• 文献检索
  • 文档翻译
  • 深度研究
  • 学术资讯
  • Suppr Zotero 插件Zotero 插件
  • 邀请有礼
  • 套餐&价格
  • 历史记录
应用&插件
Suppr Zotero 插件Zotero 插件浏览器插件Mac 客户端Windows 客户端微信小程序
定价
高级版会员购买积分包购买API积分包
服务
文献检索文档翻译深度研究API 文档MCP 服务
关于我们
关于 Suppr公司介绍联系我们用户协议隐私条款
关注我们

Suppr 超能文献

核心技术专利:CN118964589B侵权必究
粤ICP备2023148730 号-1Suppr @ 2026

文献检索

告别复杂PubMed语法,用中文像聊天一样搜索,搜遍4000万医学文献。AI智能推荐,让科研检索更轻松。

立即免费搜索

文件翻译

保留排版,准确专业,支持PDF/Word/PPT等文件格式,支持 12+语言互译。

免费翻译文档

深度研究

AI帮你快速写综述,25分钟生成高质量综述,智能提取关键信息,辅助科研写作。

立即免费体验

TREAT决策支持系统在耐药病原体低流行环境中的性能。

Performance of the TREAT decision support system in an environment with a low prevalence of resistant pathogens.

作者信息

Kofoed Kristian, Zalounina Alina, Andersen Ove, Lisby Gorm, Paul Mical, Leibovici Leonard, Andreassen Steen

机构信息

Clinical Research Centre and Department of Infectious Diseases, Copenhagen University Hospital, 2650 Hvidovre, Denmark.

出版信息

J Antimicrob Chemother. 2009 Feb;63(2):400-4. doi: 10.1093/jac/dkn504. Epub 2008 Dec 17.

DOI:10.1093/jac/dkn504
PMID:19091808
Abstract

OBJECTIVES

To evaluate a decision support system (TREAT) for guidance of empirical antimicrobial therapy in an environment with a low prevalence of resistant pathogens.

METHODS

A retrospective trial of TREAT has been performed at Copenhagen University, Hvidovre Hospital. The cohort of patients included adults with systemic inflammation and suspicion of community-acquired bacterial infection. The empirical antimicrobial treatment recommended by TREAT was compared with the empirical antimicrobial treatment prescribed by the first attending clinical physician.

RESULTS

Out of 171 patients recruited, 161 (65 with microbiologically documented infections) fulfilled the inclusion criteria of TREAT. Coverage achieved by TREAT was significantly higher than that by clinical practice (86% versus 66%, P = 0.007). There was no significant difference in the cost of future resistance between treatments chosen by TREAT and those by physicians. The direct expenses for antimicrobials were higher in TREAT when including patients without antimicrobial treatment, while there was no significant difference otherwise. The cost of side effects was significantly lower using TREAT.

CONCLUSIONS

The results of the study suggest that TREAT can improve the appropriateness of antimicrobial therapy and reduce the cost of side effects in regions with a low prevalence of resistant pathogens, however, at the expense of increased use of antibiotics.

摘要

目的

在耐药病原体低流行率的环境中,评估一种用于指导经验性抗菌治疗的决策支持系统(TREAT)。

方法

在哥本哈根大学赫勒乌医院进行了一项关于TREAT的回顾性试验。患者队列包括患有全身炎症且怀疑社区获得性细菌感染的成年人。将TREAT推荐的经验性抗菌治疗与首位主治临床医生开具的经验性抗菌治疗进行比较。

结果

在招募的171名患者中,161名(65名有微生物学记录的感染患者)符合TREAT的纳入标准。TREAT实现的覆盖范围显著高于临床实践(86%对66%,P = 0.007)。TREAT选择的治疗与医生选择的治疗在未来耐药成本方面无显著差异。当纳入未接受抗菌治疗的患者时,TREAT中抗菌药物的直接费用更高,否则无显著差异。使用TREAT时副作用成本显著更低。

