• Users Online: 37
  • Home
  • Print this page
  • Email this page
Home About us Editorial board Ahead of print Current issue Search Archives Submit article Instructions Subscribe Contacts Login 


 
 Table of Contents  
ORIGINAL ARTICLE
Year : 2018  |  Volume : 18  |  Issue : 3  |  Page : 86-95

The role of furosemide stress test in the prediction of severity and outcome of sepsis-induced acute kidney injury


1 Department of Nephrology, Alexandria University Hospital, Alexandria, Egypt
2 Department of Critical Care, Alexandria University Hospital, Alexandria, Egypt

Date of Submission15-May-2018
Date of Acceptance24-Jun-2018
Date of Web Publication09-Nov-2018

Correspondence Address:
Ahmed M Abd Elhalim Elbasha
Iziz Street, Moharam Bik, Alexandria, 21515
Egypt
Login to access the Email id

Source of Support: None, Conflict of Interest: None


DOI: 10.4103/jesnt.jesnt_13_18

Rights and Permissions
  Abstract 


Introduction Acute kidney injury (AKI) is a common complication of sepsis in ICU patients. No test has been shown to definitively predict its occurrence and progression to more severe stages. The aim of the study was to investigate the ability of furosemide stress test (FST) to predict the development and progression of AKI in critically ill patients, and to compare it to the level of serum cystatin C.
Patients and methods We studied 60 patients who were subdivided into four groups: each group included 15 patients who had normal renal functions, AKI stages 1, 2, and 3, respectively. Clinical, laboratory, and therapeutic data were collected. Serum cystatin C levels were assessed by the enzyme-linked immunosorbent assay technique and FST (at a dose of 1.0 or 1.5 mg/kg according to previous furosemide exposure) was performed for each patient with assessment of their urine output during the following 2 h.
Results In our study, we compared the ability of FST to predict the progression of AKI in each stage. The sensitivity of FST to predict the outcome of AKI was 89.29% and its specificity was 93.75%, while the sensitivity of serum cystatin C to predict the outcome was 82.14% and its specificity was 31.25% with area under the curve=0.742.
Conclusions The FST in patients with early AKI serves as a cheap, easily available tool to assess tubular kidney function with prognostic capacity to assess the occurrence and the progression of AKI in septic ICU patients.

Keywords: acute kidney injury, cystatin C, furosemide stress test, sepsis


How to cite this article:
Elsaegh HK, Naga YS, Elsayed HE, Elbasha AM. The role of furosemide stress test in the prediction of severity and outcome of sepsis-induced acute kidney injury. J Egypt Soc Nephrol Transplant 2018;18:86-95

How to cite this URL:
Elsaegh HK, Naga YS, Elsayed HE, Elbasha AM. The role of furosemide stress test in the prediction of severity and outcome of sepsis-induced acute kidney injury. J Egypt Soc Nephrol Transplant [serial online] 2018 [cited 2018 Dec 11];18:86-95. Available from: http://www.jesnt.eg.net/text.asp?2018/18/3/86/245124




  Introduction Top


Acute kidney injury (AKI) is a syndrome characterized by sudden disruption in renal function of regulating fluid and electrolyte compositions of the body and excreting waste products of metabolism. The incidence of AKI in the ICU patients ranges from 20 to 50% [1]. AKI represents an important risk factor for morbidity and mortality in the ICU and can be associated with a mortality greater than 50% [2],[3].

Sepsis is a common complication in ICU, which leads to multiorgan dysfunction and the kidney is one of the organs considerably afflicted. AKI occurs in about 19% of patients with moderate sepsis, 23% with severe sepsis, and 51% in patients suffering from septic shock [4]. Sepsis is the most common cause of AKI in ICU patients, and sepsis plays a role in 40–50% of cases. Importantly, the concurrence of AKI and sepsis increases the risk of in-hospital mortality by sixfold to eightfold [5]. Sepsis is defined as a ‘life-threatening organ dysfunction caused by a dysregulated host response to infection’ [6]. Organ dysfunction was characterized by an acute increase of at least two points in the Sequential (Sepsis-related) Organ Failure Assessment (SOFA) score [7],[8].

