Prediction of acute kidney injury using a combined model of inflammatory vascular endothelium biomarkers and ultrasound indices.
Ultrasound
endothelium
fibrosis
inflammation
kidney
predictive
Journal
Clinical hemorheology and microcirculation
ISSN: 1875-8622
Titre abrégé: Clin Hemorheol Microcirc
Pays: Netherlands
ID NLM: 9709206
Informations de publication
Date de publication:
2023
2023
Historique:
medline:
29
8
2023
pubmed:
22
5
2023
entrez:
22
5
2023
Statut:
ppublish
Résumé
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. 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. 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. 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. 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.
Sections du résumé
BACKGROUND
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
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
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
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
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.
Identifiants
pubmed: 37212089
pii: CH231754
doi: 10.3233/CH-231754
doi:
Substances chimiques
Biomarkers
0
Types de publication
Journal Article
Langues
eng
Sous-ensembles de citation
IM