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1.
Kara S. Tanaka MD Veronica R. Andaya BA Steven W. Thorpe MD Kenneth R. Gundle MD James B. Hayden MD Yee-Cheen Duong MD Raffi S. Avedian MD David G. Mohler MD Lee J. Morse MD Melissa N. Zimel MD Richard J. O'Donnell MD Andrew Fang MD Robert Lor Randall MD Tina H. Tran BS Christin New BA Rosanna L. Wustrack MD other members of Study Group FORCE 《Journal of surgical oncology》2023,127(1):148-158
2.
Jasmine Poonian Nicola Walsham Thomas Kilner Elizabeth Bradbury Kristen Brooks Emma West 《Emergency medicine Australasia : EMA》2020,32(4):700-702
Emergency Medicine staff in Australia and New Zealand are at the forefront of the healthcare response to COVID‐19. This article describes a well‐being plan for ED staff that has been devised to mitigate against the negative psychological impact of the COVID‐19 pandemic. 相似文献
3.
L. Umapathy G.G. Perez-Carrillo M.B. Keerthivasan J.A. Rosado-Toro M.I. Altbach B. Winegar C. Weinkauf A. Bilgin for the Alzheimers Disease Neuroimaging Initiative 《AJNR. American journal of neuroradiology》2021,42(4):639
BACKGROUND AND PURPOSE:Accurate and reliable detection of white matter hyperintensities and their volume quantification can provide valuable clinical information to assess neurologic disease progression. In this work, a stacked generalization ensemble of orthogonal 3D convolutional neural networks, StackGen-Net, is explored for improving automated detection of white matter hyperintensities in 3D T2-FLAIR images.MATERIALS AND METHODS:Individual convolutional neural networks in StackGen-Net were trained on 2.5D patches from orthogonal reformatting of 3D-FLAIR (n = 21) to yield white matter hyperintensity posteriors. A meta convolutional neural network was trained to learn the functional mapping from orthogonal white matter hyperintensity posteriors to the final white matter hyperintensity prediction. The impact of training data and architecture choices on white matter hyperintensity segmentation performance was systematically evaluated on a test cohort (n = 9). The segmentation performance of StackGen-Net was compared with state-of-the-art convolutional neural network techniques on an independent test cohort from the Alzheimer’s Disease Neuroimaging Initiative-3 (n = 20).RESULTS:StackGen-Net outperformed individual convolutional neural networks in the ensemble and their combination using averaging or majority voting. In a comparison with state-of-the-art white matter hyperintensity segmentation techniques, StackGen-Net achieved a significantly higher Dice score (0.76 [SD, 0.08], F1-lesion (0.74 [SD, 0.13]), and area under precision-recall curve (0.84 [SD, 0.09]), and the lowest absolute volume difference (13.3% [SD, 9.1%]). StackGen-Net performance in Dice scores (median = 0.74) did not significantly differ (P = .22) from interobserver (median = 0.73) variability between 2 experienced neuroradiologists. We found no significant difference (P = .15) in white matter hyperintensity lesion volumes from StackGen-Net predictions and ground truth annotations.CONCLUSIONS:A stacked generalization of convolutional neural networks, utilizing multiplanar lesion information using 2.5D spatial context, greatly improved the segmentation performance of StackGen-Net compared with traditional ensemble techniques and some state-of-the-art deep learning models for 3D-FLAIR.White matter hyperintensities (WMHs) correspond to pathologic features of axonal degeneration, demyelination, and gliosis observed within cerebral white matter.1 Clinically, the extent of WMHs in the brain has been associated with cognitive impairment, Alzheimer’s disease and vascular dementia, and increased risk of stroke.2,3 The detection and quantification of WMH volumes to monitor lesion burden evolution and its correlation with clinical outcomes have been of interest in clinical research.4,5 Although the extent of WMHs can be visually scored,6 the categoric nature of such scoring systems makes quantitative evaluation of disease progression difficult. Manually segmenting WMHs is tedious, prone to inter- and intraobserver variability, and is, in most cases, impractical. Thus, there is an increased interest in developing fast, accurate, and reliable computer-aided automated techniques for WMH segmentation.Convolutional neural network (CNN)-based approaches have been successful in several semantic segmentation tasks in medical imaging.7 Recent works have proposed using deep learning–based methods for segmenting WMHs using 2D-FLAIR images.8-11 More recently, a WMH segmentation challenge12 was also organized (http://wmh.isi.uu.nl/) to facilitate comparison of automated segmentation of WMHs of presumed vascular origin in 2D multislice T2-FLAIR images. Architectures that used an ensemble of separately trained CNNs showed promising results in this challenge, with 3 of the top 5 winners using ensemble-based techniques.12Conventional 2D-FLAIR images are typically acquired with thick slices (3–4 mm) and possible slice gaps. Partial volume effects from a thick slice are likely to affect the detection of smaller lesions, both in-plane and out-of-plane. 