Medicina
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Acute pancreatitis has a diverse etiology and natural history, and some patients have severe complications with a high risk of mortality. The prediction of the severity of acute pancreatitis should be achieved by a careful ongoing clinical assessment coupled with the use of a multiple-factor scoring system and imaging studies. Over the past 40 years, various scoring systems have been suggested to predict the severity of acute pancreatitis. ⋯ The interest in new biological markers and predictive models for identifying severe acute pancreatitis testifies to the continued clinical importance of early severity prediction. Although contrast-enhanced computed tomography (CT) is considered the gold standard for diagnosing pancreatic necrosis, early scanning for the prediction of severity is limited because the full extent of pancreatic necrosis may not develop within the first 48 h of presentation. This article provides an overview of the available scoring systems and biochemical markers for predicting severe acute pancreatitis, with a focus on their characteristics and limitations.
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Despite remarkable advances in the clinical outcomes after anterior cruciate ligament reconstructions (ACLRs), residual rotational instability of the knee joint remains a major concern. Since the anterolateral ligament (ALL) on the knee joint has been "rediscovered", the role of anterolateral structures, including ALL and deep iliotibial band, as secondary stabilizers of anterolateral rotatory instability has gained interest. ⋯ However, the difference in concepts between anterolateral ligament reconstructions (ALLRs) as anatomical reconstruction and lateral extra-articular tenodesis (LETs) as non-anatomical reinforcement has been conflicting in present literature. This study aimed to review the anatomy and biomechanics of anterolateral structures, surgical techniques, and the clinical outcomes of anterolateral procedures, including LET and ALLR, in patients with ACL deficiencies.
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Background and Objectives: The consumption of dietary supplements has increased over the last decades among pregnant women, becoming an efficient resource of micronutrients able to satisfy their nutritional needs during pregnancy. Furthermore, gestational drug administration might be necessary to treat several pregnancy complications such as hypertension. Folic acid (FA) and folate (FT) supplementation is highly recommended by clinicians during pregnancy, especially for preventing neural tube birth defects, while labetalol (LB) is a β-blocker commonly administered as a safe option for the treatment of pregnancy-related hypertension. ⋯ Additionally, LB (50 and 150 nM)−FA (0.2 nM) exerted an efficient wound regenerating potential in H9c2(2-1) myoblasts (wound healing rates were >80%, compared to the control at 66%), while LB-FT (at all tested concentrations) induced no significant impairment to their migration. Conclusions: Overall, our findings indicate that LB-FA and LB-FT combinations lack cytotoxicity in vitro. Moreover, beneficial effects were noticed on H9c2(2-1) cell viability and migration from LB-FA/FT administration, which should be further explored.
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Patients with severe acute pancreatitis (SAP) present complications and organ failure, which require treatment in critical care units. These extrapancreatic complications determine the clinical outcome of the disease. Intra-abdominal hypertension (IAH) deteriorates the prognosis of SAP. ⋯ Intra-abdominal pressure should be measured in all SAP cases that worsen despite adequate treatment in critical care units. Conservative measures must be introduced to treat IAH, including negative fluid balance, digestive decompression by gastric-rectal tube, and prokinetics, including neostigmine. In the case of insufficient responses to these measures, minimally invasive interventions should be preferred.
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Background and Objectives: Polysomnography is manually scored by sleep experts. However, manual scoring is a time-consuming and labor-intensive task. The goal of this study was to verify the accuracy of automated sleep-stage scoring based on a deep learning algorithm compared to manual sleep-stage scoring. ⋯ The average kappa value was 0.84. For the bootstrap method, high overall agreement between the automated deep learning algorithm and manual scoring was observed in stages W (98%), N1 (94%), N2 (92%), N3 (99%), and R (98%) and total (96%). Conclusions: Automated sleep-stage scoring using the proposed model may be a reliable method for sleep-stage classification.