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Record W2806062110 · doi:10.1080/24734306.2018.1459108

Pediatric cardiac toxicity associated with fentanyl ingestion

2018· article· en· W2806062110 on OpenAlexaff
Ryan Chuang, Farah Saleh, Bader Alyahya

Bibliographic record

VenueToxicology Communications · 2018
Typearticle
Languageen
FieldMedicine
TopicPoisoning and overdose treatments
Canadian institutionsUniversity of CalgaryMcGill UniversityAlberta Health Services
Fundersnot available
KeywordsIngestionFentanylMedicineToxicityAnesthesiaCardiac toxicityForeign Body IngestionInternal medicine

Abstract

fetched live from OpenAlex

In North America, opioid-related deaths are on the rise. We report a case of pediatric cardiac toxicity likely related to illicit fentanyl ingestion. A 14-year-old male ingested half of an illicit pill. Two hours post-ingestion, the patient experienced loss of consciousness, hypotension, cyanosis and diaphoresis. He reported chest pain 8 hours post-hospital arrival. Initial lab reports revealed elevations in lactate and high-sensitivity troponin concentrations. A chest radiograph revealed a right-sided aspiration pneumonia. An electrocardiogram showed ST elevation over the anterior leads and T wave inversion over the inferior leads. An echocardiogram demonstrated borderline systolic function. Initial cardiac magnetic resonance imaging revealed inflammation. Comprehensive urine drug screen was positive for fentanyl and its metabolites, cannabinoids, ondansetron, metoclopramide and ranitidine and was negative for xylazine. The management included administration of non-invasive positive-pressure ventilation, naloxone, acetaminophen, ceftriaxone, and clindamycin. Hypotension was treated with calcium gluconate, dopamine, and norepinephrine. He was able to wean off inotropes the next day and went home 5 days post-presentation. A repeat cardiac MRI performed six months post-ingestion was normal. Illicit fentanyl use in an adolescent appeared to cause myocardial injury with cardiogenic shock, elevated serum troponins, and transient abnormalities on electrocardiography and cardiac imaging.

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)0.000
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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.016
Threshold uncertainty score0.382

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
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 head0.039
GPT teacher head0.320
Teacher spread0.280 · 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

Citations4
Published2018
Admission routes1
Has abstractyes

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