Reliability of a Proposed Ultrasonographic Grading Scale for Severity of Primary Knee Osteoarthritis
Bibliographic record
Abstract
OBJECTIVES: The objective of this study was to examine the concordance of a grading scale (0-4) of medial femoral osteophytes in knee joint detected by ultrasound (US) compared with the corresponding grades (0-4) of Kellgren-Lawrence (K&L) scale of conventional radiography and clinical joint examination. PATIENTS AND METHODS: A cross-sectional observational study included 160 patients with knee pain who fulfilled the American College of Rheumatology (ACR) criteria for knee osteoarthritis (KOA) and 20 patients with knee pain who have not fulfilled the ACR criteria for KOA. All patients were subjected to clinical assessment (Western Ontario and McMaster Universities Index of Osteoarthritis and global visual analog scale) and radiological assessment in the form of X-ray grading according to K&L grading scale and ultrasonographic assessment of medial femoral osteophytes according to a scale that was proposed by the first author and consisted of five grades (0-4), where grade 0 denoted no osteoarthritis and grade 4 denoted the most advanced grade of KOA. Grade 2 was divided into two subgrades A and B with grade 2B considered as a more advanced stage than grade 2A. RESULTS: The proposed US grading scale had high sensitivity and specificity in detecting the different grades of KOA compared with K&L grading scale (a total sensitivity of 94.6% and a total specificity of 93.3%). Intra- and interreader reliability of US was excellent (kappa >0.93 and >0.85, respectively). CONCLUSIONS: US can reliably detect the severity of KOA. Good agreement was found between the proposed US grading scale and K&L grading scale. The proposed US grading scale is simple and reliable.
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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 | 0.010 | 0.032 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".