scholarly journals Urine microscopy as a biomarker of Acute Kidney Injury following cardiac surgery with cardiopulmonary bypass

2020 ◽  
Vol 42 (1) ◽  
pp. 18-23 ◽  
Author(s):  
João Carlos Goldani ◽  
José Antônio Poloni ◽  
Fabiano Klaus ◽  
Roger Kist ◽  
Larissa Sgaria Pacheco ◽  
...  

Abstract Introduction: Acute kidney injury (AKI) occurs in about 22% of the patients undergoing cardiac surgery and 2.3% requires renal replacement therapy (RRT). The current diagnostic criteria for AKI by increased serum creatinine levels have limitations and new biomarkers are being tested. Urine sediment may be considered a biomarker and it can help to differentiate pre-renal (functional) from renal (intrinsic) AKI. Aims: To investigate the microscopic urinalysis in the AKI diagnosis in patients undergoing cardiac surgery with cardiopulmonary bypass. Methods: One hundred and fourteen patients, mean age 62.3 years, 67.5 % male, with creatinine 0.91 mg/dL (SD 0.22) had a urine sample examined in the first 24 h after the surgery. We looked for renal tubular epithelial cells (RTEC) and granular casts (GC) and associated the results with AKI development as defined by KDIGO criteria. Results: Twenty three patients (20.17 %) developed AKI according to the serum creatinine criterion and 76 (66.67 %) by the urine output criterion. Four patients required RRT. Mortality was 3.51 %. The use of urine creatinine criterion to predict AKI showed a sensitivity of 34.78 % and specificity of 86.81 %, positive likelihood ratio of 2.64 and negative likelihood ratio of 0.75, AUC-ROC of 0.584 (95%CI: 0.445-0.723). For the urine output criterion sensitivity was 23.68 % and specificity 92.11 %, AUC-ROC was 0.573 (95%CI: 0.465-0.680). Conclusion: RTEC and GC in urine sample detected by microscopy is a highly specific biomarker for early AKI diagnosis after cardiac surgery.

2010 ◽  
Vol 26 (2) ◽  
pp. 509-515 ◽  
Author(s):  
E. Macedo ◽  
R. Malhotra ◽  
R. Claure-Del Granado ◽  
P. Fedullo ◽  
R. L. Mehta

Medicine ◽  
2016 ◽  
Vol 95 (22) ◽  
pp. e3757 ◽  
Author(s):  
Young Song ◽  
Dong Wook Kim ◽  
Young Lan Kwak ◽  
Beom Seok Kim ◽  
Hyung Min Joo ◽  
...  

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Sahar Alkhairy ◽  
Leo A. Celi ◽  
Mengling Feng ◽  
Andrew J. Zimolzak

AbstractAcute kidney injury (AKI) is common in the intensive care unit, where it is associated with increased mortality. AKI is often defined using creatinine and urine output criteria. The creatinine-based definition is more reliable but less expedient, whereas the urine output based definition is rapid but less reliable. Our goal is to examine the urine output criterion and augment it with physiological features for better agreement with creatinine-based definitions of AKI. The objectives are threefold: (1) to characterize the baseline agreement of urine output and creatinine definitions of AKI; (2) to refine the urine output criteria to identify the thresholds that best agree with the creatinine-based definition; and (3) to build generalized estimating equation (GEE) and generalized linear mixed-effects (GLME) models with static and time-varying features to improve the accuracy of a near-real-time marker for AKI. We performed a retrospective observational study using data from two independent critical care databases, MIMIC-III and eICU, for critically ill patients who developed AKI in intensive care units. We found that the conventional urine output criterion (6 hr, 0.5 ml/kg/h) has specificity and sensitivity of 0.49 and 0.54 for MIMIC-III database; and specificity and sensitivity of 0.38 and 0.56 for eICU. Secondly, urine output thresholds of 12 hours and 0.6 ml/kg/h have specificity and sensitivity of 0.58 and 0.48 for MIMIC-III; and urine output thresholds of 10 hours and 0.6 ml/kg/h have specificity and sensitivity of 0.49 and 0.48 for eICU. Thirdly, the GEE model of four hours duration augmented with static and time-varying features can achieve a specificity and sensitivity of 0.66 and 0.61 for MIMIC-III; and specificity and sensitivity of 0.66 and 0.64 for eICU. The GLME model of four hours duration augmented with static and time-varying features can achieve a specificity and sensitivity of 0.71 and 0.55 for MIMIC-III; and specificity and sensitivity of 0.66 and 0.60 for eICU. The GEE model has greater performance than the GLME model, however, the GLME model is more reflective of the variables as fixed effects or random effects. The significant improvement in performance, relative to current definitions, when augmenting with patient features, suggest the need of incorporating these features when detecting disease onset and modeling at window-level rather than patient-level.


