The Development and Validation of Hand Motion Analysis to Evaluate Competency in Central Line Catheterization
Bibliographic record
Abstract
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.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
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".