Medicina clinica
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Real-world registries have been critical to building the scientific knowledge of rare diseases, including Pulmonary Arterial Hypertension (PAH). In the past 4 decades, a considerable number of registries on this condition have allowed to improve the pathology and its subgroupś definition, to advance in the understanding of its pathophysiology, to elaborate prognostic scales and to check the transferability of the results from clinical trials to clinical practice. ⋯ For that reason, Machine Learning (ML) offer a unique opportunity to manage all these data and, finally, to obtain tools that may help to get an earlier diagnose, to help to deduce the prognosis and, in the end, to advance in Personalized Medicine. Thus, we present a narrative revision with the aims of, in one hand, summing up the aspects in which data extraction is important in rare diseases -focusing on the knowledge gained from PAH real-world registries- and, on the other hand, describing some of the achievements and the potential use of the ML techniques on PAH.
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Transthyretin-related amyloidosis (ATTRv) is a progressive multisystem disorder, predominantly involving the peripheral nerve system (PNS) and heart. Quantification of small fiber damage may help guide treatment decisions, as amyloid deposits frequently affect those fibers early in disease course. Corneal confocal microscopy (CCM) is a promising method to monitor patients with ATTRv, due to similarities between corneal nerves and PNS, as the cornea is innervated by Aδ and C fibers. ⋯ In a diverse cohort of ATTRv patients, CCM was the most frequent abnormal measurement. CCM can be a useful test to triage patients in the early disease stages and with few or equivocal symptoms.
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To elucidate the presence, importance, and characteristics of menstrual changes related to stressful circumstances during the COVID-19 lockdown in Spain. ⋯ Changes in emotional status, but not the length and intensity of the isolation or exposure to the disease, significantly influenced menstrual disturbances during the COVID-19 lockdown.