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Record W2032578179 · doi:10.1111/acem.12590

The Development and Validation of Hand Motion Analysis to Evaluate Competency in Central Line Catheterization

2015· article· en· W2032578179 on OpenAlexaff
David Clinkard, Matthew Holden, Tamás Ungi, David Messenger, Colleen Davison, Gábor Fichtinger, Robert McGraw

Bibliographic record

VenueAcademic Emergency Medicine · 2015
Typearticle
Languageen
FieldMedicine
TopicSimulation-Based Education in Healthcare
Canadian institutionsQueen's University
Fundersnot available
KeywordsMedicineCentral lineMedical physicsIntensive care medicine

Abstract

fetched live from OpenAlex

OBJECTIVES: Traditionally, technical skills proficiency has been assessed by direct observation. While direct observation and feedback are essential components in technical skills learning, they demand considerable investment of faculty time, and as an assessment tool, direct observation is inherently subjective and has been criticized as unreliable. The purpose of this study was to determine if quantitative electromagnetic motion tracking is feasible and can discriminate between experts and nonexperts during simulated ultrasound (US)-guided insertion of a central venous catheter (CVC) guidewire. METHODS: Ten nonexperts (junior emergency medicine residents) and 10 experts (critical care fellows or attending physicians) were recruited. Electromagnetic sensor probes were used to capture hand motion during an US-guided internal jugular cannulation on a standardized manikin. Hand, US, and needle motion were analyzed for the following metrics: total path length, total time, translational movements, and rotational movements. Subjects were also videotaped and evaluated using a modified, validated global rating scale (GRS) by a blinded expert. RESULTS: There was a significant difference in almost all examined motion parameters between experts and nonexperts. Experts took 66% less time (50.2 seconds vs. 148.7 seconds, p < 0.001) and had significantly less right-hand and US motion (total path length and translational and rotational movements). Left-hand total path length was the only parameter that was not significantly different between groups. Concurrent validity of motion parameters was established by strong correlations (r2 > 0.74) to a previously published, modified GRS. CONCLUSIONS: Electromagnetic hand and instrument motion analysis is technically feasible for assessing competence in US-guided insertion of a CVC guidewire in a simulation setting. In showing that it discriminates between the performances of nonexperts and experts, this study has provided evidence for construct validity. It also shows excellent correlation with a modified version of a previously validated GRS, providing evidence of concurrent validity.

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)0.002
metaresearch head score (Gemma)0.001
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 score0.017
Threshold uncertainty score0.355

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
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 head0.119
GPT teacher head0.424
Teacher spread0.305 · 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

Citations55
Published2015
Admission routes1
Has abstractyes

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