Clinical Trial Details
— Status: Not yet recruiting
Administrative data
NCT number |
NCT06241417 |
Other study ID # |
2023ZDSYLL379-P01 |
Secondary ID |
|
Status |
Not yet recruiting |
Phase |
|
First received |
|
Last updated |
|
Start date |
January 25, 2024 |
Est. completion date |
June 30, 2024 |
Study information
Verified date |
February 2024 |
Source |
Southeast University, China |
Contact |
n/a |
Is FDA regulated |
No |
Health authority |
|
Study type |
Observational
|
Clinical Trial Summary
Acute kidney injury is a common complication in critically ill patients. This condition can
significantly prolong the length of hospital stay, increase the cost of hospitalization, and
have a high mortality rate and a poor prognosis. Early assessment of patients' prognosis with
acute kidney injury is vital for clinical treatment. Point-of-care ultrasound and renal
injury biomarkers can be used to evaluate kidney injury at different levels. Therefore, it is
speculated that dynamic monitoring can accurately predict the prognosis of patients with
kidney injury.
Description:
AKI is a common complication in patients with severe disease, significantly prolonging
hospital stay, increasing hospital costs, high mortality, and poor prognosis. Epidemiological
studies abroad have shown that the incidence of AKI in the intensive care unit (ICU) is about
39%, and the 90-day case fatality rate is 34%.
The renal prognosis of AKI is also a central concern for intensivists, as the renal prognosis
also affects the long-term survival outcomes of patients with AKI. In a long-term follow-up
of 1538 hospitalized patients, Bhatraju et al. found that in the AKI population, patients who
did not recover their renal function during hospitalization had a significantly higher
long-term mortality rate than those who recovered.
The main causes of AKI include prerenal factors, renal factors, and postrenal factors. The
proportion of AKI caused by postrenal causes in ICU patients is small and can be easily
treated and corrected, and prerenal and renal factors are the main causes of AKI in ICU
patients. Therefore, the assessment of prerenal and nephrogenic factors in patients with AKI
can predict the prognosis of AKI more accurately. An important mechanism of AKI pathogenesis
is renal hypoperfusion. Urine output is often used to evaluate renal perfusion in clinical
practice, but the specificity of urine output to assess renal perfusion is poor and is
affected by factors such as age, stress, surgery, and diuretic use.
Point-of-care ultrasound has the advantages of non-invasive, simple, rapid, and reproducible
evaluation, and has been widely used in critically ill patients. Color Doppler
ultrasonography and contrast-enhanced ultrasonography can be used to measure renal perfusion
parameters and assess renal function. Darmon et al. used renal ultrasound to measure the
renal resistance index (RRI) and semi-quantitative renal perfusion (SQP) of renal blood flow
in 371 critically ill patients and found that the RRI was significantly higher in patients
with AKI than in patients without AKI, but RRI performed poorly in predicting short-term
renal prognosis in AKI. Compared with two-dimensional ultrasound, contrast-enhanced
ultrasound can visualize changes in renal microcirculation and provide a clearer assessment
of renal perfusion. Yoon et al. performed contrast-enhanced renal sonography in 48 patients
with AKI and found that the slope of renal cortex washout and peak medulla intensity
predicted renal recovery, but the predictive performance was modest.
Novel biomarkers of AKI can identify kidney injury earlier, determine the severity of the
injury, and assess prognosis. Komaru et al. measured urinary neutrophil gelatinase-associated
lipids transport proteins (NGAL) and serum interleukin-6 levels in 133 patients with AKI
requiring continuous renal replacement (CRRT) in the ICU. Urinary NGAL levels at the end of
CRRT have been found to predict successful weaning of CRRT.
Based on the above research background, the following scientific hypothesis is proposed: the
combination of renal ultrasound and AKI biomarkers can better predict the renal prognosis of
AKI patients.