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
Central MessageFormal training and assessment on the performance of median sternotomy is often overlooked in cardiothoracic surgical education. A novel model has been developed that has been validated to provide a realistic feel for performing a sternotomy and a serve as a reproducible assessment tool.See Article page 109. Formal training and assessment on the performance of median sternotomy is often overlooked in cardiothoracic surgical education. A novel model has been developed that has been validated to provide a realistic feel for performing a sternotomy and a serve as a reproducible assessment tool. See Article page 109. I vividly remember performing my first median sternotomy as a general surgery intern. The room was busy, the music was loud. The attending surgeon peered over the drape, nodded his head toward me, and signaled to the fellow to give me the saw. My only instruction: Stay midline, stay steady. Although it is the most commonly used approach in cardiac surgery, performing a so-called good sternotomy is often an afterthought. Trainees generally acquire the skill in the operating room on actual patients. Considered a basic skill, a poorly performed median sternotomy can result in significant complications.1Zeitani J. Penta de Peppo A. Moscarelli M. Guerrieri Wolf L. Scafuri A. Nardi P. et al.Influence of sternal size and 362 inadvertent paramedian sternotomy on stability of the closure site: a clinical and 363 mechanical study.J Thorac Cardiovasc Surg. 2006; 132: 38-42Abstract Full Text Full Text PDF PubMed Scopus (32) Google Scholar Recognizing an opportunity for an adjunct educational tool, and spurred by significant support from educators and program directors in Canada, Vo and colleagues2Vo T.X. Juanda N. Ngu J. Gawad N. LaBelle K. Rubens F.D. Development of a median sternotomy simulation model for cardiac surgery training.J Thorac Cardiovasc Surg Tech. 2020; 2: 109-116Google Scholar have developed a simulation model for the practice of median sternotomy and provide preliminary validation evidence for its use in training. Trehan and colleagues3Trehan K. Kemp C.D. Yang S.C. Simulation in cardiothoracic surgical training: where do we stand?.J Thorac Cardiovasc Surg. 2014; 147: 18-24Abstract Full Text Full Text PDF PubMed Scopus (65) Google Scholar have recently reviewed cardiothoracic surgical simulation. Although there are excellent models for techniques such as vascular anastomosis or cannulation for cardiopulmonary bypass, the median sternotomy is often neglected. A major strength of the study by Vo and colleagues2Vo T.X. Juanda N. Ngu J. Gawad N. LaBelle K. Rubens F.D. Development of a median sternotomy simulation model for cardiac surgery training.J Thorac Cardiovasc Surg Tech. 2020; 2: 109-116Google Scholar is that they have developed an inexpensive, realistic model focusing on performing this important task. The model is easy to reproduce, and blinded assessments by participants indicate they found the model to be realistic and useful. The checklist developed for the model served not only to elucidate the basic steps in performing a sternotomy, but also highlighted the importance of areas such as communication. In addition to serving as a training tool, the checklist developed by the authors also serves as a tool for assessment, allowing for incorporation of the model into a competency-based educational curriculum. While providing a new tool for training and competency assessment, the study does have a few limitations which the authors acknowledge. The sample size of 13 participants is small and nearly one-third had performed 10 or more sternotomies before participating in the study. Due to logistical constraints, the sample size could not be increased for the current article. Additionally, participants were junior trainees in the Canadian training system where cardiac surgical training begins at the completion of medical school, rather than after general surgery training, as is common in the United States. Whether more advanced trainees would find as much utility in the model is unclear. Lastly, the interrater reliability for assessment on the checklist was suboptimal, raising some questions as to the validity of the checklist as a good metric for assessment. Patients recognize the importance of a median sternotomy, often having more questions about having their chest cracked open than how the bypass is done or how the valve is sewn in place. As educators, we should ensure we pay as much attention to opening the chest as patients do. Development of a median sternotomy simulation model for cardiac surgery trainingJTCVS TechniquesVol. 2PreviewWe sought to develop a simulation model to train resident physicians in the performance of a median sternotomy. Full-Text PDF Open Access
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.
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 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.002 | 0.003 |
| 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