- ICH GCP
- Registre américain des essais cliniques
- Essai clinique NCT02164786
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.
Aperçu de l'étude
Statut
Type d'étude
Inscription (Anticipé)
Contacts et emplacements
Lieux d'étude
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Sichuan
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Chengdu, Sichuan, Chine, 610072
- Recrutement
- Sichuan Academy of Medical Sciences
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Contact:
- Hua Jiang, MBBS,PhD
- Numéro de téléphone: 8613980001701
- E-mail: cdjianghua@gmail.com
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Contact:
- Bin Cai, MBBS
- Numéro de téléphone: 86-18981838125
- E-mail: bin.cai@traumabank.org
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Critères de participation
Critère d'éligibilité
Âges éligibles pour étudier
Accepte les volontaires sains
Sexes éligibles pour l'étude
Méthode d'échantillonnage
Population étudiée
La description
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
Plan d'étude
Comment l'étude est-elle conçue ?
Détails de conception
Cohortes et interventions
Groupe / Cohorte |
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Acute severe disease
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Que mesure l'étude ?
Principaux critères de jugement
Mesure des résultats |
Délai |
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Mortalité à l'hospitalisation
Délai: Décès de l'admission à la sortie (jusqu'à 10 semaines)
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Décès de l'admission à la sortie (jusqu'à 10 semaines)
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Mesures de résultats secondaires
Mesure des résultats |
Délai |
|---|---|
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Multi Organ Dysfunction Syndrome(MODS)
Délai: 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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Collaborateurs et enquêteurs
Parrainer
Les enquêteurs
- Chaise d'étude: Hua Jiang, PhD, MBBS, Sichuan Academy of Medical Sciences
Dates d'enregistrement des études
Dates principales de l'étude
Début de l'étude
Achèvement primaire (Anticipé)
Achèvement de l'étude (Anticipé)
Dates d'inscription aux études
Première soumission
Première soumission répondant aux critères de contrôle qualité
Première publication (Estimation)
Mises à jour des dossiers d'étude
Dernière mise à jour publiée (Réel)
Dernière mise à jour soumise répondant aux critères de contrôle qualité
Dernière vérification
Plus d'information
Termes liés à cette étude
Mots clés
Autres numéros d'identification d'étude
- MetaLab_2014_001
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