Delayed diagnosis in axial spondyloarthritis—how can we do better?
Bibliographic record
Abstract
The wide-reaching benefits of prompt diagnosis and treatment have long been demonstrated in RA [1, 2]. A ‘window of opportunity’ for treatment initiation is reflected in clinical guidelines and drives efforts to reduce iagnostic delay, for example by establishing early arthritis services. Although international guidelines have advocated prompt referral and treatment initiation in axial spondyloarthritis (axSpA) [3], this approach has been severely hampered by a number of unique challenges. A recent systematic review and metanalysis undertaken by Zhao and colleagues confirms a mean delay of 6.7 years, which did not improve when results were stratified by year of publication [4]. There is considerable evidence that an earlier diagnosis provides better outcomes for axSpA patients. A recent systematic review showed that longer delay to diagnosis was consistently associated with higher disease activity, poorer physical function, heightened anxiety and depression, and greater healthcare costs [5]. Delay is also linked to radiographic damage, which may reflect disease progression in the absence of prompt treatment. Evidence from observational studies has shown that TNF inhibitors reduce radiographic progression in AS [6], and a post hoc analysis of C‐axSpAnd, the placebo controlled trial of certolizumab pegol in non-radiographic axSpA, demonstrated that patients with longer symptom duration have a significantly reduced response to TNF inhibitors; this is true both for the ASDAS and also important patient-reported outcomes including pain, fatigue and health-related quality of life [7].
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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 | 0.016 | 0.056 |
| Meta-epidemiology (narrow) | 0.004 | 0.002 |
| Meta-epidemiology (broad) | 0.007 | 0.004 |
| Bibliometrics | 0.004 | 0.002 |
| Science and technology studies | 0.003 | 0.003 |
| Scholarly communication | 0.008 | 0.007 |
| Open science | 0.005 | 0.002 |
| Research integrity | 0.022 | 0.035 |
| Insufficient payload (model declined to judge) | 0.008 | 0.007 |
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".