Development and internal validation of a clinical prediction model for acute adjacent vertebral fracture after vertebral augmentation

Author:

Hijikata Yasukazu12ORCID,Kamitani Tsukasa1,Nakahara Masayuki2,Kumamoto Shinji3,Sakai Tsubasa4,Itaya Takahiro1,Yamazaki Hajime5,Ogawa Yusuke1,Kusumegi Akira6,Inoue Takafumi7,Yoshida Takashi8,Furue Naoya9,Fukuhara Shun-ichi51011,Yamamoto Yosuke1,

Affiliation:

1. Department of Healthcare Epidemiology, School of Public Health in the Graduate School of Medicine, Kyoto University, Kyoto, Japan

2. Spine and Low Back Pain Center, Kitasuma Hospital, Hyogo, Japan

3. Department of Spinal Surgery, Fukuoka Kinen Hospital, Fukuoka, Japan

4. Department of Orthopaedic Surgery, Fukuoka Seisyukai Hospital, Fukuoka, Japan

5. Section of Clinical Epidemiology, Department of Community Medicine, Graduate School of Medicine, Kyoto University, Kyoto, Japan

6. Department of Spine and Spine Surgery, Shinkomonji Hospital, Fukuoka, Japan

7. Department of Spine Surgery, Shintakeo Hospital, Takeo, Japan

8. Department of Neurosurgery, Shimizu Hospital, Kyoto, Japan

9. Department of Orthopaedic Surgery, Fukuokawajiro Hospital, Fukuoka, Japan

10. Center for Innovative Research for Communities and Clinical Excellence, Fukushima Medical University, Fukushima, Japan

11. Shirakawa STAR for General Medicine, Fukushima Medical University, Fukushima, Japan

Abstract

Aims To develop and internally validate a preoperative clinical prediction model for acute adjacent vertebral fracture (AVF) after vertebral augmentation to support preoperative decision-making, named the after vertebral augmentation (AVA) score. Methods In this prognostic study, a multicentre, retrospective single-level vertebral augmentation cohort of 377 patients from six Japanese hospitals was used to derive an AVF prediction model. Backward stepwise selection (p < 0.05) was used to select preoperative clinical and imaging predictors for acute AVF after vertebral augmentation for up to one month, from 14 predictors. We assigned a score to each selected variable based on the regression coefficient and developed the AVA scoring system. We evaluated sensitivity and specificity for each cut-off, area under the curve (AUC), and calibration as diagnostic performance. Internal validation was conducted using bootstrapping to correct the optimism. Results Of the 377 patients used for model derivation, 58 (15%) had an acute AVF postoperatively. The following preoperative measures on multivariable analysis were summarized in the five-point AVA score: intravertebral instability (≥ 5 mm), focal kyphosis (≥ 10°), duration of symptoms (≥ 30 days), intravertebral cleft, and previous history of vertebral fracture. Internal validation showed a mean optimism of 0.019 with a corrected AUC of 0.77. A cut-off of ≤ one point was chosen to classify a low risk of AVF, for which only four of 137 patients (3%) had AVF with 92.5% sensitivity and 45.6% specificity. A cut-off of ≥ four points was chosen to classify a high risk of AVF, for which 22 of 38 (58%) had AVF with 41.5% sensitivity and 94.5% specificity. Conclusion In this study, the AVA score was found to be a simple preoperative method for the identification of patients at low and high risk of postoperative acute AVF. This model could be applied to individual patients and could aid in the decision-making before vertebral augmentation. Cite this article: Bone Joint J 2022;104-B(1):97–102.

Publisher

British Editorial Society of Bone & Joint Surgery

Subject

Orthopedics and Sports Medicine,Surgery

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