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Record W2143599140 · doi:10.1007/s00268-015-3101-x

The Bare Minimum: The Reality of Global Anaesthesia and Patient Safety

2015· article· en· W2143599140 on OpenAlexaff
Kelly McQueen, Tom Coonan, Andrew Ottaway, Simon Hendel, Paulin R. Bagutifils, Alison B. Froese, Robert Neighbor, Haydn Perndt

Bibliographic record

VenueWorld Journal of Surgery · 2015
Typearticle
Languageen
FieldMedicine
TopicCardiac, Anesthesia and Surgical Outcomes
Canadian institutionsQueen's UniversityDalhousie University
Fundersnot available
KeywordsMedicinePatient safetyLow and middle income countriesAbdominal surgeryVascular surgeryRegional anaesthesiaGeneral anaesthesiaMedical emergencyHealth careCardiac surgeryIntensive care medicineDeveloping countryAnesthesiaSurgeryPolitical scienceEconomic growth

Abstract

fetched live from OpenAlex

INTRODUCTION: Current guidelines for the provision of safe anaesthesia from the World Health Organization and the World Federation of Societies of Anaesthesiologists (WFSA) are unachievable in a majority of low and middle-income countries (LMICs) worldwide. METHODS: Current guidelines for anaesthesia and patient safety provisions from the WHO and WFSA are compared with local ability to achieve these recommendations in LMICs. CONCLUSIONS: Influential international organizations have historically published anaesthesia guidelines, but for the most part, without impacting substantial documentable changes or outcomes in low-income environments. This analysis, and subsequent recommendations, reviews the effectiveness of existing strategies for international guidelines, and proposes practical, step-wise implementation of patient safety approaches for LMICs.

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)0.024
metaresearch head score (Gemma)0.047
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: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.024
Threshold uncertainty score0.126

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0240.047
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.002
Science and technology studies0.0040.019
Scholarly communication0.0130.013
Open science0.0020.010
Research integrity0.0060.014
Insufficient payload (model declined to judge)0.0070.001

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 head0.040
GPT teacher head0.282
Teacher spread0.242 · 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

Citations37
Published2015
Admission routes1
Has abstractyes

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