Observational Study
Copyright ©The Author(s) 2024. Published by Baishideng Publishing Group Inc. All rights reserved.
World J Orthop. Jun 18, 2024; 15(6): 560-569
Published online Jun 18, 2024. doi: 10.5312/wjo.v15.i6.560
Three predictive scores compared in a retrospective multicenter study of nonunion tibial shaft fracture
Davide Quarta, Marco Grassi, Giuliano Lattanzi, Antonio Pompilio Gigante, Alessio D'Anca, Domenico Potena
Davide Quarta, Marco Grassi, Giuliano Lattanzi, Antonio Pompilio Gigante, Clinical Orthopedics, Department of Clinical and Molecular Science, Università Politecnica Delle Marche, Ancona 60126, Italy
Alessio D'Anca, Domenico Potena, Department of Information and Engineering, Università Politecnica delle Marche, Ancona 60121, Italy
Author contributions: Gigante AP and Quarta D designed the study; Quarta D, Lattanzi G, and Grassi M collected the patients’ clinical data; Quarta D and Grassi M analyzed the data; Quarta D wrote the paper; Potena D and D’Anca A contributed to the statistical analysis; all authors read and approved the final manuscript.
Institutional review board statement: The study was reviewed and approved by the Ethics committee of Università Politecnica delle Marche.
Informed consent statement: All study participants or their legal guardian provided informed written consent about personal and medical data collection prior to study enrolment.
Conflict-of-interest statement: We have no financial relationships to disclose.
Data sharing statement: No additional data are available.
STROBE statement: The authors have read the STROBE Statement-checklist of items, and the manuscript was prepared and revised according to the STROBE Statement-checklist of items.
Open-Access: This article is an open-access article that was selected by an in-house editor and fully peer-reviewed by external reviewers. It is distributed in accordance with the Creative Commons Attribution NonCommercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited and the use is non-commercial. See: https://creativecommons.org/Licenses/by-nc/4.0/.
Corresponding author: Davide Quarta, MD, Doctor, Clinical Orthopedics, Department of Clinical and Molecular Science, Università Politecnica Delle Marche, Via Conca 71, Ancona 60126, Italy. davide.quarta18@libero.it
Received: December 3, 2023
Revised: March 1, 2024
Accepted: April 25, 2024
Published online: June 18, 2024
Processing time: 192 Days and 8.7 Hours
Abstract
BACKGROUND

Delayed union, malunion, and nonunion are serious complications in the healing of fractures. Predicting the risk of nonunion before or after surgery is challenging.

AIM

To compare the most prevalent predictive scores of nonunion used in clinical practice to determine the most accurate score for predicting nonunion.

METHODS

We collected data from patients with tibial shaft fractures undergoing surgery from January 2016 to December 2020 in three different trauma hospitals. In this retrospective multicenter study, we considered only fractures treated with intramedullary nailing. We calculated the tibia FRACTure prediction healING days (FRACTING) score, Nonunion Risk Determination score, and Leeds-Genoa Nonunion Index (LEG-NUI) score at the time of definitive fixation.

RESULTS

Of the 130 patients enrolled, 89 (68.4%) healed within 9 months and were classified as union. The remaining patients (n = 41, 31.5%) healed after more than 9 months or underwent other surgical procedures and were classified as nonunion. After calculation of the three scores, LEG-NUI and FRACTING were the most accurate at predicting healing.

CONCLUSION

LEG-NUI and FRACTING showed the best performances by accurately predicting union and nonunion.

Keywords: Trauma, Bone, Tibial fracture, Nonunion, Scores, Prediction model

Core Tip: Nonunion continues to be one of the most harmful complications after fracture treatment. Preventative strategies and early identification of its development are needed to successfully manage nonunion fractures. In this study, we compared the most prevalent predictive models of nonunion fractures to determine the accuracy and risk factors.