Evaluation of tramadol/paracetamol 75 mg/650 mg combination therapy for early-stage knee osteoarthritis: a retrospective observational study
Bibliographic record
Abstract
OBJECTIVE: Knee osteoarthritis (KOA) is a progressive joint disorder that significantly impairs patients' quality of life. Effective long-term management of KOA remains challenging due to limited pharmacological options and associated adverse effects. This monocentric, retrospective observational study evaluated the efficacy and safety of a fixed-dose tramadol/paracetamol combination (75/650 mg) in alleviating pain in patients with grade I-II KOA according to the Kellgren-Lawrence classification. METHODS: A total of 30 patients treated for 15 days were assessed using the Numerical Rating Scale for pain, the Western Ontario and McMaster Universities Osteoarthritis Index for functional impairment, and the Pittsburgh Sleep Quality Index for sleep quality. RESULTS: Results showed a 30% and 50% pain reduction in 86% and 43% of patients, respectively, alongside significant improvements in functional mobility and sleep quality. Adverse events, including nausea, itching, and sleepiness, occurred in 10% of patients and did not necessitate treatment discontinuation. Efficacy was consistent across demographic and clinical subgroups, possibly suggesting broad treatment applicability. CONCLUSIONS: While the findings could support tramadol/paracetamol as a safe and effective first-line therapy for KOA, reinforcing its role in optimizing KOA management strategies, limitations such as the small sample size and lack of a control group highlight the need for further research.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 | 0.003 |
| 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".