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Adrenal cysts are uncommon fluid-filled masses that develop in the adrenal gland. Typically, they are non-functional, asymptomatic, and smaller than 10 cm in diameter when incidentally detected. However, the presence of giant adrenal cysts, exceeding 10 cm in diameter, creates a diagnostic challenge due to the difficulty in determining their origin. Surgical intervention is advised when the cyst surpasses 10 cm in diameter, produces symptoms, causes endocrine abnormalities, exhibits intracystic bleeding, or raises suspicion of malignancy. The preferred treatment approach involves adrenalectomy, performed either through open surgery or laparoscopy. In cases where the diagnosis is unequivocal, ultrasound-guided percutaneous drainage serves as an alternative. Here, we present an exceptional case of a massive retroperitoneal mass caused by a rare giant adrenal cyst.
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BACKGROUND AND AIMS: The quality of esophagogastroduodenoscopy (EGD) can have great impact on the detection of esophageal and gastric lesions, including malignancies. The aim of the study is to investigate the use of artificial intelligence (AI) during EGD by the endoscopists-in-training so that a real-time feedback can be provided, ensuring compliance to a pre-decided protocol for examination. METHODS: This is an observational pilot study. The videos of the EGD procedure performed between August 1, 2021, and September 30, 2021, were prospectively analyzed using AI system. The assessment of completeness of the procedure was done based on the visualizsation of pre-defined 29 locations. Endoscopists were divided into two categories - whether they are in the training period (category A) or have competed their endoscopy training (category B). RESULTS: A total of 277 procedures, which included 114 category-A and 163 category-B endoscopists, respectively, were included. Most commonly covered areas by the endoscopists were greater curvature of antrum (97.47%), second part of duodenum (96.75%), other parts of antrum such as the anterior, lesser curvature and the posterior aspect (96.75%, 94.95%, and 94.22%, respectively). Commonly missed or inadequately seen areas were vocal cords (99.28%), epiglottis (93.14%) and posterior, anterior, and lateral aspect of incisura (78.70%, 73.65%, and 73.53%, respectively). The good quality procedures were done predominantly by categoryB endoscopists (88.68% vs. 11.32%, p < 0.00001). CONCLUSION: AI can play an important role in assessing the quality and completeness of EGD and can be a part of training of endoscopy in future.
Assuntos
Inteligência Artificial , Endoscopia do Sistema Digestório , Humanos , Endoscopia do Sistema Digestório/métodos , Endoscopia Gastrointestinal , EstômagoRESUMO
Periampullary diverticula (PAD) have been encountered in 5.9 to 18.5% of patients during all the endoscopic retrograde cholangiopancreatography (ERCP). Cannulation in the presence of PAD can sometimes be difficult, time consuming, and often requires a higher level of endoscopic skills. Several techniques have been reported to facilitate and increase the chances of successful bile duct cannulation in the presence of PAD. The two-devices in one-channel method has been sparingly used. It involves the simultaneous use of a biopsy forceps and another instrument, either a cannula or sphincterotome through the same working channel. We successfully performed ERCP in three cases, where bile duct cannulation was performed in the setting of intradiverticular papilla using two-devices in one-channel method. We feel that the two-devices in one-channel method can be very useful and positioned higher up in the algorithm for successful cannulation in patients with PAD.
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BACKGROUND: Seroprevalence studies for COVID-19 evaluate the extent of undetected transmission in a defined community, with special significance among health care workers (HCW) owing to their greater exposure and potential to transmit. METHODS: A total of 1122 HCW (approximately 25% of the employees) of a large tertiary care hospital in India were recruited for this cross-sectional study. COVID PCR-positive HCW were excluded. Based on their risk-assessment, participants were grouped into three categories. A questionnaire was administered and they were tested for SARS-CoV-2-IgG antibodies using the chemiluminescence. RESULTS: The overall seroprevalence among workers was 11.94%, which included 19.85% in COVID units, 11.09% in non-COVID units, and 8% in administrative workers (p=0.007). Antibody prevalence was highest in the department of gastroenterology (11.94%), followed by oncology (10.53%), pathology (10.26%), emergency medicine (7.84%) and critical care medicine (7%). Housekeeping staff, food and beverage staff, lab assistants and technicians had higher seroprevalence rate than doctors and nurses (p < 0.0001). HCW with a history of BCG vaccination in childhood and those who received an adequate prophylactic dose of hydroxychloroquine (HCQ) had a lower seroprevalence as compared to those who did not (7.31% vs. 16.8% and 1.30% vs. 11.25% respectively). CONCLUSION: BCG vaccination, HCQ prophylaxis, and the job profile influence the seroprevalence rate in HCW. Seroprevalence rate and follow-up evaluation of its durability may help hospitals to triage their staff at risk, rationalize their placement, prioritize the use of PPE, thereby potentially reducing the risk.