P.223 Correlating the pre- and post-operative subjective experience of myelopathic impairments with the objective clinical exam
Bibliographic record
Abstract
Background: Degenerative cervical myelopathy is a debilitating condition of the spinal column resulting in a progressive, clinically measurable loss of motor and sensory function secondary to spinal cord compression. We sought to correlate the patient’s subjective experience of specific myelopathic impairments with components of the objective clinical exam, to determine if the latter provides any clinically-relevant information postoperatively. Methods: Thirty-eight myelopathy patients consented to complete the mJOA questionnaire and receive a physical exam preoperatively, and 6-weeks and 6-months postoperatively. mJOA components were correlated with the physical exam using Spearman correlations with an alpha of 0.05. Results: mJOA scores for sensation and lower limb motor function correlated with the sensory and lower limb motor exams respectively, both preoperatively and 6-weeks postoperatively. mJOA scores for upper limb motor function did not correlate with the upper limb motor exam at either timepoint. Conclusions: At baseline and immediately postoperatively, patients self-report sensation and lower limb motor function accurately. However, the patients’ subjective experience of upper limb motor function does not align with clinical exam findings, suggesting either a continued need for this component of the physical exam or a need for tools that better correlate with the patient’s experience of upper limb motor impairment.
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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 | 0.001 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.010 | 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".