Velasquezbendix9152

Background and objective COPD is the third most common cause of death worldwide and fourth most common in the United States. In hospitalized patients with COPD, mortality, morbidity and healthcare resource utilization are high. Skeletal muscle loss is frequent in patients with COPD. However, the impact of muscle loss on adverse outcomes has not been systematically evaluated. We tested the hypothesis that patients hospitalized for COPD exacerbation with, compared to those without, a secondary diagnosis of muscle loss phenotype (all ICD-9 codes associated with muscle loss including cachexia) will have higher mortality and cost of care. Methods The NIS database of hospitalized patients in 2011 (1 January-31 December) in the United States was used. The impact of a muscle loss phenotype on in-hospital mortality, LOS and cost of care for each of the 174 808 hospitalizations for COPD exacerbations was analysed. Results Of the subjects admitted for a COPD exacerbation, 12 977 (7.4%) had a secondary diagnosis of muscle loss phenotype. A diagnosis of muscle loss phenotype was associated with significantly higher in-hospital mortality (14.6% vs 5.7%, P less then 0.001), LOS (13.3 + 17.1 vs 5.7 + 7.6, P less then 0.001) and median hospital charge per patient ($13 947 vs $6610, P less then 0.001). Multivariate regression analysis showed that muscle loss phenotype increased mortality by 111% (95% CI 2.0-2.2, P less then 0.001), LOS by 68.4% (P less then 0.001) and the direct cost of care by 83.7% (P less then 0.001) compared to those without muscle loss. Conclusion In-hospital mortality, LOS and healthcare costs are higher in patients with COPD exacerbations and a muscle loss phenotype.The Plumbaginaceae (non-core Caryophyllales) is a family well known for species adapted to a wide range of arid and saline habitats. Of its salt-tolerant species, at least 45 are in the genus Limonium; two in each of Aegialitis, Limoniastrum and Myriolimon, and one each in Psylliostachys, Armeria, Ceratostigma, Goniolimon and Plumbago. All the halophytic members of the family have salt glands and salt glands are also common in the closely related Tamaricaceae and Frankeniaceae. The halophytic species of the three families can secrete a range of ions (Na+ , K+ , Ca2+ , Mg2+ , Cl- , HCO3 - , SO4 2 ) and other elements (As, Cd, Cr, Cu, Fe, Mn, Ni, Pb and Zn). Salt glands are, however, absent in salt-tolerant members of the sister family Polygonaceae. We describe the structure of the salt glands in the three families and consider whether glands might have arisen as a means to avoid the toxicity of Na+ and/or Cl- or to regulate Ca2+ concentrations with the leaves. We conclude that the establishment of lineages with salt glands took place after the split between the Polygonaceae and its sister group the Plumbaginaceae. This article is protected by copyright. All rights reserved.Aims Tuberous sclerosis complex (TSC) is a multisystem genetic disorder caused by a mutation in the TSC1 or TSC2 gene with a broad spectrum of physical and psychological manifestations. The aim of the study was to examine incontinence, psychological problems, and adaptive behavior skills in patients with TSC. Methods Through a worldwide TSC support group, 26 children (4-17 years) and 15 adults (18-50 years) with TSC were recruited (38.1% male, mean age 16.4 years). Parents or care-givers completed the Developmental Behavior Checklist (DBC), the Parental Questionnaire Enuresis/urinary Incontinence, and the Vineland Adaptive Behavior Scales (3rd edition). Results A total of 60.0% of the participants had nocturnal enuresis (NE), 51.3% daytime urinary incontinence (DUI) and 52.4% fecal incontinence (FI). 65.4% of children and 50.0% of adults had a clinically relevant DBC score. Psychological symptoms were associated with at least one subtype of incontinence. The mean adaptive behavior composite (ABC) score of the patients was 57.2 (SD = 26.1), with 38.1% in the average or below-average range (IQ >70), 26.2% with a mild, 11.9% with a moderate and 23.8% with a severe/profound intellectual disability. The incontinence rate was significantly higher in the groups with a lower ABC score. Conclusion A substantial proportion of patients with TSC are affected by incontinence and psychological symptoms. Incontinence was higher in persons with lower adaptive skills and those with at least one type of incontinence showed a significantly higher DBC score. As incontinence and psychological problems affect daily functioning and well-being, assessment, and treatment are recommended.Purpose High-Dose-Rate (HDR) brachytherapy is one of the most effective ways to treat the prostate cancer, which is the second most common cancer in men worldwide. This treatment delivers highly conformal dose through the transperineal needle implants and is guided by a real time ultrasound (US) imaging system. Currently, the brachytherapy needles in the US images are manually segmented by physicists during the treatment, which is time-consuming and error-prone. In this study, we propose a set of deep learning based algorithms to accurately segment the brachytherapy needles and locate the needle tips from the US images. Methods Two deep neural networks are developed to address this problem. First, a modified deep U-Net is used to segment the pixels belonging to the brachytherapy needles from the US images. Second, an additional VGG-16 based deep convolutional network is combined with the segmentation network to predict the locations of the needle tips. The networks are trained and evaluated on a clinical US images dataset with labeled needle trajectories collected in our hospital (Institutional Review Board approval (IRB 41755)). Results The evaluation results show that our method can accurately extract the trajectories of the needles with a resolution of 0.668 mm and 0.319 mm in x and y direction respectively. 95.4% of the x direction and 99.2% of the y direction have error ≤ 2 mm. Moreover, The position resolutions of the tips are 0.721 mm, 0.369 mm and 1.877 mm in x, y and z directions respectively, while 94.2%, 98.3% and 67.5% of the data have error ≤ 2 mm. Conclusions This paper proposed a neural network based algorithm to segment the brachytherapy needles from the US images and locate the needle tip. selleckchem It can be used in the HDR brachytherapy to help improve the efficiency and quality of the treatments.