Duloxetine for Patients with Diabetic Peripheral Neuropathic Pain: A 6-Month Open-Label Safety Study
Bibliographic record
Abstract
OBJECTIVE: Duloxetine is a relatively balanced and potent reuptake inhibitor of both serotonin and norepinephrine. Because these neurotransmitters play a role in pain inhibition, duloxetine was considered a possible treatment for diabetic peripheral neuropathic pain (DPNP). This study assessed the 6-month safety and tolerability of duloxetine in patients with DPNP; evaluation of efficacy was a secondary objective. DESIGN: In this 28-week, open-label study, in the clinical setting, 449 patients with DPNP were randomized (3:1) to receive duloxetine 60 mg twice daily (BID) (N = 334) or duloxetine 120 mg once daily (QD) (N = 115). Comprehensive safety evaluations including laboratory analyses and electrocardiograms were performed for all patients. Efficacy measures included the Brief Pain Inventory (BPI) and Clinical Global Impression of Severity (CGI-S) scales. RESULTS: Protocol completion rates were 63.8% and 62.6% for the 60 mg BID and 120 mg QD groups, respectively (P = 0.823). Discontinuations were primarily due to adverse events, 20.1% for 60 mg BID and 27.0% for 120 mg QD (P = 0.149). Heart rate increased slightly in both treatment groups (P </= 0.02 in both groups). Systolic blood pressure was unaffected, while diastolic blood pressure decreased slightly in the 120 mg QD group (P = 0.04). Sustained elevation in blood pressure was reported for 18 (5.5%) patients in the 60 mg BID group and six (5.4%) in the 120 mg QD group. Duloxetine treatment was not associated with significant QTc prolongation. There was significant improvement at endpoint on all subscales of the BPI and CGI-S (P < 0.001 in both groups). CONCLUSIONS: In this study, duloxetine 60 mg BID and 120 mg QD were safely administered and well tolerated in patients with DPNP for up to 28 weeks. There were few differences in safety or tolerability between the two dosages. At both doses, duloxetine provided clinically significant pain relief.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| 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 | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".