Bibliographic record
Abstract
PURPOSE OF REVIEW: Ankylosing spondylitis (AS) is a disease that tends to affect younger individuals, many of whom are in the prime of their lives; therefore, incorporating the most up-to-date evidence into physiotherapy practice is critical. The purpose of this review is to update the most recent evidence related to physiotherapy intervention for AS and highlight the application of the findings to current physiotherapy research and clinical practice. RECENT FINDINGS: The results of this review add to the evidence supporting physiotherapy as an intervention for AS. The emphasis continues to be on exercise as the most studied physiotherapy modality, with very few studies examining other physiotherapy modalities. Results of the studies reviewed support the use of exercise, spa therapy, manual therapy and electrotherapeutic modalities. In addition, the results of this review help to understand who might benefit from certain interventions, as well as barriers to management. SUMMARY: A review of recently published articles has resulted in a number of studies that support the body of literature describing physiotherapy as an effective form of intervention for AS. In order to continue to build on the existing research, further examination into physiotherapy modalities, beyond exercise-based intervention, needs to be explored.
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 | 0.003 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.002 |
| Bibliometrics | 0.004 | 0.005 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 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".