Duloxetine Added to Tramadol in Chronic Pain Syndrome
Bibliographic record
Abstract
Introduction About 15–20% of the population suffering from the chronic pain. Over time, chronic pain can result in different emotional problems, social isolation, sleep disturbances, which reduce the quality of life. Chronic pain syndrome (CPS) indicates persistent pain, subjective symptoms in excess of objective findings, associated dysfunctional pain behavious and self-limitation in activities of daily living. Duloxetine is a potent antidepressant approved by the Food and Drug Administration for the chronic musculoskeletal disorder, diabetic neuropathic pain, fibromyalgia, generallized anxiety disorder and major depressive disorder. Objective To determine the effect of duloxetine on the reduction of pain and psychosocial suffering. Aims The goal of the treatment should be to effectively reduce pain while improving function and reducing psychosocial suffering. Methods Thirty-six adult, nondepressed patients, already on tramadol therapy were included. Patients with VAS (visual analogue scale) ≥ 4were treated with duloxetine for 13 weeks. We measured pain intensity with the McGill Pain Questionnaire-Short Form (MPQ-SF) and compared VAS before starting the treatment with duloxetine and weekly for 13 weeks. Results Pain response was defined as a 30%decrease in the MPQ-SF. A total of 62.5% of the sample met these criteria for response. Among them, 13.8% of patients were discontinued because of adverse effects. Duloxetine significantly improved functioning and the quality of life in patients with CPS. Conclusions Because of it is analgesic properties, duloxetine in the lower antidepressant doses (60 mg taken ones daily) combined with tramadol (another analgesic agent) can be useful in CPS for patients who do not respond satisfactory to monotherapy. Disclosure of interest The authors have not supplied their declaration of competing interest.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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) | 0.006 | 0.001 |
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".