Algofunctional outcome after intra-articular bipolar pulsed radiofrequency ablation for pain in osteoarthritis of the knee: A retrospective study
Bibliographic record
Abstract
There is a paucity of research and evidence, regarding the effectiveness of applying bipolar pulsed radiofrequency (bPRF) in osteoarthritis of the knee. This study aimed to search for the impact of intra-articular bPRF (IA-bPRF) on pain, functionality, and quality of life in individuals with advanced knee osteoarthritis. A total of 35 patients experiencing knee pain were included in the study. IA-bPRF was applied at 42 °C temperature, 45 V, with a pulse-width of 20 ms and a frequency of 2 Hz for 3 cycles of 120 seconds. Pain severity was evaluated using the numeric rating scale. Assessment tools included Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC), and Lequesne Algofunctional Index for knee. All measurements were made before the intervention, as well as 2 weeks and 6 months after application of IA-bPRF. Significant improvement was observed in numeric rating scale scores for walking pain from 8.57 ± 0.17 to 4.11 ± 0.35, total WOMAC scores decreased from 75.5 ± 2.71 to 36.7 ± 3.6 and Lequesne Algofunctional Index for knee scores decreased from 18.6 ± 0.70 to 10.4 ± 0.93 by the end of the sixth month (P < .01). WOMAC subgroups for pain, stiffness and functionality, were also significantly lower at the 2nd week and 6th month compared to pre-intervention scores (P < .01). No serious adverse events related to the procedure occurred. IA-bPRF use seems to be safe and effective in relieving pain among individuals with advanced knee osteoarthritis. As a result, with further research, we expect that IA-bPRF may be considered for inclusion in upcoming guidelines for the treatment of chronic pain related to osteoarthritis 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 | 0.001 |
| 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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".