Diagnostic Performance of Clinical Examination Measures and Pain Presentation to Identify Patellofemoral Joint Osteoarthritis
Bibliographic record
Abstract
OBJECTIVE: To assess the diagnostic performance of a comprehensive set of tests and measures to discriminate patellofemoral (PF) from tibiofemoral (TF) osteoarthritis (OA). METHODS: The Clinical Assessment of the Knee Study is a study of knee pain in the general population. The presence of PF crepitus and pain with PF compression were assessed. Anterior knee pain was determined using a knee pain map. Pain with climbing/descending stairs and walking on level ground were assessed with the Western Ontario and McMaster Universities Osteoarthritis Index. Radiographs were used to define the compartment(s) of the knee affected by OA (no OA, isolated/predominant PF joint OA, and isolated/predominant TF joint OA). In knees with mixed OA, knees with more severe PF joint OA were included in the isolated/predominant PF group (the same was done for TF joint OA). We determined the sensitivity, specificity, positive predictive value (PPV), negative predictive value, and positive likelihood ratio (LR+) for each test and measure individually, and the combination of these measures, in distinguishing knees with PF joint OA from knees with TF joint OA or no OA. RESULTS: There were 745 knees included in the study. No measure had high sensitivity and specificity. Pain with climbing/descending stairs had the greatest sensitivity (90%) but poor specificity (15%). The combination of definite crepitus with no pain on walking had the greatest specificity (96%), PPV (53%), and LR+ (1.8), but poor sensitivity (7%). CONCLUSION: Typical clinical examination findings and knee pain patterns commonly thought to represent underlying PF joint pathology do not discriminate knees with PF joint OA from knees without OA or TF joint OA.
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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 | 0.003 | 0.003 |
| 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".