Randomized double‐blind comparison of serotonergic (Citalopram) versus noradrenergic (Reboxetine) reuptake inhibitors in outpatients with somatoform, DSM‐IV‐TR pain disorder
Bibliographic record
Abstract
OBJECTIVES: Whether the effect of tricyclic antidepressants on Pain Disorder arises from their noradrenergic or serotonergic actions or both remains unclear. We compared the selective serotonin reuptake inhibitor (SSRI) citalopram and the noradrenergic reuptake inhibitor (NARI) reboxetine in outpatients with Pain Disorder. We also distinguished the drugs' analgesic and antidepressant effects. METHODS: In this 8-week, randomized double-blind study, 35 patients with a DSM-IV-TR diagnosis of Pain Disorder were randomly assigned to receive either citalopram 40 mg/day (N=17 patients) or reboxetine 8 mg/day (N=18). The Present Pain Intensity (PPI) scale and the Total Pain Rating Index (tPRI) of the McGill Pain Questionnaire were used to measure the effect on pain symptoms. Changes in the Zung Self-Rating Depression Scale (Zung-D) scores were evaluated to monitor a possible antidepressant effect. For all patients who had at least one assessment, an intent-to-treat analysis was performed. RESULTS: No significant differences were found in the demographic variables or clinical characteristics of the two treatment groups. In the citalopram group, PPI and tPRI scores measured at baseline decreased after treatment (tPRI: 41.9 vs. 30.0, p=.004; PPI: 3.5 vs. 2.8, p=.045) whereas in the reboxetine group differences were not statistically significant (tPRI: 35.2 vs. 31.5; PPI: 3.7 vs. 3.1). The Zung-D showed no significant changes between baseline and endpoint assessment in either group. CONCLUSIONS: Our study suggests that the SSRI citalopram may have a moderate analgesic effect in patients with Pain Disorder, and that this analgesic activity appears to be not correlated to changes in depressive scores. If confirmed in a larger sample, this evidence suggests that patients who are intolerant or resistant to tricyclic antidepressants, may be treated with SSRIs.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.006 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.009 | 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".