Gadolinium contrast-enhanced MRI sequence does not have an incremental value in the assessment of sacroiliitis in patients with early inflammatory back pain by using MRI in combination with pelvic radiographs: a 2-year follow-up study.
Bibliographic record
Abstract
OBJECTIVES: To evaluate the potential incremental value in detecting sacroiliitis of the T1 post-gadolinium diethylenetriaminepenta-acetic acid (Gd-DTPA) MRI sequence of the sacroiliac joints (SIJ) compared with the combination of short tau inversion recovery (STIR) MRI sequence and pelvic radiographs in patients with inflammatory back pain (IBP) suspected for axial spondyloarthritis. METHODS: A 2-year follow-up study was conducted in patients with IBP of less than 2 years duration. Annual MRI of the SIJ (MRI-SIJ) was performed and scored for bone marrow oedema (BME). Pelvic radiographs were scored according to the modified New York (mNY) criteria. Agreement on the presence of BME detected by the STIR and post-Gd-DTPA sequence and the incremental value of post-Gd-DTPA sequence over STIR plus radiographs was analysed by descriptive methods and kappa statistics. RESULTS: At baseline, 20 (29%) out of 68 patients (38% male; mean (SD) age 34.9 (10.3) years) enrolled had BME both on the STIR and post-Gd-DTPA sequences; 4 patients (6%) on the STIR sequence only; none on the post-Gd-DTPA sequence only (kappa value: 0.87). Fifteen (22%) patients fulfilled the mNY criteria at baseline. Sixty-two (91%) patients had at least 1 follow-up MRI-SIJ. At 2-year follow-up, 2 patients had BME on the post-Gd-DTPA sequence without BME on the STIR sequence. These 2 patients already fulfilled the mNY criteria at baseline. CONCLUSIONS: In this cohort of patients with early IBP, the post-Gd-DTPA sequence of the MRI-SIJ did not have an incremental value in the detection of sacroiliitis compared with the STIR sequence plus pelvic radiographs.
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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 | 0.003 | 0.011 |
| 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 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".