ABSTRACT
BACKGROUND AND OBJECTIVES: This review aims to delve into the role of artificial intelligence in medicine. Ulcerative colitis (UC) is a chronic, inflammatory bowel disease (IBD) characterized by superficial mucosal inflammation, rectal bleeding, diarrhoea and abdominal pain. By identifying the challenges inherent in UC diagnosis, we seek to highlight the potential impact of artificial intelligence on enhancing both diagnosis and treatment methodologies for this condition. METHOD: A targeted, non-systematic review of literature relating to ulcerative colitis was undertaken. The PubMed and Scopus databases were searched to categorize a well-rounded understanding of the field of artificial intelligence and its developing role in the diagnosis and treatment of ulcerative colitis. Articles that were thought to be relevant were included. This paper only included articles published in English. RESULTS: Artificial intelligence (AI) refers to computer algorithms capable of learning, problem solving and decision-making. Throughout our review, we highlighted the role and importance of artificial intelligence in modern medicine, emphasizing its role in diagnosis through AI-assisted endoscopies and histology analysis and its enhancements in the treatment of ulcerative colitis. Despite these advances, AI is still hindered due to its current lack of adaptability to real-world scenarios and its difficulty in widespread data availability, which hinders the growth of AI-led data analysis. CONCLUSIONS: When considering the potential of artificial intelligence, its ability to enhance patient care from a diagnostic and therapeutic perspective shows signs of promise. For the true utilization of artificial intelligence, some roadblocks must be addressed. The datasets available to AI may not truly reflect the real-world, which would prevent its impact in all clinical scenarios when dealing with a spectrum of patients with different backgrounds and presenting factors. Considering this, the shift in medical diagnostics and therapeutics is coinciding with evolving technology. With a continuous advancement in artificial intelligence programming and a perpetual surge in patient datasets, these networks can be further enhanced and supplemented with a greater cohort, enabling better outcomes and prediction models for the future of modern medicine.
ABSTRACT
BACKGROUND: Infective endocarditis (IE) continues to be a disease with high mortality despite medical advances. OBJECTIVE: The objective of this study was to investigate the characteristics and prognosis of IE according to the affected valves. MATERIALS AND METHODS: This study was retrospective and single-centered, and it included 270 patients with a diagnosis of IE, for the period 2005-2021, who received treatment at the University Hospital "St. Georgi" in Plovdiv, Bulgaria. RESULTS: Single-valve IE (SIE) was found in 82.6% (n-223), multivalvular IE (MIE) in 16.66% (n = 45) and device IE (CDRIE) in 0.74% (n = 2) of patients. The most commonly affected valve was the aortic valve, in 44.8% (n = 121). The predominant multivalvular involvement was aortic-mitral valves (AV-MV) (13.7%, n = 37). The patients with tricuspid valve (TV) IE were significantly younger, at 39 (30) years, and were more frequently male (80.8%). Mortality was higher in MIE than in SIE (31.1% vs. 23.8%) and was the highest in multivalve aortic-tricuspid (AV-TV) IE (75%). Early surgery was performed most in AV-MV IE, in 29.7% (n = 11). The Charlson comorbidity index (CCI) was significantly higher in MV 4 (4) and AV 3 (3) vs. TV IE 1 (5) (p = 0.048 and p = 0.011, respectively). Septic shock occurred most frequently in AV-TV involvement (75%; p = 0.0001). The most common causative agents were of the Staphylococcus group. Staphylococcus aureus more often affected TV alone (46.2%, n = 124) vs. AV (9.9%, n = 14; p = 0.0001) and vs. MV (22.6%, n = 17; p = 0.022); Staphylococcus coagulase-negative (CNG) was the prevalent cause of MV IE (22.7%, n = 17) vs. AV-MV (2.7%, n = 1; p = 0.007). Streptococci were represented in a low percentage and only in left-sided IE, more frequently in AV-MV (18.9%, n = 7) vs. AV (6.6%, n = 8; p = 0.025). CONCLUSIONS: The aortic valve is the most frequently affected valve, as single-valve IE or as multivalve AV-MV, with the predominant causative agents being of the Staphylococcus group. AV-TV IE has the worst prognosis, with the most common complication of septic shock and the highest in-hospital mortality.
ABSTRACT
Urachal adenocarcinomas, constituting 10 % of bladder adenocarcinomas, pose a significant challenge with limited literature. A 43-year-old male presented with haematuria and abdominal pain, leading to surgical intervention for a 13 cm pelvic tumor. Histopathology identified an intestinal-type primary urachal adenocarcinoma, staged as IIIA, no recurrence on follow-up. Early detection is crucial for improved outcomes in these rare malignancies. While surgery remains the primary treatment, outcomes vary, emphasizing the need for research on standardized protocols. Enhanced awareness and interdisciplinary collaboration are vital for effective management. Comprehensive guidelines are essential for optimizing patient prognoses in urachal adenocarcinomas.
ABSTRACT
Infective endocarditis (IE) is a difficult-to-diagnose provocative disease that causes significant morbidity and mortality. The first-line imaging test for the diagnosis of IE is echocardiography. However, in cases of prosthetic IE or IE associated with intracardiac devices, its sensitivity is limited. A new diagnostic tool, 18F-fluorodeoxyglucose positron emission tomography (18F-FDG PET/CT), improves diagnosis in these difficult cases. The most recent European guidelines for IE (2015) include this imaging modality as a primary diagnostic criterion. We present a case of culture-negative prosthetic IE diagnosed with 18F-FDG PET/CT.