OpenAlex

BACKGROUND: Paracetamol overdose is the most common cause of acute liver failure in the United States. Administration of acetylcysteine is the standard of care for this intoxication. Laboratory values and clinical criteria are used to guide treatment duration, but decision-making is nuanced and often complex and difficult. The purpose of this study was to evaluate the effect of the introduction of a medical toxicology service on the rate of errors in the management of paracetamol overdose. METHODS: This was a single center, retrospective, cohort evaluation. Patients with suspected paracetamol overdose were divided into two groups: those attending in the 1 year period before and those in the 1 year after the introduction of the medical toxicology service. The primary outcome was the frequency of deviations from the established management of paracetamol intoxication, using international guidelines as a reference. RESULTS: = 0.005). DISCUSSION: Our study suggests that a medical toxicology service reduces the incidence of management errors, including the number of missed acetylcysteine doses in patients with paracetamol overdose. The limitations include the retrospective study design and that the study was conducted at a single center, which may limit generalizability. CONCLUSIONS: The implementation of a medical toxicology service was associated with a decrease in the number of errors in the management of paracetamol overdose.

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)0.002
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesResearch integrity, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.614
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0040.000

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 head0.214
GPT teacher head0.550
Teacher spread0.337 · 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.

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

Citations2
Published2024
Admission routes1
Has abstractyes

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