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

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.

scholarly journals Automated versus manual urine output monitoring in the intensive care unit

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Joni Minor ◽  
Ali Smith ◽  
Frederic Deutsch ◽  
John A. Kellum
Keyword(s):  
Intensive Care Unit ◽  
Acute Kidney Injury ◽  
Intensive Care ◽  
Urine Output ◽  
Kidney Injury ◽  
University Hospital ◽  
Intensive Care Patients ◽  
The Mean ◽  
Output Monitoring ◽  
Observation Period

AbstractAcute kidney injury (AKI) is defined by changes in serum creatinine and urine output (UO). Significant limitations exist regarding accurate ascertainment of urine output even within the intensive care unit. We sought to evaluate an automated urine output collections system and compare it to nursing measurements. We prospectively collected urine output using an electronic urine monitoring system and compared it to charted hourly UO in 44 patients after cardiac surgery at a single university hospital ICU. We calculated UO and oliguria rates and compared them to data from the sensor and from nursing charting. A total of 187 hourly UO measurements were obtained and on average, UO was reported 47 min late, with a median of 18 min, and a maximum of almost 6 h. Patients had a mean hourly UO of 76.3 ml over the observation period. Compared to manual measurements by study personnel, nurses significantly overestimated hourly UO by 19.9 ml (95% CI: 10.3; 29.5; p =  < 0.001). By contrast, the mean difference between the UO measured with the sensor and by study personnel was 2.29 ml (95% CI: − 6.7; 11.3), p = 0.61. Electronic UO monitoring is significantly more accurate than nurse-performed manual measurements in actual intensive care patients. Furthermore, timely ascertainment of UO is difficult to achieve with manual technique, resulting in important delays in detecting oliguria perhaps leading to missed cases of AKI.

scholarly journals Early Identification of Acute Kidney Injury in the Icu With Real-time Urine Output Monitoring: A Clinical Investigation

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

Abstract BackgroundThe inconsistencies in classifying AKI according to the KDIGO (Kidney Disease: Improving Global Outcomes) urine output (UO) criteria 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 early identification of AKI in the intensive care unit (ICU) by comparing the standard SCr criteria to real-time, consecutive, electronic urine output measurements. Methods95 catheterized patients in the GICU of Hadassah Medical Center, Israel were connected to The RenalSense™ Clarity RMS™ sensor kit to monitor UO electronically (UOelec). UOelec and SCr were recorded between 24-48 hours and up to one week, respectively, after ICU admission. ResultsReal-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 by the UOelec criteria as compared to the SCr criteria (P<0.0001). Among this population, the median (IQR) identification time of AKI UOelec was 12.75 (8.75, 26.25) hours from ICU admission and 39.06 (25.8, 108.64) hours for AKI SCr. ConclusionApplication 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 application can enable the clinician to set protocol goals for earlier intervention of the treatment of AKI.

Urine Output during Cardiopulmonary Bypass Predicts Acute Kidney Injury after Coronary Artery Bypass Grafting

2016 ◽  
Vol 19 (6) ◽  
pp. 289 ◽  
Author(s):  
Mehmet Yilmaz ◽  
Rezan Aksoy ◽  
Vildan Kilic Yilmaz ◽  
Canan Balci ◽  
Cagri Duzyol ◽  
...  
Keyword(s):  
Acute Kidney Injury ◽  
Cardiopulmonary Bypass ◽  
Coronary Artery ◽  
Coronary Artery Bypass Grafting ◽  
Coronary Artery Bypass ◽  
Urine Output ◽  
Artery Bypass ◽  
Kidney Injury ◽  
Urinary Output ◽  
Bypass Grafting

Objective: This study evaluated the relationship between the amount of urinary output during cardiopulmonary bypass and acute kidney injury in the postoperative period of coronary artery bypass grafting.Methods: Two hundred patients with normal preoperative serum creatinine levels, operated on with isolated CABG between 2012-2014 were investigated retrospectively. The RIFLE (Risk, injury, failure, loss of function, and end-stage renal disease) risk scores were calculated for each patient in the third postoperative day. Patients were distributed into two groups in relation to the presence of acute kidney injury or not and these two groups were compared.Results: The urinary output (mL/kg/hour) during cardiopulmonary bypass in the acute kidney injury negative group was significantly higher than in the acute kidney injury positive group (P = .022). In case of a urinary output value 3.70 and lower to predict acute kidney injury positivity, sensitivity was detected as 71.43%. Results of the analysis for urinary output predict positivity of acute kidney injury.Conclusion: We suggest that urine output during cardiopulmonary bypass is a significant criteria that could predict acute kidney injury following coronary artery bypass grafting with cardiopulmonary bypass. Attempts to increase the urine output during cardiopulmonary bypass could help to maintain the renal functions during and after surgery.

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