Differential Diagnosis for Cervical Spondylotic Myelopathy
Bibliographic record
Abstract
STUDY DESIGN: Literature review. OBJECTIVE: To identify case series that have been confused with cervical spondylotic myelopathy (CSM) to develop a comprehensive differential diagnosis. SUMMARY OF BACKGROUND DATA: Myelopathy can be caused by a number of different etiologies. In those patients with CSM, the presentation is not always clear. Distinct radiographical and clinical characteristics, which are not always obvious, aid in arriving at the correct diagnosis. METHODS: A PubMed search was done to identify reports written in English describing conditions that may present in a manner similar to CSM to differentiate them from CSM. Material from review articles and relevant textbooks was also considered. Information regarding the number of patients, the specific diagnosis presenting as myelopathy, the diagnostic findings, and the method(s) for distinguishing CSM from the initial diagnosis was abstracted from included articles. Salient features of the conditions were summarized. RESULTS: A total of 35 citations (totaling 474 patients) that reported on diagnoses confused with CSM based on clinical presentation were included. All were case reports or small case series. The differential diagnoses were organized into 7 categories: congenital/anatomic, degenerative, neoplastic, inflammatory/autoimmune, idiopathic, circulatory, and metabolic. The primary conditions in the differential included amyotrophic lateral sclerosis, multiple sclerosis, syringomyelia, and spinal tumors. CONCLUSION: In the vast majority of cases, magnetic resonance imaging was an invaluable tool in determining the correct diagnosis. Electrodiagnostic studies, cerebrospinal fluid profile, unique symptomatology, and consideration of patient demographics can also aid in the diagnosis. Bilateral sensory complaints in the hands are suspicious for cervical cord pathology and MR imaging of the same should be done even if the electromyography/nerve conduction studies (NCS) suggest bilateral carpal tunnel syndrome. SUMMARY STATEMENTS: Physical exam findings are not always consistent with severity of disease in CSM; therefore, correlation to plain radiographs, MRI, and patient symptomatology is essential for arriving at the correct diagnosis. In some cases where these studies are still equivocal, use of other studies should be considered including electrodiagnostic studies as well as cerebrospinal fluid examination.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.017 | 0.012 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.000 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".