Abdelwahed OM, Aboulhoda BE, Awadallah MY, Gouda SAA, Abdallah H, Rashed L, Khaled M, Ghobrial EE, Alghabban HM, Sharawy N. Prediction of acute kidney injury using a combined model of inflammatory vascular endothelium biomarkers and ultrasound indices.
Clin Hemorheol Microcirc 2023;
84:283-301. [PMID:
37212089 DOI:
10.3233/ch-231754]
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Abstract
BACKGROUND
Acute kidney injury (AKI) is a common complication of sepsis, with the burden of long hospital admission. Early prediction of AKI is the most effective strategy for intervention and improvement of the outcomes.
OBJECTIVE
In our study, we aimed to investigate the predictive performance of the combined model using ultrasound indices (grayscale and Doppler indieces), endothelium injury (E-selectin, VCAM-1, ICAM1, Angiopoietin 2, syndecan-1, and eNOS) as well as inflammatory biomarkers (TNF-a, and IL-1β) to identify AKI.
METHODS
Sixty albino rats were divided into control and lipopolysaccharide (LPS) groups. Renal ultrasound, biochemical and immunohistological variables were recorded 6 hrs, 24 hrs, and 48 hrs after AKI.
RESULTS
Endothelium injury and inflammatory markers were found to be significantly increased early after AKI, and correlated significantly with kidney size reduction and renal resistance indices elevation.
CONCLUSIONS
Using area under the curve (AUC), the combined model was analyzed based on ultrasound and biochemical variables and provided the highest predictive value for renal injury.
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