Glomerular filtration rate (GFR) is considered as the best measure of renal function. Serum creatinine level and urine output are the most usual representatives for GFR to diagnose AKI. Although the definition and staging of AKI are still based on serum creatinine, it is considered a late marker for renal function assessment. Before creatinine rises, about 50% of kidney function is lost. Creatinine does not describe renal parenchymal cell injury and it is just a functional marker. In addition, it is affected by age, sex, race, diet, fluid status, and muscle mass [9],[10]. New renal biomarkers differ in their function, in their source, in their distribution, and in the time of their release after kidney injury [11]. Biomarkers of AKI include the following: cystatin C, neutrophil gelatinase-associated lipocalin (NGAL), kidney injury molecule 1, interleukin-18 (IL-18), liver-type fatty acid-binding protein, tissue inhibitor of metalloproteinases-2, insulin-like growth factor-binding protein 7, calprotectin, urinary angiotensinogen, and urinary microRNA [12].

The furosemide stress test (FST) is a provocative test used to distinguish patients with AKI who are going to progress to higher stages of AKI and possibly dialysis from those who will have a less severe course. This test depends on demonstration of the 2-h urine output − at a cutoff of 200 cm3 at 2 h − after a standardized high-dose FST (1 mg/kg of furosemide in naive patients or 1.5 mg/kg in those with previous exposure) in clinically euvolemic critically ill patients with sepsis to identify severity and predict progression of AKI [13].

The aim of this work was to assess the performance of the FST in the prediction of the severity and outcome of AKI and to compare it to cystatin C in septic ICU patients.


  Patients and methods Top


The study patients were selected from the ICUs of the Alexandria Main University Hospital. Informed consent was taken from patients and All drugs used in the research are approved by the Egyptian Ministry of Health. All patients fulfilled the criteria of sepsis on admission to the ICU [14]. The presence and the stage of AKI were evaluated on admission to the ICU using the KDIGO classification [15].

Patients were categorized into four groups: group I included 15 patients with normal renal functions, while groups II, III, and IV included 15 patients in each group with AKI stages 1, 2, and 3, respectively, diagnosed by serum creatinine. Patients with septic shock at the time of admission, diabetes mellitus, malignancy, liver cirrhosis, previous history of chronic kidney disease, and patients receiving immunosuppressive drugs were excluded from this study.

All patients were subjected to detailed history taking, clinical evaluation, assessment of the degree of sepsis by SOFA and qSOFA scores, laboratory investigations including: complete blood picture, blood urea, serum creatinine, serum cystatin C, estimated GFR estimated by chronic kidney disease epidemiology collaboration (CKD-EPI) cystatin C [16], C-reactive protein, total and direct bilirubin, and FST.

FST was done by administration of 1 mg/kg of furosemide i.v. or 1.5 mg/kg if the patient received furosemide within the preceding 7 days followed by observation of the urinary output in the first 2 h after the administration of furosemide. The volume status of the patients was first corrected and it was only performed on euvolemic or hypervolemic patients.

Statistical analysis [17]

Data were fed into the computer and analyzed using the IBM SPSS (version 21.0; SPSS Inc., Chicago, Illinois, USA) [18]. Qualitative data were described using number and percent. Quantitative data were described using range (minimum and maximum), mean, SD, and median. The comparison between different groups regarding categorical variables was done using the χ2 test. When more than 20% of the cells have an expected count of less than five, correction for χ2 was conducted using the Monte Carlo correction. The distributions of quantitative variables were tested for normality using the Kolmogorov–Smirnov test and Shapiro–Wilk test. Parametric tests were conducted in normally distributed data, while nonparametric tests were conducted in abnormally distributed data. For normally distributed data, the comparison between more than two independent populations was performed using the F test (analysis of variance) and the post-hoc test (least significant difference). Correlations between two quantitative variables were assessed using the Pearson coefficient. For abnormally distributed data, comparison between more than two independent populations was done using the Kruskal–Wallis test and the pairwise comparison was done using the Mann–Whitney test. Significance of the obtained results was judged at the 5% level. To calculate the sensitivity and specificity for serum cystatin C concentrations at normal cutoff values, conventional receiver-operating characteristic curves were generated, and an area under the curve (AUC) was calculated to ascertain the quality of cystatin C as a biomarker.


