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Record W3080987163 · doi:10.1097/aco.0000000000000912

Wrong-site nerve blocks: evidence-review and prevention strategies

2020· review· en· W3080987163 on OpenAlexaff
Kwesi Kwofie, Vishal Uppal

Bibliographic record

VenueCurrent Opinion in Anaesthesiology · 2020
Typereview
Languageen
FieldHealth Professions
TopicPatient Safety and Medication Errors
Canadian institutionsDalhousie University
Fundersnot available
KeywordsChecklistCognitionMedicinePsychologyPatient safetyHealth carePsychiatryPolitical scienceCognitive psychology

Abstract

fetched live from OpenAlex

PURPOSE OF REVIEW: There has been increasing attention to wrong site medical procedures over the last 20 years. This review aims to provide a summary of the current understanding and recommendations for the prevention of wrong-site nerve blocks (WSNB). RECENT FINDINGS: Various procedural, patient, practitioner, and organizational factors have been associated with the risk of WSNB. Recent findings have suggested that the use of a checklist is likely to reduce the incidence of WSNB. However, despite the widespread use of preprocedural checklists, WSNB continue to occur at significant frequency. This may be due to the inability of practitioners and teams to implement checklists correctly or the cognitive errors that prevent checklists from being executed as designed. SUMMARY: Though the evidence is limited, it is recommended that a combination of multiple strategies should be employed to prevent WSNB. These include the use of preprocedural markings, well constructed checklists, time-out/stop-moments, and cognitive/physical aids. Effective implementation requires team education and engagement that empowers all team members to speak up as part of a culture of safety.

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)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.832
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.002
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 head0.354
GPT teacher head0.547
Teacher spread0.193 · 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 designOther design
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

Citations10
Published2020
Admission routes1
Has abstractyes

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