Predicting the Magnitude of Distal Junctional Kyphosis Following Cervical Deformity Correction.

Abstract

Study design

Retrospective review of a cervical deformity database.

Objective

This study aimed to develop a model that can predict the postoperative distal junctional kyphosis angle (DJKA) using preoperative and postoperative radiographic measurements.

Summary of background data

Distal junctional kyphosis (DJK) is a complication following cervical deformity correction that can reduce of patient quality of life and functional status. Although researchers have identified the risk factors for DJK, no model has been proposed to predict the magnitude of DJK.

Materials and methods

The DJKA was defined as the Cobb angle from the lower instrumented vertebra (LIV) to LIV-2 with traditional DJK having a DJKA change >10°. Models were trained using 66.6% of the randomly selected patients and validated in the remaining 33.3%. Preoperative and postoperative radiographic parameters associated with DJK were identified and ranked using a conditional variable importance table. Linear regression models were developed using the factors most strongly associated with postoperative DJKA.

Results

A total of 131 patients were included with a mean follow-up duration of 14±8 months. The mean postoperative DJKA was 14.6±14° and occurred in 35% of the patients. No significant differences between the training and validation cohort were observed. The variables most associated with postoperative DJK were: preoperative DJKA (DJKApre), postoperative C2-LIV, and change in cervical lordosis (∆CL). The model identified the following equation as predictive of DJKA: DJKA=9.365+(0.123×∆CL)-(0.315×∆C2-LIV)-(0.054×DJKApre). The predicted and actual postoperative DJKA values were highly correlated ( R =0.871, R2 =0.759, P <0.001).

Conclusions

The variables that most increased the DJKA were the preoperative DJKA, postoperative alignment within the construct, and change in cervical lordosis. Future studies can build upon the model developed to be applied in a clinical setting when planning for cervical deformity correction.

Department

Description

Provenance

Citation

Published Version (Please cite this version)

10.1097/brs.0000000000004492

Publication Info

Ayres, Ethan W, Themistocles S Protopsaltis, Fares Ani, Renaud Lafage, Arnaav Walia, Gregory M Mundis, Justin S Smith, David K Hamilton, et al. (2023). Predicting the Magnitude of Distal Junctional Kyphosis Following Cervical Deformity Correction. Spine, 48(4). pp. 232–239. 10.1097/brs.0000000000004492 Retrieved from https://hdl.handle.net/10161/27974.

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Scholars@Duke

Shaffrey

Christopher Ignatius Shaffrey

Professor of Orthopaedic Surgery

I have more than 25 years of experience treating patients of all ages with spinal disorders. I have had an interest in the management of spinal disorders since starting my medical education. I performed residencies in both orthopaedic surgery and neurosurgery to gain a comprehensive understanding of the entire range of spinal disorders. My goal has been to find innovative ways to manage the range of spinal conditions, straightforward to complex. I have a focus on managing patients with complex spinal disorders. My patient evaluation and management philosophy is to provide engaged, compassionate care that focuses on providing the simplest and least aggressive treatment option for a particular condition. In many cases, non-operative treatment options exist to improve a patient’s symptoms. I have been actively engaged in clinical research to find the best ways to manage spinal disorders in order to achieve better results with fewer complications.


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