La calprotectine sérique est corrélée avec l’activité de la maladie dans les spondyloarthrites axiales débutantes mais ne prédit pas la progression radiographique à 2 ans : résultats de la cohorte DESIR
Bibliographic record
Abstract
Objectives: To determine whether serum calprotectin levels at baseline can predict the radiographic progression in spine after 2 years in the early axSpA cohort DESIR (DEvenir des Spondyloarthrites Indifférenciées Récentes). Methods: Patients presenting with early inflammatory back pain from DESIR cohort were analyzed. axSpA patients were defined as patients who fulfilled the axial Assessment in SpondyloArthritis Society (ASAS) criteria at baseline. Calprotectin was assessed in the serum at the inclusion by enzyme-linked immunosorbent assay. Radiographic spinal progression was defined as worsening by ≥2 units of the modified Stoke Ankylosing Spondylitis Spine Score (mSASSS) 2 years after the inclusion. Magnetic resonance imaging (MRI) spine and sacroiliac joint (SIJ) inflammation was graded using BERLIN and Spondyloarthritis Research Consortium of Canada (SPARCC) score. Results: Overall, 426 had an early axSpA with a calprotectin level assessment. 211 patients had mSASSS scoring at baseline and M24 and 399 an MRI scoring at baseline. Calprotectin level was significantly higher in patients who fulfilled axSpA ASAS sacroiliitis arm than those who did not fulfill or who fulfilled ASAS HLA B27 arm without signs of sacroiliitis. Calprotectin at baseline did not predict radiographic progression at M24 (p=0.81). Calprotectin correlated at baseline with SIJ, spine MRI inflammation (Berlin score (r=0.15, p=0.003), sacroiliac (r=0.12, p=0.012) and spine (r=0.16, p=0.002) SPARCC score) and disease activity index (BASDAI (r=0.16, p=0.001), ASDAS-CRP (r=0.26, p<0.001)). Conclusions: Calprotectin is weakly correlated with disease activity but does not seem to be a helpful biomarker for predicting clinically relevant radiographic progression at 2 years follow-up in early axSpA.
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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) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".