Background Rhinoplasty is a complex procedure that requires meticulous planning and precise execution. Plastic surgeons involved in teaching residents must balance a trainee’s hands-on experience while ensuring appropriate execution of difficult maneuvers. Surgical simulation, a field of growing importance with the shift towards competency-based education, may aid in trainee skill development. Through the concept of deliberate practice, the authors looked to explore the utility and economics of 3-dimensional (3D) printing technology to develop a step-specific rhinoplasty simulator. Objectives The main objective of this study was to address rhinoplasty skills previously identified as “learning areas of weakness” and develop a low-cost, step-specific simulator to help rhinoplasty teaching. Methods A patient’s facial bones, upper and lower lateral cartilages, and septum were segmented from a computed tomography scan and rendered in 3D format. This was 3D printed utilizing Ultimaker Polylactic filament with a polyvinyl acetate dissolvable support for bone, a mixture of Rigur 450 and Tango plus polyjet material for cartilage, and Smooth-On Dragon Skin for skin. Results A modular simulator was developed with 3 separate, interchangeable components with a perfect fit design. The simulator allowed for deliberate practice of the 5 rhinoplasty learning areas of weakness, with a maximal recurring cost of $75 CAD. Conclusions Through the employment of 3D printing, a low-cost, maneuver-specific rhinoplasty simulator reinforcing deliberate practice was developed. This concept of simulation-based deliberate practice may be of increasing interest when considering the implementation of competency-based curricular standards in plastic surgery education.
Background: Rhinoplasty is known for its complexity in planning and execution. For trainees, knowledge acquisition is often adequately attained. The mastery of skills, however, occurs by means of hands-on exposure, which continues to be a challenge. This article discusses the positive progress made in rhinoplasty training, and objectively demonstrates a need for more hands-on rhinoplasty exposure for residents. Methods: A systematic review was performed in adherence to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines. Concurrently, an online survey was developed, assessing resident comfort and training in rhinoplasty, and e-mailed to Canadian and U.S. plastic surgery training programs. Results: One hundred thirty-eight residents completed the survey, 62 junior (first- to third-year residents) and 76 senior residents (fourth- to sixth-year residents). Seventy-two percent of senior residents (95 percent of sixth-year residents) reported adequate rhinoplasty exposure, as opposed to 13 percent of junior residents. Seventy-five percent of senior residents most often participated as observers or first assistants, 25 percent participated as co-surgeons, and 73.9 percent did not perform a key rhinoplasty step more than five times. Residents felt the three most difficult steps of rhinoplasty were nasal osteotomy (76.1 percent), caudal septum/anterior nasal spine manipulation (65.2 percent), and nasal tip sutures (55.8 percent), and 73.9 percent felt that simulator training would substantially improve confidence. Conclusions: Despite sufficient exposure to rhinoplasties, residents were least confident in performing rhinoplasties relative to other aesthetic procedures, likely because of the high proportion of rhinoplasty exposure that is observational as opposed to hands-on acquisition of surgical maneuvers in the operating room. The survey established the maneuvers residents find the most difficult, and as programs adopt competency-based training, developing rhinoplasty simulators targeting specific identified steps may help improve competence for rhinoplasty skills.
Background: Virtual reality simulators and machine learning have the potential to augment understanding, assessment and training of psychomotor performance in neurosurgery residents.Objective: This study outlines the first application of machine learning to distinguish "skilled" and "novice" psychomotor performance during a virtual reality neurosurgical task.Methods: Twenty-three neurosurgeons and senior neurosurgery residents comprising the "skilled" group and 92 junior neurosurgery residents and medical students the "novice" group. The task involved removing a series of virtual brain tumors without causing injury to surrounding tissue.Over 100 features were extracted and 68 selected using t-test analysis. These features were provided to 4 classifiers: K-Nearest Neighbors, Parzen Window, Support Vector Machine, and Fuzzy K-Nearest Neighbors. Equal Error Rate was used to assess classifier performance. Results:Ratios of train set size to test set size from 10% to 90% and 5 to 30 features, chosen by the forward feature selection algorithm, were employed. A working point of 50% train to test set size ratio and 15 features resulted in an equal error rates as low as 8.3% using the Fuzzy K-Nearest Neighbors classifier. Conclusion:Machine learning may be one component helping realign the traditional apprenticeship educational paradigm to a more objective model based on proven performance standards.
A majority of patients with tuberculosis (TB) in India are diagnosed and treated in the private sector. Yet, most private providers do not use most recent WHO-endorsed microbiological tests such as liquid cultures, line probe assays and Xpert MTB/RIF due to a combination of factors such as lack of awareness, misaligned incentives and high prices that are unaffordable for patients. We designed a market-based approach to transform a high-price, low-volume market equilibrium into a low-price, high-volume equilibrium to improve the uptake of these tests. Toward this end, a non-profit consortium of private laboratories, called Initiative for Promoting Affordable and Quality Tuberculosis Tests (IPAQT) was formed in India in March 2013. It negotiated lower pricing on equipment and reagents with manufacturers, closer to that offered to the public sector. In return, IPAQT assured that this discount was passed on to patients, who typically paid for these tests out of their pockets, through an informally agreed on retail ceiling price. IPAQT also invested in demand generation activities that complemented the supply-side effort. IPAQT membership grew from 56 laboratories in 2013 to 211 in 2018. During this period, the initiative resulted in a 10-fold increase in the uptake of Xpert and a 30%–50% reduction in price. This initiative is planned to be expanded to other South Asian countries with similar TB epidemic and private market structure and dynamics. However, long-term sustainability of the initiative would require developing more cost-effective marketing activities and integration with broader private sector engagement agenda of the national TB programme.
Background: Breast implant-associated anaplastic large cell lymphoma (BIA-ALCL) awareness has increased, resulting in concerns regarding the safety of implant-based reconstruction. Breast cancer patients are first seen by surgical oncologists, who are therefore potentially the first health-care professionals to encounter concerns regarding BIA-ALCL. We therefore surveyed surgical oncologists on their understanding of BIA-ALCL to better assess potential effects on plastic surgery practice. Methods: An anonymous web-based survey consisting of 9 multiple-choice questions was sent to breast surgical oncologists that are members of the Canadian Society of Surgical Oncology (n = 135). Results: Forty-two members responded (n = 42/135, 31%) and all participants were aware of BIA-ALCL. All participants reported that BIA-ALCL has not deterred them from referring patients for implant-based reconstruction. Twenty-two respondents (52%) discuss BIA-ALCL with their patients and 21% (n = 9) believe that BIA-ALCL typically follows a metastatic course. Eight respondents (19%) reported having a poor understanding of BIA-ALCL, while 14% (n = 6) were unable to identify the link to textured implants. There were no statistical differences based on case-load volume. Conclusions: Approximately half of the respondent Canadian breast surgical oncologists discuss BIA-ALCL with their patients, yet there is a knowledge gap in terms of the epidemiology and clinical-pathological course of BIA-ALCL. It is of utmost importance to ensure that the plastic surgery community aims at including surgical oncologist colleagues in educational platforms regarding BIA-ALCL to ensure collaboration and unity in an effort to offer the most accurate information to patients, and prevent misinformation that may deter patients from seeking implant-based reconstruction.
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