A Double-Blind, Randomized Multicenter Trial Comparing Duloxetine with Placebo in the Management of Diabetic Peripheral Neuropathic Pain
Bibliographic record
Abstract
OBJECTIVE: Assess efficacy and safety of duloxetine, a selective serotonin and norepinephrine reuptake inhibitor, on the reduction of pain severity, in patients with diabetic peripheral neuropathic pain (DPNP). METHODS: This was a multicenter, parallel, double-blind, randomized, placebo-controlled trial that enrolled 348 patients with pain due to peripheral neuropathy caused by type 1 or type 2 diabetes mellitus. Patients (N = 116 per group) were randomly assigned to receive duloxetine 60 mg once daily (QD), duloxetine 60 mg twice daily (BID), or placebo, for 12 weeks. The primary outcome measure was the weekly mean score of 24-hour average pain severity evaluated on an 11-point Likert scale. Secondary outcome measures and safety were evaluated. RESULTS: Compared with placebo-treated patients, both duloxetine-treated groups improved significantly more (P < 0.001) on the 24-hour average pain score. Duloxetine demonstrated superiority to placebo in all secondary analyses of the primary efficacy measure. A significant treatment effect for duloxetine was observed in most secondary measures for pain. Discontinuations due to adverse events were more frequent in the duloxetine 60 mg BID- (12.1%) versus the placebo- (2.6%) treated group. Duloxetine showed no adverse effects on diabetic control, and both doses were safely administered and well tolerated. CONCLUSIONS: In this clinical trial, duloxetine 60 mg QD and duloxetine 60 mg BID were effective and safe in the management of DPNP.
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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) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.007 | 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".