Neuropathic pain in knee osteoarthritis: Prevalence, diagnosis, and clinical implications
Bibliographic record
Abstract
OBJECTIVES: This study aims to explore the prevalence of neuropathic pain (NP) in patients with knee osteoarthritis (KOA) and to assess its correlation with functional status. PATIENTS AND METHODS: Between December 2023 and May 2024, a total of 193 patients (48 males, 145 females; mean age: 58.7±12.8 years; range, 22 to 89 years) who were diagnosed with KOA and had persistent knee pain for more than three months were included. The painDETECT and Douleur Neuropathique en 4 Questions (DN4) questionnaires were utilized to evaluate NP. The Visual Analog Scale (VAS) was used to assess pain severity, while the Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC) was utilized to assess functional status. RESULTS: The painDETECT indicated NP in 27.5% of patients, while the DN4 scale showed 30.6%. Patients with NP exhibited significantly elevated VAS and WOMAC scores to patients without NP, indicating a greater severity of pain and functional impairment in this subgroup (p<0.05). The agreement between the painDETECT and DN4 was moderate (κ=0.472). There were significant correlations between the painDETECT and DN4 scores with the WOMAC total score (r=0.371 and r=0.242, respectively, p<0.001). CONCLUSION: Neuropathic pain is common in KOA patients and is associated with higher pain intensity and poorer functional outcomes. The moderate agreement between the painDETECT and DN4 scores may lead to a certain degree of diagnostic variation. Combining more than one method may increase the diagnostic accuracy.
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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 | 0.001 |
| 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".