The initial development and assessment of an automatic alert warning of acute kidney injury.

BACKGROUND Acute kidney injury (AKI) recognition by clinicians has been shown to be suboptimal. Little work has focused on the use of an automated warning of a rise in a patient's creatinine, indicating AKI. METHODS Over 3 months in 2008 we ran a prospective observational study of 'alerts' sent by our Integrated Clinical Environment pathology system, identifying all patients with a ≥ 75% rise in their creatinine from its previous value. Information was collected on subsequent renal function, comorbidities and other potential predictors of survival. RESULTS In the 3-month period 463 adults with a first episode of AKI were identified by an alert; 87% were hospital inpatients. Median follow-up was 404 days. In-hospital mortality was 36% for those who were admitted. After performing Weibull survival analysis, significant predictors of poorer survival were the presence of metastatic, haematological or lower risk malignancy, a residential or nursing home address and higher age, number of non-malignant comorbidities or C-reactive protein level. Predictors of better survival were higher serum albumin level or nadir GFR during the episode and Indian subcontinent ethnicity. A receiver-operator curve for a prognostic score developed from the analysis showed an area under the curve of 0.84. CONCLUSIONS The alerts identified a group of AKI patients who are at moderately high risk of death. The prognostic score using a combination of covariates shows early promise. Both the alerts and the score warrant further development as tools for earlier intervention in AKI.

[1]  S. Hou,et al.  Hospital-acquired renal insufficiency. , 2002, American journal of kidney diseases : the official journal of the National Kidney Foundation.

[2]  内野 滋彦 An assessment of the RIFLE criteria for acute renal failure in hospitalized patients , 2008 .

[3]  R. Parker,et al.  Communities and Local Government , 2008 .

[4]  David Collett Modelling Survival Data in Medical Research , 1994 .

[5]  H. Sugiyama,et al.  Clinical Usefulness of a Prognostic Score in Histological Analysis of Renal Biopsy in Patients with Lupus Nephritis , 2009, The Journal of Rheumatology.

[6]  J P Kassirer,et al.  Adding insult to injury. Usurping patients' prerogatives. , 1983, The New England journal of medicine.

[7]  P. Bossuyt,et al.  How to adjust for comorbidity in survival studies in ESRD patients: a comparison of different indices. , 2002, American journal of kidney diseases : the official journal of the National Kidney Foundation.

[8]  R. Lins,et al.  Re-evaluation and modification of the Stuivenberg Hospital Acute Renal Failure (SHARF) scoring system for the prognosis of acute renal failure: an independent multicentre, prospective study. , 2004, Nephrology, dialysis, transplantation : official publication of the European Dialysis and Transplant Association - European Renal Association.

[9]  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.

[10]  John A Kellum,et al.  Acute Kidney Injury Network: report of an initiative to improve outcomes in acute kidney injury , 2007, Critical care.

[11]  J. Feehally,et al.  Acute renal failure associated with haematological malignancies: A review of 10 years experience , 1991, European journal of haematology.

[12]  J. Decruyenaere,et al.  Outcome in critically ill medical patients treated with renal replacement therapy for acute renal failure: comparison between patients with and those without haematological malignancies. , 2005, Nephrology, dialysis, transplantation : official publication of the European Dialysis and Transplant Association - European Renal Association.

[13]  J Pascual,et al.  The spectrum of acute renal failure in the intensive care unit compared with that seen in other settings. The Madrid Acute Renal Failure Study Group. , 1998, Kidney international. Supplement.

[14]  I. Khan,et al.  Acute renal failure: factors influencing nephrology referral and outcome. , 1997, QJM : monthly journal of the Association of Physicians.

[15]  R. Henning,et al.  Immediate postoperative renal function deterioration in cardiac surgical patients predicts in-hospital mortality and long-term survival. , 2004, Journal of the American Society of Nephrology : JASN.

[16]  Testing new biomarkers for acute kidney injury: association, prediction, and intervention. , 2009, American journal of kidney diseases : the official journal of the National Kidney Foundation.

[17]  J. Stewart Adding insult to injury: care of patients with acute kidney injury. , 2009, British journal of hospital medicine.

[18]  R. Bellomo,et al.  Acute renal failure – definition, outcome measures, animal models, fluid therapy and information technology needs: the Second International Consensus Conference of the Acute Dialysis Quality Initiative (ADQI) Group , 2004, Critical care.

