Workshop (Clinical/Best Practice Implementation) ID 2000428
Bibliographic record
Abstract
Background/Objectives This workshop aims to overview degenerative cervical myelopathy (DCM), which is the most common cause of non-traumatic spinal cord injury across the world. DCM is estimated to affect approximately 1 in 50 adults; however, < 10% receive a diagnosis, and lifelong disability remains a common outcome. Upon completion of this workshop, attendees will (1) understand the diagnostic criteria and investigations for DCM and avoid misdiagnosis in the primary care level; (2) recognise the indications and role of surgical treatment; (3) comprehend the impact of prehabilitation and rehabilitation; (4) understand the alternatives for non-operative management of DCM; and (5) appreciate the importance of raising awareness of this disease. Methods/Overview This workshop will review the diagnostic criteria and investigations for individuals with different degrees of DCM, the current clinical practice guidelines for management of DCM with focus on the role of surgical decompression of spinal cord, the role of prehabilitation and rehabilitation, current non-operative options for patients with DCM, and some initiatives focused on raising awareness of this disease. Results This workshop will include lectures (10-15 minutes each) with illustrative cases followed by open discussion on the following topics: (i) diagnosis, misdiagnosis and investigations in DCM; (ii) surgical management of DCM; (iii) prehabilitation and rehabilitation in DCM; and (iv) non-operative management of DCM. Conclusions Although DCM is the most common cause of non-traumatic spinal cord disease, there is a need for the development of a tailored and multi-disciplinary care framework for management of DCM, which would improve patients’ outcomes. Greater awareness of DCM among healthcare professionals is urged to avoid misdiagnosis and mitigate the long-term consequences of this disease.
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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 | 0.013 | 0.022 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.006 | 0.004 |
| Open science | 0.004 | 0.009 |
| Research integrity | 0.009 | 0.006 |
| Insufficient payload (model declined to judge) | 0.550 | 0.289 |
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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.
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".