Artificial intelligence (AI) and machine learning (ML) is a promising field of cardiovascular medicine. Many AI tools have been shown to be efficacious with a high level of accuracy. Yet, their use in real life is not well established. In the era of health technology and data science, it is crucial to consider how these tools could improve healthcare delivery. This is particularly important in countries with limited resources, such as low- and middle-income countries (LMICs). LMICs have many barriers in the care continuum of cardiovascular diseases (CVD), and big portion of these barriers come from scarcity of resources, mainly financial and human power constraints. AI/ML could potentially improve healthcare delivery if appropriately applied in these countries. Expectedly, the current literature lacks original articles about AI/ML originating from these countries. It is important to start early with a stepwise approach to understand the obstacles these countries face in order to develop AI/ML-based solutions. This could be detrimental to many patients’ lives, in addition to other expected advantages in other sectors, including the economy sector. In this report, we aim to review what is known about AI/ML in cardiovascular medicine, and to discuss how it could benefit LMICs.

Nephrotic syndrome (NS) is a kidney illness characterized by excessive proteinuria, hypoalbuminemia, edema, and hyperlipidemia, which may lead to kidney failure and necessitate renal transplantation. End-stage renal disease, cardiovascular issues, and mortality are much more common in those with NS. Therefore, the present study aimed to identify potential new biomarkers associated with the pathogenesis and diagnosis of NS. The liquid chromatography–mass spectrometry (LC–MS) metabolomics approach was applied to profile the metabolome of human serum of patients with NS. A total of 176 metabolites were significantly altered in NS compared to the control. Arginine, proline, and tryptophan metabolism; arginine, phenylalanine, tyrosine, and tryptophan biosynthesis were the most common metabolic pathways dysregulated in NS. Furthermore, alanyl-lysine and isoleucyl-threonine had the highest discrimination between NS and healthy groups. The candidate biomarkers may lead to understanding the possible metabolic alterations associated with NS and serve as potential diagnostic biomarkers.

A compelling intervention to maintain healthy gut microbiota in graft-versus-host-disease (GVHD) is fecal microbial transplantation (FMT). To examine its role in GVHD, we conducted a systemic literature search using multiple electronic databases. Upon pooling of data, 79 patients from six studies and five case reports were included. Complete remission (CR) occurred in 55.9% of patients, and partial remission (PR) occurred in 26.5% of patients (82.4% overall response rate). A limited number of patients had treatment-related mortality (TRM), while few showed mild gastrointestinal (GI)-related and non-GI adverse effects. None of the studies directly examined the role of FMT in the prevention of GVHD. In conclusion, FMT seems to be a safe and effective strategy for the management of GVHD based on the current evidence. Due to the small number of patients evaluated and the absence of randomized data, one cannot portray FMT as a standard of care yet; however, the low toxicity along with the clinical improvement justifies this modality to be tested in a randomized fashion.

Cystic renal disease (CRD) comprises a heterogeneous group of genetic and acquired disorders. The cystic lesions are detected through imaging, either incidentally or after symptoms develop, due to an underlying disease process. In this study, we aim to study the metabolomic profiles of CRD patients for potential disease-specific biomarkers using unlabeled and labeled metabolomics using low and high-resolution mass spectrometry (MS), respectively. Dried-blood spot (DBS) and serum samples, collected from CRD patients and healthy controls, were analyzed using the unlabeled and labeled method. The metabolomics profiles for both sets of samples and groups were collected, and their data were processed using the lab’s standard protocol. The univariate analysis showed (FDR p < 0.05 and fold change 2) was significant to show a group of potential biomarkers for CRD discovery, including uridine diphosphate, cystine-5-diphosphate, and morpholine. Several pathways were involved in CRD patients based on the metabolic profile, including aminoacyl-tRNA biosynthesis, purine and pyrimidine, glutathione, TCA cycle, and some amino acid metabolism (alanine, aspartate and glutamate, arginine and tryptophan), which have the most impact. In conclusion, early CRD detection and treatment is possible using a metabolomics approach that targets alanine, aspartate, and glutamate pathway metabolites.

Tuberculosis (TB) is an infection caused by Mycobacterium tuberculosis that primarily affects the lungs. Although TB can affect many organs, involvement of the head and neck is extremely rare and involvement of the salivary glands is even rarer. Clinical diagnosis is challenging and may be misdiagnosed, as it mimics neoplasms on physical exams and imaging. In this paper, we present a case of parotid tuberculosis in a 28-year-old man who presented with a painful left parotid mass, loss of appetite, fever, and weight loss for six months. Suspicion of infection arose, and treatment began with intravenous antibiotics, followed by oral antibiotics, with no improvement. A biopsy of the patient's left parotid gland was performed, and a diagnosis of parotid TB with jaw osteomyelitis due to Mycobacterium tuberculosis infection was made. The patient was started on isoniazid for one week, followed by isoniazid, ethambutol, and rifampicin for six months. Follow-up after six months showed full resolution of the swelling.