These tools will no longer be maintained as of December 31, 2024. Archived website can be found here. PubMed4Hh GitHub repository can be found here. Contact NLM Customer Service if you have questions.
Pubmed for Handhelds
PUBMED FOR HANDHELDS
Search MEDLINE/PubMed
Title: Validation of Cardiac Surgery-Associated Neutrophil Gelatinase-Associated Lipocalin Score for Prediction of Cardiac Surgery-Associated Acute Kidney Injury. Author: Mostafa EA, Shahin KM, El Midany AAH, Hassaballa AS, El-Sokkary IN, Gamal MA, Elsaid ME, ElBarbary MG, Khorshid R, Elelwany SE. Journal: Heart Lung Circ; 2022 Feb; 31(2):272-277. PubMed ID: 34219024. Abstract: BACKGROUND: The Cardiac Surgery-Associated Neutrophil Gelatinase-Associated Lipocalin (CSA-NGAL) score has been developed to stratify patients with cardiac surgery-associated acute kidney injury (CSA-AKI). Its predictive power needs to be validated to guide clinical decision for such high-risk patients. METHODS: A prospective study was conducted on 637 consecutive adult patients who developed postoperative AKI after cardiac surgery with cardiopulmonary bypass. AKI was defined according to Kidney Disease: Improving Global Outcomes criteria (KDIGO). The CSA-NGAL score was calculated. Assessment of the diagnostic performance of the scoring model was performed by area under the receiver operating curve analysis. RESULTS: The area under the curve for the postoperative Urinary NGAL showed an area under the curve ([standard error (SE)] 0.80 (0.38); p<0.001; 95% CI 0.72-0.87). Its sensitivity for CSA-AKI in the first 24 hours was 66% and specificity was 80% (cut-off value 300.1 ng/mL). There was a positive correlation between NGAL score and KDIGO criteria, with a significant increase in postoperative mean Urinary NGAL values as the KDIGO stage increased. CONCLUSION: The CSA-NGAL score has a high sensitivity, specificity and positive predictive value that can translate into improved outcomes and resource allocation. It is believed that adding it to the existing clinical scoring systems for AKI prediction will be productive.[Abstract] [Full Text] [Related] [New Search]