WeChat Mini Program
Old Version Features

老年大肠埃希菌血流感染的临床特征及耐药特点(附94例分析)

Shandong Medical Journal(2022)

Cited 0|Views28
Abstract
目的 总结老年大肠埃希菌血流感染的临床特征及耐药特点.方法 回顾性分析94例老年大肠埃希菌血流感染患者的临床资料.结果 94例老年大肠埃希菌血流感染患者中,女性占59例(62.8%),患者来源前三的科室分别是感染性疾病科(46例,48.9%)、急诊内科(10例,10.6%)、血液内科(7例,7.4%),主要基础性疾病为高血压(30例,31.9%)、糖尿病(26例,27.7%)、心脏病(25例,26.6%)、脑血管疾病(20例,21.3%)、肿瘤疾病(10例,10.6%),感染途径前三位的分别是泌尿道感染(30.9%)、呼吸道感染(28.7%)、消化道感染(18.1%),大多患者表现为发热或非特异症状,白细胞、C反应蛋白(CRP)、降钙素原(PCT)明显增高.检出产超广谱β-内酰胺酶(ESBLs)大肠埃希菌35株(37.2%),同时检出1例多重耐药(MDR)大肠埃希菌菌株;大肠埃希菌对亚胺培南、厄他培南、头孢替坦、妥布霉素、呋喃妥因、阿米卡星的耐药率均<5%,其中产ESBLs大肠埃希菌对头孢唑林、氨苄西林完全耐药,而非产ESBLs大肠埃希菌对大多数药物敏感率较高.结论 老年大肠埃希菌血流感染患者以女性为主,主要分布在感染性疾病科,均合并基础病,主要感染途径为泌尿道,临床症状非特异性,白细胞、CRP、PCT是良好的辅助诊断指标.产ESBLs大肠埃希菌对多种抗菌药物耐药,其耐药率普遍高于非产ESBLs大肠埃希菌,临床上需监测其耐药性,加强抗生素的合理使用.
More
求助PDF
上传PDF
Bibtex
AI Read Science
AI Summary
AI Summary is the key point extracted automatically understanding the full text of the paper, including the background, methods, results, conclusions, icons and other key content, so that you can get the outline of the paper at a glance.
Example
Background
Key content
Introduction
Methods
Results
Related work
Fund
Key content
  • Pretraining has recently greatly promoted the development of natural language processing (NLP)
  • We show that M6 outperforms the baselines in multimodal downstream tasks, and the large M6 with 10 parameters can reach a better performance
  • We propose a method called M6 that is able to process information of multiple modalities and perform both single-modal and cross-modal understanding and generation
  • The model is scaled to large model with 10 billion parameters with sophisticated deployment, and the 10 -parameter M6-large is the largest pretrained model in Chinese
  • Experimental results show that our proposed M6 outperforms the baseline in a number of downstream tasks concerning both single modality and multiple modalities We will continue the pretraining of extremely large models by increasing data to explore the limit of its performance
Upload PDF to Generate Summary
Must-Reading Tree
Example
Generate MRT to find the research sequence of this paper
Data Disclaimer
The page data are from open Internet sources, cooperative publishers and automatic analysis results through AI technology. We do not make any commitments and guarantees for the validity, accuracy, correctness, reliability, completeness and timeliness of the page data. If you have any questions, please contact us by email: report@aminer.cn
Chat Paper
Summary is being generated by the instructions you defined