目的分析近7年大肠埃希菌及肺炎克雷伯菌耐药率与抗菌药物使用强度(antibiotics use density,AUD)的相关性,为临床合理使用抗菌药物提供参考。方法回顾性分析该院2016—2022年大肠埃希菌及肺炎克雷伯菌的耐药率与同期主要抗菌药物的AUD...目的分析近7年大肠埃希菌及肺炎克雷伯菌耐药率与抗菌药物使用强度(antibiotics use density,AUD)的相关性,为临床合理使用抗菌药物提供参考。方法回顾性分析该院2016—2022年大肠埃希菌及肺炎克雷伯菌的耐药率与同期主要抗菌药物的AUD,采用Pearson相关性分析法分析两者的相关性。结果大肠埃希菌对对哌拉西林/他唑巴坦的耐药率与头孢呋辛的AUD呈正相关(P<0.05);对头孢吡肟的耐药率与头孢西丁、氨曲南的AUD呈正相关(P<0.01、P<0.05);对头孢西丁的耐药率与头孢西丁的AUD呈正相关(P<0.05);对亚胺培南的耐药率与头孢哌酮/舒巴坦、阿米卡星的AUD呈正相关(P<0.01)。肺炎克雷伯菌对阿莫西林/克拉维酸的耐药率与头孢西丁、氨曲南的AUD呈正相关(P<0.01);对哌拉西林/他唑巴坦的耐药率与头孢西丁的AUD呈正相关(P<0.05),对头孢噻肟的耐药率与阿莫西林/克拉维酸的AUD呈正相关(P<0.01);对头孢吡肟的耐药率与头孢西丁、左氧氟沙星的AUD呈正相关(P<0.05);对阿米卡星的耐药率与头孢他啶、头孢噻肟、亚胺培南的AUD呈正相关(P<0.01、P<0.05)。大肠埃希菌对哌拉西林/他唑巴坦的耐药率与头孢唑啉的AUD呈负相关(P<0.05);对头孢唑啉的耐药率与头孢他啶、头孢噻肟的AUD呈负相关(P<0.05);对头孢吡肟的耐药率与哌拉西林/他唑巴坦、头孢噻肟的AUD呈负相关(P<0.05);对头孢西丁的耐药率与头孢噻肟的AUD呈负相关(P<0.05);对亚胺培南的耐药率与阿莫西林/克拉维酸的AUD呈负相关(P<0.05)。肺炎克雷伯菌对阿莫西林/克拉维酸的耐药率与哌拉西林/他唑巴坦的AUD呈负相关(P<0.05);对头孢西丁的耐药率与哌拉西林/他唑巴坦的AUD呈负相关(P<0.05)。结论大肠埃希菌及肺炎克雷伯菌的耐药率与多种抗菌药物的AUD相关,应加强抗菌药物的合理管控,延缓细菌耐药的发生。展开更多
The rotary motion deblurring is an inevitable procedure when the imaging seeker is mounted in the rotating missiles.Traditional rotary motion deblurring methods suffer from ringing artifacts and noise,especially for l...The rotary motion deblurring is an inevitable procedure when the imaging seeker is mounted in the rotating missiles.Traditional rotary motion deblurring methods suffer from ringing artifacts and noise,especially for large blur extents.To solve the above problems,we propose a progressive rotary motion deblurring framework consisting of a coarse deblurring stage and a refinement stage.In the first stage,we design an adaptive blur extents factor(BE factor)to balance noise suppression and details reconstruction.And a novel deconvolution model is proposed based on BE factor.In the second stage,a triplescale deformable module CNN(TDM-CNN)is designed to reduce the ringing artifacts,which can exploit the 2D information of an image and adaptively adjust spatial sampling locations.To establish a standard evaluation benchmark,a real-world rotary motion blur dataset is proposed and released,which includes rotary blurred images and corresponding ground truth images with different blur angles.Experimental results demonstrate that the proposed method outperforms the state-of-the-art models on synthetic and real-world rotary motion blur datasets.The code and dataset are available at https://github.com/JinhuiQin/RotaryDeblurring.展开更多
