Development and validation of clinical prediction models for acute kidney injury recovery at hospital discharge in critically ill adults

[1]  D. Hajage,et al.  Delayed versus early initiation of renal replacement therapy for severe acute kidney injury: a systematic review and individual patient data meta-analysis of randomised clinical trials , 2020, The Lancet.

[2]  Jayoun Kim,et al.  Machine learning algorithm to predict mortality in patients undergoing continuous renal replacement therapy , 2020, Critical Care.

[3]  Yong-ming Yao,et al.  Platelet count as a new biomarker for acute kidney injury induced by hemorrhagic shock , 2020, Platelets.

[4]  E. McArthur,et al.  Predicting mortality among critically ill patients with acute kidney injury treated with renal replacement therapy: Development and validation of new prediction models. , 2019, Journal of critical care.

[5]  Xi Zhu,et al.  Epidemiology of acute kidney injury in intensive care units in Beijing: the multi-center BAKIT study , 2019, BMC Nephrology.

[6]  J. Kellum,et al.  Acute kidney injury from sepsis: current concepts, epidemiology, pathophysiology, prevention and treatment. , 2019, Kidney international.

[7]  Jayoun Kim,et al.  Development of a new mortality scoring system for acute kidney injury with continuous renal replacement therapy , 2019, Nephrology.

[8]  Fei Wang,et al.  Stratified Mortality Prediction of Patients with Acute Kidney Injury in Critical Care , 2019, MedInfo.

[9]  Suman V. Ravuri,et al.  A Clinically Applicable Approach to Continuous Prediction of Future Acute Kidney Injury , 2019, Nature.

[10]  Nicholas Namias,et al.  Comparing Machine Learning Algorithms for Predicting Acute Kidney Injury , 2019, The American surgeon.

[11]  S. Kane-Gill,et al.  Review of the Literature on the Costs Associated With Acute Kidney Injury , 2019, Journal of pharmacy practice.

[12]  J. Kellum,et al.  Plasma Biomarkers in Predicting Renal Recovery from Acute Kidney Injury in Critically Ill Patients , 2019, Blood Purification.

[13]  L. Eshelman,et al.  Automated Continuous Acute Kidney Injury Prediction and Surveillance: A Random Forest Model , 2019, Mayo Clinic proceedings.

[14]  Ke Lin,et al.  Predicting in-hospital mortality of patients with acute kidney injury in the ICU using random forest model , 2019, Int. J. Medical Informatics.

[15]  S. Faubel,et al.  Effects of Baseline Thrombocytopenia and Platelet Decrease Following Renal Replacement Therapy Initiation in Patients With Severe Acute Kidney Injury* , 2019, Critical care medicine.

[16]  W. Beaubien-Souligny,et al.  Predicting Outcomes in Acute Kidney Injury Survivors: Searching for the Crystal Ball , 2019, Kidney international reports.

[17]  C. McCulloch,et al.  Predicting Renal Recovery After Dialysis-Requiring Acute Kidney Injury , 2019, Kidney international reports.

[18]  Yuan Luo,et al.  Early prediction of acute kidney injury following ICU admission using a multivariate panel of physiological measurements , 2019, BMC Medical Informatics and Decision Making.

[19]  Xiaoqian Jiang,et al.  Early Prediction of Acute Kidney Injury in Critical Care Setting Using Clinical Notes , 2018, 2018 IEEE International Conference on Bioinformatics and Biomedicine (BIBM).

[20]  J. Lundgren,et al.  Predicting recovery from acute kidney injury in critically ill patients: development and validation of a prediction model. , 2018, Critical care and resuscitation : journal of the Australasian Academy of Critical Care Medicine.

[21]  Ł. Krzych,et al.  Mortality of patients with acute kidney injury requiring renal replacement therapy. , 2018, Advances in clinical and experimental medicine : official organ Wroclaw Medical University.

[22]  J. Bahk,et al.  Neutrophil, Lymphocyte, and Platelet Counts and Acute Kidney Injury After Cardiovascular Surgery. , 2017, Journal of cardiothoracic and vascular anesthesia.

[23]  Glenn M. Chertow,et al.  The Economic Consequences of Acute Kidney Injury , 2017, Nephron.

[24]  Lucila Ohno-Machado,et al.  A risk prediction score for acute kidney injury in the intensive care unit , 2017, Nephrology, dialysis, transplantation : official publication of the European Dialysis and Transplant Association - European Renal Association.

[25]  M. van Meurs,et al.  Incidence, timing and outcome of AKI in critically ill patients varies with the definition used and the addition of urine output criteria , 2017, BMC Nephrology.

[26]  E. Macedo,et al.  A clinical score to predict mortality in septic acute kidney injury patients requiring continuous renal replacement therapy: the HELENICC score , 2017, BMC Anesthesiology.

[27]  Jan Gunst,et al.  AKIpredictor, an online prognostic calculator for acute kidney injury in adult critically ill patients: development, validation and comparison to serum neutrophil gelatinase-associated lipocalin , 2017, Intensive Care Medicine.

