Validation of a Urinary Biomarker as Diagnostic Tool for AKI in Sepsis
This trial is active, not recruiting.
|Condition||sepsis at intensive care unit|
|Treatment||urinary proteomic analysis|
|Sponsor||University Hospital, Ghent|
|Start date||June 2009|
|End date||June 2015|
|Trial size||150 participants|
|Trial identifier||NCT01981993, 2009/048|
Early diagnosis and prognostication of acute kidney injury in patients with sepsis is key to further our understanding this disease and in the evaluation of new interventions for this condition. Many urinary biomarkers have been proposed, but no single one seems to consistently provide additional information on top of clinical and routine biochemical parameters. Some authors have proposed to use a panel of urinary biomarkers to increase the accuracy However, this approach has so far not been tested in a large group of patients with sepsis. In addition, newer and more performant analytical techniques have been developed that warrant testing in the clinical field.
PATIENTS AND METHODS:
At least 150 consecutive patients admitted to a tertiary care intensive care unit (ICU) with sepsis will be included. After bladder catheterisation, urinary samples will be collected at time points 0, 4 hours and 24 hours after admission, and further daily on day 1-5. Samples will be immediately centrifuged and frozen at -80°C until analysis. Samples will be extracted by removing larger proteins (>20kDa) and de-salting step prior to mass spectrometry analysis. Investigators will use capillary electrophoresis-mass spectrometry (CE-MS) to assess urinary peptides predictive of AKI: 20 peptides constituting the AKI marker pattern previously established from a cohort of ICU patients. Simultaneously, samples will be analysed using matrix-assisted laser desorption ionisation time-of-flight mass spectrometry (MALDI-TOF MS), an alternative platform to CE-MS, which is currently being developed for routine ICU use. A proof of concept of the technique involved has been successfully applied to a set of urine samples from patients diagnosed with diabetes presenting normoalbuminuria (controls) and macroalbuminuria (cases).
Clinical, demographic and biochemical data of patients will be collected during the first 5 days.
- in the short term:
- development of acute kidney injury according to RIFLE criteria
- need for renal replacement therapy during ICU stay
- on the longer term
- need for renal replacement therapy
- estimated glomerular filtration rate as calculated by MDRD at 3 months, 1 year and 2 years.
Using cut-offs , Receiver Operating Characteristics curves, negative and positive predictive value will be used to describe diagnostic performance of the biomarker panel alone, or in combination with basic clinical and/or routine biochemical parameters. Univariate and multivariate logistic regression for death will be used to evaluate prognostication value of the biomarker set.
In addition, new discriminatory cut-offs of proteomic patterns as determined by more recent proteomic analysis techniques will be determined in a training set (half of the cohort) and validated in the other half of the cohort. Using the MALDI-TOF MS platform, investigators will assess urinary peptides that were predictive of AKI in a training set (ca. 75 patients) with good diagnostic performance of the marker panel (accuracy above 0.8) . Performance of the biomarker panel will be assessed in a blinded test set of ca. 75 patients to evaluate validity of the model in AKI detection.
development of acute kidney injury according to RIFLE criteria
time frame: at 3 months after inclusion
change in need for renal replacement therapy
time frame: at 3 months - 1 year and 2 year after inclusion
change in estimated glomerular filtration rate as calculated by MDRD
time frame: at 3 months, 1 year and 2 years after inclusion
time frame: 1 year and 2 years after inclusion
Male or female participants at least 18 years old.
Inclusion Criteria: - sepsis at ICU Exclusion Criteria: - na
|Official title||Value of a Urinary Biomarker Set Obtained by a Proteomics Approach to Predict Acute Kidney Injury and Prognosis in Sepsis Patients: a Prospective Cohort Study|
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