Novel Plasma Biomarker-Based Model for Predicting Acute Kidney Injury After Cardiac Surgery: A Case Control Study

Introduction: Acute kidney injury (AKI) after cardiac surgery is independently associated with a prolonged hospital stay, increased cost of care, and increased post-operative mortality. Delayed elevation of serum creatinine (SCr) levels requires novel biomarkers to provide a prediction of AKI after cardiac surgery. Our objective was to find a novel blood biomarkers combination to construct a model for predicting AKI after cardiac surgery and risk stratification. Methods: This was a case-control study. Weighted Gene Co-expression Network Analysis (WGCNA) was applied to Gene Expression Omnibus (GEO) dataset GSE30718 to seek potential biomarkers associated with AKI. We measured biomarker levels in venous blood samples of 67 patients with AKI after cardiac surgery and 59 control patients in two cohorts. Clinical data were collected. We developed a multi-biomarker model for predicting cardiac-surgery-associated AKI and compared it with a traditional clinical-factor-based model. Results: From bioinformatics analysis and previous articles, we found 6 potential plasma biomarkers for the prediction of AKI. Among them, 3 biomarkers, such as growth differentiation factor 15 (GDF15), soluble suppression of tumorigenicity 2 (ST2, IL1RL1), and soluble urokinase plasminogen activator receptor (uPAR) were found to have prediction ability for AKI (area under the curve [AUC] > 0.6) in patients undergoing cardiac surgery. They were then incorporated into a multi-biomarker model for predicting AKI (C-statistic: 0.84, Brier 0.15) which outperformed the traditional clinical-factor-based model (C-statistic: 0.73, Brier 0.16). Conclusion: Our research validated a promising plasma multi-biomarker model for predicting AKI after cardiac surgery.

[1]  S. Ostrowski,et al.  Prognostic value of suPAR and hsCRP on acute kidney injury after cardiac surgery , 2021, BMC Nephrology.

[2]  B. Feldt-Rasmussen,et al.  Elevated suPAR Is an Independent Risk Marker for Incident Kidney Disease in Acute Medical Patients , 2020, Frontiers in Cell and Developmental Biology.

[3]  Yi Yang,et al.  Preoperative Serum Fibrinogen is Associated With Acute Kidney Injury after Cardiac Valve Replacement Surgery , 2020, Scientific Reports.

[4]  A. McMahon,et al.  Renoprotective and Immunomodulatory Effects of GDF15 following AKI Invoked by Ischemia-Reperfusion Injury. , 2020, Journal of the American Society of Nephrology : JASN.

[5]  Jianghua Chen,et al.  Biomarkers of Acute Kidney Injury after Cardiac Surgery : A Narrative , 2019 .

[6]  C. Ronco,et al.  Current understanding and future directions in the application of TIMP-2 and IGFBP7 in AKI clinical practice , 2019, Clinical chemistry and laboratory medicine.

[7]  Dilara Ayyildiz,et al.  Introduction to Bioinformatics. , 2019, Methods in molecular biology.

[8]  J. Kellum,et al.  Kidney-Immune System Crosstalk in AKI. , 2019, Seminars in nephrology.

[9]  H. Yi,et al.  The Accuracy of Urinary TIMP-2 and IGFBP7 for the Diagnosis of Cardiac Surgery-Associated Acute Kidney Injury: A Systematic Review and Meta-Analysis , 2018, Journal of intensive care medicine.

[10]  Jeremiah R. Brown,et al.  Preoperative serum ST2 level predicts acute kidney injury after adult cardiac surgery , 2018, The Journal of thoracic and cardiovascular surgery.

[11]  Qing-lin Li,et al.  AKI in the very elderly patients without preexisting chronic kidney disease: a comparison of 48-hour window and 7-day window for diagnosing AKI using the KDIGO criteria , 2018, Clinical interventions in aging.

[12]  L. Forni,et al.  Cardiac and Vascular Surgery–Associated Acute Kidney Injury: The 20th International Consensus Conference of the ADQI (Acute Disease Quality Initiative) Group , 2018, Journal of the American Heart Association.

[13]  J. Lefrant,et al.  Interest of Urinary [TIMP-2] × [IGFBP-7] for Predicting the Occurrence of Acute Kidney Injury After Cardiac Surgery: A Gray Zone Approach , 2017, Anesthesia and analgesia.

