The Role of Artificial Intelligence in the Diagnosis and Treatment of Ulcerative Colitis.

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.

Rare case of enteric type of urachal adenocarcinoma: A case report.

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.

Coexistence of ankylosing spondylitis and Behçet's disease: Successful treatment with upadacitinib.

BACKGROUND: Ankylosing spondylitis (AS) and Behçet's disease (BD) are distinct inflammatory disorders, but their coexistence is a rare clinical entity. This case sheds light on managing this complex scenario with Janus kinase (JAK) inhibitors. CASE PRESENTATION: A 42-year-old woman presented with a decade-long history of lower back pain, nocturnal spinal discomfort, recurrent eye issues, oral and genital ulcers, hearing loss, pus formation in the left eye, and abdominal pain. Multidisciplinary consultations and diagnostic tests confirmed AS (HLA-B27 positivity and sacroiliitis) and BD (HLA-B51). Elevated acute-phase markers were observed. CONCLUSION: This case fulfills diagnostic criteria for both AS and BD, emphasizing their coexistence. Notably, treatment with upadacitinib exhibited promising efficacy, underscoring its potential as a therapeutic option in patients with contraindications for conventional treatments. Our findings illuminate the intricate management of patients presenting with these two diverse systemic conditions and advocate for further exploration of JAK inhibitors in similar cases.

Artificial Intelligence in the Diagnosis of Colorectal Cancer: A Literature Review.

BACKGROUND: The aim of this review is to explore the role of artificial intelligence in the diagnosis of colorectal cancer, how it impacts CRC morbidity and mortality, and why its role in clinical medicine is limited. METHODS: A targeted, non-systematic review of the published literature relating to colorectal cancer diagnosis was performed with PubMed databases that were scouted to help provide a more defined understanding of the recent advances regarding artificial intelligence and their impact on colorectal-related morbidity and mortality. Articles were included if deemed relevant and including information associated with the keywords. RESULTS: The advancements in artificial intelligence have been significant in facilitating an earlier diagnosis of CRC. In this review, we focused on evaluating genomic biomarkers, the integration of instruments with artificial intelligence, MR and hyperspectral imaging, and the architecture of neural networks. We found that these neural networks seem practical and yield positive results in initial testing. Furthermore, we explored the use of deep-learning-based majority voting methods, such as bag of words and PAHLI, in improving diagnostic accuracy in colorectal cancer detection. Alongside this, the autonomous and expansive learning ability of artificial intelligence, coupled with its ability to extract increasingly complex features from images or videos without human reliance, highlight its impact in the diagnostic sector. Despite this, as most of the research involves a small sample of patients, a diversification of patient data is needed to enhance cohort stratification for a more sensitive and specific neural model. We also examined the successful application of artificial intelligence in predicting microsatellite instability, showcasing its potential in stratifying patients for targeted therapies. CONCLUSIONS: Since its commencement in colorectal cancer, artificial intelligence has revealed a multitude of functionalities and augmentations in the diagnostic sector of CRC. Given its early implementation, its clinical application remains a fair way away, but with steady research dedicated to improving neural architecture and expanding its applicational range, there is hope that these advanced neural software could directly impact the early diagnosis of CRC. The true promise of artificial intelligence, extending beyond the medical sector, lies in its potential to significantly influence the future landscape of CRC's morbidity and mortality.

Comprehensive Exploration of Antinuclear Antibodies (ANAs): Unveiling Clinical Significance, Associations with Cancer, and the Nuances of Differential Diagnosis in Positive ANA Patients.

This comprehensive review delves into the complex realm of antinuclear antibodies (ANAs), expanding beyond their traditional involvement in autoimmune rheumatic disorders. By digging into historical changes, diagnostic complexity, and clinical significance, the debate reveals the shifting relationships between ANAs, particularly with cancer. Specialized studies provide practical insights on ANA testing processes, standardization, and upcoming challenges. Examining prevalence trends in the United States provides a time dimension to ANA dynamics, linking autoimmune and oncological considerations. The debate delves into the complexity of lupus erythematosus, emphasizing ANAs' diverse presentations and their potential as flexible diagnostic and prognostic indicators. The complex relationship between ANAs and cancer is highlighted, demonstrating their potential as early markers or indicators of malignancies. Looking ahead, this synthesis anticipates advances in personalized medicine and collaborative research, putting ANAs at the forefront of advanced diagnostics and treatments for autoimmune disorders and cancer. This synthesis envisions a future for ANA research in which these antibodies play a critical role in promoting personalized treatment, enhancing diagnostics, and fostering collaborative initiatives that cross traditional boundaries. As ANAs grow more prominent at the junction of autoimmune illnesses and cancer, this synthesis lays the path for further research and novel advances in understanding, diagnosing, and treating complicated medical conditions.

Analysis of Pathology in Premature Infants in Obstetrics and Gynecology Clinic at St George University Hospital, Plovdiv between 2013 and 2015.

