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| 1 | Solar energy assessment using remote sensing technologies显示文摘 | Annette Hammer Detlev Heinemann Carsten Hoyer Rolf Kuhlemann Elke Lorenz Richard Müller Hans Georg Beyer | 2003 | Remote Sensing of Environment2003，，3： | 1 |
| 2 | Synthesis of fused-ring cyclobutenones via a tandem cyeloaddition-beta-elimination sequence显示文摘 | George B Trimitsis A Tuncay R D Beyer | 1978 | J Org Chem1978，58，： | 1 |
| 3 | Animal models of systemic sclerosis : Prospects and limitations 显示文摘 | Christian Beyer Georg Schett Oliver Distler | 2010 | Arthritis Rheu- matology2010，62，10： | 1 |
| 4 | Wake effects in liner wind farm显示文摘 | HANS GEORG BEYER THOMAS PAHLKE WOLF- GANG SCHMIDT | 1994 | Journal of Wind Engineering and Industrial Aero- dynamics1994，51，3： | 1 |
| 5 | 静脉注射甲氧基聚乙二醇促红细胞生成素-β对慢性肾病透析患者血红蛋白浓度的稳定作用:一项随机非劣效性试验(MAXIMA)显示文摘背景使用依泊汀类(epoetin促红细胞生成素)药物治疗慢性肾病所致贫血的传统疗法需要频繁注射、调整剂量并密切监测血红蛋白浓度:本研究旨在比较每2周或4周静脉注射1次甲氧基聚乙二醇促红细胞生成素-β与每周注射1~3次依泊汀对血液透析患者血红蛋白浓度的稳定作用。
方法从96个中心筛选出1115例具有稳定的慢性肾性贫血且正在行透析治疗和静脉注射依泊汀的患者,进行了开放标记、平行组、非劣效性试验,以比较两种给药间隔的甲氧基聚乙二醇促红细胞生成素-β治疗与标准依泊汀治疗的疗效。在4周的导入期内,确定了基线血红蛋白浓度以及患者是否合格。随机分配方案如下:223例患者每2周注射1次甲氧基聚乙二醇促红细胞生成素-β,224例患者每4周注射1次甲氧基聚乙二醇促红细胞生成素-β,226例患者接受标准依泊汀治疗。初始剂量根据转换用药方案前1周所给予的依泊汀平均剂量确定。主要终点为评价期相对于基线水平的血红蛋白浓度改变。采用意向性治疗分析和符合方案分析方法。本研究在ClinicalTrials.gov注册,注册号NCT00077610。
结果在673例随机分组的患者中,133例从符合方案分析中被剔除,剔除原因包括缺铁、评估期血红蛋白浓度测定次数少于5次、需要输血:就治疗后患者的血红蛋白浓度相对于基线水平的平均变化而言,每2周(-0.71g/L.95%CI-2.20~0.77)和每4周(-0.25g/L,95%CI-1.79~1.29)静脉注射1次甲氧基聚乙二醇促红细胞生成素-β不劣于标准依泊汀治疗(-0.75g/L.95%CI-2.26~0.75;所有比较P〈0.0001)。在至少注射了1次研究药物的666例患者中,不良事件或严重不良事件的发生率在各治疗组间没有差异(P值分别为0.30和0.40).
结论这种长效促红细胞生成类药品的安全性与传统依泊汀治疗相同,每4周静脉注射1次能够治疗血液透析患者的贫血。 | Nathan W Levin Steven Fishbane Francisco Valdes Canedo Steven Zeig George M Nassar John E Moran Giuseppe Villa Ulrich Beyer Delphine Oguey 赵乐(译) | 2008 | 世界临床医学2008，2，3： | 0 |
| 6 | Machine learning-based decision tool for selecting patients with idiopathic acute pancreatitis for endosonography to exclude a biliary aetiology显示文摘BACKGROUND Biliary microlithiasis/sludge is detected in approximately 30%of patients with idiopathic acute pancreatitis(IAP).As recurrent biliary pancreatitis can be prevented,the underlying aetiology of IAP should be established.AIM To develop a machine learning(ML)based decision tool for the use of endosonography(EUS)in pancreatitis patients to detect sludge and microlithiasis.METHODS We retrospectively used routinely recorded clinical and laboratory parameters of 218 consecutive patients with confirmed AP admitted to our tertiary care hospital between 2015 and 2020.Patients who did not receive EUS as part of the diagnostic work-up and whose pancreatitis episode could be adequately explained by other causes than biliary sludge and microlithiasis were excluded.We trained supervised ML classifiers using H_(2)O.ai automatically selecting the best suitable predictor model to predict microlithiasis/sludge.The predictor model was further validated in two independent retrospective cohorts from two tertiary care centers(117 patients).RESULTS Twenty-eight categorized patients’variables recorded at admission were identified to compute the predictor model with an accuracy of 0.84[95%confidence interval(CI):0.791-0.9185],positive predictive value of 0.84,and negative predictive value of 0.80 in the identification cohort(218 patients).In the validation cohort,the robustness of the prediction model was confirmed with an accuracy of 0.76(95%CI:0.673-0.8347),positive predictive value of 0.76,and negative predictive value of 0.78(117 patients).CONCLUSION We present a robust and validated ML-based predictor model consisting of routinely recorded parameters at admission that can predict biliary sludge and microlithiasis as the cause of AP. | Simon Sirtl Michal Żorniak Eric Hohmann Georg Beyer Miriam Dibos Annika Wandel Veit Phillip Christoph Ammer-Herrmenau Albrecht Neesse Christian Schulz Jörg Schirra Julia Mayerle Ujjwal Mukund Mahajan | 2023 | World Journal of Gastroenterology2023，29，35： | 0 |
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