Reducing Persistent Postoperative Pain and Disability 1 Year After Breast Cancer Surgery: A Randomized, Controlled Trial Comparing Thoracic Paravertebral Block to Local Anesthetic Infiltration
Bibliographic record
Abstract
BACKGROUND: The objective of this study was to compare the effect of thoracic paravertebral block (TPVB) and local anesthetic (LA) on persistent postoperative pain (PPP) 1 year following breast cancer surgery. Secondary objectives were to compare the effect on arm morbidity and quality of life. METHODS: Women scheduled for elective breast cancer surgery were randomly assigned to either TPVB or LA followed by general anesthesia. An NRS value of >3 at rest or with movement 1 year following surgery defined PPP. Blinded interim analysis suggested rates of PPP much lower than anticipated, making detection of the specified 20 % absolute reduction in the primary outcome impossible. Recruitment was stopped, and all enrolled patients were followed to 1 year. RESULTS: A total of 145 participants were recruited; 65 were randomized to TPVB and 64 to LA. Groups were similar with respect to demographic and treatment characteristics. Only 9 patients (8 %; 95 % CI 4-14 %) met criteria for PPP 1 year following surgery; 5 were in the TPVB and 4 in the LA group. Brief Pain Inventory severity and interference scores were low in both groups. Arm morbidity and quality of life were similar in both groups. The 9 patients with PPP reported shoulder-arm morbidity and reduced quality of life. CONCLUSIONS: This study reports a low incidence of chronic pain 1 year following major breast cancer surgery. Although PPP was uncommon at 1 year, it had a large impact on the affected patients' arm morbidity and quality of life.
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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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 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) | 0.005 | 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".