Validation of a three‐dimensional printed model for training of surgical extraction of supernumerary teeth

Introduction This study aimed to validate a three‐dimensional (3D) printed model to provide training for supernumerary teeth (SNTs) extraction. Materials and Methods Each of the 30 participants, grouped as experienced and without experience, conducted two identically simulated surgeries on a 3D‐prin...

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Veröffentlicht in:European journal of dental education 2020-11, Vol.24 (4), p.637-643
Hauptverfasser: Chae, Yong Kwon, Lee, Hyeonjong, Jih, Myeong Kwan, Lee, Hyo‐Seol, Lee, Jung‐Woo, Kim, Su‐Hwan, Kim, Gyu‐Tae, Choi, Sung Chul, Nam, Ok Hyung
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Sprache:eng
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Zusammenfassung:Introduction This study aimed to validate a three‐dimensional (3D) printed model to provide training for supernumerary teeth (SNTs) extraction. Materials and Methods Each of the 30 participants, grouped as experienced and without experience, conducted two identically simulated surgeries on a 3D‐printed replica of human mixed dentition with a SNT. The surgery time, area of bony window and volume of removed material were measured; subsequently, responses to a five‐item questionnaire were recorded. The collected data were statistically analysed. Results The surgery time was 228.37 ± 141.53 seconds and 125.47 ± 53.03 seconds in the first and second surgery, respectively. The training significantly decreased the surgery time in the participants without experience (P = .000). However, there were no significant differences in the area of window opening (P = .271) and volume of removed material between the two surgeries (P = .075). The participants who perceived educational benefits accounted for more than 60% of the respondents for every question. Participants without experience in SNT extraction showed a tendency to rate a higher score than did those with experience. Conclusions A 3D‐printed model for surgical extraction of a SNT can improve surgical skill and, especially, shorten the learning curve in beginners.
ISSN:1396-5883
1600-0579
DOI:10.1111/eje.12543