All Saints University Lango

Hyperkalemia, defined as a serum potassium level greater than 5.0 mEq/L, disrupts electrolyte balance and may cause neuromuscular symptoms, including palpitations, fatigue, or weakness. Severe cases exceeding 6.5 mEq/L can lead to life-threatening arrhythmias and cardiac arrest if left untreated. We present a 92-year-old female with stage 4 chronic kidney disease, diastolic heart failure, and a chronic right leg ulcer who arrived at the emergency department with lethargy and intermittent confusion following a fall. Laboratory results revealed a potassium level of 9.7 mEq/L, an estimated creatinine clearance of 9.4 mL/minute, a renal function index of 10.5, a bicarbonate level of 10.9 mEq/L, and a pH of 7.19. ECG demonstrated sinus bradycardia at 40 bpm, low-amplitude P waves, mild PR prolongation, and tall, narrow, symmetric T waves, most prominent in V2-V3 and multiple limb leads. The patient underwent emergent hemodialysis, which normalized her potassium level to 4.3 mEq/L within 24 hours. A repeat ECG showed resolution of abnormalities and restoration of a sinus rhythm at 95 bpm. This case highlights the life-saving importance of rapid ECG recognition, immediate laboratory confirmation, and prompt initiation of therapy in the management of severe hyperkalemia.

Although COVID-19 prevention measures played an important role in containing the pandemic, they had unintended consequences especially among vulnerable populations. This formative research sought to explore the impact of COVID-19 on women and youth in the Nakivale Refugee Settlement (NRS), Uganda. In this mixed-methods study, we administered surveys to 258 women and youth aged 15–35 years from NRS to capture data including food insecurity, asset index, financial support and social support. We conducted four focus group discussions (FGDs) with 40 purposively selected participants composed of women, youth and leaders. Quantitative data were descriptively analysed using STATA 13. Qualitative data were analysed using thematic analysis. Participants reported severe food insecurity ( n = 242, 90%), probable depression ( n = 129, 50%), low social-economic status ( n = 136, 54%), loss of employment/income ( n = 204, 79%), saving ( n = 203, 78%), assets ( n = 202, 78%) and financial support ( n = 210, 81%). Results from FGDs indicate that COVID-19 resulted in significant losses in human, social, natural, physical and financial capital among refugee women and youth. Future emergency response strategies should be designed based on the differentiated needs of vulnerable women and youth focusing on ensuring continuous access to essential services such as inclusive and gender-sensitive access to health, education and livelihood services.

Artificial intelligence (AI) is revolutionizing early cancer detection by enhancing the sensitivity, efficiency, and precision of screening programs for breast, colorectal, and lung cancers. Deep learning algorithms, such as convolutional neural networks, are pivotal in improving diagnostic accuracy by identifying patterns in imaging data that may elude human radiologists. AI has shown remarkable advancements in breast cancer detection, including risk stratification and treatment planning, with models achieving high specificity and precision in identifying invasive ductal carcinoma. In colorectal cancer screening, AI-powered systems significantly enhance polyp detection rates during colonoscopies, optimizing the adenoma detection rate and improving diagnostic workflows. Similarly, low-dose CT scans integrated with AI algorithms are transforming lung cancer screening by increasing the sensitivity and specificity of early-stage cancer detection, while aiding in accurate lesion segmentation and classification. This review highlights the potential of AI to streamline cancer diagnosis and treatment by analyzing vast datasets and reducing diagnostic variability. Despite these advancements, challenges such as data standardization, model generalization, and integration into clinical workflows remain. Addressing these issues through collaborative research, enhanced dataset diversity, and improved explainability of AI models will be critical for widespread adoption. The findings underscore AI's potential to significantly impact patient outcomes and reduce cancer-related mortality, emphasizing the need for further validation and optimization in diverse healthcare settings.

The gut microbiome's impact on physiological processes, influenced by diet and lifestyle, is profound. Dysbiosis, an imbalance in microbiota composition, is associated with diseases like obesity. This review explores the gut microbiome's role in metabolism and calorie intake, alongside recent AI advancements impacting personalized nutrition. AI has revolutionized microbiome research, especially in multi-omics data analysis. AI-driven approaches enable the integration and interpretation of diverse omics datasets, including genomics, metabolomics, and proteomics, providing comprehensive insights into the gut microbiome's functional dynamics and its impact on host metabolism. These facilitate the identification of microbial biomarkers associated with disease states and dietary interventions, paving the way for personalized nutrition strategies tailored to individual gut microbiome profiles. AI platforms can also offer tailored dietary recommendations based on microbiome composition and health objectives. Healthcare professionals leverage AI to optimize dietary interventions, promoting gut microbiome modulation and preventing chronic diseases. Challenges like data standardization and privacy persist, yet addressing them is vital for maximizing AI's benefits in health outcomes and precision medicine. Ongoing AI and microbiome research promise to revolutionize personalized nutrition and metabolic health worldwide.

