Adequacy of hemodialysis in acute kidney injury: Real‐time monitoring of dialysate ultraviolet absorbance vs. blood‐based Kt/Vurea

2020 ◽  
Author(s):  
George Vasquez‐Rios ◽  
Frank Zhang ◽  
Mitchell G. Scott ◽  
Anitha Vijayan
Keyword(s):  
Acute Kidney Injury ◽  
Real Time ◽  
Kidney Injury ◽  
Real Time Monitoring ◽  
Ultraviolet Absorbance

Clearance and beyond: the complementary roles of GFR measurement and injury biomarkers in acute kidney injury (AKI)

2011 ◽  
Vol 301 (4) ◽  
pp. F697-F707 ◽  
Author(s):  
Zoltán H. Endre ◽  
John W. Pickering ◽  
Robert J. Walker
Keyword(s):  
Acute Kidney Injury ◽  
Serum Creatinine ◽  
Real Time ◽  
Renal Injury ◽  
Kidney Injury ◽  
Predictive Performance ◽  
Causal Pathways ◽  
Real Time Measurement ◽  
Diagnostic Potential ◽  
Baseline Information

Acute kidney injury (AKI) is a common and frequently fatal illness in critically ill patients. The reliance on daily measurements of serum creatinine as a surrogate of glomerular filtration rate (GFR) not only delays diagnosis and development of successful therapies but also hinders insight into the pathophysiology of human AKI. Measurement of GFR under non-steady-state conditions remains an elusive gold standard against which biomarkers of renal injury need to be judged. Approaches to the rapid (near real-time) measurement of GFR are explored. Even if real-time GFR was available, absent baseline information will always limit diagnosis of AKI based on GFR or serum creatinine to a detection of change. Biomarkers of renal cellular injury have provided new strategies to facilitate detection and early intervention in AKI. However, the diagnostic and predictive performance of urinary biomarkers of injury vary, depending on both the time after renal injury and on the preinjury GFR. Progress in understanding the role of each novel biomarker in the causal pathways of AKI promises to enhance their diagnostic potential. We predict that combining rapid measures of GFR with biomarkers of renal injury will yield substantive progress in the treatment of AKI.

Impact of real-time electronic alerting of acute kidney injury on therapeutic intervention and progression of RIFLE class*

2012 ◽  
Vol 40 (4) ◽  
pp. 1164-1170 ◽  
Author(s):  
Kirsten Colpaert ◽  
Eric A. Hoste ◽  
Kristof Steurbaut ◽  
Dominique Benoit ◽  
Sofie Van Hoecke ◽  
...  
Keyword(s):  
Acute Kidney Injury ◽  
Real Time ◽  
Therapeutic Intervention ◽  
Kidney Injury

Continuous Real-Time Urine Output Monitoring for Early Detection of Acute Kidney Injury

2011 ◽  
pp. 194-200 ◽  
Author(s):  
Anthi Panagiotou ◽  
Francesco Garzotto ◽  
Silvia Gramaticopolo ◽  
Pasquale Piccinni ◽  
Chiara Trentin ◽  
...  
Keyword(s):  
Acute Kidney Injury ◽  
Early Detection ◽  
Real Time ◽  
Urine Output ◽  
Kidney Injury ◽  
Output Monitoring

scholarly journals SP235STROKE VOLUME VARIATION: "A REAL TIME " BIOMARKER OF ACUTE KIDNEY INJURY DURING ABDOMINAL AORTIC ANEURYSM SURGERY

2017 ◽  
Vol 32 (suppl_3) ◽  
pp. iii184-iii184
Author(s):  
Paolo Lentini ◽  
Luca Zanoli ◽  
Antonio Granata ◽  
Roberto Dell'Aquila
Keyword(s):  
Acute Kidney Injury ◽  
Abdominal Aortic Aneurysm ◽  
Aortic Aneurysm ◽  
Real Time ◽  
Kidney Injury ◽  
Aneurysm Surgery ◽  
Volume Variation ◽  
Abdominal Aortic ◽  
Aortic Aneurysm Surgery

scholarly journals Scoping review exploring the impact of digital systems on processes and outcomes in the care management of acute kidney injury and progress towards establishing learning healthcare systems