3D-FLAIR images, with isotropic resolution, have been shown to achieve higher resolution and contrast-to-noise ratio13 and have shown promising results in MS lesion detection using 3D CNNs.14 Additionally, the isotropic resolution enables viewing and evaluation of the images in multiple planes. This multiplanar reformatting of 3D-FLAIR without the use of interpolating kernels is only possible due to the isotropic nature of the acquisition. Network architectures that use information from the 3 orthogonal views have been explored in recent works for CNN-based segmentation of 3D MR imaging data.15 The use of data from multiple planes allows more spatial context during training without the computational burden associated with full 3D training.16 The use of 3 orthogonal views simultaneously mirrors how humans approach this segmentation task.Ensembles of CNNs have been shown to average away the variances in the solution and the choice of model- and configuration-specific behaviors of CNNs.17 Traditionally, the solutions from these separately trained CNNs are combined by averaging or using a majority consensus. In this work, we propose the use of a stacked generalization framework (StackGen-Net) for combining multiplanar lesion information from 3D CNN ensembles to improve the detection of WMH lesions in 3D-FLAIR. A stacked generalization18 framework learns to combine solutions from individual CNNs in the ensemble. We systematically evaluated the performance of this framework and compared it with traditional ensemble techniques, such as averaging or majority voting, and state-of-the-art deep learning techniques. 相似文献
4.
5.
Characteristics of hyperparathyroid states in the Canadian multicentre osteoporosis study (CaMos) and relationship to skeletal markers 下载免费PDF全文
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7.
K. Bhatia Group of Obstetric Anaesthetists of Lancashire Greater Manchester Mersey Study Collaborators 《Anaesthesia》2022,77(4):389-397
Since the start of the COVID-19 pandemic, few studies have reported anaesthetic outcomes in parturients with SARS-CoV-2 infection. We reviewed the labour analgesic and anaesthetic interventions utilised in symptomatic and asymptomatic parturients who had a confirmed positive test for SARS-CoV-2 across 10 hospitals in the north-west of England between 1 April 2020 and 31 May 2021. Primary outcomes analysed included the analgesic/anaesthetic technique utilised for labour and caesarean birth. Secondary outcomes included a comparison of maternal characteristics, caesarean birth rate, maternal critical care admission rate along with adverse composite neonatal outcomes. A positive SARS-CoV-2 test was recorded in 836 parturients with 263 (31.4%) reported to have symptoms of COVID-19. Neuraxial labour analgesia was utilised in 104 (20.4%) of the 509 parturients who went on to have a vaginal birth. No differences in epidural analgesia rates were observed between symptomatic and asymptomatic parturients (OR 1.03, 95%CI 0.64–1.67; p = 0.90). The neuraxial anaesthesia rate in 310 parturients who underwent caesarean delivery was 94.2% (95%CI 90.6–96.0%). The rates of general anaesthesia were similar in symptomatic and asymptomatic parturients (6% vs. 5.7%; p = 0.52). Symptomatic parturients were more likely to be multiparous (OR 1.64, 95%CI 1.19–2.22; p = 0.002); of Asian ethnicity (OR 1.54, 1.04–2.28; p = 0.03); to deliver prematurely (OR 2.16, 95%CI 1.47–3.19; p = 0.001); have a higher caesarean birth rate (44.5% vs. 33.7%; OR 1.57, 95%CI 1.16–2.12; p = 0.008); and a higher critical care utilisation rate both pre- (8% vs. 0%, p = 0.001) and post-delivery (11% vs. 3.5%; OR 3.43, 95%CI 1.83–6.52; p = 0.001). Eight neonates tested positive for SARS-CoV-2 while no differences in adverse composite neonatal outcomes were observed between those born to symptomatic and asymptomatic mothers (25.8% vs. 23.8%; OR 1.11, 95%CI 0.78–1.57; p = 0.55). In women with COVID-19, non-neuraxial analgesic regimens were commonly utilised for labour while neuraxial anaesthesia was employed for the majority of caesarean births. Symptomatic women with COVID-19 are at increased risk of significant maternal morbidity including preterm birth, caesarean birth and peripartum critical care admission. 相似文献
8.
