A Cross-sectional Analysis of Radiographic Ankle Osteoarthritis Frequency and Associated Factors: The Johnston County Osteoarthritis Project
Bibliographic record
Abstract
OBJECTIVE: Because there are no epidemiologic data regarding the frequency of ankle osteoarthritis (OA) in a general population, we sought to analyze this disabling condition in a large, well-characterized, community-based cohort of older individuals. METHODS: Cross-sectional data, including ankle radiographs, were from the most recent data collection (2013-2015) of the Johnston County OA Project. Radiographic ankle OA (rAOA) was defined as a Kellgren-Lawrence arthritis grading scale of ≥ 2 on weight-bearing lateral and mortise radiographs. The presence of pain, aching, or stiffness in the ankles as well as history of ankle injury (limiting ability to walk for at least 2 days) were assessed. Chi-square statistics (categorical variables) and Student t tests (continuous variables) were used to compare all participant characteristics by rAOA status. Joint-based logistic regression models with generalized estimating equations were used to examine associations of rAOA and covariates of interest [age, body mass index (BMI), sex, race, ankle symptoms, and injury history]. RESULTS: . Nearly 7% of this sample had rAOA. Increasing age, high BMI, history of ankle injury, and presence of ankle symptoms were all independently associated with greater odds of having rAOA; no significant differences were seen by sex or race. CONCLUSION: The frequency of rAOA was higher than estimates generally quoted in the literature. While injury was an important contributor, other factors such as age, BMI, and symptoms were also significantly associated with rAOA.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".