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Background: Multimodal analgesia is now widely practised to minimise postoperative opioid consumption while optimising pain control. The aim of this meta-analysis was to assess the analgesic efficacy of erector spinae plane block (ESPB) in patients undergoing laparoscopic abdominal surgeries. This will be determined by perioperative opioid consumption, subjective pain scores, and incidences of postoperative nausea and vomiting. Methods: The authors systemically searched electronic databases for randomised controlled trials (RCTs) published up to February 2023 comparing ESPB with other adjuvant analgesic techniques in laparoscopic abdominal surgeries. Nine randomised controlled trials encompassing 666 subjects were included in our study. Results: ESPB was shown to reduce postoperative opioid consumption [mean difference (MD) of -5.95 mg (95% CI: -8.86 to - 3.04; P< 0.0001); I2= 89%], intraoperative opioid consumption MD of - 102.4 mcg (95% CI: - 145.58 to -59.21; P< 0.00001); I2=39%, and incidence of nausea [RR 0.38 (95% CI: 0.25-0.60; P<0.0001); I2=0%] and vomiting [RR 0.32 (95% CI: 0.17-0.63; P =0.0009); I2=0%] in laparoscopic abdominal surgeries. Subgroup analysis on laparoscopic colorectal surgeries further showed reduction in postoperative pain scores MD of -0.68 (95% CI: - 0.94 to - 0.41); P<0.00001; I2= 0%]. Conclusions: This study concludes that ESPB is a valuable technique with proven efficacy to potentially promote faster postoperative recovery through optimising pain control while minimising opioid requirements. [ABSTRACT FROM AUTHOR]

Background: Recent developments in artificial intelligence (AI) systems have enabled advancements in endoscopy. Deep learning systems, using convolutional neural networks, have allowed for real-time AI-aided detection of polyps with higher sensitivity than the average endoscopist. However, not all endoscopists welcome the advent of AI systems. Methods: We conducted a survey on the knowledge of AI, perceptions of AI in medicine, and behaviours regarding use of AI-aided colonoscopy, in a single centre 2 months after the implementation of Medtronic's GI Genius in colonoscopy. We obtained a response rate of 66.7% (16/24) amongst consultant-grade endoscopists. Fisher's exact test was used to calculate the significance of correlations. Results: Knowledge of AI varied widely amongst endoscopists. Most endoscopists were optimistic about AI's capabilities in performing objective administrative and clinical tasks, but reserved about AI providing personalised, empathetic care. 68.8% (n = 11) of endoscopists agreed or strongly agreed that GI Genius should be used as an adjunct in colonoscopy. In analysing the 31.3% (n = 5) of endoscopists who disagreed or were ambivalent about its use, there was no significant correlation with their knowledge or perceptions of AI, but a significant number did not enjoy using the programme (p-value = 0.0128) and did not think it improved the quality of colonoscopy (p-value = 0.033). Conclusions: Acceptance of AI-aided colonoscopy systems is more related to the endoscopist's experience with using the programme, rather than general knowledge or perceptions towards AI. Uptake of such systems will rely greatly on how the device is delivered to the end user. [ABSTRACT FROM AUTHOR]

This article discusses the case of a 56-year-old male who presented with per rectal bleeding and was found to have idiopathic colonic and small bowel varices during a colonoscopy. The patient underwent further imaging and was diagnosed with a tubulovillous adenoma with clear margins. Idiopathic colonic varices are rare and typically present with lower gastrointestinal bleeding. Treatment options for active bleeding include endoscopic modalities, angioembolization, or surgical resection. The prognosis for patients with idiopathic colonic varices tends to be better compared to those with portal hypertension. [Extracted from the article]

Background: Colonoscopy is a mainstay to detect premalignant neoplastic lesions in the colon. Real-time Artificial Intelligence (AI)-aided colonoscopy purportedly improves the polyp detection rate, especially for small flat lesions. The aim of this study is to evaluate the performance of real-time AI-aided colonoscopy in the detection of colonic polyps. Methods: A prospective single institution cohort study was conducted in Singapore. All real-time AI-aided colonoscopies, regardless of indication, performed by specialist-grade endoscopists were anonymously recorded from July to September 2021 and reviewed by 2 independent authors (FHK, JL). Sustained detection of an area by the program was regarded as a "hit". Histology for the polypectomies were reviewed to determine adenoma detection rate (ADR). Individual endoscopist's performance with AI were compared against their baseline performance without AI endoscopy. Results: A total of 24 (82.8%) endoscopists participated with 18 (62.1%) performing ≥ 5 AI-aided colonoscopies. Of the 18, 72.2% (n = 13) were general surgeons. During that 3-months period, 487 "hits" encountered in 298 colonoscopies. Polypectomies were performed for 51.3% and 68.4% of these polypectomies were adenomas on histology. The post-intervention median ADR was 30.4% was higher than the median baseline polypectomy rate of 24.3% (p = 0.02). Of the adenomas excised, 14 (5.6%) were sessile serrated adenomas. Of those who performed ≥ 5 AI-aided colonoscopies, 13 (72.2%) had an improvement of ADR compared to their polypectomy rate before the introduction of AI, of which 2 of them had significant improvement. Conclusions: Real-time AI-aided colonoscopy have the potential to improved ADR even for experienced endoscopists and would therefore, improve the quality of colonoscopy. [ABSTRACT FROM AUTHOR]