S. Hegde1, E. Hofman2, S. Dubagunta2, D. Awad2, O. Khan2, K. Eisaman2, I. Hossain2, C. Park1 1University Of Texas Southwestern Medical Center, Surgery, Dallas, TX, USA 2University of Texas Dallas, Engineering, Richardson, TEXAS, USA
Introduction: Simulation-based training leads to improved clinical performance but may be influenced by quality and frequency of training. Within simulation training, chest tube insertion remains a challenge as one of the main pitfalls of insertion is a controlled pleural entry. This study evaluates a novel training model with real-time pressure monitoring to enhance simulation in surgical trainees.
Methods: This proprietary training model comprised of a modified Kelly clamp device with three force sensors at the index finger (sensor 1) and two finger loops (sensors 2 and 3), and a manikin with a replaceable chest wall pad. Standard force values (Newtons "N') were obtained by experts; expert data revealed that 3-5 seconds was an acceptable time range to complete the chest tube insertion. Participant level ranged from PGY-1 to PGY-6. Each individual was provided an introduction to the procedure and chest tube trainer. Force (newtons) and time (milliseconds) measurements were obtained from entry through dermis to pleural space puncture. A significant pressure drop suggested puncturing through the chest wall (completion of the procedure).
Results: Force data was captured during each phase of the procedure—linear, plateau, and drop. Linear phase (~3,000ms) was from start of procedure to point of maximum force (< 30N). Plateau phase was from maximum force to just before a drop in pressure. Drop phase was a drop in pressure by 5+ Newtons in a span of 150 ms signaling completion of procedure. All participants were able to complete the task successfully. Force for pleural entry ranged from 17N to 30N; time to pleural entry ranged from 7,500 to 15,000ms. There was variability in use of all three sensors. All participants used the index sensor, however there was variability in the use of the loops sensors depending on the handedness of the participant. Left-handed users relied more on sensors 1 and 3 while right-handed users relied more on sensors 1 and 2. Given this variability, only force measurements from sensor 1 were utilized for assessment.
Conclusion: While this training modality utilized only one sensor and focused specifically on controlled pleural entry aspect of thoracostomy, this novel force-sensing chest tube trainer with continuous pressuring monitoring has a wide range of applications in simulation-based training of emergency surgical tasks. Next steps include incorporating simultaneous audio-visual feedback to help improve accuracy and effciency.
