Scanning of the Sacroiliac Joint and Entheses by Color Doppler Ultrasonography in Patients with Ankylosing Spondylitis
Bibliographic record
Abstract
OBJECTIVE: To assess Doppler ultrasonography by comparing its detection of sacroiliitis with detection of enthesitis in patients with ankylosing spondylitis (AS). METHODS: One hundred sixty-one patients with AS (according to modified New York criteria or Spondyloarthritis International Society classification criteria for axial spondyloarthritis) underwent ultrasonography (US) of the sacroiliac joint (SIJ) and major entheses of the lower limbs. Vascularization of the SIJ and morphologic changes and vascularization of entheses were observed. The resistive index of the SIJ was measured. Doppler ultrasonography examination was repeated in 20 patients by another ultrasonographer. RESULTS: In the AS active group [Bath Ankylosing Spondylitis Disease Activity Index (BASDAI) ≥ 4], 90.7% of SIJ showed vascularization; this was significantly more than in the inactive group (38.5%). The resistive index of the active group in the SIJ area was significantly lower than that of the inactive group. Doppler US scanning of the SIJ was more sensitive (92.0%) than that of the entheses (52.2%). Agreement of Doppler US scanning of the SIJ and BASDAI was good, while agreement of the entheses and BASDAI was poor. CONCLUSION: Lower resistive index value and vascularization in the SIJ had good agreement with AS activity. Doppler US is more sensitive in detecting sacroiliitis than in detecting enthesitis.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| 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".