The correlation between clinical and radiological severity of osteoarthritis of the knee
Bibliographic record
Abstract
INTRODUCTION: Primary osteoarthritis (OA) is a common cause of knee pain. Appropriate management of knee OA is based on clinical and radiological findings. Pain, deformity, and functional impairments are major clinical factors considered along with radiological findings when making management decisions. Differences in management strategies might exist due to clinical and radiological factors. This study aims at finding possible associations between clinical and radiological observations. METHODS: A prospective cross-sectional study of 52 patients with primary osteoarthritis of the knee managed conservatively at a tertiary hospital arthroplasty clinic was conducted for three months. English speaking patients with primary OA were identified and included in this study. Pain and functional impairment were assessed using Wong-Baker Faces pain scale, The Knee Society Score (KSS), and Western Ontario and McMaster Osteoarthritis Index (WOMAC). The Body Mass Index (BMI) of all participants was measured. Standard two views plain radiographs were used for radiographic grading of the OA. Anonymized radiographs were presented to two senior consultant orthopaedic surgeons who graded the OA using Kellgren and Lawrence (KL) and Ahlbäck classification systems. The severity of the functional impairment and pain score was then compared to the radiological grading. RESULTS: , median self-reported pain, total WOMAC, and pain WOMAC scores were 8, 60, and 13, respectively. We observed no significant correlation between BMI and pain scores. Inter-rater reliability for KL and Ahlbäck grading was strong. There was no significant correlation between WOMAC scores and the radiological grades. CONCLUSION: There was no correlation between pain and functional scores, patient factors and radiological severity of OA of the knee.
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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 | 0.001 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| 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) | 0.005 | 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".