Efficacy of Duloxetine on electrodiagnostic findings of Paclitaxel-induced peripheral neuropathy, does it have a prophylactic effect? A randomized clinical trial
Bibliographic record
Abstract
This study aimed to evaluate the efficacy of Duloxetine on electrodiagnostic findings of Paclitaxel-induced peripheral neuropathy in patients with breast cancer. This randomized, double-blind clinical trial was conducted on 40 patients with breast cancer who received Paclitaxel as their first chemotherapy session. All the patients were randomly allocated into two groups, intervention (20 subjects) and placebo (20 subjects). The intervention group received 30 mg duloxetine/day in the first week, followed by 60 mg (twice daily) until 8 weeks. The patient neurotoxicity questionnaire (PNQ) was used to evaluate the severity of neuropathy. Nerve conduction study was also performed. The evaluations were performed at the baseline and 8 weeks after the treatment. Out of 20 subjects in the placebo group, 10 (50%) patients had neurotoxicity (two milds, three moderate, four severe, and one incapacitated), according to PNQ. However, in the duloxetine group, two patients had mild neurotoxicity ( P = 0.03). Significant differences between groups related to the mean of Median Sensory Latency ( P <0.001), Median Motor Latency ( P < 0.001), and Median Motor velocity ( P = 0.001) were reported. However, the relative risk of polyneuropathy between the two groups (relative risk: 1) was not significant. Regarding the results, duloxetine could be an effective treatment for preventing paclitaxel-induced peripheral neuropathy in patients with breast cancer, and an electrodiagnostic study confirmed this effect.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".