The relationship of cervicothoracic mobility restrictions to fall risk and fear of falling in ankylosing spondylitis
Bibliographic record
Abstract
Objective The objective of this study is to determine whether restricted cervical mobility in ankylosing spondylitis (AS) is associated with increased fall frequency or fear of falling. Methods A total of 134 AS patients and 199 age- and gender-matched control subjects (CS) with soft-tissue cervicothoracic pain were prospectively evaluated for fall risk. Subjects were divided into non-fallers, single fallers, and multiple fallers. Dynamic cervical rotations and static cervicothoracic axial measurements were compared between the groups. In total, 88 AS patients were reviewed more than once; Kaplan–Meier plots were constructed for fall risk as a function of cervical rotation amplitudes. Falls Efficacy Scale-International (FES-I) questionnaire measured the fear of falling. Results In total, 34% of AS patients and 29% of CS fell (p = 0.271) in the year prior to evaluation. In AS, static anatomical measurements were unrelated to fall occurrence. The trends of multiple AS fallers to greater flexed forward postures and reduced dynamic cervical rotations were not statistically significant. Cervicothoracic pain (p = 0.0459), BASDAI (p = 0.002), and BASFI (p = 0.003) scores were greater in multiple fallers. FES-I scores were greater in fallers (p = 0.004). Of the 88 AS patients reviewed (or seen) on more than one occasion, 46.5% fell over the 9-year observation period, including all multiple fallers and 71.4% of single fallers. Survival curves showed increased fall risk as cervical rotational amplitudes decreased. Conclusion In AS, decreased cervical rotations increase fall risk and fear of falling. In multiple fallers, falls were associated with greater disease activity. Cervical muscle stiffness in AS may cause non-veridical proprioceptive inputs and contribute to increased fall frequency similar to individuals with soft-tissue cervicothoracic pain.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 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 | 0.000 |
| 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".