Literature DB >> 24048553

A clinical prediction model to determine outcomes in patients with cervical spondylotic myelopathy undergoing surgical treatment: data from the prospective, multi-center AOSpine North America study.

Lindsay A Tetreault1, Branko Kopjar, Alexander Vaccaro, Sangwook Tim Yoon, Paul M Arnold, Eric M Massicotte, Michael G Fehlings.   

Abstract

BACKGROUND: Cervical spondylotic myelopathy is a progressive spine disease and the most common cause of spinal cord dysfunction worldwide. The objective of this study was to develop a prediction model, based on data from a prospective multi-center study, relating a combination of clinical and imaging variables to surgical outcome in patients with cervical spondylotic myelopathy.
METHODS: Two hundred and seventy-eight patients diagnosed with cervical spondylotic myelopathy treated surgically were enrolled at twelve different sites in the multi-center AOSpine North America study. Univariate analyses were performed to evaluate the relationship between outcome, assessed with the modified Japanese Orthopaedic Association (mJOA) score, and various clinical and imaging predictors. A set of important candidate variables for the final model was selected on the basis of author consensus, literature support, and statistical findings. Logistic regression was used to formulate the final model.
RESULTS: Univariate analyses demonstrated that the odds of a successful outcome decreased with a longer duration of symptoms (odds ratio [OR] = 0.80, 95% confidence interval [CI] = 0.65 to 0.98, p = 0.030); a lower baseline mJOA score (OR = 0.74, 95% CI = 0.65 to 0.84, p < 0.0001); the presence of psychological comorbidities (OR = 0.51, 95% CI = 0.29 to 0.92, p = 0.024); the presence of broad-based, unstable gait (OR = 2.72, 95% CI = 1.47 to 5.06, p = 0.0018) or other gait impairment (OR = 3.56, 95% CI = 1.75 to 7.22, p = 0.0005); and older age (OR = 0.96, 95% CI = 0.93 to 0.98, p = 0.0004). The dependent variable, the mJOA score at one year, was dichotomized for logistic regression: a "successful" outcome was defined as a final score of ≥16 and a "failed" outcome was a score of <16. The final model included age (OR = 0.97, 95% CI = 0.94 to 0.99, p = 0.0017), duration of symptoms (OR = 0.78, 95% CI = 0.61 to 0.997, p = 0.048), smoking status (OR = 0.46, 95% CI = 0.21 to 0.98, p = 0.043), impairment of gait (OR = 2.66, 95% CI = 1.17 to 6.06, p = 0.020), psychological comorbidities (OR = 0.33, 95% CI = 0.15 to 0.69, p = 0.0035), baseline mJOA score (OR = 1.22, 95% CI = 1.05 to 1.41, p = 0.0084), and baseline transverse area of the cord on magnetic resonance imaging (OR = 1.02, 95% CI = 0.99 to 1.05, p = 0.19). The area under the receiver operator characteristic curve was 0.79, indicating good model prediction.
CONCLUSIONS: On the basis of the results of the AOSpine North America study, we identified a list of the most important predictors of surgical outcome for cervical spondylotic myelopathy.

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Year:  2013        PMID: 24048553     DOI: 10.2106/JBJS.L.01323

Source DB:  PubMed          Journal:  J Bone Joint Surg Am        ISSN: 0021-9355            Impact factor:   5.284


  39 in total

1.  Predictors of morbidity and mortality among patients with cervical spondylotic myelopathy treated surgically.

Authors:  I David Kaye; Bryan J Marascalchi; Angel E Macagno; Virginie A Lafage; John A Bendo; Peter G Passias
Journal:  Eur Spine J       Date:  2015-05-23       Impact factor: 3.134

2.  Development of a model to predict the probability of incurring a complication during spine surgery.

Authors:  Pascal Zehnder; Ulrike Held; Tim Pigott; Andrea Luca; Markus Loibl; Raluca Reitmeir; Tamás Fekete; Daniel Haschtmann; Anne F Mannion
Journal:  Eur Spine J       Date:  2021-03-09       Impact factor: 3.134

3.  Early neurological recovery course after surgical treatment of cervical spondylotic myelopathy: a prospective study with 2-year follow-up using three different functional assessment tests.

Authors:  Hugues Pascal Moussellard; Alain Meyer; David Biot; Frédéric Khiami; Elhadi Sariali
Journal:  Eur Spine J       Date:  2014-04-29       Impact factor: 3.134

Review 4.  Predictive modeling of complications.

Authors:  Joseph A Osorio; Justin K Scheer; Christopher P Ames
Journal:  Curr Rev Musculoskelet Med       Date:  2016-09

5.  Diffusion tensor imaging can predict surgical outcomes of patients with cervical compression myelopathy.

Authors:  Satoshi Maki; Masao Koda; Mitsuhiro Kitamura; Taigo Inada; Koshiro Kamiya; Mitsutoshi Ota; Yasushi Iijima; Junya Saito; Yoshitada Masuda; Koji Matsumoto; Masatoshi Kojima; Takayuki Obata; Kazuhisa Takahashi; Masashi Yamazaki; Takeo Furuya
Journal:  Eur Spine J       Date:  2017-06-16       Impact factor: 3.134

6.  Use of multivariate linear regression and support vector regression to predict functional outcome after surgery for cervical spondylotic myelopathy.

Authors:  Haydn Hoffman; Sunghoon I Lee; Jordan H Garst; Derek S Lu; Charles H Li; Daniel T Nagasawa; Nima Ghalehsari; Nima Jahanforouz; Mehrdad Razaghy; Marie Espinal; Amir Ghavamrezaii; Brian H Paak; Irene Wu; Majid Sarrafzadeh; Daniel C Lu
Journal:  J Clin Neurosci       Date:  2015-06-23       Impact factor: 1.961

7.  Delayed decompression exacerbates ischemia-reperfusion injury in cervical compressive myelopathy.

Authors:  Pia M Vidal; Spyridon K Karadimas; Antigona Ulndreaj; Alex M Laliberte; Lindsay Tetreault; Stefania Forner; Jian Wang; Warren D Foltz; Michael G Fehlings
Journal:  JCI Insight       Date:  2017-06-02

Review 8.  Degenerative cervical myelopathy.

Authors:  So Kato; Michael Fehlings
Journal:  Curr Rev Musculoskelet Med       Date:  2016-09

9.  Preoperative Neck Disability Severity Limits Extent of Postoperative Improvement Following Cervical Spine Procedures.

Authors:  Elliot D K Cha; Conor P Lynch; Shruthi Mohan; Cara E Geoghegan; Caroline N Jadczak; Kern Singh
Journal:  Neurospine       Date:  2021-06-30

10.  A Bibliometric Analysis and Visualization of Current Research Trends in the Treatment of Cervical Spondylotic Myelopathy.

Authors:  Mengchen Yin; Chongqing Xu; Junming Ma; Jie Ye; Wen Mo
Journal:  Global Spine J       Date:  2020-09-01
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