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Analysis of recovery trajectories in degenerative cervical myelopathy to facilitate improved patient counseling and individualized treatment recommendations

Blessing N. R. Jaja Neuroscience Research Program, Li Ka Shing Knowledge Institute, St. Michael’s Hospital, Toronto;

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Christopher D. Witiw Neuroscience Research Program, Li Ka Shing Knowledge Institute, St. Michael’s Hospital, Toronto;
Department of Surgery, Division of Neurosurgery, University of Toronto;

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Erin M. Harrington Trauma and Neurosurgery Research Program, St. Michael’s Hospital, Toronto; and

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Yingshi He Trauma and Neurosurgery Research Program, St. Michael’s Hospital, Toronto; and

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Ali Moghaddamjou Department of Surgery, Division of Neurosurgery, University of Toronto;

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Michael G. Fehlings Neuroscience Research Program, Li Ka Shing Knowledge Institute, St. Michael’s Hospital, Toronto;
Division of Neurosurgery, Toronto Western Hospital, University Health Network, Toronto, Ontario, Canada

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Jefferson R. Wilson Neuroscience Research Program, Li Ka Shing Knowledge Institute, St. Michael’s Hospital, Toronto;
Department of Surgery, Division of Neurosurgery, University of Toronto;

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OBJECTIVE

There is a need to better understand and predict postsurgical outcomes for degenerative cervical myelopathy (DCM) patients, particularly to support treatment decisions for patients with mild DCM. The goal of this study was to identify and predict outcome trajectories for DCM patients up to 2 years postsurgery.

开云体育世界杯赔率

The authors analyzed two North American multicenter prospective DCM studies (n = 757). Functional recovery and physical health component quality of life were assessed in DCM patients at baseline, 6 months, and 1 and 2 years postoperatively using the modified Japanese Orthopaedic Association (mJOA) score and Physical Component Summary (PCS) of the SF-36, respectively. Group-based trajectory modeling was used to identify recovery trajectories for mild, moderate, and severe DCM. Prediction models for recovery trajectories were developed and validated in bootstrap resamples.

RESULTS

Two recovery trajectories were identified for the functional and physical components of quality of life: good recovery and marginal recovery. Depending on outcome and myelopathy severity, one-half to three-fourths of the study patients followed the good recovery trajectory characterized by improvement in mJOA and PCS scores over time. The remaining one-half to one-fourth of patients followed the marginal recovery trajectory, experiencing little improvement and, in certain cases, worsening postoperatively. The prediction model for mild DCM had an area under the curve of 0.72 (95% CI 0.65–0.80), with preoperative neck pain, smoking, and posterior surgical approach noted as dominant predictors of marginal recovery.

CONCLUSIONS

Surgically treated DCM patients follow distinct recovery trajectories in the first 2 years postoperatively. While most patients experience substantial improvement, a significant minority experience little improvement or worsening. The ability to predict DCM patient recovery trajectories in the preoperative setting facilitates the formulation of individualized treatment recommendations for patients with mild symptoms.

ABBREVIATIONS

CITL = calibration in the large ; DCM = degenerative cervical myelopathy ; GBTM = group-based trajectory modeling ; LASSO = Least Absolute Shrinkage and Selection Operator ; MCID = minimal clinically important difference ; mJOA = modified Japanese Orthopaedic Association ; PCS = Physical Component Summary ; SMD = standardized mean difference .

Supplementary Materials

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Approaching the debate of laminectomy versus fusion for grade 1 lumbar spondylolisthesis, the authors leveraged simulation to show how differences between the fusion groups of landmark randomized control trials (RCTs) led to seemingly divergent conclusions, and they offer insights into the design of future RCTs. Lami = laminectomy alone; SLIP = Spinal Laminectomy versus Instrumented Pedicle Screw. See the article in this issue by Meade et al. (pp 696–704). Reprinted with permission, Cleveland Clinic Foundation ©2023. All rights reserved.

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