A Novel Experience Of Ultrasound-Guided Erector Spinae Plane Block With Sedation In Breast Cancer Surgery: A Case Report.

We report the anaesthetic management of a breast cancer patient, at a high risk for undergoing general anaesthesia, using a single-shot ultrasound-guided Erector Spinae Plane Block (ESPB) with monitored sedation. Targetted at T4, 20 mL of 0.375% bupivacaine provided complete surgical anaesthesia in 15 minutes. Concurrent sedation was administered with target controlled infusion of propofol with entropy monitoring throughout the procedure. The surgery lasted 90 minutes and the patient remained pain free and haemodynamically stable throughout. At the end of the surgery, the patient received 1 g of paracetamol intravenously, and did not require any further analgesics other than routinely administered paracetamol until her discharge from the hospital. On top of the successful execution of our plan, this case was especially interesting as her postoperative analgesia remained completely opioid-free.

Proceeding the categorization of microplastics through deep learning-based image segmentation.

Microplastics (MPs) have been recognized as prominent anthropogenic pollutants that inflict significant harm to marine ecosystems. Various approaches have been proposed to mitigate the risks posed by MPs. Gaining an understanding of the morphology of plastic particles can provide valuable insights into the source and their interaction with marine organisms, which can assist the development of response measures. In this study, we present an automated technique for identifying MPs through segmentation of MPs in microscopic images using a deep convolutional neural network (DCNN) based on a shape classification nomenclature framework. We used MP images from diverse samples to train a Mask Region Convolutional Neural Network (Mask R-CNN) based model for classification. Erosion and dilation operations were added to the model to improve segmentation results. On the testing dataset, the mean F1-score (F1) of segmentation and shape classification was 0.7601 and 0.617, respectively. These results demonstrate the potential of proposed method for the automatic segmentation and shape classification of MPs. Furthermore, by adopting a specific nomenclature, our approach represents a practical step towards the global standardization of MPs categorization criteria. This work also identifies future research directions to improve accuracy and further explore the possibilities of using DCNN for MPs identification.

Clinical Practice for Venous Thromboembolism Prophylaxis in Patients Undergoing Oncological Surgeries.

Objective To determine the proportion of patients receiving venous thromboembolism (VTE) prophylaxis after oncological surgeries as per the hospital standards and its comparison with the international guidelines. Methodology In the month of September 2019, all patients after elective oncological surgeries were reviewed for VTE prophylaxis administration and education. Results were shared with the department of surgery and Hospital Quality and Patient Safety Department. Education was provided to the relevant staff and hospital policy for VTE prophylaxis was revised followed by a loop audit which was done in October 2020. The primary endpoint was to compare the proportion of patients receiving prophylaxis as per the hospital guidelines. Results Total 425 patients were included in this audit (209 in September 2019 and 216 in October 2020). Compliance with mechanical prophylaxis increased from 84.7 % to 98.6% and pharmacological prophylaxis improved from 39.7% (n=83) to 73.1% (n=158). Adherence to local protocols enhanced significantly from 1.9% (n=4) to 56.4% (n=122). The main cause of non-compliance was lack of risk assessment for VTE. Conclusion VTE prophylaxis can be improved by setting protocols in accordance with the international guidelines and local protocols. This can prevent significant morbidity and mortality in surgical patients as well as hospital costs.

Development of Coral Investigation System Based on Semantic Segmentation of Single-Channel Images.

Among aquatic biota, corals provide shelter with sufficient nutrition to a wide variety of underwater life. However, a severe decline in the coral resources can be noted in the last decades due to global environmental changes causing marine pollution. Hence, it is of paramount importance to develop and deploy swift coral monitoring system to alleviate the destruction of corals. Performing semantic segmentation on underwater images is one of the most efficient methods for automatic investigation of corals. Firstly, to design a coral investigation system, RGB and spectral images of various types of corals in natural and artificial aquatic sites are collected. Based on single-channel images, a convolutional neural network (CNN) model, named DeeperLabC, is employed for the semantic segmentation of corals, which is a concise and modified deeperlab model with encoder-decoder architecture. Using ResNet34 as a skeleton network, the proposed model extracts coral features in the images and performs semantic segmentation. DeeperLabC achieved state-of-the-art coral segmentation with an overall mean intersection over union (IoU) value of 93.90%, and maximum F1-score of 97.10% which surpassed other existing benchmark neural networks for semantic segmentation. The class activation map (CAM) module also proved the excellent performance of the DeeperLabC model in binary classification among coral and non-coral bodies.

Pectoral Nerves I, II and Serratus Plane Blocks in Multimodal Analgesia for Mastectomy: A Randomised Clinical Trial.

OBJECTIVE: To primarily assess pain score in first 24 hours in PECS (PECtoral Serratus) block group undergoing mastectomy; secondary objective was to observe opioid and antiemetic consumption in the postoperative period. STUDY DESIGN: Observer-blinded randomised control trial. PLACE AND DURATION OF STUDY: Department of Anesthesiology, Shaukat Khanum Memorial Cancer Hospital Lahore (SKMCH), from February to December 2017. METHODOLOGY: One hundred and twenty patients of more than 18 years, ASA I and II, planned for unilateral elective modified radical mastectomy under general anesthesia, were scheduled randomly to receive either general anesthesia plus PECS block (n = 60) or general anesthesia alone (n = 60). Pain scores at fixed intervals were measured using Numeric Pain Rating Score (NPRS) after the surgery. RESULTS: Pain score in the PECS block group was significantly lower than the control group in postoperative period. Less dose of morphine was required in the PECS block group postoperatively for pain control. Postoperative nausea and vomiting (PONV) incidence was lower in the intervention group (PECS block) as compared with the control group. CONCLUSION: PECS block has a better analgesic efficacy in patients undergoing mastectomy.

Massive Haemorrhage In Patient After Repair Of Post Esophagectomy Diaphragmatic Hernia And A Loading Dose Of Clopidogrel.

Postoperative diaphragmatic hernia (PDH) is an increasingly reported complication of esophageal cancer surgery. It occurs more frequently with minimally invasive techniques and very little is known about its pathogenesis. Currently, no consensus exists concerning preventive measures and its management. A 36 years old male underwent minimally invasive esophagectomy and presented with chest pain and dyspnoea in the emergency department 8 months after the procedure. He was started on acute coronary syndrome treatment protocol but was later diagnosed on CT scan to have diaphragmatic hernia through a defect in the oesophageal hiatus. As he was already loaded with dual anti platelet therapy it led to qualitative defect of the platelet which resulted in bleeding post procedure and the patient needed resuscitation with blood products. Dual anti-platelet therapy is an integral component of early management strategy in acute coronary syndrome. Chest X-ray was not helpful, but abdominal or chest computed tomography was useful for accurate diagnosis.