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31.
Yu Fan Xiaoling Liao Yuesong Pan Kehui Dong Yilong Wang Yongjun Wang 《Journal of stroke and cerebrovascular diseases》2019,28(1):220-226
Background
The intravenous thrombolysis (IVT) with recombinant tissue plasminogen activator (rt-PA) therapy is safe and efficient during the treatment of acute ischemic stroke. Nonetheless, the different outcomes among various stroke subgroups have limited data with regard to the safety and efficacy of cryptogenic stroke (CS). The present study compared the safety and efficacy when IVT with rt-PA was used for the treatment of CS and the other stroke subtypes.Methods
This study classified the IVT with rt-PA patients within 4.5 hours after stroke onset, based on the trial of ORG 10172 in acute stroke treatment criteria in terms of diagnostic evaluation. The data were obtained from the Thrombolysis Implementation and Monitor of Acute Ischemic Stroke in China database, a large multicenter prospective registry. A multivariable logistic regression model was employed to compare the differences between the subtypes in symptomatic intracerebral hemorrhage (sICH) within 7 days and studied the mortality and the outcome during 90 days.Results
In total, 1118 patients were recruited; of these, 131 (11.7%) suffered from CS and 987 (88.3%) with the other etiology. In the CS group, patients were younger than those in the other etiology groups (P < .001). Moreover, it had a lower prevalence of previous stroke (P?=?.0117), receiving antiplatelet drug in 24 hours prior to thrombolysis (P?=?.0017), and functional independence (mRS > 1 before stroke, P?=?.003). The CS group had lower blood pressure (systolic blood pressure P?=?.0001; diastolic blood pressure; P?=?.0212) before thrombolysis, atrial fibrillation (P < .001), and diabetes mellitus (P?=?.0005). Transient ischemic attack, hypertension, hyperlipidemia, blood glucose, receiving anticoagulants in 24 hours prior to thrombolysis, and standard dosage of rt-PA were equally distributed in both groups. After the adjustment of confounders between the CS and the other subgroups, no obvious differences were observed in sICH rate and mortality (P > .05) The CS patients exhibited excellent recovery (mRS, 0-1; 63.78%) and functional independence (mRS, 0-2; 74.8%) than the large artery atherosclerosis patients.Conclusions
IVT with rt-PA is a safe and effective method for the treatment of CS patients. 相似文献32.
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新型冠状病毒肺炎(corona virus disease 2019,COVID-19)自2019年12月爆发以来,由于具有高传染性,迅速在世界各地蔓延,国内外疫情防治形势空前严峻。COVID-19不仅造成肺部、肠道、肾脏等多脏器损害,且部分患者以眼表损害为首发或伴发症状出现,临床上很容易被忽视。COVID-19的眼表损害归属于祖国医学“天行赤眼”范畴,本文结合国内外最新的文献报道,探讨新型冠状病毒(2019 novel corona virus,2019-nCoV)对眼表的损害,阐明其可能机制,并从中西医角度提出可行的治疗措施。 相似文献
36.