[19]  C. Safran,et al.  Effect of computer-based alerts on the treatment and outcomes of hospitalized patients. , 1994, Archives of internal medicine.

[20]  S Van Hoecke,et al.  IMPLEMENTATION OF A REAL-TIME ELECTRONIC ALERT BASED ON THE RIFLE CRITERIA FOR ACUTE KIDNEY INJURY IN ICU PATIENTS , 2007, Acta clinica Belgica.

[21]  L. Fried,et al.  Charlson comorbidity index as a predictor of outcomes in incident peritoneal dialysis patients. , 2001, American journal of kidney diseases : the official journal of the National Kidney Foundation.

[22]  A. S. Tayade,et al.  Role of hypoalbuminemia and hypocholesterolemia as copredictors of mortality in acute renal failure. , 1999, Kidney international.

[23]  S. Love,et al.  Survival Analysis Part II: Multivariate data analysis – an introduction to concepts and methods , 2003, British Journal of Cancer.

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

[25]  C. Mackenzie,et al.  A new method of classifying prognostic comorbidity in longitudinal studies: development and validation. , 1987, Journal of chronic diseases.

[26]  E. Siew,et al.  Urine neutrophil gelatinase-associated lipocalin moderately predicts acute kidney injury in critically ill adults. , 2009, Journal of the American Society of Nephrology : JASN.

[27]  J. Pascual,et al.  Prognosis of acute tubular necrosis: an extended prospectively contrasted study. , 1993, Nephron.

[28]  A. Go,et al.  Commonly used surrogates for baseline renal function affect the classification and prognosis of acute kidney injury. , 2010, Kidney international.

[29]  M. Carvalho,et al.  Prognosis of critically ill patients with cancer and acute renal dysfunction. , 2006, Journal of clinical oncology : official journal of the American Society of Clinical Oncology.

[30]  E. Fiaccadori,et al.  Prevalence and clinical outcome associated with preexisting malnutrition in acute renal failure: a prospective cohort study. , 1999, Journal of the American Society of Nephrology : JASN.

[31]  Saba Sarwar,et al.  National Confidential Enquiry into Patient Outcome and Death , 2007 .

[32]  R. Bellomo,et al.  An assessment of the RIFLE criteria for acute renal failure in hospitalized patients* , 2006, Critical care medicine.

[33]  G. Prescott,et al.  Incidence and outcomes in acute kidney injury: a comprehensive population-based study. , 2007, Journal of the American Society of Nephrology : JASN.

[34]  N. Tamimi,et al.  Non-specialist management of acute renal failure. , 2001, QJM : monthly journal of the Association of Physicians.

[35]  James A Russell,et al.  Early changes in organ function predict eventual survival in severe sepsis* , 2005, Critical care medicine.

[36]  R. Kaplan,et al.  Nephrology consultation in acute renal failure: does timing matter? , 2002, The American journal of medicine.

[37]  K. Carroll,et al.  On the use and utility of the Weibull model in the analysis of survival data. , 2003, Controlled clinical trials.

[38]  R. Lafayette,et al.  Predictors of mortality and the provision of dialysis in patients with acute tubular necrosis. The Auriculin Anaritide Acute Renal Failure Study Group. , 1998, Journal of the American Society of Nephrology : JASN.

[39]  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.

[40]  K. Kelly Distant effects of experimental renal ischemia/reperfusion injury. , 2003, Journal of the American Society of Nephrology : JASN.

[41]  M. Saul,et al.  A simple comorbidity scale predicts clinical outcomes and costs in dialysis patients. , 2000, The American journal of medicine.

[42]  R. Star Treatment of acute renal failure. , 1998, Kidney international.

[43]  S. Love,et al.  Survival Analysis Part III: Multivariate data analysis – choosing a model and assessing its adequacy and fit , 2003, British Journal of Cancer.

[44]  E. Paganini,et al.  Risk modeling in acute renal failure requiring dialysis: the introduction of a new model. , 1996, Clinical nephrology.

[45]  R. Bellomo,et al.  A comparison of observed versus estimated baseline creatinine for determination of RIFLE class in patients with acute kidney injury. , 2009, Nephrology, dialysis, transplantation : official publication of the European Dialysis and Transplant Association - European Renal Association.