Metabolomics Dynamics Study for Severe Patient

Sponsor
Sichuan Academy of Medical Sciences (Other)
Overall Status
Unknown status
CT.gov ID
NCT02164786
Collaborator
(none)
600
1
54
11.1

Study Details

Study Description

Brief Summary

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.

Study Design

Study Type:
Observational
Anticipated Enrollment :
600 participants
Observational Model:
Cohort
Time Perspective:
Prospective
Official Title:
Modeling Metabolomic Dynamics Based on Nuclear Magnetic Resonance and High Performance Liquid Chromatography for Severe Patient: a Cohort Study
Study Start Date :
Jun 1, 2014
Anticipated Primary Completion Date :
May 1, 2018
Anticipated Study Completion Date :
Dec 1, 2018

Arms and Interventions

Arm Intervention/Treatment
Acute severe disease

Outcome Measures

Primary Outcome Measures

  1. Mortality at hospitalization [Death events from admission to discharge(up to 10 weeks)]

Secondary Outcome Measures

  1. Multi Organ Dysfunction Syndrome(MODS) [MODS events occurence from admission to discharge(up to 10 weeks)]

Eligibility Criteria

Criteria

Ages Eligible for Study:
18 Years to 70 Years
Sexes Eligible for Study:
All
Accepts Healthy Volunteers:
Yes
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

Contacts and Locations

Locations

Site City State Country Postal Code
1 Sichuan Academy of Medical Sciences Chengdu Sichuan China 610072

Sponsors and Collaborators

  • Sichuan Academy of Medical Sciences

Investigators

  • Study Chair: Hua Jiang, PhD, MBBS, Sichuan Academy of Medical Sciences

Study Documents (Full-Text)

None provided.

More Information

Publications

None provided.
Responsible Party:
Sichuan Academy of Medical Sciences
ClinicalTrials.gov Identifier:
NCT02164786
Other Study ID Numbers:
  • MetaLab_2014_001
First Posted:
Jun 17, 2014
Last Update Posted:
Apr 28, 2017
Last Verified:
Apr 1, 2016

Study Results

No Results Posted as of Apr 28, 2017