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Record W2518804482 · doi:10.1111/anae.13572

Construct validity of a novel assessment tool for ultrasound‐guided axillary brachial plexus block

2016· article· en· W2518804482 on OpenAlexaff
Osman Ahmed, Brian D. OʼDonnell, Anthony G. Gallagher, Dara S. Breslin, Christoph Nix, George Shorten

Bibliographic record

VenueAnaesthesia · 2016
Typearticle
Languageen
FieldMedicine
TopicAnesthesia and Pain Management
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsMedicineBrachial plexusBrachial plexus blockConstruct validityReliability (semiconductor)UltrasoundProtocol (science)Physical therapyUltrasonographyRadiologyAxillaMedical physicsSurgeryInternal medicinePatient satisfactionPathologyBreast cancer

Abstract

fetched live from OpenAlex

The purpose of this study was to examine the construct validity and reliability of a novel metrics-based assessment tool, previously developed for ultrasound-guided axillary brachial plexus block. Five expert and eight novice anaesthetists performed a total of 18 ultrasound-guided axillary brachial plexus blocks on the same number of patients. A trained investigator video-taped procedures according to a pre-defined protocol. Two trained consultant anaesthetists independently scored the videos using the assessment tool. Compared with novices, experts completed more steps (mean 41.0 vs. 33.1, p = 0.001), had fewer procedural errors (2.8 vs. 7.9, p < 0.0001), had fewer critical errors (0.8 vs. 1.3, p = 0.030), and fewer total errors (3.5 vs. 9.1, p < 0.0001). The mean inter-rater reliability for scoring of experts' performance was 0.91, for novices' performance was 0.84, and for all performance combined (n = 18) was 0.88. This assessment tool is valid, and discriminates reliably between expert and novice performance for placement of ultrasound-guided axillary brachial plexus blocks.

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)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.070
Threshold uncertainty score0.579

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
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 head0.037
GPT teacher head0.304
Teacher spread0.268 · 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.

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

Citations15
Published2016
Admission routes1
Has abstractyes

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