INTRODUCTION: Premature birth is now one of the most profound prenatal problems worldwide because of the high morbidity and mor-tality it is associated with at the beginning of life. Advances in prenatal medicine over the past decades have led to a significant improve-ment of neonatal survival in risk groups of newborns. Infants of gestational age of 22-25 weeks represent the greatest medical, social, and ethical dilemma in neonatology. Most of these newborns need intensive care to survive, and most infants born between 28 and 32 weeks of gestation require special care. Those born 34 to 36 weeks' gestation also have higher rates of short-term morbid premature birth-related conditions such as respiratory distress syndrome (RDS) and intraventricular hemorrhage (IVH) than their peers born at term. AIM: To carry out an analysis of morbidity during the neonatal period in premature babies. MATERIALS AND METHODS: A retrospective triennial study was conducted on 598 premature newborns. RESULTS: The results of the study show that morbidity rate in premature born infants is high. The most frequent reasons for admission to the neonatal intensive care unit are the other forms of respiratory distress syndrome (45%). Respiratory distress syndrome (RDS) was observed in 23.41% of the prematurity, 10.7% of them were suspected of having other pathology, and 20.9% of premature neonates  manifested no complications in the neonatal period. There was a significant difference in the diagnosis of newborns after birth (p=0.0001, r=0.58), with the newborns with RDS demonstrating the most complications in the neonatal period. CONCLUSIONS: The conclusions to be drawn from the analysis of the data are as follows: there is wide comorbidity in the prematurity of RDS. Lower gestational age strongly correlates with the development of RDS. If no corticosteroid therapy is administered the risk of developing hyaline membrane disease increases. There is extremely high probability of neonatal mortality in children with hyaline membrane disease. There is significant difference between the primary diagnosis and the condition of the child at discharge from the medical establishment. Adequate and specialized prenatal care is essential when trying to reduce the incidence of preterm birth.

Surgical treatment of pneumothorax in patients with COVID-19 - results and management.

INTRODUCTION: The new coronavirus, SARS-CoV-2, provokes infection with different clinical presentation. It involves an asymptomatic condition, mild variants with fever and dry cough to severe pneumonia, adynamia and respiratory failure with lethal outcome. The fibrotic lung tissue after the inflammatory process is a background for development of a secondary pneumothorax. Although it rarely causes lethal outcomes in COVID-19 patients, pneumothorax requires early diagnosis and adequate treatment to prevent any complications and decrease mortality rate. AIM: The aim of this study was to analyse the results of surgical treatment of hospitalized COVID-19 patients with pneumothorax in terms of demographic data, concomitant diseases, complications, and outcome. MATERIALS AND METHODS: Longitudinal prospective study was carried out with 26 patients with pneumothorax as a result of SARS-CoV-2 infection. They were treated at the Intensive Care Unit of the Infectious Disease Clinic and at the Second Clinic of Surgery, St George University Hospital in Plovdiv over a 6-month period from September 2020 to February 2021. RESULTS: Seventeen of the patients were men and nine - women. Twenty-four of all patients underwent thoracentesis and two of them had a video-assisted thoracoscopy. The mean age of the studied patients with pneumothorax and COVID-19 was 66.77±12.61 years, which shows that it is the patients of advanced age with concomitant diseases that are at a higher risk of serious complications and adverse outcome. Of the hospitalized 1245 patients with COVID-19, 385 (30.92%) passed away. Of all hospitalized patients with SARS-CoV-2, 26 (2.08%) developed pneumothorax. Sixteen of them (62%) passed away. The possibility of a lethal outcome for intubated patients increased more than twice. CONCLUSIONS: The pneumothorax as a complication of COVID-19 carries high mortality and severely worsens the prognosis for these patients.

Acute exogenous intoxications and homocysteine.

INRODUCTION: Oxidative stress is an important pathogenetic factor in a number of socially significant diseases, including the acute exogenous poisoning. Homocysteine is a sulfur-containing amino acid synthesized on the basis of methionine, which plays an important role as an oxidizing agent in the human body. As such a factor, it was the monitored subject of this study. AIM: To measure the level of homocysteine in acute exogenous poisoning with alcohol, heroin and cerebro-toxic drugs. MATERIALS AND METHODS: This is a prospective longitudinal study including 118 patients with moderate or severe acute poisoning with cerebro-toxic drugs (n=45), alcohol (n=40), heroin (n=33) and a "control group" (n=35). Clinical laboratory tests were performed according to the standards of a clinical laboratory. In the statistical analysis we used alternative and variance analysis, parametric methods for hypothesis assessment, and nonparametric methods for normal distribution. RESULTS AND DISCUSSION: The results showed that for the three groups of intoxications, the average homocysteine levels were higher than those of the control group (р<0.001). The intergroup comparison criterion for normal distribution showed that the changes in patients with alcohol intoxication (u=3.39; р<0.001) and heroin intoxication (u=2.00; р<0.001) were highly statistically significant without correlating with the severity of the poisoning (р>0.05). CONCLUSION: There is a risk of oxidative stress in intoxication with alcohol and narcotics. A reliable marker for the complex evaluation of oxidative stress in people is monitoring the serum level of homocysteine and its careful interpretation.

Evaluating the Effectiveness of Simulation Training in Obstetrics and Gynecology, Pediatrics and Emergency Medicine.

Simulation training in medicine is a powerful tool for acquiring knowledge and practical skills in an environment close to the real world. Decreasing training opportunities directly on the patient tend to introduce simulations close to the real hospital environment without compromising the patient's safety. The aim of the study was to evaluate the effectiveness of simulation training in the Medical Simulation Training Center (MSTC) at the Medical University of Plovdiv. A prospective observational descriptive study was performed at the MSTC at Plovdiv Medical University between September 2017 and March 2019. The study included 245 respondents who participated in one or more practical simulation trainings and were surveyed. The results of the study suggest that the knowledge, skills and attitudes of the trainees improve after training sessions. By increasing the number of visits, the self-esteem and confidence in performing the manipulation also increases, knowledge and technical performance significantly improve and mistakes are reduced. A statistically significant relationship has been demonstrated between the sequence of visits and acquired competencies (p=0.0001). There are no performance mistakes in those attending three or more times, but 16.2% of them still experience uncertainty while performing. Here, however, 83.8% performed the manipulation automatically and without mistakes. Simulation training in medicine is effective and useful. It has its place in the curriculum for students and is a good tool for acquiring knowledge, skills and techniques in postgraduate education.