Background: Video-assisted thoracoscopic surgery (VATS) is a commonly performed minimally invasive procedure that has led to lower levels of pain, as well as procedure-related mortality and morbidity. However, VATS requires analgesia that blocks both visceral and somatic nerve fibers for more effective pain control. This randomized controlled trial evaluated the effect of erector spinae plane block (ESPB) in the postoperative analgesia management of patients undergoing VATS. Methods: We performed a prospective, randomized, single-center study between December 2018 and December 2019. Fifty-four patients were recruited to two equal groups (ESPB and control group). Following exclusion, 46 patients were included in the final analysis. Patients were randomly assigned to receive preoperative ultrasound-guided ESPB with either ropivacaine or saline. The primary outcome was the numeric rating scale (NRS) score, assessed 12 hours postoperatively. Secondary outcomes were the Riker Sedation-Agitation Scale (SAS) score for emergence agitation, postoperative cumulative opioid consumption, length of post-anesthesia care unit (PACU) stay, incidence of postoperative nausea and vomiting (PONV) and dizziness, and ESPB-related adverse events. Results: The NRS in the ESPB group during the postoperative period immediately after PACU admission was significantly lower than that in the control group (5.96±1.68 and 7.59±1.18, respectively; P<0.001) and remained lower until 6 hours postoperatively (P=0.001 at 1 hour and P=0.005 at 6 hours). At 12 hours postoperatively, NRS scores were not significantly different between groups (P=0.12). The median [interquartile range (IQR)] of the postoperative rescue pethidine consumption in PACU was significantly lower [25 mg (25 mg)] in the ESPB group than that in the control group [50 mg (56.2 mg); P=0.006]. The median (IQR) of PACU residual time was significantly lower [25 min (10 min)] in the ESPB group than that in the control group [30 min (15 min); P=0.034]. The median (IQR) Riker SAS was also lower in the ESPB group [4 (1.0)] than that in the control group [5 (1.25); P<0.001] in PACU. Conclusions: A single preoperative injection of ESPB with ropivacaine may improve acute postoperative analgesia and emergence agitation in patients undergoing VATS.

Background. Rotator cuff tendinopathy is a primary cause of shoulder pain and dysfunction. Several effective nonsurgical treatment methods have been described for chronic rotator cuff tendinopathy. Prolotherapy with polydeoxyribonucleotide (PDRN), which consists of active deoxyribonucleotide polymers that stimulate tissue repair, is a nonsurgical regenerative injection that may be a viable treatment option. The objective of this study was to assess the efficacy of PDRN in the treatment of chronic rotator cuff tendinopathy. Method. The records of patients with chronic rotator cuff tendinopathy (n=131) were reviewed retrospectively, and the patients treated with PDRN prolotherapy (n=32) were selected. We measured the main outcome of the shoulder pain and disability index score on a numerical rating scale of average shoulder pain. Results. Compared with baseline data, significant improvements in the shoulder pain and disability index and pain visual analog scale scores were demonstrated at one week after the end of treatment, and at one month and three months later. Conclusions. PDRN prolotherapy may improve the conservative treatment of painful rotator cuff tendinopathy for a specific subset of patients.

Background: Postoperative nausea and vomiting (PONV) is a still highly relevant problem and is known to be a distressing side effect in patients. The aim of this study was to develop a machine learning model to predict PONV up to 24 h with fentanyl-based intravenous patient-controlled analgesia (IV-PCA). Methods: From July 2019 and July 2020, data from 2,149 patients who received fentanyl-based IV-PCA for analgesia after non-cardiac surgery under general anesthesia were applied to develop predictive models. The rates of PONV at 1 day after surgery were measured according to patient characteristics as well as anesthetic, surgical, or PCA-related factors. All statistical analyses and computations were performed using the R software. Results: A total of 2,149 patients were enrolled in this study, 337 of whom (15.7%) experienced PONV. After applying the machine-learning algorithm and Apfel model to the test dataset to predict PONV, we found that the area under the receiver operating characteristic curve using logistic regression was 0.576 (95% confidence interval [CI], 0.520–0.633), k-nearest neighbor was 0.597 (95% CI, 0.537–0.656), decision tree was 0.561 (95% CI, 0.498–0.625), random forest was 0.610 (95% CI, 0.552–0.668), gradient boosting machine was 0.580 (95% CI, 0.520–0.639), support vector machine was 0.649 (95% CI, 0.592–0.707), artificial neural network was 0.686 (95% CI, 0.630–0.742), and Apfel model was 0.643 (95% CI, 0.596–0.690). Conclusions: We developed and validated machine learning models for predicting PONV in the first 24 h. The machine learning model showed better performance than the Apfel model in predicting PONV.

Lee SH, et al. J Korean Med Sci. 2020 May;35(26):e225. https://doi.org/10.3346/jkms.2020.35.e225