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A clinical model to predict postoperative improvement in sub-domains of the modified Japanese Orthopedic Association score for degenerative cervical myelopathy
A clinical model to predict postoperative improvement in sub-domains of the modified Japanese Orthopedic Association score for degenerative cervical myelopathy
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A clinical model to predict postoperative improvement in sub-domains of the modified Japanese Orthopedic Association score for degenerative cervical myelopathy
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A clinical model to predict postoperative improvement in sub-domains of the modified Japanese Orthopedic Association score for degenerative cervical myelopathy
A clinical model to predict postoperative improvement in sub-domains of the modified Japanese Orthopedic Association score for degenerative cervical myelopathy

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A clinical model to predict postoperative improvement in sub-domains of the modified Japanese Orthopedic Association score for degenerative cervical myelopathy
A clinical model to predict postoperative improvement in sub-domains of the modified Japanese Orthopedic Association score for degenerative cervical myelopathy
Journal Article

A clinical model to predict postoperative improvement in sub-domains of the modified Japanese Orthopedic Association score for degenerative cervical myelopathy

2023
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Overview
PurposeThe modified Japanese Orthopedic Association (mJOA) score consists of six sub-domains and is used to quantify the severity of cervical myelopathy. The current study aimed to assess for predictors of postoperative mJOA sub-domains scores following elective surgical management for patients with cervical myelopathy and develop the first clinical prediction model for 12-month mJOA sub-domain scores.Please confirm if the author names are presented accurately and in the correct sequence (given name, middle name/initial, family name). Author 1 Given name: [Byron F.] Last name [Stephens], Author 2 Given name: [Lydia J.] Last name [McKeithan], Author 3 Given name: [W. Hunter] Last name [Waddell], Author 4 Given name: [Anthony M.] Last name [Steinle], Author 5 Given name: [Wilson E.] Last name [Vaughan], Author 6 Given name: [Jacquelyn S.] Last name [Pennings], Author 7 Given name: [Jacquelyn S.] Last name [Pennings], Author 8 Given name: [Scott L.] Last name [Zuckerman], Author 9 Given name: [Kristin R.] Last name [Archer], Author 10 Given name: [Amir M.] Last name [Abtahi] Also, kindly confirm the details in the metadata are correct.Last Author listed should be Kristin R. ArcherMethodsA multivariable proportional odds ordinal regression model was developed for patients with cervical myelopathy. The model included patient demographic, clinical, and surgery covariates along with baseline sub-domain scores. The model was internally validated using bootstrap resampling to estimate the likely performance on a new sample of patients.ResultsThe model identified mJOA baseline sub-domains to be the strongest predictors of 12-month scores, with numbness in legs and ability to walk predicting five of the six mJOA items. Additional covariates predicting three or more items included age, preoperative anxiety/depression, gender, race, employment status, duration of symptoms, smoking status, and radiographic presence of listhesis. Surgical approach, presence of motor deficits, number of surgical levels involved, history of diabetes mellitus, workers’ compensation claim, and patient insurance had no impact on 12-month mJOA scores.ConclusionOur study developed and validated a clinical prediction model for improvement in mJOA scores at 12 months following surgery. The results highlight the importance of assessing preoperative numbness, walking ability, modifiable variables of anxiety/depression, and smoking status. This model has the potential to assist surgeons, patients, and families when considering surgery for cervical myelopathy.Level of evidenceLevel III.