Bibliographic record
Abstract
OBJECTIVE: To review recent developments in diagnosis and treatment of ankylosing spondylitis (AS). QUALITY OF EVIDENCE: Level I evidence from three randomized placebo-controlled trials shows that AS is highly responsive to anti-tumour necrosis factor-alpha (anti-TNFalpha) therapies when the standard approach of nonsteroidal anti-inflammatory drugs (NSAIDs) and physical modalities fails. MAIN MESSAGE: Ankylosing spondylitis is associated with disability comparable to that of rheumatoid arthritis. Diagnosis should first focus on eliciting a history of nocturnal back pain, diurnal variation in symptoms with prolonged morning stiffness, and a good response to NSAID therapy. Physical examination is often unrevealing. Pelvic x-ray results are often normal in early disease. Magnetic resonance imaging is the most sensitive imaging technique for detecting early inflammatory lesions and should be considered when history supports the diagnosis but results of plain radiography are normal. When patients have failed at least two courses of NSAID therapy, anti-TNF(alpha)therapies are of proven benefit. CONCLUSION: New magnetic resonance imaging techniques and highly effective therapies make AS more readily detectable and managable.
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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.005 | 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".