Impact of Pregabalin on the Occurrence of Postthoracotomy Pain Syndrome
Bibliographic record
Abstract
BACKGROUND: Postthoracotomy pain syndrome (PTPS) is a frequent cause of chronic postoperative pain. Pregabalin might reduce the incidence of chronic postoperative pain. The goal of this study was to evaluate the impact of perioperative pregabalin on the occurrence of PTPS, defined as any surgical site pain 3 months after surgery. METHODS: We conducted a randomized, placebo-controlled, double-blind trial in patients undergoing elective thoracotomy. Patients received either pregabalin 150 mg orally twice a day initiated 1 hour before thoracotomy and continued until 4 days after thoracotomy (10 doses total) or a placebo using the same protocol. All patients received preincision thoracic epidural analgesia. Postthoracotomy pain syndrome was evaluated using the Brief Pain Inventory questionnaire through a telephone interview. Secondary outcomes included evaluation of neuropathic characteristics through the Leeds Assessment of Neuropathic Symptoms and Signs questionnaire, analgesic use 3 months after surgery, and evaluation of acute postoperative pain and opioid consumption. RESULTS: One hundred fourteen patients were randomized, and 99 patients completed the study (placebo, n = 49; pregabalin, n = 50). Postthoracotomy pain syndrome occurred in 49 (49.5%) of 99 patients and more frequently in the pregabalin group (31/50 [62%] vs 18/49 [37%] in the placebo group, P = 0.01). However, among patients with PTPS, those in the pregabalin group required significantly less analgesics, reported less moderate to severe average pain, and presented significantly less neuropathic characteristics than patients in the placebo group 3 months after surgery. CONCLUSIONS: Pregabalin did not reduce the incidence of PTPS in this study. Future research on PTPS should focus on the impact of regional analgesia on central sensitization.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.009 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".