- ICH GCP
- US Clinical Trials Registry
- Klinisk utprøving 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.
Studieoversikt
Status
Studietype
Registrering (Forventet)
Kontakter og plasseringer
Studiesteder
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Sichuan
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Chengdu, Sichuan, Kina, 610072
- Rekruttering
- Sichuan Academy of Medical Sciences
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Ta kontakt med:
- Hua Jiang, MBBS,PhD
- Telefonnummer: 8613980001701
- E-post: cdjianghua@gmail.com
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Ta kontakt med:
- Bin Cai, MBBS
- Telefonnummer: 86-18981838125
- E-post: bin.cai@traumabank.org
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Deltakelseskriterier
Kvalifikasjonskriterier
Alder som er kvalifisert for studier
Tar imot friske frivillige
Kjønn som er kvalifisert for studier
Prøvetakingsmetode
Studiepopulasjon
Beskrivelse
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
Studieplan
Hvordan er studiet utformet?
Designdetaljer
Kohorter og intervensjoner
Gruppe / Kohort |
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Acute severe disease
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Hva måler studien?
Primære resultatmål
Resultatmål |
Tidsramme |
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Dødelighet ved sykehusinnleggelse
Tidsramme: Dødshendelser fra innleggelse til utskrivning (opptil 10 uker)
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Dødshendelser fra innleggelse til utskrivning (opptil 10 uker)
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Sekundære resultatmål
Resultatmål |
Tidsramme |
---|---|
Multi Organ Dysfunction Syndrome(MODS)
Tidsramme: 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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Samarbeidspartnere og etterforskere
Etterforskere
- Studiestol: Hua Jiang, PhD, MBBS, Sichuan Academy of Medical Sciences
Studierekorddatoer
Studer hoveddatoer
Studiestart
Primær fullføring (Forventet)
Studiet fullført (Forventet)
Datoer for studieregistrering
Først innsendt
Først innsendt som oppfylte QC-kriteriene
Først lagt ut (Anslag)
Oppdateringer av studieposter
Sist oppdatering lagt ut (Faktiske)
Siste oppdatering sendt inn som oppfylte QC-kriteriene
Sist bekreftet
Mer informasjon
Begreper knyttet til denne studien
Nøkkelord
Andre studie-ID-numre
- MetaLab_2014_001
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