Adalimumab Significantly Reduces the Recurrence Rate of Anterior Uveitis in Patients with Ankylosing Spondylitis
Bibliographic record
Abstract
OBJECTIVE: To investigate whether use of adalimumab decreases the frequency of attacks of anterior uveitis (AU) in patients with ankylosing spondylitis (AS). METHODS: Consecutive patients with AS, visiting an outpatient clinic and treated for at least 12 weeks with adalimumab, were enrolled. The number of attacks of AU in the year before start and during treatment were assessed by patient history and ophthalmological controls. RESULTS: In the 77 patients a total of 52 AU attacks occurred in the year before baseline (68 attacks per 100 patient-yrs), whereas during adalimumab treatment 19 attacks were seen (14 per 100 patient-yrs; reduction rate 80%). Twenty-six patients with AU in the year before start of adalimumab treatment had recurrent attacks, with a median number of 2.0 AU attacks per year [interquartile range (IQR) 1.00-3.00], whereas during treatment this decreased to 10 patients with a median number of 0.56 attacks per year (IQR 0.30-0.75). Hence, the number of attacks per year decreased by 72% (p = 0.000). CONCLUSION: In patients with AS, a significant reduction in the number of AU attacks, as well as in the number of attacks per patient, was observed during adalimumab treatment.
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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 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".