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Record W2892673878 · doi:10.1080/15563650.2018.1504954

Utilization of lipid emulsion therapy in fatal overdose cases: an observational study

2018· article· en· W2892673878 on OpenAlexaff
Susan C. Smolinske, Robert S. Hoffman, Éric Villeneuve, Lotte C. G. Hoegberg, Sophie Gosselin

Bibliographic record

VenueClinical Toxicology · 2018
Typearticle
Languageen
FieldMedicine
TopicPoisoning and overdose treatments
Canadian institutionsHôpital Charles-Le MoyneMcGill University Health Centre
Fundersnot available
KeywordsMedicineObservational studyAdverse effectLipid emulsionFat emulsionInternal medicineSurgeryEmergency medicine

Abstract

fetched live from OpenAlex

OBJECTIVE: Although anecdotal reports suggest that intravenous lipid emulsion (ILE) therapy is effective in a large variety of overdoses, the few controlled human trials published to date yielded disappointing results. Because of potential publication biases, there are few reports concerning the failure of ILE. The primary aim of this study was to identify fatal poisoning cases in the American Association of Poison Control Centers (AAPCC) National Poison Data System (NPDS) in which ILE was administered. METHODS: We obtained an approved release of data from NPDS for years 2010-2015 in which the words "lipid," "ILE," or "fat" appeared in the narrative. Duplicate cases were excluded as were cases in which ILE was not clearly given. Case data were extracted by one author using a predetermined tool, and the information was confirmed by a second author. The timing of ILE administration was characterized into one of four categories: cardiac arrest, first line, last resort, or part of multiple therapies given simultaneously. Response to ILE and adverse events was recorded. RESULTS: Of the 826 cases retrieved from NPDS, 459 met final inclusion criteria. Over 50% of included cases involved either a calcium channel blocker or a beta-adrenergic antagonist. Of note, less than 25% of cases involved a substance for which the Lipid Emulsion Working Group found evidence to support its use. Most often, ILE was given along with multiple therapies (277 cases) or as a last resort (137 cases). In 127 cases, ILE was given during cardiac arrest. ILE was used as first line therapy in 34 cases. Response rates were reported as follows: no response (45%), unknown response (38%), transient/minimal response (7%), ROSC (7%), and immediate worsening (3%). Possible adverse reactions included: ARDS in 39 patients, lipemia causing a delay in laboratory evaluation in three cases, lipemia causing failure of a CRRT filter in two cases, worsening or new onset seizure in two cases, asystole immediately after administration in two cases, and fat embolism in one case. CONCLUSION: Within the Association of Poison Control Centers (AAPCC) National Poison Data System (NPDS), hundreds of cases exist in which ILE therapy was given and death occurred. In many of these cases, ILE was given prior to cardiovascular collapse. Although there is some suggestion of transient improvement in a small subset of cases, adverse effects are also reported. When taken in totality, the number of published cases of failed lipid emulsion therapy outnumbers the published instances of ILE success. Given all the uncertainty generated by case reports, the evaluation of the role and efficacy of ILE therapy in non-local anesthetic poisoning needs robust controlled clinical trials.

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)0.003
metaresearch head score (Gemma)0.012
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.005
Threshold uncertainty score0.014

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.012
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.003
Science and technology studies0.0010.001
Scholarly communication0.0010.002
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.001

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 head0.522
GPT teacher head0.538
Teacher spread0.016 · 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 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

Citations29
Published2018
Admission routes1
Has abstractyes

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