Sniffing out acute kidney injury in the ICU: Do we have the tools?

Current Opinion in Critical Care

Volumn 19, Issue 6, 2013, Pages 531-536

  Kashani, Kianoush ^a   Herasevich, Vitaly ^b  

^a Department of Internal Medicine   (United States)

^b MAYO CLINIC   (United States)

Author keywords

acute kidney injury; electronic medical records; electronic surveillance; smart alert; sniffer

Indexed keywords

CREATININE;

ACUTE KIDNEY FAILURE; CREATININE BLOOD LEVEL; ELECTRONIC SYNDROMIC SURVEILLANCE SYSTEM; GENERAL MEDICAL DEVICE; HIGH RISK PATIENT; HUMAN; INFORMATION TECHNOLOGY; INTENSIVE CARE; PATIENT CARE; PATIENT MONITORING; REVIEW; SENSITIVITY AND SPECIFICITY; URINE FLOW RATE; URINE VOLUME;

ACUTE KIDNEY INJURY; ALGORITHMS; CLINICAL ALARMS; CLINICAL LABORATORY INFORMATION SYSTEMS; CREATININE; EARLY DIAGNOSIS; EQUIPMENT DESIGN; FEMALE; HUMANS; INTENSIVE CARE UNITS; MALE; PATIENT SELECTION; QUALITY IMPROVEMENT; REPRODUCIBILITY OF RESULTS; SENSITIVITY AND SPECIFICITY;

EID: 84888199941     PISSN: 10705295     EISSN: 15317072     Source Type: Journal    
DOI: 10.1097/MCC.0000000000000024     Document Type: Review

References (38)

