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The influence of glycemic status on the performance of cystatin C for acute kidney injury detection in the critically ill

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NIAID Data Ecosystem2026-03-11 收录
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https://figshare.com/articles/dataset/The_influence_of_glycemic_status_on_the_performance_of_cystatin_C_for_acute_kidney_injury_detection_in_the_critically_ill/7945463
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Objective: Serum cystatin C (sCysC) used clinically for detecting early acute kidney injury (AKI) was reported to be independently associated with hemoglobin (HbA1c) levels, diabetes, and prediabetes. We aimed to assess the influence of HbA1c levels, diabetes, or prediabetes on the performance of sCysC for AKI detection in critically ill adults. Methods: A prospective observational study was conducted in a mixed medical-surgical intensive care unit (ICU). Patients were divided into four quartiles based on levels of HbA1c or serum glucose at ICU admission, respectively. Additionally, patients were stratified into four subgroups according to HbA1c levels and history of diabetes, namely recognized diabetes (previous diagnosis of diabetes), unrecognized diabetes, prediabetes, and normal glycemic status. Comparisons were made using the area under the receiver operator characteristic curve (AUC) for AKI detection, and reassessed after patient stratification by above-mentioned glycemic status. Results: Multivariable linear regression revealed that HbA1c levels and history of diabetes were positively related with sCysC (all p < .05). Although stratification for above-mentioned glycemic status displayed no significant difference between AUC of sCysC (all p > .05), sCysC yielded the highest AUCs for detecting AKI in diabetic patients. Moreover, higher optimal cutoff values of sCysC to detect AKI were observed in patients with versus without diabetes. Conclusion: Glycemic status has no significant impact on the accuracy of sCysC for AKI detection in critically ill adults and a higher optimal cutoff value of sCysC for AKI detection should be considered in diabetic patients.
创建时间:
2019-04-03
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