结论

研究结果表明,在耐药病原体低流行率的地区,TREAT可提高抗菌治疗的合理性并降低副作用成本,然而,代价是抗生素使用增加。

相似文献

1
Performance of the TREAT decision support system in an environment with a low prevalence of resistant pathogens.TREAT决策支持系统在耐药病原体低流行环境中的性能。
J Antimicrob Chemother. 2009 Feb;63(2):400-4. doi: 10.1093/jac/dkn504. Epub 2008 Dec 17.
2
Bacteremia in previously hospitalized patients: prolonged effect from previous hospitalization and risk factors for antimicrobial-resistant bacterial infections.既往住院患者的菌血症:既往住院的长期影响及耐抗菌药物细菌感染的危险因素。
Ann Emerg Med. 2008 May;51(5):639-46. doi: 10.1016/j.annemergmed.2007.12.022. Epub 2008 Mar 19.
3
Computerized antimicrobial decision support: an offline evaluation of a database-driven empiric antimicrobial guidance program in hospitalized patients with a bloodstream infection.计算机化抗菌决策支持:对住院血流感染患者数据库驱动的经验性抗菌指导方案的离线评估。
Int J Med Inform. 2004 Jun 15;73(5):455-60. doi: 10.1016/j.ijmedinf.2004.04.002.
4
Empirical treatment of bacteraemic urinary tract infection. Evaluation of a decision support system.菌血症性尿路感染的经验性治疗。一个决策支持系统的评估。
Dan Med Bull. 1999 Sep;46(4):349-53.
5
Evaluation of the decision support system for antimicrobial treatment, TREAT, in an acute medical ward of a university hospital.评价抗菌治疗决策支持系统 TREAT 在一家大学附属医院急性内科病房的应用。
Int J Infect Dis. 2014 Dec;29:156-61. doi: 10.1016/j.ijid.2014.08.019. Epub 2014 Oct 23.
6
Cost-effectiveness of empirical prescribing of antimicrobials in community-acquired pneumonia in three countries in the presence of resistance.在存在耐药性的情况下,三个国家社区获得性肺炎经验性使用抗菌药物的成本效益
J Antimicrob Chemother. 2007 May;59(5):977-89. doi: 10.1093/jac/dkm033. Epub 2007 Mar 29.
7
The TREAT project: decision support and prediction using causal probabilistic networks.TREAT项目:使用因果概率网络的决策支持与预测
Int J Antimicrob Agents. 2007 Nov;30 Suppl 1:S93-102. doi: 10.1016/j.ijantimicag.2007.06.035. Epub 2007 Sep 24.
8
Importance of appropriateness of empiric antibiotic therapy on clinical outcomes in intra-abdominal infections.
Int J Technol Assess Health Care. 2006 Spring;22(2):242-8. doi: 10.1017/S0266462306051063.
9
Bacterial incidence and antibiotic sensitivity pattern in moderate and severe infections in hospitalised patients.住院患者中、重度感染的细菌发生率及抗生素敏感性模式
J Indian Med Assoc. 2009 Jan;107(1):21-2, 24-5.
10
Selection of antibiotic-resistant pathogens in the community.社区中抗生素耐药病原体的选择。
Pediatr Infect Dis J. 2006 Oct;25(10):974-6. doi: 10.1097/01.inf.0000239270.33190.71.

引用本文的文献

1
Implemented machine learning tools to inform decision-making for patient care in hospital settings: a scoping review.实施机器学习工具以在医院环境中为患者护理决策提供信息:范围综述。
BMJ Open. 2023 Feb 7;13(2):e065845. doi: 10.1136/bmjopen-2022-065845.
2
Economic evaluations of big data analytics for clinical decision-making: a scoping review.大数据分析在临床决策中的经济评价:范围综述。
J Am Med Inform Assoc. 2020 Jul 1;27(9):1466-1475. doi: 10.1093/jamia/ocaa102.
3
The effectiveness of computerised decision support on antibiotic use in hospitals: A systematic review.
计算机化决策支持对医院抗生素使用的有效性:一项系统评价。
PLoS One. 2017 Aug 24;12(8):e0183062. doi: 10.1371/journal.pone.0183062. eCollection 2017.
4
Interventions to improve antibiotic prescribing practices for hospital inpatients.改善医院住院患者抗生素处方行为的干预措施。
Cochrane Database Syst Rev. 2017 Feb 9;2(2):CD003543. doi: 10.1002/14651858.CD003543.pub4.