Clinicoradiographic correlation between the Western Ontario and McMaster Universities Osteoarthritis Index and Kellgren–Lawrence system assessments among patients with osteoarthritis of the knee presenting at a tertiary hospital in southeastern Nigeria
Bibliographic record
Abstract
Background: In the evaluation of patients with knee osteoarthritis, surgeons use clinical instruments and heavily rely on radiographic parameters, especially when considering invasive treatment options. Research exploring the agreement between clinical and radiographic tools in Caucasian and Asian populations has yielded mixed results. This study aimed to examine—using the Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC) and Kellgren–Lawrence (K–L) grades—whether a correlation exists between clinical and radiographic findings in a sample of Nigerian patients with osteoarthritis. Methods: We enrolled patients with knee osteoarthritis from the orthopaedic clinic at a tertiary hospital in Nnewi, Nigeria. We calculated their WOMAC knee scores using the WOMAC questionnaire and performed knee radiographs in anteroposterior, lateral, and skyline views. We assigned K–L grades based on radiographic findings. We used Spearman correlation analysis to determine the correlation between the WOMAC knee scores and K–L grades. Results: The study included 128 patients (215 knees) with a mean age of 64.8 years. The median WOMAC score was 58.0, and the most common K–L grade was grade III. Among the 40- to 59-year and ≥70-year age groups, women had lower WOMAC scores, even in combination with K–L grade IV. Overall, there was no significant correlation between WOMAC scores and K–L grades (P=0.59, Spearman ρ=0.012). Conclusions: There was no correlation between clinical and radiographic features in knee osteoarthritis in this sample of patients managed at a tertiary hospital in southeastern Nigeria.
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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 | 0.000 | 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".