Development of a dynamic Chest Wall and operating table simulator to enhance congenital heart surgery simulation
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
BACKGROUND: The Hands-On Surgical Training in Congenital Heart Surgery (HOST-CHS) program using 3D printed heart models has received positive feedback from attendees. However, improvements were necessary in the simulator set up to replicate the ergonomics experienced in the operating room. This paper illustrates the development of a dynamic chest wall and operating table simulator to enhance the simulation experience. METHODS: The simulator was designed to address the limitations with the existing set up. This included a suboptimal operating position, unrealistic surgical exposure and limitations in illuminating the operative field and recording procedures. A combination of computer-aided design and various 3D-printing techniques were used to build the components. The simulator's usefulness was evaluated by surgeons who attended the 5th annual HOST course via a questionnaire. RESULTS: The simulator consists of three components; an operating table simulator which allows height adjustment and pitch-and-roll motion; a suture retraction disc, which holds sutures under tension to improve exposure; and a pediatric chest wall cavity to replicate a surgeon's access experience during surgery. Nineteen surgeons completed the questionnaire. All surgeons agreed that the addition of the simulator was acceptable for surgical simulation and that it helped replicate the ergonomics experienced in the operating room. CONCLUSIONS: The inclusion of the HOST-CHS simulator adds value to simulation in congenital heart surgery (CHS) as it replicates the view and exposure a surgeon experiences. Improvements like these will help develop high-fidelity simulation programs in CHS, which could be utilized to train surgeons globally.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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 it