The Diagnostic Performance of Vertebral Displacement Measurements Derived From Ultrasonic Indentation in an In Vivo Model of Degenerative Disc Disease
Bibliographic record
Abstract
STUDY DESIGN: The diagnostic performance of a newly described variable was assessed in an in vivo model of disc degeneration using a split-pair experimental design. OBJECTIVE: To determine if vertebral displacement measures generated from ultrasonic indentation could distinguish between experimental and control groups of animals. SUMMARY OF BACKGROUND DATA: Few procedures are available that noninvasively assess subcutaneous vertebral mechanics. Information from such a procedure would be of value in determining potential clinical relevance of spinal mechanics with respect to low back pain. METHODS: Eight adolescent pigs underwent endplate perforation surgery to initiate lumbar disc degeneration. After 4 months of recovery, these and eight age-matched controls were assessed by ultrasonic indentation, a noninvasive procedure that quantifies vertebral displacements in the plane of loading-indentation. Each animal then received a facetectomy and was reindented at the same location as confirmed by ultrasonic imaging. Discal materials were removed postmortem for analysis. RESULTS: Degenerative discs exhibited morphologic changes consistent with early degenerative disc disease. Prefacetectomy comparison of vertebral displacement measures between control and experimental animals resulted in sensitivity, specificity, and diagnostic accuracy values of 75.0%, 83.3%, and 77%, respectively. After facetectomy these values increased to 87.5%, 83.3%, and 85%, respectively. These measures of diagnostic performance were comparable or superior to those of existing clinical techniques (invasive or otherwise) used to assess degenerative conditions of the spine. CONCLUSIONS: The results of this study suggest that noninvasive measures of vertebral displacement are clinically significant and possess the additional advantages of being objective and noninvasive.
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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) | 0.000 | 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".