Methods of measuring radiographic patellofemoral joint alignment and morphology: A scoping review
Bibliographic record
Abstract
Objective: Conduct a scoping review to identify radiographic measures of patellofemoral joint (PFJ) alignment and bony morphology reported in literature published during a representative period (2014-2018), and describe their reported measurement properties. Design: Eight electronic databases were searched using keywords relating to "patellofemoral" and "radiograph". Identified records were screened for eligibility by two independent assessors. English-language studies published in the years 2014-2018 were included if they reported: (i) acquiring PFJ radiographs; (ii) method of radiograph acquisition; and (iii) descriptions of radiographic PFJ alignment and bony morphology measures. Non-human and cadaveric studies, single-case studies, and studies with mean participant age <10 years were excluded. For studies that reported measurement properties (reliability, validity, responsiveness), quality appraisal was performed by two independent assessors using the COSMIN Risk of Bias tool. Descriptive data were reported. Results: Of 18,678 records identified, 336 articles met our criteria . Ninety-one unique radiographic alignment and morphology measures were described. Most prevalent were measures of patellar height (222, 66.1 %), patellar alignment (142, 42.3 %), and patellar inclination (121, 36 %). Reliability data were reported by 83 (24.7 %) of the studies. Conclusions: During the selected period, 91 different radiographic measures of PFJ alignment and morphology were reported, with multiple methods used to obtain similar measures, and limited data on reliability and validity. These findings make it difficult to recommend specific measures for clinical and research use. Further studies are needed to determine the measurement properties of radiographic PFJ alignment and morphology measures, and to establish consensus-based recommendations for priority measures and acquisition methods for specific PFJ conditions.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| 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) | 0.000 | 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".