2021 ◽  
Vol 28 (1) ◽  
pp. e100345
Author(s):  
Clair Ka Tze Chew ◽  
Helen Hogan ◽  
Yogini Jani
Keyword(s):  
Acute Kidney Injury ◽  
Real Time ◽  
Clinical Data ◽  
Early Recognition ◽  
Kidney Injury ◽  
Healthcare Systems ◽  
Digital Systems ◽  
Stakeholder Perspectives ◽  
Micro Level ◽  
The Impact

ObjectivesDigital systems have long been used to improve the quality and safety of care when managing acute kidney injury (AKI). The availability of digitised clinical data can also turn organisations and their networks into learning healthcare systems (LHSs) if used across all levels of health and care. This review explores the impact of digital systems i.e. on patients with AKI care, to gauge progress towards establishing LHSs and to identify existing gaps in the research.MethodsEmbase, PubMed, MEDLINE, Cochrane, Scopus and Web of Science databases were searched. Studies of real-time or near real-time digital AKI management systems which reported process and outcome measures were included.ResultsThematic analysis of 43 studies showed that most interventions used real-time serum creatinine levels to trigger responses to enable risk prediction, early recognition of AKI or harm prevention by individual clinicians (micro level) or specialist teams (meso level). Interventions at system (macro level) were rare. There was limited evidence of change in outcomes.DiscussionWhile the benefits of real-time digital clinical data at micro level for AKI management have been evident for some time, their application at meso and macro levels is emergent therefore limiting progress towards establishing LHSs. Lack of progress is due to digital maturity, system design, human factors and policy levers.ConclusionFuture approaches need to harness the potential of interoperability, data analytical advances and include multiple stakeholder perspectives to develop effective digital LHSs in order to gain benefits across the system.

Early identification of acute kidney injury in the ICU with real-time urine output monitoring: a clinical investigation

2021 ◽  
Vol 22 (1) ◽  
Author(s):  
Dafna Willner ◽  
Aliza Goldman ◽  
Hagar Azran ◽  
Tal Stern ◽  
Dvora Kirshenbom ◽  
...  
Keyword(s):  
Acute Kidney Injury ◽  
Real Time ◽  
Early Identification ◽  
Urine Output ◽  
Electronic Monitoring ◽  
Clinical Investigation ◽  
Medical Center ◽  
Kidney Injury ◽  
Icu Admission ◽  
Output Monitoring

Abstract Background KDIGO (Kidney Disease: Improving Global Outcomes) provides two sets of criteria to identify and classify acute kidney injury (AKI): serum creatinine (SCr) and urine output (UO). Inconsistencies in the application of KDIGO UO criteria, as well as collecting and classifying UO data, have prevented an accurate assessment of the role this easily available biomarker can play in the early identification of AKI. Study goal To assess and compare the performance of the two KDIGO criteria (SCr and UO) for identification of AKI in the intensive care unit (ICU) by comparing the standard SCr criteria to consistent, real-time, consecutive, electronic urine output measurements. Methods Ninety five catheterized patients in the General ICU (GICU) of Hadassah Medical Center, Israel, were connected to the RenalSense™ Clarity RMS™ device to automatically monitor UO electronically (UOelec). UOelec and SCr were recorded for 24–48 h and up to 1 week, respectively, after ICU admission. Results Real-time consecutive UO measurements identified significantly more AKI patients than SCr in the patient population, 57.9% (N = 55) versus 26.4% (N = 25), respectively (P < 0.0001). In 20 patients that had AKI according to both criteria, time to AKI identification was significantly earlier using the UOelec criteria as compared to the SCr criteria (P < 0.0001). Among this population, the median (interquartile range (IQR)) identification time of AKI UOelec was 12.75 (8.75, 26.25) hours from ICU admission versus 39.06 (25.8, 108.64) hours for AKI SCr. Conclusion Application of KDIGO criteria for AKI using continuous electronic monitoring of UO identifies more AKI patients, and identifies them earlier, than using the SCr criteria alone. This can enable the clinician to set protocol goals for earlier intervention for the prevention or treatment of AKI.

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