2011 ◽  
Vol 27 (1) ◽  
pp. 161-165 ◽  
Author(s):  
S. S. Han ◽  
K. J. Kang ◽  
S. J. Kwon ◽  
S. J. Wang ◽  
S. H. Shin ◽  
...  

2021 ◽  
Vol 18 (6) ◽  
pp. 38-47
Author(s):  
Yu. S. Polushin ◽  
D. V. Sokolov ◽  
N. S. Molchan ◽  
R. V. Аkmalova ◽  
O. V. Galkina

Changes in classification criteria and active introduction of biomarkers of acute kidney injury (KDIGO, 2012) are changing approaches to diagnosis and treatment of postoperative renal dysfunction including cardiac surgery patients operated with cardiopulmonary bypass (CPB). The objective: to compare the detection rate of AKI after surgery with CPB with the use of biomarkers and kidney disease improving global outcomes criteria, as well as to evaluate the cause and localization of structural changes of the nephron.Subjects and Methods. A monocenter observational study among elective cardiac surgery patients (n = 97) was conducted. Inclusion criteria: age over 18 years, duration of surgery (coronary bypass surgery, prosthetic heart valves) from 90 to 180 minutes, no signs of end stage kidney disease. AKI was diagnosed based on changes in serum creatinine and biomarkers (NGAL, IgG, albumin in urine). The studied parameters were recorded 15 minutes after the start and end of anesthesia, as well as 24 and 48 hours after surgery. Retrospectively, the group was divided into three subgroups: 1) patients without AKI after surgery; 2) patients in whom signs of AKI were detected after 24 hours but regressed by the 48th hour; 3) patients in whom AKI persisted during all 48 hours of follow-up.Results. 24 hours after surgery, AKI based on KDIGO criteria was recorded in 56.3% of patients. Using biomarkers, signs of tubular damage (NGAL) at the end of anesthesia were detected in 95.9% of patients; after 24 hours, they were registered in 73.2% of cases. In a subgroup where AKI persisted for more than 24 hours, glomeruli were damaged in addition to tubules which was manifested not only by selective but also by non-selective proteinuria. The duration of CPB, hemodilution (Hb < 90 g/l), the release of free hemoglobin in the blood (> 1.5 mg/l) at low (< 1 g/l) values of haptoglobin were significantly associated with AKI development.Conclusion. The KDIGO criteria do not allow detecting a subclinical form of renal dysfunction which may occur in about 40% of patients after surgery with CPB. AKI can be caused by damage to both the tubular part of the nephron and glomeruli in cases of prolonged CPB with the development of hemolysis, the release of free hemoglobin in the blood, and persisting anemia at the end of the surgery. The NGAL assessment makes it possible to detect subclinical kidney injury in the absence of elevated serum creatinine levels.


2016 ◽  
Vol 19 (6) ◽  
pp. 289 ◽  
Author(s):  
Mehmet Yilmaz ◽  
Rezan Aksoy ◽  
Vildan Kilic Yilmaz ◽  
Canan Balci ◽  
Cagri Duzyol ◽  
...  

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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