Background: Long-term data on postoperative neurological survivorship for patients with degenerative cervical myelopathy (DCM) undergoing decompressive surgery are limited. The purposes of this study were to assess neurological survivorship after primary decompressive surgery for DCM and to identify predictors for postoperative deterioration.Methods: A longitudinal clinical data set containing surgical details, medical comorbidities, and radiographic features was assembled for 195 patients who underwent a surgical procedure for DCM between 1999 and 2020, with a mean period of observation of 75.9 months. Kaplan-Meier curves were plotted, and a log-rank test was performed for the univariate analysis of factors related to neurological failure. Lasso regression facilitated the variable selection in the Cox proportional hazards model for multivariate analysis.Results: The overall neurological survivorship was 89.3% at 5 years and 77.3% at 10 years. Cox multivariate analysis following lasso regression identified elevated hazard ratios (HRs) for suture laminoplasty (HR, 4.76; p < 0.001), renal failure (HR, 4.43; p = 0.013), T2 hyperintensity (HR, 3.34; p = 0.05), and ossification of the posterior longitudinal ligament (OPLL) (HR, 2.32; p = 0.032). Subgroup analysis among subjects with OPLL demonstrated that the neurological failure rate was significantly higher in the absence of fusion (77.8% compared with 26.3%; p = 0.019).Conclusions: Overall, patients who underwent a surgical procedure for DCM exhibited an extended period with neurological improvement. Cervical fusion was indicated in OPLL to reduce neurological failure. Our findings on predictors for early deterioration facilitate case selection, prognostication, and counseling as the volume of primary cervical spine surgeries and reoperations increases globally.Level of Evidence: Prognostic Level III. See Instructions for Authors for a complete description of levels of evidence. Degenerative cervical myelopathy (DCM) is an acquired cause of spinal cord dysfunction estimated to affect 5% of the population over the age of 40 years 1 . Cervical spondylosis due to age-related degenerative changes to the intervertebral disc and facet joints is the predominant cause of canal narrowing in the middle-aged population, but ossification of the posterior longitudinal ligament (OPLL) accounts for a considerable case volume in the Asian population, with a tendency for affecting younger adults 2 . Surgical decompression of the cervical spinal cord is an effective means to prevent neurological deterio-ration and promote recovery in patients with DCM. Practice guidelines have recommended a surgical procedure for patients with moderate or severe symptoms according to the modified Japanese Orthopaedic Association (mJOA) score 1 . Short-term to intermediate-term outcomes of surgical decompression have been well described in the literature. Over 70% of patients have demonstrated neurological improvement postoperatively, with a slowing of recovery by 6 months 2 . The postoperative mJOA ...

Current practice of osteoarthritis has its insufficiencies which researchers are tackling with artificial intelligence (AI). This article discusses three kinds of AI models, namely diagnostic models, prediction models and morphological models. Diagnostic models enhance efficiency in diagnosis by providing an automated algorithm in knee images processing. Prediction models utilize behavioral and radiological data to assess the risk of osteoarthritis before symptom onset and needs to perform surgery. Morphological models detect biomechanical changes to facilitate understanding of pathophysiology and provide personalized intervention. Through reviewing present evidence, we demonstrate that AI could assist doctors in diagnosis, predict osteoarthritis and guide future research.