The therapeutic benefits of NSAIDs and physical therapy in knee osteoarthritis
Bibliographic record
Abstract
INTRODUCTION: Osteoarthritis (OA) has been established as a progressive wear and tear disease of the synovial joints, which also involves a certain degree of inflammation. Considering there is no disease modifying medication available at the moment, the current guidelines focus on the symptomatic treatment of the affection. Our study aimed to evaluate the therapeutic advantages of the synergistic use of non-steroidal anti-inflammatory drugs (NSAIDs) and physical therapy in the treatment of knee osteoarthritis (KOA). PATIENTS, MATERIALS AND METHODS: The study comprised 46 individuals who were diagnosed with KOA and were admitted to the Department of Physical Medicine and Rehabilitation at the Emergency Clinical County Hospital of Craiova, Romania, between January 2021 and April 2022. All the participants received the same combination of pharmacological (Diclofenac 150 mg∕day, no more than 10 days∕month as needed) and non-pharmacological treatment (a 24-week plan of physical therapy). RESULTS: The patient group exhibited a statistically significant reduction in both the average Western Ontario and McMaster Universities Osteoarthritis (WOMAC) index (p=0.0142) and the average Visual Analog Scale (VAS) (p=0.0023). Additionally, there was a statistically significant increase in both the average Knee Outcome Survey-Activities of Daily Living (KOS-ADL) (p=0.0128) and the average Oxford Knee Score (OKS) (p=0.0023). The study found a significant positive correlation between higher VAS ratings and cholesterol levels (p=0.0092), but no significant correlation between VAS scores and triglyceride levels (p=0.0986). Patients were evaluated for a further 24 weeks beyond the conclusion of the research to see if surgical intervention was necessary during this time. CONCLUSIONS: Our investigation tracked the WOMAC, VAS, KOS-ADL, and OKS measurements in a cohort of patients with KOA. The results demonstrate that the utilization of NSAIDs in conjunction with physical therapy effectively alleviates pain and enhances joint functionality.
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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) | 0.000 | 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) | 0.001 | 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".