The American journal of medicine
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Machine learning has emerged as a significant tool to augment the medical decision-making process. Studies have steadily accrued detailing algorithms and models designed using machine learning to predict and anticipate pathologic states. The cardiac intensive care unit is an area where anticipation is crucial in the division between life and death. In this paper, we aim to review important studies describing the utility of machine learning algorithms to describe the future of artificial intelligence in the cardiac intensive care unit, especially in regards to the prediction of successful ventilatory weaning, acute respiratory distress syndrome, arrhythmia, and acute kidney injury.
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As the prevalence of obesity rises in the United States, so does the incidence of obesity-related kidney disease. Obesity itself is an independent risk factor for chronic kidney disease where the pathophysiology is complex, involving altered hemodynamics, renin-angiotensin-aldosterone system overactivation, and adipokines leading to inflammation and fibrosis. Obesity-related kidney disease comprises both obesity-related glomerulopathy and fatty kidney disease. ⋯ Whether the renal ectopic fat is a distinct clinical entity or a pathologic mechanism contributing to obesity-related glomerulopathy, the treatment paradigm of weight and proteinuria reduction remains the same. We present the pathophysiology behind obesity-related kidney disease, clinical outcomes, and treatment strategies, which include lifestyle interventions, use of renin-angiotensin-aldosterone system inhibitors, glucagon-like peptide 1 receptor agonists, sodium-glucose co-transporter-2 inhibitors, and bariatric surgery. With old and novel therapeutics, we are attempting to stave off the silent epidemic that obesity-related kidney disease is becoming.
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Review
Should antihypertensive medications be routinely administered in the nighttime instead of daytime?
The optimal timing for administering antihypertensive medications remains a topic of debate. This review examines the effectiveness of nighttime vs daytime administration of antihypertensive medications in controlling blood pressure (BP). The MAPEC and Hygia trials suggest that nighttime dosing achieves better BP control and significantly lowers cardiovascular events. ⋯ In contrast, the HARMONY and TIME trials found no significant difference in BP control nor cardiovascular outcomes between daytime and nighttime dosing. Current research suggests that the timing of antihypertensive medication administration may not be a crucial factor. Therefore, the decision about the timing of antihypertensive medications administration should be individualized, taking into account patient preference and clinical context, in order to promote consistent compliance.