Utilizing Raman spectroscopy for urinalysis to diagnose acute kidney injury stages in cardiac surgery patients

Autor: Mukta Sharma, Chia-Lung Tsai, Ying-Chang Li, Cheng-Chia Lee, Yu-Li Hsieh, Chih-Hsiang Chang, Shao-Wei Chen, Liann-Be Chang
Jazyk: angličtina
Rok vydání: 2024
Předmět:
Zdroj: Renal Failure, Vol 46, Iss 2 (2024)
Druh dokumentu: article
ISSN: 0886022X
1525-6049
0886-022X
DOI: 10.1080/0886022X.2024.2375741
Popis: Background The successful treatment and improvement of acute kidney injury (AKI) depend on early-stage diagnosis. However, no study has differentiated between the three stages of AKI and non-AKI patients following heart surgery. This study will fill this gap in the literature and help to improve kidney disease management in the future.Methods In this study, we applied Raman spectroscopy (RS) to uncover unique urine biomarkers distinguishing heart surgery patients with and without AKI. Given the amplified risk of renal complications post-cardiac surgery, this approach is of paramount importance. Further, we employed the partial least squares-support vector machine (PLS-SVM) model to distinguish between all three stages of AKI and non-AKI patients.Results We noted significant metabolic disparities among the groups. Each AKI stage presented a distinct metabolic profile: stage 1 had elevated uric acid and reduced creatinine levels; stage 2 demonstrated increased tryptophan and nitrogenous compounds with diminished uric acid; stage 3 displayed the highest neopterin and the lowest creatinine levels. We utilized the PLS-SVM model for discriminant analysis, achieving over 90% identification rate in distinguishing AKI patients, encompassing all stages, from non-AKI subjects.Conclusions This study characterizes the incidence and risk factors for AKI after cardiac surgery. The unique spectral information garnered from this study can also pave the way for developing an in vivo RS method to detect and monitor AKI effectively.
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