Suppr超能文献

多参数智能监护在重症监护中的应用 II:一个公共接入重症监护病房数据库。

Multiparameter Intelligent Monitoring in Intensive Care II: a public-access intensive care unit database.

机构信息

Massachusetts Institute of Technology, Cambridge, MA, USA.

出版信息

Crit Care Med. 2011 May;39(5):952-60. doi: 10.1097/CCM.0b013e31820a92c6.

Abstract

OBJECTIVE

We sought to develop an intensive care unit research database applying automated techniques to aggregate high-resolution diagnostic and therapeutic data from a large, diverse population of adult intensive care unit patients. This freely available database is intended to support epidemiologic research in critical care medicine and serve as a resource to evaluate new clinical decision support and monitoring algorithms.

DESIGN

Data collection and retrospective analysis.

SETTING

All adult intensive care units (medical intensive care unit, surgical intensive care unit, cardiac care unit, cardiac surgery recovery unit) at a tertiary care hospital.

PATIENTS

Adult patients admitted to intensive care units between 2001 and 2007.

INTERVENTIONS

None.

MEASUREMENTS AND MAIN RESULTS

The Multiparameter Intelligent Monitoring in Intensive Care II (MIMIC-II) database consists of 25,328 intensive care unit stays. The investigators collected detailed information about intensive care unit patient stays, including laboratory data, therapeutic intervention profiles such as vasoactive medication drip rates and ventilator settings, nursing progress notes, discharge summaries, radiology reports, provider order entry data, International Classification of Diseases, 9th Revision codes, and, for a subset of patients, high-resolution vital sign trends and waveforms. Data were automatically deidentified to comply with Health Insurance Portability and Accountability Act standards and integrated with relational database software to create electronic intensive care unit records for each patient stay. The data were made freely available in February 2010 through the Internet along with a detailed user's guide and an assortment of data processing tools. The overall hospital mortality rate was 11.7%, which varied by critical care unit. The median intensive care unit length of stay was 2.2 days (interquartile range, 1.1-4.4 days). According to the primary International Classification of Diseases, 9th Revision codes, the following disease categories each comprised at least 5% of the case records: diseases of the circulatory system (39.1%); trauma (10.2%); diseases of the digestive system (9.7%); pulmonary diseases (9.0%); infectious diseases (7.0%); and neoplasms (6.8%).

CONCLUSIONS

MIMIC-II documents a diverse and very large population of intensive care unit patient stays and contains comprehensive and detailed clinical data, including physiological waveforms and minute-by-minute trends for a subset of records. It establishes a new public-access resource for critical care research, supporting a diverse range of analytic studies spanning epidemiology, clinical decision-rule development, and electronic tool development.

摘要

目的

我们旨在开发一个重症监护病房(ICU)研究数据库,应用自动化技术从大量不同的成年 ICU 患者中聚合高分辨率的诊断和治疗数据。这个免费提供的数据库旨在支持重症医学的流行病学研究,并作为评估新的临床决策支持和监测算法的资源。

设计

数据收集和回顾性分析。

地点

一家三级医院的所有成人 ICU(内科 ICU、外科 ICU、心脏监护病房、心脏外科恢复病房)。

患者

2001 年至 2007 年期间入住 ICU 的成年患者。

干预措施

无。

测量和主要结果

多参数智能监护在重症监护 II(MIMIC-II)数据库包含 25328 例 ICU 入住。研究人员收集了关于 ICU 患者入住的详细信息,包括实验室数据、治疗干预情况,如血管活性药物滴注率和呼吸机设置、护理进展记录、出院小结、放射学报告、医嘱输入数据、国际疾病分类,第 9 版代码,以及对于一部分患者,高分辨率生命体征趋势和波形。数据被自动去识别以符合健康保险流通与责任法案标准,并与关系数据库软件集成,为每位患者的入住创建电子 ICU 记录。这些数据于 2010 年 2 月通过互联网免费提供,同时提供了详细的用户指南和一系列数据处理工具。整个医院的死亡率为 11.7%,按重症监护病房划分有所不同。ICU 入住的中位数为 2.2 天(四分位间距,1.1-4.4 天)。根据主要的国际疾病分类,第 9 版代码,以下疾病类别各占病例记录的至少 5%:循环系统疾病(39.1%);创伤(10.2%);消化系统疾病(9.7%);肺部疾病(9.0%);传染病(7.0%);和肿瘤(6.8%)。

结论

MIMIC-II 记录了多样化和非常大的 ICU 患者入住人群,并包含了全面和详细的临床数据,包括一部分记录的生理波形和每分钟趋势。它为重症监护研究建立了一个新的公共访问资源,支持从流行病学、临床决策规则开发到电子工具开发的各种分析研究。

相似文献

3
Open-access MIMIC-II database for intensive care research.用于重症监护研究的开放获取MIMIC-II数据库。
Annu Int Conf IEEE Eng Med Biol Soc. 2011;2011:8315-8. doi: 10.1109/IEMBS.2011.6092050.
4
Artificial intelligence applications in the intensive care unit.人工智能在重症监护病房的应用。
Crit Care Med. 2001 Feb;29(2):427-35. doi: 10.1097/00003246-200102000-00038.
7
Applying machine learning to continuously monitored physiological data.将机器学习应用于连续监测的生理数据。
J Clin Monit Comput. 2019 Oct;33(5):887-893. doi: 10.1007/s10877-018-0219-z. Epub 2018 Nov 11.

引用本文的文献

本文引用的文献

3
Use of electronic health records in U.S. hospitals.美国医院中电子健康记录的使用情况。
N Engl J Med. 2009 Apr 16;360(16):1628-38. doi: 10.1056/NEJMsa0900592. Epub 2009 Mar 25.
4
The cardiac output from blood pressure algorithms trial.基于血压算法的心输出量试验。
Crit Care Med. 2009 Jan;37(1):72-80. doi: 10.1097/CCM.0b013e3181930174.
7
Automated de-identification of free-text medical records.自由文本医疗记录的自动去识别化
BMC Med Inform Decis Mak. 2008 Jul 24;8:32. doi: 10.1186/1472-6947-8-32.

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验