Alexander C. Egbe Rosalyn Adigun Vidhu Anand Collin P. West Victor M. Montori Hassan M. Murad Emmanuel Akintoye Karim Osman Heidi M. Connolly 《The Canadian journal of cardiology》2019,35(12):1784-1790
BackgroundAlthough there are robust data about the pathophysiology and prognostic implications of left ventricular (LV) systolic dysfunction in patients with acquired heart disease, similar prognostic data about LV systolic dysfunction are sparse in the tetralogy of Fallot (TOF) population. The purpose of this study was to perform a meta-analysis of all studies that assessed the relationship between LV ejection fraction (LVEF) and cardiovascular adverse events (CAEs) defined as death, aborted sudden death, or sustained ventricular tachycardia.MethodsWe used random-effects models to calculate hazard ratios (HRs) and 95% confidence intervals (CIs).ResultsOf the 1,809 citations, 7 studies with 2,854 patients (age 28 ± 4 years) were included. During 5.6 ± 3.4 years' follow-up, there were 82 deaths, 17 aborted sudden cardiac deaths, and 56 sustained ventricular tachycardia events. Overall, CAEs occurred in 5.1% (144 patients). As a continuous variable, LVEF was a predictor of CAE (HR 1.29, 95% CI, 1.09-1.53, P = 0.001) per 5% decrease in LVEF. Similarly, LVEF < 40% was also a predictor of CAE (HR 3.22, 95% CI, 2.16-4.80, P < 0.001).ConclusionsLV systolic dysfunction was an independent predictor of CAE, and we observed a 30% increase in the risk of CAE for every 5% decrease in LVEF, and a 3-fold increase in the risk of CAE in patients with LVEF <40% compared with other patients. These findings underscore the importance of incorporating LV systolic function in clinical risk stratification of patients with TOF and the need to explore new treatment options to address this problem. 相似文献
9.
L. Misery E. Weisshaar E. Brenaut A.W.M. Evers F. Huet S. Ständer A. Reich E. Berardesca E. Serra-Baldrich J. Wallengren D. Linder J.W. Fluhr J.C. Szepietowski H. Maibach for the Special Interest Group on sensitive skin of the International Forum for the Study of Itch 《Journal of the European Academy of Dermatology and Venereology》2020,34(2):222-229
The special interest group on sensitive skin of the International Forum for the Study of Itch previously defined sensitive skin as a syndrome defined by the occurrence of unpleasant sensations (stinging, burning, pain, pruritus and tingling sensations) in response to stimuli that normally should not provoke such sensations. This additional paper focuses on the pathophysiology and the management of sensitive skin. Sensitive skin is not an immunological disorder but is related to alterations of the skin nervous system. Skin barrier abnormalities are frequently associated, but there is no cause and direct relationship. Further studies are needed to better understand the pathophysiology of sensitive skin – as well as the inducing factors. Avoidance of possible triggering factors and the use of well-tolerated cosmetics, especially those containing inhibitors of unpleasant sensations, might be suggested for patients with sensitive skin. The role of psychosocial factors, such as stress or negative expectations, might be relevant for subgroups of patients. To date, there is no clinical trial supporting the use of topical or systemic drugs in sensitive skin. The published data are not sufficient to reach a consensus on sensitive skin management. In general, patients with sensitive skin require a personalized approach, taking into account various biomedical, neural and psychosocial factors affecting sensitive skin. 相似文献
10.
Parallel enzyme‐linked immunosorbent assay screening for human immunodeficiency virus among blood donors in five Chinese blood centres: a retrospective analysis 下载免费PDF全文