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An audit of a Multistep Quality Improvement Initiative to Enhance Patient Safety After Sugammadex Administration to Female Patients Using Hormonal Contraceptives

2025· article· en· W4416871707 on OpenAlexaff
Alisoun Milne, G. P. Dobson, D MacDonald

Bibliographic record

VenueObstetric Anesthesia Digest · 2025
Typearticle
Languageen
FieldMedicine
TopicAnesthesia and Sedative Agents
Canadian institutionsDalhousie University
Fundersnot available
KeywordsSugammadexAuditPatient safetyQuality managementAnesthesiologyPatient careNeuromuscular BlockadeQuality (philosophy)

Abstract

fetched live from OpenAlex

( Can J Anesth/J Can Anesth . 2025;72:508–510. doi: 10.1007/s12630-025-02917-3) This article outlines a quality improvement initiative aimed at enhancing patient safety for women who receive sugammadex (SUG), a neuromuscular blockade reversal agent for aminosteroid muscle relaxants. SUG can interfere with the effectiveness of hormonal birth control, posing a risk of unintended pregnancy for those taking these medications. Despite this, patient counseling on the interaction is often inconsistent, especially postoperatively, when patient recall may be compromised. Concern also exists regarding anesthesiology team knowledge on the topic. To address these issues, the authors implemented a multistep strategy to improve staff awareness and patient education.

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.099
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
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 head0.019
GPT teacher head0.328
Teacher spread0.309 · 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

Citations0
Published2025
Admission routes1
Has abstractyes

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