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分析 MIMIC-III 中的成人疾病特征和死亡率。

Analysis of adult disease characteristics and mortality on MIMIC-III.

机构信息

School of Life Science & Technology, University of Electronic Science & Technology of China, Chengdu, China.

Department of Biomedical Informatics, University of Utah, Salt Lake City, Utah, United States of America.

出版信息

PLoS One. 2020 Apr 30;15(4):e0232176. doi: 10.1371/journal.pone.0232176. eCollection 2020.

Abstract

PURPOSE

To deeply analyze the basic information and disease information of adult patients in the MIMIC-III (Medical Information Mart for Intensive Care III) database, and provide data reference for clinicians and researchers.

MATERIALS AND METHODS

Tableau2019.1.0 and Navicat12.0.29 were used for data analysis and extraction of disease distribution of adult patients in the MIMIC-III database.

RESULT

A total of 38,163 adult patients were included in the MIMIC-III database. Only 38,156 patients with the first diagnosis were selected. Among them, 21,598 were males accounting for 56.6% the median age was 66 years (Q1-Q3: 53-78), the median length of a hospital stay was 7 days (Q1-Q3: 4-12), and the median length of an ICU stay was 2.1 days (Q1-Q3: 1.2-4.1). Septicemia was the disease with the highest mortality rate among patients and the total mortality rate was 48.9%. The disease with the largest number of patients at the last time was other forms of chronic ischemic heart disease.

CONCLUSION

By analyzing the patients' basic information, the admission spectrum and the disease morbidity and mortality can help more researchers understand the MIMIC-III database and facilitate further research.

摘要

目的

深入分析 MIMIC-III(重症监护医疗信息集市 III)数据库中成年患者的基本信息和疾病信息,为临床医生和研究人员提供数据参考。

材料和方法

使用 Tableau2019.1.0 和 Navicat12.0.29 对 MIMIC-III 数据库中成年患者的疾病分布进行数据分析和提取。

结果

MIMIC-III 数据库共纳入 38163 例成年患者,仅选择了 38156 例具有首诊的患者。其中男性 21598 例,占 56.6%,中位年龄为 66 岁(Q1-Q3:53-78),中位住院时间为 7 天(Q1-Q3:4-12),中位 ICU 住院时间为 2.1 天(Q1-Q3:1.2-4.1)。败血症是患者死亡率最高的疾病,总死亡率为 48.9%。最后一次就诊患者人数最多的疾病是其他形式的慢性缺血性心脏病。

结论

通过分析患者的基本信息、入院谱以及疾病发病率和死亡率,有助于更多的研究人员了解 MIMIC-III 数据库,并促进进一步的研究。

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