Observational studyRenal failure2019
The influence of glycemic status on the performance of cystatin C for acute kidney injury detection in the critically ill.
Observational study in Renal failure, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers.
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Who cites it
18 citing papers in PubMed, 29 citations in OpenAlex.
- Stress hyperglycemia ratio as a predictor of acute kidney injury and its outcomes in critically ill patients.Renal failure · 2025Article
- The nadir platelet count in the first 48 h after ICU admission is a potential predictor of acute kidney injury in hemorrhagic shock patients.BMC cardiovascular disorders · 2024Observational
- Prevalence and associated factors of glomerular hyperfiltration among adult stable sickle cells in Kinshasa, DR Congo.Renal failure · 2024Article
- Recent Advances of Proteomics in Management of Acute Kidney Injury.Diagnostics (Basel, Switzerland) · 2023Review
- Observational
- Proficient Novel Biomarkers Guide Early Detection of Acute Kidney Injury: A Review.Diseases (Basel, Switzerland) · 2022Review
- Use of ultra high performance liquid chromatography with high resolution mass spectrometry to analyze urinary metabolome alterations following acute kidney injury in post-cardiac surgery patients.Journal of mass spectrometry and advances in the clinical lab · 2022Article
- The incidence, risk factors and outcomes of acute kidney injury in critically ill patients undergoing emergency surgery: a prospective observational study.BMC nephrology · 2022Observational
- Urinary proteome analysis of acute kidney injury in post-cardiac surgery patients using enrichment materials with high-resolution mass spectrometry.Frontiers in bioengineering and biotechnology · 2022Article
- Combining renal cell arrest and damage biomarkers to predict progressive AKI in patient with sepsis.BMC nephrology · 2021Article
- Isoliquiritigenin attenuates septic acute kidney injury by regulating ferritinophagy-mediated ferroptosis.Renal failure · 2021Article
- Assessment of 17 clinically available renal biomarkers to predict acute kidney injury in critically ill patients.Journal of translational internal medicine · 2021Article
- Divergence between serum creatine and cystatin C in estimating glomerular filtration rate of critically ill COVID-19 patients.Renal failure · 2021Article
- The influence of hyperbilirubinemia on indexes of kidney function in neonates.Pediatric nephrology (Berlin, Germany) · 2021Article
- The effect of glucocorticoids on serum cystatin C in identifying acute kidney injury: a propensity-matched cohort study.BMC nephrology · 2020Observational
- Establishment and Validation of a Liquid Chromatography-Tandem Mass Spectrometry Method for the Determination of Tigecycline in Critically Ill Patients.International journal of analytical chemistry · 2020Article
- Effect of hydrocortisone on the 28-day mortality of patients with septic acute kidney injury.Renal failure · 2019Article
- Corticosteroids significantly increase cystatin C levels in the plasma by promoting cystatin C production in rats.Renal failure · 2019Article
Corrections and comments
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Authors and funding
14 authors at 4 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
objectiveSerum 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.
methodsA 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.
resultsMultivariable 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.
conclusionGlycemic 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.
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