Abstract

Background

The purpose of this study was to evaluate the advantages of robot navigation system-assisted intramedullary nail treatment for humeral shaft fractures and compare it’s efficacy with that of traditional surgical intramedullary nail treatment.

Materials and methods

This was a retrospective analysis of patients with humeral shaft fractures who received intramedullary nail treatment at our centre from March 2020 to September 2022. The analysis was divided into a robot group and a traditional surgical group on the basis of whether the surgery involved a robot navigation system. We compared the baseline data (age, sex, cause of injury, fracture AO classification, and time of injury-induced surgery), intraoperative conditions (surgery time, length of main nail insertion incision, postoperative fluoroscopy frequency, intraoperative bleeding), fracture healing time, and shoulder joint function at 1 year postsurgery (ASES score and Constant–Murley score) between the two groups of patients.

Results

There was no statistically significant difference in the baseline data or average fracture healing time between the two groups of patients. However, the robotic group had significantly shorter surgical times, longer main nail incisions, fewer intraoperative fluoroscopies, and less intraoperative blood loss than did the traditional surgery group (P < 0.001).

Conclusion

Robot navigation system-assisted intramedullary nail fixation for humeral shaft fractures is a reasonable and effective surgical plan. It can help surgeons determine the insertion point and proximal opening direction faster and more easily, shorten the surgical time, reduce bleeding, avoid more intraoperative fluoroscopy, and enable patients to achieve better shoulder functional outcomes.

Details

Title
A clinical study on robot navigationassisted intramedullary nail treatment for humeral shaft fractures
Author
Qi, Hongfei; Ai, Xianjie; Ren, Taotao; Li, Zhong; Zhang, Chengcheng; Wu, Bo; Cui, Yu; Li, Ming
Pages
1-7
Section
Research
Publication year
2024
Publication date
2024
Publisher
BioMed Central
e-ISSN
14712474
Source type
Scholarly Journal
Language of publication
English
ProQuest document ID
3115132701
Copyright
© 2024. This work is licensed under http://creativecommons.org/licenses/by-nc-nd/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.