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91.
目的 探讨综合医院发热门诊应对新型冠状病毒感染肺炎的应急管理方法及效果。
方法 加强发热门诊的管理,包括优化发热预检分诊工作流程、合理布局发热门诊、修订发热门诊工作职责与流程指引、合理调配人力资源、加强相关人员培训、严格落实院感防控措施、提供后勤保障、加强健康宣教与管理。
结果 接诊患者13 761例次,采集咽拭子591例次,静脉输液11 973例次,氧气吸入998例次。
结论 加强综合医院发热门诊管理,能有效提高护理人员对新型冠状病毒肺炎疫情的应对能力,保障护理安全。 相似文献
92.
This meta-analysis examined whether early decompressive craniectomy (DC) can improve control of intracranial pressure (ICP) and mortality in patients with traumatic brain injury (TBI).Medline, Cochrane, EMBASE, and Google Scholar databases were searched until May 14, 2015, using the following terms: traumatic brain injury, refractory intracranial hypertension, high intracranial pressure, craniectomy, standard care, and medical management. Randomized controlled trials in which patients with TBI received DC and non-DC medical treatments were included.Of the 84 articles identified, 8 studies were selected for review, with 3 randomized controlled trials s having a total of 256 patients (123 DCs, 133 non-DCs) included in the meta-analysis. Patients receiving DC had a significantly greater reduction of ICP and shorter hospital stay. They also seemed to have lower odds of death than patients receiving only medical management, but the P value did not reach significance (pooled odds ratio 0.531, 95% confidence interval 0.209–1.350, Z = 1.95, P = 0.183) with respect to the effect on overall mortality; a separate analysis of 3 retrospective studies yielded a similar result.Whereas DC might effectively reduce ICP and shorten hospital stay in patients with TBI, its effect in decreasing mortality has not reached statistical significance. 相似文献
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The associations between saturated fatty acid (SFA) consumption and risk of breast cancer (BC) remains inconclusive. Therefore, we conducted this meta-analysis to determine the quantitative relations between dietary SFA intake and incidence of BC.Literatures published up to April 2015 were systematically screened through Pubmed and Web of Science. Relevant publication quality was evaluated by conducting the Newcastle-Ottawa scale. We used fixed effects models or random effect models to calculate the summary relative risks (RRs) and odds ratios (ORs), and conducted sensitivity analyses and evaluated the publication bias.We identified a total of 52 studies (24 cohort studies and 28 case–control studies), with over 50,000 females diagnosed with BC. The associations between dietary SFA intake and risk of BC were 1.18 for case–control studies (high vs low intake, 95% confidence interval [CI] = 1.03–1.34) and 1.04 for cohort studies (95% CI = 0.97–1.11). When restricted analyses to population-based studies, positive associations were observed for both cohort (RR [95% CI] = 1.11 [1.01–1.21]) and case–control studies (OR [95% CI] = 1.26 [1.03–1.53]). Additionally, for case–control studies, significant positive associations between higher SFA intake and BC risk were observed for Asian (OR [95% CI] = 1.17 [1.02–1.34]) and Caucasian (OR [95% CI] = 1.19 [1.00–1.41]), as well as for postmenopausal women (OR = 1.33, 95% CI: 1.02–1.73). In contrast, higher dietary SFA intake was not associated with risk of BC among premenopausal women, in cohort studies or hospital-based studies.A positive association between higher dietary SFA intake and postmenopausal BC risk was observed in case–control but not in cohort studies. More studies are warranted to confirm these findings. 相似文献
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98.
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
99.
Wen Wang Yanmei Liu Chuan Yu Jing Tan Weiyi Xiong Duo Dong 《Expert opinion on drug safety》2020,19(3):339-347
ABSTRACTObjectives: Limited evidence has suggested that cefoperazone-sulbactam causes coagulation disorders and bleeding.Methods: The authors conducted a retrospective study to compare patients receiving cefoperazone-sulbactam versus those treated with cefoperazone-tazobactam or ceftazidime. Propensity-score matching was used to explore whether treatment with cefoperazone-sulbactam increased the risk of prothrombin time (PT) prolongation, coagulation disorders, and bleeding, or decreased platelets (PLT).Results: The cohort included 23,242 patients. Among patients receiving cefoperazone-sulbactam, the risk of PT prolongation, coagulation disorders, decreased PLT, and bleeding was 5.3%, 9.2%, 15.7%, and 4.2%, respectively. Propensity-score matching analyses suggested that cefoperazone-sulbactam increased the risk of PT prolongation (aOR 2.26, 95% CI 1.61–3.18), coagulation disorders (aOR 1.81, 95% CI 1.43–2.30), and decreased PLT (aOR 1.46, 95% CI 1.25–1.72), but not increase bleeding (aOR 1.05, 95% CI 0.79–1.40) compared with ceftazidime. Patients receiving cefoperazone-sulbactam had higher risk of PT prolongation (aOR 1.53, 95% CI 1.11–2.10), coagulation disorders (aOR 1.53, 95% CI 1.21–1.95), but not decreased PLT (aOR 0.93, 95% CI 0.81–1.07) or bleeding (aOR 1.11, 95% CI 0.87–1.42), compared with those receiving cefoperazone-tazobactam.Conclusion: Cefoperazone-sulbactam may be associated with a higher risk of PT prolongation and coagulation disorders compared with cefoperazone-tazobactam and ceftazidime. 相似文献
100.
目的探讨补骨脂素抗增生性瘢痕的作用机制。方法体外培养成纤维细胞,按随机数字表法分为正常组(培养正常成纤维细胞)、瘢痕组(培养增生性瘢痕成纤维细胞)、TGF-β1组(10 ng/ml TGF-β1处理增生性瘢痕成纤维细胞5 min^12 h)、Smurf2 RNA干扰组[Smad泛素化调节因子2(Smad ubiquitin regulatory factor2,Smurf2)siRNA转染增生性瘢痕成纤维细胞72 h]、补骨脂素组(10μmol/L补骨脂素处理增生性瘢痕成纤维细胞继续培养72 h)、补骨脂素+TGF-β1组(增生性瘢痕成纤维细胞加入补骨脂素培养72 h后加入TGF-β1培养6 h)。采用Western blot法检测Smurf2、α-平滑肌肌动蛋白(α-actin SMA,α-SMA)蛋白表达;RT-PCR法检测Ⅰ型胶原蛋白mRNA表达;ELISA法检测TGF-β1蛋白分泌。结果与正常组比较,瘢痕组Smurf2蛋白[(0.83±0.08)比(0.38±0.07)]表达增加(P<0.05);与瘢痕组比较,Smurf2 RNA干扰组TGF-β1[(2.2±0.18)比(4.2±0.47)]表达降低(P<0.05);TGF-β1组Smurf2[(0.71±0.06)比(0.42±0.04)]、α-SMA[(1.42±0.12)比(0.91±0.09)]蛋白表达增加(P<0.05),Ⅰ型胶原蛋白mRNA[(0.72±0.09)比(0.41±0.07)]表达增加(P<0.05);补骨脂素组Smurf2[(0.05±0.01)比(0.42±0.04)]、α-SMA[(0.71±0.07)比(0.91±0.09)]蛋白表达降低(P<0.05),Ⅰ型胶原蛋白mRNA表达[(0.12±0.04)比(0.41±0.07)]降低(P<0.05)。结论补骨脂素可能通过TGF-β1/Smurf2信号通路抑制α-SMA蛋白表达,从而降低Ⅰ型胶原蛋白表达,起到抑制瘢痕形成的作用。 相似文献