[28]  S. Uchino,et al.  Prediction Models and Their External Validation Studies for Mortality of Patients with Acute Kidney Injury: A Systematic Review , 2017, PloS one.

[29]  A. Bihorac,et al.  Mortality and cost of acute and chronic kidney disease after cardiac surgery , 2016, Current opinion in anaesthesiology.

[30]  J. Kellum,et al.  Recovery after Acute Kidney Injury , 2016, American journal of respiratory and critical care medicine.

[31]  William D. White,et al.  Platelet Counts, Acute Kidney Injury, and Mortality after Coronary Artery Bypass Grafting Surgery , 2016, Anesthesiology.

[32]  C. Combe,et al.  Kinetic eGFR and Novel AKI Biomarkers to Predict Renal Recovery. , 2015, Clinical journal of the American Society of Nephrology : CJASN.

[33]  Christopher M. Keener,et al.  Biomarker Enhanced Risk Prediction for Adverse Outcomes in Critically Ill Patients Receiving RRT. , 2015, Clinical journal of the American Society of Nephrology : CJASN.

[34]  H. Fan,et al.  Thrombocytopenia as a predictor of severe acute kidney injury in patients with heat stroke , 2015, Renal failure.

[35]  R. Thiele,et al.  AKI associated with cardiac surgery. , 2015, Clinical journal of the American Society of Nephrology : CJASN.

[36]  Gary S Collins,et al.  Transparent Reporting of a multivariable prediction model for Individual Prognosis Or Diagnosis (TRIPOD): Explanation and Elaboration , 2015, Annals of Internal Medicine.

[37]  J. Kellum.  How Can We Define Recovery after Acute Kidney Injury? Considerations from Epidemiology and Clinical Trial Design , 2014, Nephron Clinical Practice.

[38]  R. Bellomo,et al.  Validation of the Kidney Disease Improving Global Outcomes criteria for AKI and comparison of three criteria in hospitalized patients. , 2014, Clinical journal of the American Society of Nephrology : CJASN.

[39]  A. Khwaja.  KDIGO Clinical Practice Guidelines for Acute Kidney Injury , 2012, Nephron Clinical Practice.

[40]  H. Sørensen,et al.  One-year mortality among Danish intensive care patients with acute kidney injury: a cohort study , 2012, Critical Care.

[41]  G. Chertow,et al.  Model to predict mortality in critically ill adults with acute kidney injury. , 2011, Clinical journal of the American Society of Nephrology : CJASN.

[42]  G. Van den Berghe,et al.  Early versus Late Parenteral Nutrition in Critically Ill Adults , 2011, The New England journal of medicine.

[43]  J. Kellum,et al.  Urinary biomarkers and renal recovery in critically ill patients with renal support. , 2011, Clinical journal of the American Society of Nephrology : CJASN.

[44]  M. Legrand.  Faculty Opinions recommendation of Plasma and urine neutrophil gelatinase-associated lipocalin in septic versus non-septic acute kidney injury in critical illness. , 2010 .

[45]  M. Rosner,et al.  Acute kidney injury. , 2009, Current drug targets.

[46]  C.J.H. Mann,et al.  Clinical Prediction Models: A Practical Approach to Development, Validation and Updating , 2009 .

[47]  Achim Zeileis,et al.  Bias in random forest variable importance measures: Illustrations, sources and a solution , 2007, BMC Bioinformatics.

[48]  S. Bagshaw.  Epidemiology of renal recovery after acute renal failure , 2006, Current opinion in critical care.

[49]  T. Ikizler,et al.  Mortality after acute renal failure: models for prognostic stratification and risk adjustment. , 2006, Kidney international.

[50]  Joseph V Bonventre,et al.  Acute kidney injury, mortality, length of stay, and costs in hospitalized patients. , 2005, Journal of the American Society of Nephrology : JASN.

[51]  R. Bellomo,et al.  Acute renal failure in critically ill patients: a multinational, multicenter study. , 2005, JAMA.

[52]  G. John,et al.  Prediction of Mortality in Acute Renal Failure in Tropics , 2005, Renal failure.

[53]  W. Knaus,et al.  Definitions for sepsis and organ failure and guidelines for the use of innovative therapies in sepsis. The ACCP/SCCM Consensus Conference Committee. American College of Chest Physicians/Society of Critical Care Medicine. , 1992, Chest.

[54]  D Snypes,et al.  Evaluation of performance. , 1966, The Alabama nurse.

[55]  R. Higgins,et al.  Financial Impact of Acute Kidney Injury After Cardiac Operations in the United States. , 2018, The Annals of thoracic surgery.

[56]  Ho Jun Chin,et al.  U-shape relationship of white blood cells with acute kidney injury and mortality in critically ill patients. , 2014, The Tohoku journal of experimental medicine.

[57]  G. Williamson.  The explorer. , 1980, The Australasian nurses journal.