1. Hoste EA, Kellum JA, Katz NM, et al. Epidemiology of acute kidney injury. Contrib Nephrol 2010; 165:1-8
2. Chertow GM, Burdick E, Honour M, et al. Acute kidney injury, mortality, length of stay, and costs in hospitalized patients. J Am Soc Nephrol 2005; 16:3365-3370 (Pubitemid 46179340)
3. Mehta RL, McDonald B, Gabbai F, et al. Nephrology consultation in acute renal failure: does timing matter? Am J Med 2002; 113:456-461 (Pubitemid 35335796)
4. Kiers HD, Griesdale DE, Litchfield A, et al. Effect of early achievement of physiologic resuscitation goals in septic patients admitted from the ward on the kidneys. J Crit Care 2010; 25:563-569
5. Bagshaw SM, George C, Bellomo R, Committee ADM. Early acute kidney injury and sepsis: a multicentre evaluation. Crit Care 2008; 12:R47
6. Colpaert K, Hoste EA, Steurbaut K, et al. Impact of real-time electronic alerting of acute kidney injury on therapeutic intervention and progression of RIFLE class. Crit Care Med 2012; 40:1164-1170
7. Macedo E, Malhotra R, Claure-Del Granado R, et al. Defining urine output criterion for acute kidney injury in critically ill patients. Nephrol Dial Transplant 2011; 26:509-515
8. Thomas M, Sitch A, Dowswell G. The initial development and assessment of an automatic alert warning of acute kidney injury. Nephrol Dial Transplant 2011; 26:2161-2168
9. Selby NM, Crowley L, Fluck RJ, et al. Use of electronic results reporting to diagnose and monitor AKI in hospitalized patients. Clin J Am Soc Nephrol 2012; 7:533-540
10. Herasevich V, Pickering BW, Dong Y, et al. Informatics infrastructure for syndrome surveillance, decision support, reporting, and modeling of critical illness. Mayo Clin Proc 2010; 85:247-254
11. Lenert L, Sundwall DN. Public health surveillance and meaningful use regulations: a crisis of opportunity. Am Jo Public Health 2012; 102:1-7; e.
12. Mandl KD, Overhage JM, Wagner MM, et al. Implementing syndromic surveillance: a practical guide informed by the early experience. J Am Med Inform Assoc 2004; 11:141-150 (Pubitemid 38327503)
13. KashiourisM, OHoro J, Pickering B, Herasevich V. Diagnostic performance of electronic syndromic surveillance systems in acute care. Appl Clin Inform 2013; 4:212-224
14. Klompas M, Kleinman K, Platt R. Development of an algorithm for surveillance of ventilator-associated pneumonia with electronic data and comparison of algorithm results with clinician diagnoses. Infect Control Hosp Epidemiol 2008; 29:31-37 (Pubitemid 351267771)
15. Herasevich V, Tsapenko M, Kojicic M, et al. Limiting ventilator-induced lung injury through individual electronic medical record surveillance. Crit Care Med 2011; 39:34-39
16. Slooter AJ, Vriens EM, Leijten FS, et al. Seizure detection in adult ICU patients based on changes in EEG synchronization likelihood. Neurocrit Care 2006; 5:186-192
17. Gharaviri A, Teshnehlab M, Moghaddam HA. Ischemia detection via ECG using ANFIS. Conf ProcIEEE Eng Med Biol 2008; 2008:1163-1166
18. Aboukhalil A, Nielsen L, Saeed M, et al. Reducing false alarm rates for critical arrhythmias using the arterial blood pressure waveform. J Biomed Inform 2008; 41:442-451
19. Thiel SW, Rosini JM, Shannon W, et al. Early prediction of septic shock in hospitalized patients. J Hosp Med 2010; 5:19-25
20. Freeman R, Moore LS, Garcia Alvarez L, et al. Advances in electronic surveillance for healthcare-associated infections in the 21st century: a systematic review. J Hosp Infect 2013; 84:106-119
21. Woeltje KF, McMullen KM, Butler AM, et al. Electronic surveillance for healthcare-associated central line-associated bloodstream infections outside the intensive care unit. Infect Control Hosp Epidemiol 2011; 32:1086-1090
22. Herasevich V, Pickering BW, Dong Y, et al. Informatics infrastructure for syndrome surveillance, decision support, reporting, and modeling of critical illness. Mayo Clin Proc 2010; 85:247-254
23. Han YY, Carcillo JA, Venkataraman ST, et al. Unexpected increased mortality after implementation of a commercially sold computerized physician order entry system. Pediatrics 2005; 116:1506-1512 (Pubitemid 46056501)
24. Herasevich V, Kor DJ, Subramanian A, Pickering BW. Connecting the dots: rule-based decision support systems in the modern EMR era. J Clin Monit Comput 2013; 27:443-448
25. Blum JM, Tremper KK. Alarms in the intensive care unit: too much of a good thing is dangerous - is it time to add some intelligence to alarms? Crit Care Med 2010; 38:702-703
26. Bellomo R, Ronco C, Kellum JA, et al. Acute Dialysis Quality Initiative w. 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. Crit Care 2004; 8:R204-212
27. Mehta RL, Kellum JA, Shah SV, et al. Acute kidney injury network: report of an initiative to improve outcomes in acute kidney injury. Crit Care 2007; 11:R31
28. KDIGO clinical practice guideline for acute kidney injury. Kidney International Supplements 2012; 2:1-141
29. Wlodzimirow K, Abu-Hanna A, Slabbekoorn M, et al. A comparison of RIFLE with and without urine output criteria for acute kidney injury in critically ill patients. Crit Care 2012; 16:R200
30. Panagiotou A, Garzotto F, Gramaticopolo S, et al. Continuous real-time urine output monitoring for early detection of acute kidney injury. Contrib Nephrol 2011; 171:194-200
31. Colpaert K, Hoste E, Van Hoecke S, et al. Implementation of a real-time electronic alert based on the RIFLE criteria for acute kidney injury in ICU patients. Acta Clin Belg Suppl 2007; 322-325
32. Colpaert K, Hoste EA, Steurbaut K, et al. Impact of real-time electronic alerting of acute kidney injury on therapeutic intervention and progression of RIFLE class. Crit Care Med 2012; 40:1164-1170; 1110.1097/CCM. 1160b1013e3182387a3182386b.
33. Goldstein SL, Chawla LS. Renal angina. Clin J Am Soc Nephrol 2010; 5:943-949
34. Mehran R, Aymong ED, Nikolsky E, et al. A simple risk score for prediction of contrast-induced nephropathy after percutaneous coronary intervention: development and initial validation. J Am Coll Cardiol 2004; 44:1393-1399 (Pubitemid 39303939)
35. Thakar CV, Arrigain S, Worley S, et al. A clinical score to predict acute renal failure after cardiac surgery. J Am Soc Nephrol 2005; 16:162-168 (Pubitemid 43073168)
36. Matheny ME, Miller RA, Ikizler TA, et al. Development of inpatient risk stratification models of acute kidney injury for use in electronic health records. Med Decis Making 2010; 30:639-650
37. Rind DM, Safran C, Phillips RS, et al. Effect of computer-based alerts on the treatment and outcomes of hospitalized patients. Arch Intern Med 1994; 154:1511-1517 (Pubitemid 24208577)
38. Kashani K, Hanson LN, Li M, Herasevich V. The utility of electronic screening for enrollment in clinical studies: a descriptive study. JASN Abstract Supplement 2011; 22:150A-151A.