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Record W3024811850 · doi:10.4097/kja.20203

Impact of an ultrasound-guided regional anesthesia workshop on participants' confidence levels and clinical practice

2020· article· en· W3024811850 on OpenAlexaff
Dong Ai An, Nicholas D. Black, Sarah Tierney, Vincent Chan, Ahtsham U. Niazi

Bibliographic record

VenueKorean journal of anesthesiology · 2020
Typearticle
Languageen
FieldMedicine
TopicAnesthesia and Pain Management
Canadian institutionsOttawa HospitalUniversity of OttawaToronto Western HospitalUniversity of Toronto
FundersHeron Therapeutics
KeywordsMedicineAttendanceCurriculumClinical PracticeMedical educationRegional anesthesiaFamily medicineAnesthesia

Abstract

fetched live from OpenAlex

The use of ultrasound-guided regional anesthesia (UGRA) has increased, leading to a growing demand for UGRA training [1].Education may be particularly challenging for those already in established practice because educational opportunities are less obvious.In 2009, the American and European Societies of Regional Anesthesia published guidelines for training pathways in UGRA [2].For practicing anesthesiologists, they recommended workshops consisting of "didactic teaching and hands-on experience [2]." However, there is limited evidence [3] suggesting that these workshops are effective and can impact participants' clinical practice.We aimed to assess if attendance at a UGRA workshop improved confidence in block performance and impacted clinical practice.Since 2004, the regional anesthesia group at Toronto Western Hospital, University Health Network has conducted semi-annual UGRA workshops.These 2-day workshops consist of didactic lectures, live scanning of models under expert supervision, and needling practice on low fidelity simulators.The course curriculum includes teaching on upper and lower limb blocks, truncal blocks, and neuraxial ultrasound.To assess the impact of the workshop, participants were sent an online survey after completion of two courses in 2018.The primary outcome assessed with our survey was the change in participants' confidence levels post-workshop.Secondary outcomes included participants' perceptions on whether or not the workshop made a relevant impact on their clinical practice and to identify the important factors, which can increase the use of UGRA in clinical practice.Of the 99 people who participated in the two workshops, 58 (59%) responded to the follow-up survey, and 34% of the participants stated that they felt confident in performing UGRA blocks prior to attending the workshop, which increased to 66% after the workshop (P < 0.001; McNemar's test) (Fig. 1A).The major reason participants said they were not confident was the lack of needling practice (67%).Other common reasons included inadequate scanning practice (20%) and insufficient knowledge of block procedure (13%).For less experienced participants (defined as having previously performed less than 50 blocks), there was a significant increase in the percentage of participants who felt confident after the workshop.The number of confident participants in the less experienced group rose from 6% before the workshop to 61% after (P < 0.001; McNemar's test) (Fig. 1B).In contrast, more experienced participants (defined as having previously performed more than 50 blocks) showed no change in their confidence levels before and after the workshop (Fig. 1B).Most (95%) participants stated that the workshop made a relevant impact on their clin-

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)0.004
metaresearch head score (Gemma)0.026
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.010
Threshold uncertainty score0.032

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.026
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0010.002
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0100.001

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 head0.296
GPT teacher head0.459
Teacher spread0.163 · 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

Citations3
Published2020
Admission routes1
Has abstractyes

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