Visual Assessment of the Spine Bruckel Instrument, a Novel Status Tool to Reflect Appearance of the Spine in Patients with Ankylosing Spondylitis
Bibliographic record
Abstract
OBJECTIVE: The Visual Assessment of the Spine Bruckel Instrument (VASBI) is a new status tool developed by the Spondylitis Association of America and the University of Toronto to reflect spinal appearance in patients with ankylosing spondylitis (AS). Our objective was to validate the VASBI according to the Outcome Measures in Rheumatoid Arthritis Clinical Trials filter (truth, discrimination, and feasibility). METHODS: Three hundred patients with AS were asked to rate their degree of perceived spinal deformity using the VASBI. To evaluate construct validity, VASBI scores were compared with functional outcome, spinal mobility, and radiographic spinal damage. Test-retest reliability was evaluated using kappa statistic (kappa). RESULTS: Patient VASBI demonstrated strong correlation with spinal mobility (r = 0.543) and moderate correlation with functional impairment (r = 0.490) and structural damage (r = 0.309). Reliability for VASBI was very good (kappa = 0.973, p < 0.001). CONCLUSION: The VASBI is a novel tool with practical applications in a busy clinical setting as it simplifies assessment of AS spinal deformity. Our study demonstrates that the VASBI has good feasibility, construct validity, and reliability.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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 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".