La tasa de filtrado glomerular estimada es un biomarcador precoz de la insuficiencia renal aguda asociada a la cirugía cardíaca

Rosner, 2006, Acute kidney injury associated with cardiac surgery, Clin J Am Soc Nephrol, 1, 19, 10.2215/CJN.00240605 Mao, 2013, Cardiac surgery-associated acute kidney injury, Cardiorenal Med, 3, 178, 10.1159/000353134 Thakar, 2005, A clinical score to predict acute renal failure after cardiac surgery, J Am Soc Nephrol, 16, 162, 10.1681/ASN.2004040331 Wijeysundera, 2007, Derivation and validation of a simplified predictive index for renal replacement therapy after cardiac surgery, JAMA, 297, 1801, 10.1001/jama.297.16.1801 Kashani, 2013, Discovery and validation of cell cycle arrest biomarkers in human acute kidney injury, Crit Care, 17, R25, 10.1186/cc12503 Haase, 2009, Accuracy of neutrophil gelatinase-associated lipocalin (NGAL) in diagnosis and prognosis in acute kidney injury: A systematic review and meta-analysis, Am J Kidney Dis, 54, 1012, 10.1053/j.ajkd.2009.07.020 Zhang, 2011, Cystatin C in prediction of acute kidney injury: A systemic review and meta-analysis, Am J Kidney Dis, 58, 356, 10.1053/j.ajkd.2011.02.389 Liu, 2013, Urinary interleukin 18 for detection of acute kidney injury: A meta-analysis, Am J Kidney Dis, 62, 1058, 10.1053/j.ajkd.2013.05.014 Coca, 2008, Urinary biomarkers for acute kidney injury: Perspectives on translation, Clin J Am Soc Nephrol, 3, 481, 10.2215/CJN.03520807 Wyckoff, 2012, Advances in acute kidney injury associated with cardiac surgery: The unfolding revolution in early detection, J Cardiothorac Vasc Anesth, 26, 340, 10.1053/j.jvca.2012.01.001 Wijeysundera, 2006, Improving the identification of patients at risk of postoperative renal failure after cardiac surgery, Anesthesiology, 104, 65, 10.1097/00000542-200601000-00012 Najafi, 2009, Is preoperative serum creatinine a reliable indicator of outcome in patients undergoing coronary artery bypass surgery?, J Thorac Cardiovasc Surg, 137, 304, 10.1016/j.jtcvs.2008.08.001 Atkinson, 2001, Biomarkers and surrogate endpoints: Preferred definitions and conceptual framework, Clin Pharmacol Ther, 69, 89, 10.1067/mcp.2001.113989 Mehta, 2007, Acute Kidney Injury Network: Report of an initiative to improve outcomes in acute kidney injury, Crit Care, 11, R31, 10.1186/cc5713 Levey, 1999, A more accurate method to estimate glomerular filtration rate from serum creatinine: A new prediction equation, Ann Intern Med, 130, 461, 10.7326/0003-4819-130-6-199903160-00002 Candela-Toha, 2008, Predicting acute renal failure after cardiac surgery: External validation of two new clinical scores, Clin J Am Soc Nephrol, 3, 1260, 10.2215/CJN.00560208 Heagerty, 2000, Time-dependent ROC curves for censored survival data and a diagnostic marker, Biometrics, 56, 337, 10.1111/j.0006-341X.2000.00337.x Pepe, 2003, The receiver operating characteristic curve, 66 Omar, 2004, Cardiac surgery risk modeling for mortality: A review of current practice and suggestions for improvement, Ann Thorac Surg, 77, 2232, 10.1016/j.athoracsur.2003.10.032 Heagerty, 2005, Survival model predictive accuracy and ROC curves, Biometrics, 61, 92, 10.1111/j.0006-341X.2005.030814.x Schuirmann, 1987, A comparison of the two one-sided tests procedure and the power approach for assessing the equivalence of average bioavailability, J Pharmacokinet Biopharma, 15, 657, 10.1007/BF01068419 Nguyen, 2009, Misapplications of commonly used kidney equations: Renal physiology in practice, Clin J Am Soc Nephrol, 4, 528, 10.2215/CJN.05731108 Mehta, 2006, Bedside tool for predicting the risk of postoperative dialysis in patients undergoing cardiac surgery, Circulation, 114, 2208, 10.1161/CIRCULATIONAHA.106.635573 Englberger, 2010, Validation of clinical scores predicting severe acute kidney injury after cardiac surgery, Am J Kidney Dis, 56, 623, 10.1053/j.ajkd.2010.04.017 Mishra, 2005, Neutrophil gelatinase-associated lipocalin (NGAL) as a biomarker for acute renal injury after cardiac surgery, Lancet, 365, 1231, 10.1016/S0140-6736(05)74811-X Pepe, 2008, Evaluating the ROC performance of markers for future events, Lifetime Data Anal, 14, 86, 10.1007/s10985-007-9073-x Pipili, 2014, Prediction of the renal replacement therapy requirement in mechanically ventilated critically ill patients by combining biomarkers for glomerular filtration and tubular damage, J Crit Care, 29, 10.1016/j.jcrc.2014.02.011 McIlroy, 2010, Biomarkers of acute kidney injury: An evolving domain, Anesthesiology, 112, 998, 10.1097/ALN.0b013e3181cded3f KDIGO Clinical practice guideline for acute kidney injury. Kidney Int Suppl. 2012;2:1-138. Meersch, 2017, Prevention of cardiac surgery-associated AKI by implementing the KDIGO guidelines in high risk patients identified by biomarkers: the PrevAKI randomized controlled trial, Intensive Care Med., 43, 1551, 10.1007/s00134-016-4670-3 Lagny, 2015, Incidence and outcomes of acute kidiney injury after cardiac surgery using either criteria of the RIFLE classification, BMC Nephrol, 16, 1, 10.1186/s12882-015-0066-9 Englberger, 2011, Clinical accuracy of RIFLE and Acute Kidney Injury Network (AKIN) criteria for acute kidney injury in patients undergoing cardiac surgery, Crit Care, 15, R16, 10.1186/cc9960 McIlroy, 2010, Neutrophil gelatinase-associated lipocalin and acute kidney injury after cardiac surgery: The Effect of baseline renal function on diagnostic performance, Clin J Am Soc Nephrol, 5, 211, 10.2215/CJN.04240609