文摘目的分析近7年大肠埃希菌及肺炎克雷伯菌耐药率与抗菌药物使用强度(antibiotics use density,AUD)的相关性,为临床合理使用抗菌药物提供参考。方法回顾性分析该院2016—2022年大肠埃希菌及肺炎克雷伯菌的耐药率与同期主要抗菌药物的AUD,采用Pearson相关性分析法分析两者的相关性。结果大肠埃希菌对对哌拉西林/他唑巴坦的耐药率与头孢呋辛的AUD呈正相关(P<0.05);对头孢吡肟的耐药率与头孢西丁、氨曲南的AUD呈正相关(P<0.01、P<0.05);对头孢西丁的耐药率与头孢西丁的AUD呈正相关(P<0.05);对亚胺培南的耐药率与头孢哌酮/舒巴坦、阿米卡星的AUD呈正相关(P<0.01)。肺炎克雷伯菌对阿莫西林/克拉维酸的耐药率与头孢西丁、氨曲南的AUD呈正相关(P<0.01);对哌拉西林/他唑巴坦的耐药率与头孢西丁的AUD呈正相关(P<0.05),对头孢噻肟的耐药率与阿莫西林/克拉维酸的AUD呈正相关(P<0.01);对头孢吡肟的耐药率与头孢西丁、左氧氟沙星的AUD呈正相关(P<0.05);对阿米卡星的耐药率与头孢他啶、头孢噻肟、亚胺培南的AUD呈正相关(P<0.01、P<0.05)。大肠埃希菌对哌拉西林/他唑巴坦的耐药率与头孢唑啉的AUD呈负相关(P<0.05);对头孢唑啉的耐药率与头孢他啶、头孢噻肟的AUD呈负相关(P<0.05);对头孢吡肟的耐药率与哌拉西林/他唑巴坦、头孢噻肟的AUD呈负相关(P<0.05);对头孢西丁的耐药率与头孢噻肟的AUD呈负相关(P<0.05);对亚胺培南的耐药率与阿莫西林/克拉维酸的AUD呈负相关(P<0.05)。肺炎克雷伯菌对阿莫西林/克拉维酸的耐药率与哌拉西林/他唑巴坦的AUD呈负相关(P<0.05);对头孢西丁的耐药率与哌拉西林/他唑巴坦的AUD呈负相关(P<0.05)。结论大肠埃希菌及肺炎克雷伯菌的耐药率与多种抗菌药物的AUD相关,应加强抗菌药物的合理管控,延缓细菌耐药的发生。
基金the National Natural Science Foundation of China under Grant 62075169,Grant 62003247,and Grant 62061160370the Hubei Province Key Research and Development Program under Grant 2021BBA235the Zhuhai Basic and Applied Basic Research Foundation under Grant ZH22017003200010PWC.
文摘The rotary motion deblurring is an inevitable procedure when the imaging seeker is mounted in the rotating missiles.Traditional rotary motion deblurring methods suffer from ringing artifacts and noise,especially for large blur extents.To solve the above problems,we propose a progressive rotary motion deblurring framework consisting of a coarse deblurring stage and a refinement stage.In the first stage,we design an adaptive blur extents factor(BE factor)to balance noise suppression and details reconstruction.And a novel deconvolution model is proposed based on BE factor.In the second stage,a triplescale deformable module CNN(TDM-CNN)is designed to reduce the ringing artifacts,which can exploit the 2D information of an image and adaptively adjust spatial sampling locations.To establish a standard evaluation benchmark,a real-world rotary motion blur dataset is proposed and released,which includes rotary blurred images and corresponding ground truth images with different blur angles.Experimental results demonstrate that the proposed method outperforms the state-of-the-art models on synthetic and real-world rotary motion blur datasets.The code and dataset are available at https://github.com/JinhuiQin/RotaryDeblurring.
