Predicting development of severe clinically relevant distal junctional kyphosis following adult cervical deformity surgery, with further distinction from mild asymptomatic episodes.

Abstract

OBJECTIVE:This retrospective cohort study aimed to develop a formal predictive model distinguishing between symptomatic and asymptomatic distal junctional kyphosis (DJK). In this study the authors identified a DJK rate of 32.2%. Predictive models were created that can be used with high reliability to help distinguish between severe symptomatic DJK and mild asymptomatic DJK through the use of surgical factors, radiographic parameters, and patient variables. METHODS:Patients with cervical deformity (CD) were stratified into asymptomatic and symptomatic DJK groups. Symptomatic: 1) DJK angle (DJKA) > 10° and either reoperation due to DJK or > 1 new-onset neurological sequela related to DJK; or 2) either a DJKA > 20° or ∆DJKA > 20°. Asymptomatic: ∆DJK > 10° in the absence of neurological sequelae. Stepwise logistic regressions were used to identify factors associated with these types of DJK. Decision tree analysis established cutoffs. RESULTS:A total of 99 patients with CD were included, with 32.2% developing DJK (34.3% asymptomatic, 65.7% symptomatic). A total of 37.5% of asymptomatic patients received a reoperation versus 62.5% symptomatic patients. Multivariate analysis identified independent baseline factors for developing symptomatic DJK as follows: pelvic incidence (OR 1.02); preoperative cervical flexibility (OR 1.04); and combined approach (OR 6.2). Having abnormal hyperkyphosis in the thoracic spine, more so than abnormal cervical lordosis, was a factor for developing symptomatic disease when analyzed against asymptomatic patients (OR 1.2). Predictive modeling identified factors that were predictive of symptomatic versus no DJK, as follows: myelopathy (modified Japanese Orthopaedic Association score 12-14); combined approach; uppermost instrumented vertebra C3 or C4; preoperative hypermobility; and > 7 levels fused (area under the curve 0.89). A predictive model for symptomatic versus asymptomatic disease (area under the curve 0.85) included being frail, T1 slope minus cervical lordosis > 20°, and a pelvic incidence > 46.3°. Controlling for baseline deformity and disability, symptomatic patients had a greater cervical sagittal vertical axis (4-8 cm: 47.6% vs 27%) and were more malaligned according to their Scoliosis Research Society sagittal vertical axis measurement (OR 0.1) than patients without DJK at 1 year (all p < 0.05). Despite their symptomatology and higher reoperation rate, outcomes equilibrated in the symptomatic cohort at 1 year following revision. CONCLUSIONS:Overall, 32.2% of patients with CD suffered from DJK. Symptomatic DJK can be predicted with high reliability. It can be further distinguished from asymptomatic occurrences by taking into account pelvic incidence and baseline cervicothoracic deformity severity.

Department

Description

Provenance

Citation

Published Version (Please cite this version)

10.3171/2021.8.spine21533

Publication Info

Passias, Peter G, Sara Naessig, Nicholas Kummer, Lara Passfall, Renaud Lafage, Virginie Lafage, Breton Line, Bassel G Diebo, et al. (2021). Predicting development of severe clinically relevant distal junctional kyphosis following adult cervical deformity surgery, with further distinction from mild asymptomatic episodes. Journal of neurosurgery. Spine, 36(6). pp. 1–8. 10.3171/2021.8.spine21533 Retrieved from https://hdl.handle.net/10161/28058.

This is constructed from limited available data and may be imprecise. To cite this article, please review & use the official citation provided by the journal.

Scholars@Duke

Passias

Peter Passias

Instructor in the Department of Orthopaedic Surgery
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.


Unless otherwise indicated, scholarly articles published by Duke faculty members are made available here with a CC-BY-NC (Creative Commons Attribution Non-Commercial) license, as enabled by the Duke Open Access Policy. If you wish to use the materials in ways not already permitted under CC-BY-NC, please consult the copyright owner. Other materials are made available here through the author’s grant of a non-exclusive license to make their work openly accessible.