Long-term Efficacy of Pectoserratus Plane Block (PSPB) for Prevention of Post-mastectomy Pain Syndrome
Bibliographic record
Abstract
OBJECTIVES: Pectoserratus plane block (PSPB) leads to lower postoperative pain intensity. We examined whether PSPB could also reduce the incidence of post-mastectomy pain syndrome (PMPS) in women undergoing breast cancer surgery. METHODS: We performed an extension study of a randomized trial that compared PSPB versus control in women undergoing mastectomy. The primary outcome was any chronic pain at the surgical site or adjacent areas, defined as persistent/recurrent pain lasting ≥3 months. Secondary outcomes included neuropathic pain (score ≥4 in the Douleur Neuropathique 4 questionnaire), use of analgesic/anti-inflammatory drugs, pain intensity through the short-form McGill Pain Questionnaire, and type, frequency, and location of the pain. RESULTS: Of the 60 patients that completed the 24-hour follow-up (short-term trial), 53 (88%) completed the long-term follow-up (27 in the PSPB group and 26 in the placebo group). Six of 27 patients (22%) in the PSPB group and 17 of 26 patients (65%) in the placebo group reported any chronic pain (relative risk [RR], 0.34; 95% confidence interval [95% CI]=0.16-0.73, P =0.005). The risk of neuropathic pain was also lower in the PSPB group than in the placebo group (18.5% vs. 54%, respectively; RR, 0.34; 95% CI=0.14-0.82, P =0.02). There were no differences regarding all other pain-related outcomes considering the patients who developed PMPS. DISCUSSION: The results suggest that, in the long term, PSPB-treated participants were associated with a statistically significantly lower risk of PMPS than those who received standard general anesthesia. TRIAL REGISTRATION: ClinicalTrials.gov (NCT03966326).
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".