Background. Ultrasound-guided percutaneous cryoneurolysis is an analgesic technique in which a percutaneous probe is used to reversibly ablate a peripheral nerve(s) using exceptionally low temperature, and has yet to be evaluated with randomized, controlled trials. Pain following mastectomy can be difficult to treat, and we hypothesized that the severity of surgically-related pain would be lower on postoperative day 2 with the addition of cryoanalgesia as compared with patients receiving solely standard-of-care treatment. Methods. Preoperatively, participants at 1 enrolling center received a single injection ropivacaine 0.5% paravertebral nerve block at T3 or T4 and a perineural was catheter inserted. Participants subsequently had an active or sham ultrasound-guided percutaneous cryoneurolysis procedure of the ipsilateral T2-T5 intercostal nerves in a randomized, patient- and observer-masked fashion. Participants all received a continuous paravertebral block with ropivacaine 0.2% until the early morning of discharge (usually postoperative day 2). The primary end point was the average pain level measured using a 0-10 numeric rating scale the afternoon of postoperative day 2. Participants were followed for 1 year. Results. On postoperative day 2, participants who had received active cryoneurolysis (n=31) had a median [IQR] pain score of 0 [0, 1.4] versus 3.0 [2.0, 5.0] in patients given sham (n=29): difference (97.5%CI) -2.5 (-3.5, -1.5), P<0.001. There was evidence of superior analgesia through Month 12. During the first 3 weeks, cryoneurolysis lowered cumulative opioid use by 98%, with the active group using 0.3 [0, 2.8] mg of oxycodone compared with 15.0 [4.0, 24.0] mg in the sham group (P<0.001). No oral analgesics were required by any patient between Months 1-12. After 1 year chronic pain had developed in 1 (3%) active compared with 5 (17%) sham participants (P<0.001). Conclusions. Percutaneous cryoneurolysis markedly improved analgesia without systemic side effects or complications following mastectomy.
BackgroundParavertebral and serratus plane blocks are both used to treat pain following breast surgery. However, it remains unknown if the newer serratus block provides comparable analgesia to the decades-old paravertebral technique.MethodsSubjects undergoing unilateral or bilateral non-mastectomy breast surgery were randomized to a single-injection serratus or paravertebral block in a subject-masked fashion (ropivacaine 0.5%; 20 mL unilateral; 16 mL/side bilateral). We hypothesized that (1) analgesia would be non-inferior in the recovery room with serratus blocks (measurement: Numeric Rating Scale), and (2) opioid consumption would be non-inferior with serratus blocks in the operating and recovery rooms. In order to claim that serratus blocks are non-inferior to paravertebral blocks, both hypotheses must be at least non-inferior.ResultsWithin the recovery room, pain scores for participants with serratus blocks (n=49) had a median (IQR) of 4.0 (0–5.5) vs 0 (0–3.0) for those with paravertebral blocks (n=51): 0.95% CI −3.00 to −0.00; p=0.001. However, the difference in morphine equivalents did not reach statistical significance for superiority with the serratus group consuming 14 mg (10–19) vs 10 mg (10–16) for the paravertebral group: 95% CI −4.50 to 0.00, p=0.123. Since the 95% CI lower limit of −4.5 was less than our prespecified margin of −2.0, we failed to conclude non-inferiority of the serratus block with regard to opioid consumption.ConclusionsSerratus blocks provided inferior analgesia compared with paravertebral blocks. Without a dramatic improvement in safety profile for serratus blocks, it appears that paravertebral blocks are superior to serratus blocks for postoperative analgesia after non-mastectomy breast surgery.Trial registration numberNCT03860974.
Purpose of Review Obtaining negative margins in breast conservation surgery continues to be a challenge. Re-excisions are difficult for patients and expensive for the health systems. This paper reviews the literature on current strategies and intraoperative clinical trials to reduce positive margin rates. Recent Findings The best available data demonstrate that intraoperative imaging with ultrasound, intraoperative pathologic assessment such as frozen section, and cavity margins have been the most successful intraoperative strategies to reduce positive margins. Emerging technologies such as optical coherence tomography and fluorescent imaging need further study but may be important adjuncts. Summary There are several proven strategies to reduce positive margin rates to < 10%. Surgeons should utilize best available resources within their institutions to produce the best outcomes for their patients.
Introduction: The use of opioids in mastectomy patients is a particular challenge, having to balance the management of acute pain while minimizing risks of continuous opioid use postoperatively. Despite attempts to decrease postmastectomy opioid use, including regional anesthetics, gabapentinoids, topical anesthetics, and nonopioid anesthesia, prolonged opioid use remains clinically significant among these patients. The goal of this study is to identify risk factors and develop machine-learning-based models to predict patients who are at higher risk for postoperative opioid use after mastectomy. Methods: In this retrospective cohort study, we collected data from patients that underwent mastectomy procedures. The primary outcome of interest was defined as oxycodone milligram equivalents (OME) greater than or equal to the 75% of OME use on a postoperative day 1. Model performance (area under the receiveroperating characteristics curve (AUC)) of various machine learning approaches was calculated via 10-fold cross-validation. Odds ratio (OR) and 95% confidence intervals (CI) were reported.Results: There were a total of 148 patients that underwent mastectomy and were included. The medium (quartiles) postoperative day 1 opioid use was 5 mg OME (0.25 mg OME). Using multivariable logistic regression, the most protective factors against higher opioid use was being postmenopausal (OR: 0.13, 95% CI: 0.03-0.61, p = 0.009) and cancer diagnosis (OR: 0.19, 95% CI: 0.05-0.73, p = 0.01). The AUC was 0.725 (95% CI: 0.572-0.876). There was no difference in the performance of other machine-learning-based approaches.Conclusions: The ability to predict patients' postoperative pain could have a significant impact on preoperative counseling and patient satisfaction.
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