[14]  P. Heuschmann,et al.  TIMP-2*IGFBP7 (Nephrocheck®) Measurements at Intensive Care Unit Admission After Cardiac Surgery are Predictive for Acute Kidney Injury Within 48 Hours , 2017, Kidney and Blood Pressure Research.

[15]  M. Scholz,et al.  Urine Biomarkers of Tubular Renal Cell Damage for the Prediction of Acute Kidney Injury After Cardiac Surgery-A Pilot Study. , 2017, Journal of cardiothoracic and vascular anesthesia.

[16]  Li-feng Huang,et al.  Diagnostic value of urinary tissue inhibitor of metalloproteinase-2 and insulin-like growth factor binding protein 7 for acute kidney injury: a meta-analysis , 2017, Critical Care.

[17]  A. Hoffmeier,et al.  Prevention of cardiac surgery-associated AKI by implementing the KDIGO guidelines in high risk patients identified by biomarkers: the PrevAKI randomized controlled trial , 2017, Intensive Care Medicine.

[18]  Astrid E. Berggreen,et al.  Preoperative plasma growth-differentiation factor-15 for prediction of acute kidney injury in patients undergoing cardiac surgery , 2016, Critical Care.

[19]  G. Ashuntantang,et al.  Outcomes of acute kidney injury in children and adults in sub-Saharan Africa: a systematic review. , 2016, The Lancet. Global health.

[20]  R. Mehta,et al.  Acute Kidney Injury in Western Countries , 2016, Kidney Diseases.

[21]  N. Tangri,et al.  Urinary, Plasma, and Serum Biomarkers' Utility for Predicting Acute Kidney Injury Associated With Cardiac Surgery in Adults: A Meta-analysis. , 2015, American journal of kidney diseases : the official journal of the National Kidney Foundation.

[22]  Yan Wang,et al.  Acute kidney injury in China: a cross-sectional survey , 2015, The Lancet.

[23]  D. Chae,et al.  Effects of acute kidney injury and chronic kidney disease on long-term mortality after coronary artery bypass grafting. , 2015, American heart journal.

[24]  O. Moerer,et al.  Quantification of urinary TIMP-2 and IGFBP-7: an adequate diagnostic test to predict acute kidney injury after cardiac surgery? , 2015, Critical Care.

[25]  J. Kellum,et al.  Urinary TIMP-2 and IGFBP7 as Early Biomarkers of Acute Kidney Injury and Renal Recovery following Cardiac Surgery , 2014, PloS one.

[26]  K. Famulski,et al.  Molecular phenotypes of acute kidney injury in kidney transplants. , 2012, Journal of the American Society of Nephrology : JASN.

[27]  A. Garg,et al.  Postoperative biomarkers predict acute kidney injury and poor outcomes after adult cardiac surgery. , 2011, Journal of the American Society of Nephrology : JASN.

[28]  S. Body,et al.  Plasma Neutrophil Gelatinase-Associated Lipocalin and Acute Postoperative Kidney Injury in Adult Cardiac Surgical Patients , 2010, Anesthesia and analgesia.

[29]  Steve Horvath,et al.  WGCNA: an R package for weighted correlation network analysis , 2008, BMC Bioinformatics.

[30]  A. Garg,et al.  The prognostic importance of a small acute decrement in kidney function in hospitalized patients: a systematic review and meta-analysis. , 2007, American journal of kidney diseases : the official journal of the National Kidney Foundation.

[31]  John T Granton,et al.  Derivation and validation of a simplified predictive index for renal replacement therapy after cardiac surgery. , 2007, JAMA.

[32]  Sean M. O'Brien,et al.  Bedside Tool for Predicting the Risk of Postoperative Dialysis in Patients Undergoing Cardiac Surgery , 2006, Circulation.

[33]  S. Arrigain,et al.  A clinical score to predict acute renal failure after cardiac surgery. , 2004, Journal of the American Society of Nephrology : JASN.

[34]  L. Bachmann,et al.  Minimal changes of serum creatinine predict prognosis in patients after cardiothoracic surgery: a prospective cohort study. , 2004, Journal of the American Society of Nephrology : JASN.