A cutaneous horn is a yellow or white-colored conical projection made up of complex keratin that arises from the surface of the skin. It is usually diagnosed clinically but requires histologic examination to rule out malignancy or determine the underlying lesion. Verruca vulgaris, a human papillomavirus-associated lesion, is a very common benign underlying lesion. We present a case of an 80-year-old female who presented with a cutaneous horn on a unique location, the proximal interphalangeal joint (PIP) of her left fourth digit. Post-excision biopsy revealed a diagnosis of a verruca vulgaris-associated cutaneous horn.

Pancreatic pseudocyst is a common complication of pancreatitis and is usually located in the peripancreatic space, spleen, and retroperitoneum. An infected intrahepatic pseudocyst following acute on chronic pancreatitis is extremely rare. Here, we report a case of intrahepatic pancreatic pseudocyst with superimposed infection following chronic pancreatitis in a 42-year-old female who presented with severe abdominal pain, vomiting, and bloating sensation. Her labs showed elevated pancreatic enzymes (amylase and lipase), and a provisional diagnosis of acute pancreatitis was made. Imaging revealed a cystic lesion in the left lobe and a calcified pancreas. Endoscopic aspiration of the cystic lesion and pathologic examination confirmed infected intrahepatic pancreatic pseudocyst due to the high serum amylase level and positive Enterococci on culture in aspirated cystic fluid, complicated by chronic pancreatitis.

Age-related Macular Degeneration (AMD) is a major cause of blindness in the elderly. It is more prevalent in people above 65 years of age. Blindness caused by AMD is usually irreversible. Visual function in AMD patients deteriorates progressively and significantly impacts on their quality of life. The social costs of AMD are also on the high side. While treatment modalities like anti-VEGF treatment have been designed for neurovascular age-related macular degeneration, no treatment has yet been developed for geographical atrophy, and as such, prevention stands as the most cost-effective management of age-related macular degeneration. Current therapies are only capable of slowing the disease's natural course, but is incapable of stopping the progression of the disease. It is therefore important to have an in-depth understanding of the possibilities in order to be able to prevent disease progression. Pertaining to this, therefore, identification of risk factors plays a major role. A lot of research has been carried out on such risk factors as diet, light exposure, and lifestyle. Many studies have shown that an increased intake of nutrients, including zeaxanthin, lutein, omega-3 fatty acids, beta carotene, and zinc, drastically reduces the risk of agerelated macular degeneration. With respect to lifestyle habits, the relationship between AMD and smoking has been studied and accepted. It is also important to note that retinal damage due to blue light and ultraviolet rays should be considered. This review aims to summarize current knowledge on steps towards the prevention and management of AMD.

A neurodegenerative disorder, Alzheimer's disease (AD), is characterized by dementia in which there is an age-related decline in cognition and higher functions. Stroke is a cerebrovascular disorder that frequently presents in old age and is a known risk factor for AD development. However, the association that AD can be a risk factor for stroke is not well-studied. This review article compiled various studies that pointed out the association between stroke development in patients with dementia, particularly AD-related dementia. The pathophysiological progression of stroke in AD cases and the genetic makeup possibly affecting the interrelation between these disorders were analyzed in detail using currently available data and studies. Therapeutic and management modalities already in use for AD were put together, and the possibility of early intervention in such patients benefitting cerebrovascular pathologies, particularly stroke-related, was explored. Prognostic differences between patients of stroke with and without AD were also reviewed, and how appropriate management can reduce the burden on health care settings when both present simultaneously was emphasized.

Cancer of the lung is a malignant lung tumor with a wide range of histological variants. The tumor arises from different types of cells, such as bronchioles, epithelium, bronchial mucous glands, or the alveoli. How effective the treatment depends on the histological variant of the lung tumor. It is therefore necessary that the histology of cancer and the respective biomarkers be accurately identified. Detection of malignant cells is possible only when the clinician has an accurate knowledge of the origin and nature of these cells. It is pertinent to state that these malignant cells release certain biomarkers into the general circulation. Currently, screening for malignant tumors is done with various panels of biomarkers. To date, there is no one serum biomarker capable of identifying the various lung cancer types. As such, accurate diagnosis is done only with immunohistochemistry and histological analysis of tumor biopsies. This article discusses the different protein biomarkers employed in the diagnosis of lung cancer and recent advances in uniform biomarker discovery.