Can radiographic patellofemoral osteoarthritis be diagnosed using clinical assessments?
Bibliographic record
Abstract
INTRODUCTION: The aim of this study was to determine whether participant characteristics and clinical assessments could identify radiographic osteoarthritis (OA) in individuals with clinically diagnosed, symptomatic patellofemoral osteoarthritis (PFOA). METHODS: Participant characteristics and clinical assessments were obtained from 179 individuals aged 50 years and over with clinically diagnosed symptomatic PFOA, who were enrolled in a randomised trial. Anteroposterior, lateral, and skyline X-rays were taken of the symptomatic knee. The presence of radiographic PFOA was defined as "no or early PFOA" (Kellgren and Lawrence [KL] grade ≤1 in the PF compartment) or "definite PFOA" (KL grade ≥2). Diagnostic test statistics were applied to ascertain which participant characteristics and clinical assessments could identify the presence of definite radiographic PFOA. RESULTS: ), longer pain duration (>2.75 years), higher maximum knee pain during stair ambulation (>47/100 mm), and fewer repeated single step-ups to pain onset (<21) were associated with the presence of definite radiographic PFOA. Multivariate logistic regression indicated that BMI, pain duration, and repeated single step-ups to pain onset were independently associated with radiographic PFOA and identified the presence of definite radiographic PFOA with an overall accuracy of 73%. CONCLUSION: In individuals over 50 years of age with a clinical diagnosis of PFOA, higher BMI, longer pain duration, and fewer repeated single step-ups to pain onset increased the likelihood of radiographic PFOA. However, overall diagnostic accuracy was modest, suggesting that radiographic PFOA cannot be confidently identified using these tests.
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 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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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) | 0.000 | 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".