Validation of the Spondyloarthritis Research Consortium of Canada magnetic resonance imaging spinal inflammation index: Is it necessary to score the entire spine?
Bibliographic record
Abstract
OBJECTIVE: The Spondyloarthritis Research Consortium of Canada (SPARCC) magnetic resonance imaging (MRI) spinal inflammation index has been developed to objectively measure inflammation in ankylosing spondylitis (AS) and to assess change in response to therapeutic intervention. Scoring of the entire spine limits feasibility and a scoring method that records inflammation in only the more severely affected spinal segments may improve feasibility without sacrificing performance. METHODS: MRI films of 68 patients with AS were assessed in random order by 2 blinded readers. Interreader reliability was assessed by intraclass correlation coefficient. Pre- and posttreatment MRI films of 29 patients randomized to placebo or anti-tumor necrosis factor alpha (anti-TNFalpha) therapy were read by readers blinded to chronology, and responsiveness was assessed by effect size and standardized response mean. The performance of scores based on 6, 8, 10, and all 23 spinal discovertebral units (DVU) was compared. RESULTS: The median number of affected spinal levels per patient was 6.0 and 62% of all affected levels were included when analysis was limited to only the 6 most severely affected levels per patient. Comparison of DVU scores that were limited to only the more severely affected DVU (6-, 8-, 10-DVU score) with scores for all 23 spinal DVU showed excellent interreader reliability for status and change scores (Spearman's correlation >0.90) as well as similar construct validity. Responsiveness to anti-TNFalpha therapy was greater when the more limited scoring methods were used and was greatest with the 6-DVU score. CONCLUSION: The SPARCC MRI spinal inflammation index performs better when analysis is limited to a maximum of 6 most severely affected levels compared with assessment of the entire spine. This should improve its feasibility in clinical trials and research.
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 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 | 0.018 | 0.035 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".