RESUMO
This comprehensive literature review explores the transformative impact of artificial intelligence (AI) predictive analytics on healthcare, particularly in improving patient outcomes regarding disease progression, treatment response, and recovery rates. AI, encompassing capabilities such as learning, problem-solving, and decision-making, is leveraged to predict disease progression, optimize treatment plans, and enhance recovery rates through the analysis of vast datasets, including electronic health records (EHRs), imaging, and genetic data. The utilization of machine learning (ML) and deep learning (DL) techniques in predictive analytics enables personalized medicine by facilitating the early detection of conditions, precision in drug discovery, and the tailoring of treatment to individual patient profiles. Ethical considerations, including data privacy, bias, and accountability, emerge as vital in the responsible implementation of AI in healthcare. The findings underscore the potential of AI predictive analytics in revolutionizing clinical decision-making and healthcare delivery, emphasizing the necessity of ethical guidelines and continuous model validation to ensure its safe and effective use in augmenting human judgment in medical practice.
RESUMO
ST-Elevation Myocardial Infarction and non-ST Elevation Myocardial Infarction belong to the acute coronary syndrome group of diseases. These conditions are characterized by the complete or partial blockage of one or several coronary arteries, resulting in myocardial injury or necrosis. Various medications are used in their treatment, with the most recent addition being Glycoprotein IIb/IIIa inhibitors. They work by hindering the activity of glycoprotein IIb/IIIa receptors, which, in turn, prevents the clumping of platelets. Some of the GpIIb/IIIa inhibitors available in this category include abciximab, tirofiban, eptifibatide, roxifiban, and orbofiban. With this comprehensive literature review, we aimed to explore the potential adverse effects of these medications and compare the three in terms of their side effects profile. We searched through PubMed and Google Scholar and pinpointed 13 articles aligned with our inclusion criteria: six articles utilized eptifibatide, four were related to abciximab, and three used tirofiban. In 85% of the cases, a severe drop in platelet count, reaching as low as 1000/µL, was reported. Additionally, several other side effects were noted: one case documented multiple bruising spots appearing around the patient's body, two cases reported diffuse alveolar hemorrhage, and one case described a cardiac tamponade resulting from hemorrhagic pericarditis. Our study highlights the crucial significance of keeping a watchful eye on and comprehending the potential drawbacks linked to these medications in cardiovascular treatment. The necessity of researching these medications and their side effects is also evident, as this will significantly enhance the quality of treatment provided.
