Alveolar Dead Space as Predictor of Organ Failure in Severe Sepsis
NCT01315782
Infections, Inflammation
Houston, Texas, United States
View Trial DetailsNCT Number: NCT03996720
In patients diagnosed as sepsis on PICU admission, early and accurate identification of patients who will develop organ dysfunction (severe sepsis) is critical for effective management and positive outcome. A multiple marker approach would improve clinical utility compared with use of a single marker. The primary goal of this part of study is to define a combination of multiple markers, derived from novel biomarkers (nCD-64, IL-27, sTREM, HLA-DR, IL-10), metabolomics and routine clinical parameters, which could predict severe sepsis and determine the severity of disease.
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Notify Me29 day–18 year
All sexes
Observational
Children's Hospital of Fudan University, Shanghai, Shanghai Municipality, China
We intend to enroll pediatric sepsis patients at four PICUs and divide them into two groups based on clinical outcomes: severe sepsis group (patients who progress into severe sepsis), sepsis group (patients who do not progress in to severe sepsis). We intend to perform predictive modeling using multivariable analyses of the novel biomarkers and derive a biomarker panel and algorithm for early diagnosis of severe sepsis. The predictive value of the biomarker panel for early identification of severe sepsis will be compared with established indices, such as PRISM III and pSOFA score.
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Inclusion criteria
Exclusion criteria
Time frame: 28 day
Sepsis plus one of the following: cardiovascular organ dysfunction OR acute respiratory distress syndrome OR two or more other organ dysfunctions
Time frame: 28 day
death
Time frame: 28 day
infection acquired 48h after PICU admission
Time frame: 28 day
from PICU admission to discharge
Children's Hospital of Fudan University
Other
Integration of Metabolic and Inflammatory Mediator Profiles as a Potential Diagnostic Approach for Severe Sepsis in PICU
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