The role of electrotherapy in reducing the pain of patients with knee osteoarthritis during the COVID-19 pandemic
Bibliographic record
Abstract
Introduction. Osteoarthritis is considered to be the most common form of arthritis and a leading disability cause worldwide, especially due to the painful symptom. The latter is a clinical marker in evaluating the limits of joint mobility and therefore, the pain reduction is a goal of the recovery treatment for patients with knee osteoarthritis. The purpose of this study was to show whether the pain phenomenon characteristic of knee osteoarthritis can be reduced by electrotherapy, even in the context of the COVID-19 pandemic. Material and method. The study lasted 5 months and included 171 patients diagnosed clinically and radiologically with knee osteoarthritis. The followed parameters were pain, physical dysfunction in daily activities, anxiety and quality of life. Results and discussions. The two groups of studied patients were homogeneous in terms of weight by gender and age groups. The evaluation of patients according to scales enabled the registration of statistically significant values, the value of p <0.05, which explains the validation of the working hypothesis. The feeling of pain is closely related to the level of anxiety. Conclusions. Analgesic electrotherapy significantly reduced the pain syndrome of the patients for whom it was used. It has been shown that the patients' anxiety can influence the pain phenomenon. Given the conditions caused by the Covid-19 pandemic, the anxiety of the patients who were in the outpatient department to receive recovery treatment was increased, but after the recovery treatment there was a decrease, so these patients' quality of life increased. Keywords: pain, analgesic electrotherapy, knee osteoarthritis, recovery treatment,
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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 | 0.006 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| 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".