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Record W2937036283 · doi:10.1111/anae.14662

Catastrophic drug errors involving tranexamic acid administered during spinal anaesthesia

2019· review· en· W2937036283 on OpenAlexaff
Santosh Patel, Barbara Robertson, I. McConachie

Bibliographic record

VenueAnaesthesia · 2019
Typereview
Languageen
FieldHealth Professions
TopicPatient Safety and Medication Errors
Canadian institutionsLondon Health Sciences Centre
Fundersnot available
KeywordsMedicineTranexamic acidAnesthesiaAccidentalResuscitationCatheterClinical trialAnesthesiologySurgeryBlood lossInternal medicine

Abstract

fetched live from OpenAlex

We have reviewed accidental spinal administration of tranexamic acid. We performed a MEDLINE search of cases of administration of tranexamic acid during epidural or spinal anaesthesia between 1960 and 2018. No reports of epidural administration were identified. We identified 21 cases of spinal tranexamic acid administration. Life-threatening neurological and/or cardiac complications, requiring resuscitation and/or intensive care, occurred in 20 patients; 10 patients died. We used a Human Factors Analysis Classification System model to analyse any contributing factors, and the reports were also assessed using four published recommendations for the reduction in neuraxial drug error. In 20 cases, ampoule error was the cause; in the last case a spinal catheter was mistaken for an intravenous catheter. All were classified as skill-based errors. Several human factors related to organisational policy; dispensing and storage of drugs and preparation for spinal anaesthesia tasks were present. All errors could have been prevented by implementing the four published recommendations.

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)0.002
metaresearch head score (Gemma)0.009
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Case report · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.008
Threshold uncertainty score0.010

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.009
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0080.009
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.150
GPT teacher head0.431
Teacher spread0.281 · 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 designCase report
Domainnot available
GenreReview

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

Citations82
Published2019
Admission routes1
Has abstractyes

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