Arshia K. Sethi

Introduction: Endoscopic submucosal dissection (ESD) is a technique for removing dysplastic lesions in the gastrointestinal tract, but it carries risks like pain and perforation. Dexmedetomidine, an α2-receptor agonist, offers potential benefits as an adjunct sedative during ESD by providing anxiolysis and analgesia. This systematic review and meta-analysis assess its efficacy and safety. Methodology: We searched databases including Embase, Medline/PubMed, Scopus, and Web of Science up to April 21, 2024, following PRISMA guidelines. Eligible studies used dexmedetomidine with other sedatives for ESD. We analyzed outcomes such as en-bloc and complete resection rates, sedation duration, and adverse events, using RevMan for meta-analysis with a random-effects model. Results: The initial search retrieved 216 studies, and eight studies were included in the final analysis after screening. Dexmedetomidine showed no significant difference in en-bloc or complete resection rates compared to controls. Sedation and procedure times were similar between the two groups as well. Dexmedetomidine significantly reduced restlessness (OR 0.15, 95% CI:0.07 to 0.29) and increased bradycardia (OR 7.15, 95% CI 3.17 to 16.11) compared to controls. Upon subgroup analysis, Dexmedetomidine plus Propofol and Dexmedetomidine plus Midazolam revealed the same findings regarding restlessness and bradycardia compared to controls, which confirmed the adjunctive effects of Dexmedetomidine. Conclusion: Dexmedetomidine appears safe and effective as an adjunctive sedative in ESD, reducing restlessness without significant adverse events. The risk of bradycardia is increased, which may reflect reduced physiological stress. Future studies should explore optimal dosing and compare Dexmedetomidine with other sedatives in diverse populations.

Bouveret Syndrome is an infrequent manifestation of gallstone disease, causing gastric outlet obstruction. This syndrome has diagnostic and therapeutic challenges due to its rarity and non-specific clinical presentation. Here, we present a case report involving a 78-year-old female patient who experienced gastric outlet blockage due to the presence of a sizable gallstone. A novel technique was applied wherein a trapezoid RX wire-guided retrieval basket (Boston Scientific) was utilized with Esophagogastroduodenoscopy to remove the stone without the need for surgical intervention. Post-procedure monitoring demonstrated a smooth recovery with immediate relief of symptoms. Imaging confirmed the absence of residual gallstones or obstruction.

Respiratory disorders, being one of the leading causes of disability worldwide, account for constant evolution in management technologies, resulting in the incorporation of artificial intelligence (AI) in the recording and analysis of lung sounds to aid diagnosis in clinical pulmonology practice. Although lung sound auscultation is a common clinical practice, its use in diagnosis is limited due to its high variability and subjectivity. We review the origin of lung sounds, various auscultation and processing methods over the years and their clinical applications to understand the potential for a lung sound auscultation and analysis device. Respiratory sounds result from the intra-pulmonary collision of molecules contained in the air, leading to turbulent flow and subsequent sound production. These sounds have been recorded via an electronic stethoscope and analyzed using back-propagation neural networks, wavelet transform models, Gaussian mixture models and recently with machine learning and deep learning models with possible use in asthma, COVID-19, asbestosis and interstitial lung disease. The purpose of this review was to summarize lung sound physiology, recording technologies and diagnostics methods using AI for digital pulmonology practice. Future research and development in recording and analyzing respiratory sounds in real time could revolutionize clinical practice for both the patients and the healthcare personnel.

Production of bowel sounds, established in the 1900s, has limited application in existing patient-care regimes and diagnostic modalities. We review the physiology of bowel sound production, the developments in recording technologies and the clinical application in various scenarios, to understand the potential of a bowel sound recording and analysis device—the phonoenterogram in future gastroenterological practice. Bowel sound production depends on but is not entirely limited to the type of food consumed, amount of air ingested and the type of intestinal contractions. Recording technologies for extraction and analysis of these include the wavelet-based filtering, autoregressive moving average model, multivariate empirical mode decompression, radial basis function network, two-dimensional positional mapping, neural network model and acoustic biosensor technique. Prior studies evaluate the application of bowel sounds in conditions such as intestinal obstruction, acute appendicitis, large bowel disorders such as inflammatory bowel disease and bowel polyps, ascites, post-operative ileus, sepsis, irritable bowel syndrome, diabetes mellitus, neurodegenerative disorders such as Parkinson’s disease and neonatal conditions such as hypertrophic pyloric stenosis. Recording and analysis of bowel sounds using artificial intelligence is crucial for creating an accessible, inexpensive and safe device with a broad range of clinical applications. Microwave-based digital phonoenterography has huge potential for impacting GI practice and patient care.