Antidepressant Drugs for Prevention of Acute and Chronic Postsurgical Pain
Bibliographic record
Abstract
BACKGROUND: This review evaluates trials of antidepressants for acute and chronic postsurgical pain. METHODS: Trials were systematically identified using predefined inclusion and exclusion criteria. Extracted data included the following: pain at rest and with movement, adverse effects, and other outcomes. RESULTS: Fifteen studies (985 participants) of early postoperative pain evaluated amitriptyline (three trials), bicifadine (two trials), desipramine (three trials), duloxetine (one trial), fluoxetine (one trial), fluradoline (one trial), tryptophan (four trials), and venlafaxine (one trial). Three studies (565 participants) of chronic postoperative pain prevention evaluated duloxetine (one trial), escitalopram (one trial), and venlafaxine (one trial). Heterogeneity because of differences in drug, dosing regimen, outcomes, and/or surgical procedure precluded any meta-analyses. Superiority to placebo was reported in 8 of 15 trials for early pain reduction and 1 of 3 trials for chronic pain reduction. The majority of positive trials did not report sufficient data to estimate treatment effect sizes. Many studies had inadequate size, safety evaluation/reporting, procedure specificity, and movement-evoked pain assessment. CONCLUSIONS: There is currently insufficient evidence to support the clinical use of antidepressants-beyond controlled investigations-for treatment of acute, or prevention of chronic, postoperative pain. Multiple positive trials suggest the therapeutic potential of antidepressants, which need to be replicated. Other nontrial evidence suggests potential safety concerns of perioperative antidepressant use. Future studies are needed to better define the risk-benefit ratio of antidepressants in postoperative pain management. Higher-quality trials should optimize dosing, timing and duration of antidepressant treatment, trial size, patient selection, safety evaluation and reporting, procedure specificity, and assessment of movement-evoked pain relevant to postoperative functional recovery.
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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 | 0.004 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".