Clinical trial NCT01649440: Sepsis Metabolomics
Official title: Systemic Metabolic Changes of Sepsis Patients Revealed by an LC-MS/MS Based Metabolomic Approach
Study type: OBSERVATIONAL
Overall status: COMPLETED
Conditions: Normal Control
SIRS
Sepsis
Severe Sepsis
Death
Keywords: Metabolomics
serum
sepsis
biomarkers
Lead sponsor: Chinese PLA General Hospital
Sponsor class: OTHER
First posted: 2012-07-25
Enrollment: 65
Sex: ALL
Minimum age (years): 18
Standard ages: ADULT
OLDER_ADULT
Accepts healthy volunteers: yes
Observational model: CASE_CONTROL
Time perspective: PROSPECTIVE
Sampling method: PROBABILITY_SAMPLE
Study population: All subjects were selected from among inpatients who were hospitalized between July 2010 and Mar 2012 in the Respiratory ICU, Surgical ICU, and Emergency ICU, Chinese People's Liberation Army (CPLA) General Hospital.

Brief summary: The occurrence of sepsis and its relevant multiple organ dysfunction remain a major problem in intensive care units with high morbidity and mortality. The differentiation between non-infectious and infectious etiologies, severity and organ function evaluation, and prognostic assessment are all challenging in routine clinical practice. Many biomarkers have been suggested for these purpose; however sensitivity and specificity even of high-ranking biomarkers still remain insufficient. Recently, metabolic profiling has attracted interest for biomarker discovery. In this study, LC-MS/MS will be perform to identify serum metabolic biomarkers for differentiation of SIRS/sepsis, severity and organ function evaluation, and prognostic assessment among 65 patients. The investigators enrolled 35 patients who were diagnosed with sepsis, 15 patients who were diagnosed with SIRS, and 15 normal patients. Moreover, the sepsis were further divided into sepsis, severe sepsis, and sepsis patients before death. Small metabolites that were present in patient serum samples were measured by LC-MS/MS techniques and analyzed using multivariate statistical methods, such as Principal Component Analysis (PCA), Partial Least Squares-Discriminant Analysis (PLS-DA), and Orthogonal Partial Least Squares Discriminant Analysis. Based on the multivariate statistical analysis above, the investigators could distinguish sepsis from normal and SIRS; distinguish the difference among sepsis, severe sepsis and death. We hypothesis that some metabolites as identified in this study are promising biomarker candidates in the field of sepsis diagnosis and treatment.


Eligibility criteria: Inclusion Criteria:

* male and female aged 18 years old and over;
* clinically confirmed infection;
* fulfilled at least two criteria of systemic inflammatory response syndrome
* core temperature higher than 38 °C or lower than 36 °C
* respiratory rate above 20/min, or PCO2 below 32 mmHg
* pulse rate above 90/min, and
* white blood cell count greater than 12,000/μl or lower than \< 4,000/μl or less than 10% of bands.

Exclusion Criteria:

* younger than 18 years of age;
* acquired immunodeficiency syndrome;
* reduced polymorphonuclear granulocyte counts (\< 500 μL-1);
* died within 24h after admission into the ICU, or refused to participate in the study, or declined treatment during the period of observation.

Primary outcomes:
measure: death
timeFrame: sepsis patients within 48 hours before death
Secondary outcomes:
Other outcomes:
Locations:
city: Beijing
country: China
facility: Chinese PLA General Hospital
state: Beijing
Study officials:
affiliation: Department of Respiratory Diseases, Chinese PLA General Hospital
name: Lixin Xie, Dr
role: STUDY_DIRECTOR
References:
citation: Su L, Huang Y, Zhu Y, Xia L, Wang R, Xiao K, Wang H, Yan P, Wen B, Cao L, Meng N, Luan H, Liu C, Li X, Xie L. Discrimination of sepsis stage metabolic profiles with an LC/MS-MS-based metabolomics approach. BMJ Open Respir Res. 2014 Dec 10;1(1):e000056. doi: 10.1136/bmjresp-2014-000056. eCollection 2014.