Subscribe to RSS
DOI: 10.1055/s-0044-1795114
Reply to Developing 3D-Printed Wrist Splints for Distal Radius and Scaphoid Fractures
Correspondence
This is a correspondence on published article on “Developing 3D-Printed Wrist Splints for Distal Radius and Scaphoid Fractures[1].” This work sheds light on the development of a personalized patient-specific anatomical support device (PSAB) for fracture therapy, leveraging innovations in additive printing. However, some limitations in the literature and technique require more evaluation. First, while the reported patient satisfaction score of 79% suggests broad acceptance, the subjective nature of comfort and satisfaction surveys may add bias. The study lacked a thorough qualitative analysis that looked into specific characteristics of discomfort or discontent, which is critical for enhancing PSAB design. Furthermore, a bigger and more diverse sample size would have enhanced the results' generalizability, as the study only included 10 healthy volunteers, who may not fully represent the broader patient group, which consists of persons with fractures.
Future directions of this research may involve the integration of dynamic monitoring technologies, such as implantable sensors or wearable devices, to provide real-time feedback on the performance of the splint and the patient's activity level. This approach will not only provide a more comprehensive understanding of the mechanical properties of the splint, but also allow for customization based on the patient's needs and treatment progress. In addition, considering a wider range of materials, including biocompatible or adaptive materials, may improve the comfort and effectiveness of PSABs.
Finally, exploring the potential of machine learning algorithms to analyze patient feedback data may allow for iterative improvements in PSAB design based on the user experience. This data-driven approach will allow for the identification of common issues and the appropriate adjustment of the support device to suit different anatomical and functional needs, ultimately promoting innovation in fracture care and improving patient outcomes. Interdisciplinary collaborations between engineering, medicine, and user experience design will pave the way for more effective and personalized orthopaedic solutions.
Publication History
Article published online:
22 November 2024
© 2024. Thieme. All rights reserved.
Thieme Medical Publishers, Inc.
333 Seventh Avenue, 18th Floor, New York, NY 10001, USA
-
References
- 1 Tobler-Ammann B, Schuind F, Voillat L. et al. Developing 3D-printed wrist splints for distal radius and scaphoid fractures. J Wrist Surg 2024; 13 (05) 390-397
-
References
- 1 Tobler-Ammann B, Schuind F, Voillat L. et al. Developing 3D-printed wrist splints for distal radius and scaphoid fractures. J Wrist Surg 2024; 13 (05) 390-397
- 2 Wilson CD, Mand D, Ring D, Ramtin S. A systematic review of satisfaction measures in hand and wrist surgery. J Hand Surg Am 2023; 48 (01) 1-8
- 3 Valdes K, Kannas S, Kakar S, Veneziano J, Dake T, Sierra F. Patient satisfaction of hand therapy services. J Hand Ther 2021; 34 (04) 585-590
- 4 Goodrich GW, Lazenby JM. Elements of patient satisfaction: an integrative review. Nurs Open 2023; 10 (03) 1258-1269
- 5 Wolff AL, Kwasnicki RM, Farnebo S, Horwitz MD. Dynamic assessment of the upper extremity: a review of available and emerging technologies. J Hand Surg Eur Vol 2023; 48 (05) 404-411
- 6 Bullock IM, Ma RR, Dollar AM. A hand-centric classification of human and robot dexterous manipulation. IEEE Trans Haptics 2013; 6 (02) 129-144
- 7 Feix T, Romero J, Schmiedmayer HB. et al. The GRASP taxonomy of human grasp types. IEEE Trans Hum Mach Syst 2016; 46 (01) 66-77
- 8 Elendu C, Amaechi DC, Elendu TC. et al. Ethical implications of AI and robotics in healthcare: a review. Medicine (Baltimore) 2023; 102 (50) e36671
- 9 Yarali E, Mirzaali MJ, Ghalayaniesfahani A, Accardo A, Diaz-Payno PJ, Zadpoor AA. 4D printing for biomedical applications. Adv Mater 2024; 36 (31) e2402301
- 10 Pugliese R, Regondi S. Artificial intelligence-empowered 3D and 4D printing technologies toward smarter biomedical materials and approaches. Polymers (Basel) 2022; 14 (14) 2794
- 11 Khanbhai M, Anyadi P, Symons J, Flott K, Darzi A, Mayer E. Applying natural language processing and machine learning techniques to patient experience feedback: a systematic review. BMJ Health Care Inform 2021; 28 (01) e100262