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Multiple Biomarkers in ICU Sepsis Patients

Z

Zhongnan Hospital

Status

Unknown

Conditions

AKI
Sepsis, Severe
Septic Shock
Sepsis

Study type

Observational

Funder types

Other

Identifiers

NCT03802136
2018062

Details and patient eligibility

About

Acute kidney injury (AKI) is a common condition among sepsis patients in the intensive care unit (ICU) and is associated with high morbidity and mortality. Oxidative stress biomarkers were investigated in panels and were reported to predict renal failure in sepsis patients. Some biomarkers would be able to identify who will recover and not recover better than serum creatinine. Thus, a combining oxidative stress biomarkers are needed to predict the occurrence or progression of AKI in critically ill patients.

Full description

Acute kidney injury (AKI) is a common condition among sepsis patients in the intensive care unit (ICU) and is associated with high morbidity and mortality. Oxidative stress biomarkers were investigated in panels and were reported to predict renal failure in sepsis patients. Research on AKI has focused on new damage biomarkers for early detection of AKI and worsening of renal function. Some biomarkers would be able to identify who will recover and not recover better than serum creatinine. Thus, a combining functional and damage markers as well as oxidative stress biomarkers are needed to predict the occurrence or progression of AKI in critically ill patients. Therefore, this prospective, observational study will be conducted in Mainland China

Enrollment

120 estimated patients

Sex

All

Ages

18 to 80 years old

Volunteers

No Healthy Volunteers

Inclusion criteria

  • sepsis patients in appropriate age

Exclusion criteria

  • ever blood transfusion ever CPR(cardiopulmonary resuscitation)

Trial design

120 participants in 2 patient groups

high concentration of biomarkers
Description:
the patients with biomarkers level over the normal max value
low concentration of biomarkers
Description:
the patients with biomarkers level below the normal max value

Trial contacts and locations

1

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Central trial contact

Li He; zhiyong peng, professor

Data sourced from clinicaltrials.gov

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