A New Performance Test for Cervical Myelopathy
Bibliographic record
Abstract
STUDY DESIGN: Our original performance test for evaluating the severity of cervical myelopathy, the triangle step test (TST), was introduced along with an assessment of its validity. OBJECTIVE: The TST was designed to evaluate the lower extremity motor function objectively and quantitatively. This study aimed to assess the validity of the test by analyzing the relation to the other analytic methods. SUMMARY OF BACKGROUND DATA: Several rating scales and performance tests have been proposed to evaluate the severity of cervical myelopathy. Simple walking test is useful; however, the test is limited for the patients who can walk safely. METHODS: Each subject sitting on a chair was instructed to step on marks at each apex of a triangular board and the number of steps in 10 seconds was counted for each foot. The subjects were 270 cervical myelopathy patients who had visited our hospital since 2002. As a control group, 60 healthy adults also underwent this test. All subjects were simultaneously evaluated by the Nurick score, the Japan Orthopedic Association score and the finger grip and release test. An assessment of the effect of surgery was analyzed for 94 patients who underwent surgical treatments. RESULTS: The mean of the lower count for each subject (TST score) in the control group was 25.4 +/- 3.7 steps, which was superior to 18.4 +/- 5.2 steps for myelopathy patients. TST score significantly correlated to the other analytic measures for cervical myelopathy. Regarding the effect of surgery, a performance of 16.7 +/- 4.5 steps before surgery improved to 21.2 +/- 4.9 steps at follow-up. Patients who could step more than 20 times before surgery, showed greater neurologic recovery. CONCLUSION: TST score correlated with other analytic methods for cervical myelopathy. This test is very useful to quantitatively evaluate lower extremity function and its improvement following surgical intervention.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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 teacher head, 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".