目的:探讨醛-酮还原酶家族7成员A3(AKR7A3)在肺腺癌中的异常表达及与临床病理特征的关系,并探究其临床意义。方法:采用生物信息学数据库分析、免疫组化、Western Blot、Real-time PCR等方法对肺腺癌组织及不同细胞中AKR7A3的表达进行检测与分析。结果:Oncomine数据库分析结果显示,在肺腺癌中,AKR7A3的表达普遍高于正常肺组织,分别为正常肺组织的1.811倍(P=0.022)、1.356倍(P<0.01)、1.413倍(P=0.002)。Kaplan-Meier Plotter数据库分析结果显示,AKR7A3高表达的患者较低表达的患者生存时间缩短,差异具有统计学意义(P=0.003 7)。免疫组化染色显示肺腺癌组织中AKR7A3的表达较癌旁增高,在与临床病理特征的相关性分析中,发现其与肿瘤分化程度(P<0.01)、淋巴结转移情况(P=0.029)以及TNM分期(P<0.01)相关,且会造成患者生存时间缩短(P=0.031)。Cox多因素分析表明AKR7A3可能是影响肺腺癌患者预后的独立危险因素(P=0.012)。Western Blot及Real-time PCR实验提示不同肺腺癌细胞中AKR7A3蛋白及mRNA表达普遍增高。结论:AKR7A3在肺腺癌中表达增高,对预后有不良影响,有促进肿瘤发生发展的作用。 相似文献
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The significance of hepatobiliary scintigraphy (HBS) for hepatic graft function assessment was established mostly on retrospective studies and was not widely recognized due to the lack of quantitative data and variation in accuracy. This prospective study was performed to investigate the effectiveness of quantitative HBS for assessing hepatocyte dysfunction and biliary complication in liver transplant recipients.In 57 recipients who had undergone orthotopic liver transplantation, a total of 67 dynamic 99mTc-EHIDA scans were performed and quantitative parameters including the hepatocyte extraction fraction (HEF), time to maximum hepatic radioactivity (Tmax), and time for peak activity to decrease by 50% (T1/2) were calculated. The scintigraphic results based on the 3 parameters were compared against the final diagnosis. A ROC curve analysis was carried out to identify the cutoff value of Tmax for diagnosis of biliary stricture. Correlation between the parameters of postoperative HBS and conventional biochemical liver function indices were also analyzed.Quantitative 99mTc-EHIDA HBS had an overall sensitivity of 94.12% (16/17), specificity of 93.33% (42/45), and diagnostic accuracy of 93.55% (58/62) for detecting hepatocyte dysfunction and biliary complication in liver transplant recipients. The recommended cutoff value of Tmax for diagnosis of post-transplant biliary stricture was set at 15.75 min with a sensitivity of 100.0% and a specificity of 94.0%. The scintigraphic parameters (HEF, Tmax) were statistically significantly associated with the conventional liver function parameters.Quantitative 99mTc-EHIDA HBS offers a noninvasive imaging modality with high sensitivity and specificity to diagnose hepatocyte dysfunction as well as distinguish between patients with or without biliary stricture following liver transplantation. Furthermore, HEF and Tmax values obtained from dynamic HBS show good correlation with conventional liver function parameters. 相似文献
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Learning to Discretize: Solving 1D Scalar Conservation Laws via Deep Reinforcement Learning 下载免费PDF全文
Yufei Wang Ziju Shen Zichao Long & Bin Dong 《Communications In Computational Physics》2020,28(5):2158-2179
Conservation laws are considered to be fundamental laws of nature. It has
broad applications in many fields, including physics, chemistry, biology, geology, and
engineering. Solving the differential equations associated with conservation laws is a
major branch in computational mathematics. The recent success of machine learning,
especially deep learning in areas such as computer vision and natural language processing, has attracted a lot of attention from the community of computational mathematics and inspired many intriguing works in combining machine learning with traditional methods. In this paper, we are the first to view numerical PDE solvers as an
MDP and to use (deep) RL to learn new solvers. As proof of concept, we focus on
1-dimensional scalar conservation laws. We deploy the machinery of deep reinforcement learning to train a policy network that can decide on how the numerical solutions should be approximated in a sequential and spatial-temporal adaptive manner.
We will show that the problem of solving conservation laws can be naturally viewed
as a sequential decision-making process, and the numerical schemes learned in such a
way can easily enforce long-term accuracy. Furthermore, the learned policy network
is carefully designed to determine a good local discrete approximation based on the
current state of the solution, which essentially makes the proposed method a meta-learning approach. In other words, the proposed method is capable of learning how to
discretize for a given situation mimicking human experts. Finally, we will provide details on how the policy network is trained, how well it performs compared with some
state-of-the-art numerical solvers such as WENO schemes, and supervised learning
based approach L3D and PINN, and how well it generalizes. 相似文献