Metabolomics Dynamics Study for Severe Patient
Modeling Metabolomic Dynamics Based on Nuclear Magnetic Resonance and High Performance Liquid Chromatography for Severe Patient: a Cohort Study
Acute severe disease is a major public health challenge that often affects young adults.In past decade, there are lot of new techniques have been developed that aim to improve the outcome of acute severe disease, But few of these works success. According to recently studies, the mortality of the multiple organ dysfunction syndrome(MODS) that is the major cause of death in patients who suffering from acute severe disease, is not improved. On the contrary, if MODS be predicted in early stage of acute severe disease, the death can be prevented. Because acute severe disease poses complex injury that involves multiple pathological processes, understanding the cellular and metabolic network malfunction during acute severe disease is crucial for clinical monitoring and intervention.
Human metabolism is a complex network with hundreds of cross-linked paths. During critical illness, the metabolic network is dynamically disturbed at multiple points. Classical research typically isolates a small part of this network to investigate the impact of pathological physiology molecular mechanisms on clinical outcome. In particular, researchers have examined metabolic disturbances such as cytokine network dysfunction, skeletal muscle breakdown, insulin resistance, dyslipidemia, testosterone and growth hormone/Insulin like growth factor (IGF)dysfunctions, low thyroxine syndrome, and deficiency of vitamin D and calcium with secondary hyperparathyroidism. These complex metabolic disturbances appear and interact at different stages during the pathological process after acute severe illness. Therefore, an integrated approach that combines the biochemical/molecular changes with network disturbances is the key to understanding acute severe illness at the systems biology level and establishing an accurate quantitative model for clinical monitoring.
An interdisciplinary method that includes high-throughput quantitative techniques and effective mathematical and visualization tools is necessary. Furthermore, interdisciplinary methods present the opportunity to develop innovative clinical diagnosis and monitoring methods for severe injuries. The aim of this study is to provide a novel high-throughput method that integrated proton-nuclear magnetic resonance (NMR) metabolomic fingerprinting and High Performance Liquid Chromatography with advance mathematics tools to modeling metabolic dynamics after acute severe disease.
研究概览
地位
研究类型
注册 (预期的)
联系人和位置
学习地点
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Sichuan
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Chengdu、Sichuan、中国、610072
- 招聘中
- Sichuan Academy of Medical Sciences
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接触:
- Hua Jiang, MBBS,PhD
- 电话号码:8613980001701
- 邮箱:cdjianghua@gmail.com
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接触:
- Bin Cai, MBBS
- 电话号码:86-18981838125
- 邮箱:bin.cai@traumabank.org
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参与标准
资格标准
适合学习的年龄
接受健康志愿者
有资格学习的性别
取样方法
研究人群
描述
Inclusion Criteria:
- Age:18-70 years
- Acute Physiology And Chronic Health Evaluation(APACHE)II>10
Exclusion Criteria:
- With comorbidity (Diabetes,Hyperthyroidism or primary organ dysfunction )
- Pregnancy
学习计划
研究是如何设计的?
设计细节
队列和干预
团体/队列 |
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Acute severe disease
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研究衡量的是什么?
主要结果指标
结果测量 |
大体时间 |
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住院死亡率
大体时间:从入院到出院的死亡事件(最长 10 周)
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从入院到出院的死亡事件(最长 10 周)
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次要结果测量
结果测量 |
大体时间 |
|---|---|
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Multi Organ Dysfunction Syndrome(MODS)
大体时间:MODS events occurence from admission to discharge(up to 10 weeks)
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MODS events occurence from admission to discharge(up to 10 weeks)
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合作者和调查者
调查人员
- 学习椅:Hua Jiang, PhD, MBBS、Sichuan Academy of Medical Sciences
研究记录日期
研究主要日期
学习开始
初级完成 (预期的)
研究完成 (预期的)
研究注册日期
首次提交
首先提交符合 QC 标准的
首次发布 (估计)
研究记录更新
最后更新发布 (实际的)
上次提交的符合 QC 标准的更新
最后验证
更多信息
与本研究相关的术语
其他研究编号
- MetaLab_2014_001
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