Which Metrological Index, the BASMI or EDASMI, is Best Correlatedwith Disease-Related Parameters in Spondylarthritis Patients?
Bibliographic record
Abstract
OBJECTIVE: This study aimed at comparing the Edmonton Ankylosing Spondylitis Metrology Index (EDASMI) and Bath Ankylosing Spondylitis Metrology Index (BASMI) to determine which of the two is best correlated with disease-related parameters in axial spondyloarthritis (axSpA) patients. METHODS: A cross-sectional study was carried out involving 86 patients with radiographic axSpA. Sociodemographic data, the Bath Ankylosing Spondylitis Disease Activity Index (BASDAI), the Ankylosing Spondylitis Disease Activity Score (ASDAS), the Bath Ankylosing Spondylitis Functional Index (BASFI), and the Ankylosing Spondylitis Quality of Life (ASQoL) questionnaire were applied. Spinal mobility was assessed by two indices: the BASMI and the EDASMI. Structural damage of the spine was also evaluated by two indices: the Bath Ankylosing Spondylitis Radiology Index (BASRI) and the modified Stoke Ankylosing Spondylitis Spine Score (mSASSS). RESULTS: Eighty-six patients with an average age of 43.21 ± 11.43 years (20-79) were included. Impaired spinal mobility, which corresponds to higher BASMI scores, was correlated with prolonged disease duration (p < 0.01, r = 0.310), higher ASDAS-CRP (p < 0.001, r = 0.386), severe functional disability on the BASFI (p < 0.01, r = 0.505) and poorer quality of life according to the ASQoL (p < 0.01, r = 0.369). However, the EDASMI score did not correlate with any disease parameter. The BASMI was correlated with the total BASRI (p < 0.01, r = 0.634) and mSASSS (p < 0.01, r = 0.388). Unlike the BASMI, the EDASMI was neither correlated with the BASRI (p = 0.520, r = 0.245) nor the mSASSS (p = 0.252, r = -0.120). CONCLUSION: Our results indicate that among the studied metrological indices, the BASMI is more contributory since it is correlated with clinical disease parameters and structural damage, unlike the EDASMI.
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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 | 0.002 |
| 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 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".