  Results Top


We assessed a total of 60 patients, who were divided into four groups with 15 patients in each group. The demographic, clinical, and laboratory characteristics of the different groups are summarized in [Table 1] and [Table 2].
Table 1 Comparison between the studied groups according to laboratory investigations

Click here to view
Table 2 Comparison between the studied groups according to FST

Click here to view


Values are expressed as the mean±SD and n (%); Glasgow coma scale; central venous pressure; hemoglobin; platelets; white blood cells; C-reactive protein.

As regards the response of the patients to FST it was well-tolerated with no adverse effects. In group I, seven (46.7%) patients responded to FST by less than 200 ml/2 h, while eight (53.3%) patients responded to FST by more than 200 ml/2 h. Also in group II, seven (46.7%) patients responded to FST by less than 200 ml/2 h, while eight (53.3%) patients responded to FST by more than 200 ml/2 h. In group III, two (13.3%) patients responded to FST by less than 200 ml/2 h, while 13 (86.7%) patients responded to FST by more than 200 ml/2 h. In group IV, 11 (73.3%) patients responded to FST by less than 200 ml/2 h, while four (26.7%) patients responded to FST by more than 200 ml/2 h. There was a statistically significant difference in response to FST between the four groups (P=0.012) ([Table 3] and [Figure 1]).
Table 3 Relation between FST and outcome in each group and in all AKI patients

Click here to view
Figure 1 Comparison between the studied groups according to FST. FST, furosemide stress test.

Click here to view


Serum cystatin level was estimated in patients just before furosemide administration. In AKI patients, the mean value of cystatin C in patients with less than 200 ml urine after FST was 4.27±1.69 mg/l, while it was 2.34±1.15 mg/l in patients with more than 200 ml urine after FST with a statistically significant difference between the two groups (P<0.001) ([Figure 2]).
Figure 2 Relation between FST and cystatin in each group and in all AKI patients. AKI, acute kidney injury; FST, furosemide stress test.

Click here to view


We followed the course of disease in each group of patients. In group I, there were eight (53.3%) patients who remained with normal renal function (nonprogressors), while seven (46.7%) patients progressed to AKI. In group II, eight (53.3%) patients were nonprogressors and seven (46.7%) patients progressed to higher stages of AKI. In group III, 13 (86.7%) patients were nonprogressors and two (13.3%) patients progressed to higher stages of AKI, while in group IV, three (20%) patients were nonprogressors and 12 (80%) patients progressed to needing hemodialysis ([Figure 3]).
Figure 3 Comparison between the studied groups according to the outcome.

Click here to view


Of the total study sample, 53.3% (32 patients) were nonprogressors, whose creatinine remained at the same level or even decreased, while 46.7% (28 patients) had a rising serum creatinine level and progressed to higher KDIGO stages or needed renal replacement therapy (RRT). Twelve (20% of the total patients) patients required RRT ([Figure 4]).
Figure 4 Disease progression.

Click here to view


We assessed the value of serum cystatin level in predicting the progression of AKI and we found that the mean value of serum cystatin in nonprogressor patients was lower than its mean value in patients who progressed to higher AKI stages in groups I, II, and IV ([Table 4]).
Table 4 Relation between FST and outcome in total sample (n=60)

Click here to view


Serum cystatin C level had a value in predicting disease progression with a sensitivity of 82.14% and a specificity of 31.25% (AUC=0.742, P=0.001) at a cutoff level of 1.2 mg/l ([Figure 5] and [Table 5]).
Figure 5 ROC curve for serum cystatin C to predict disease progression. ROC, receiver-operating characteristic.

Click here to view
Table 5 Demographic and clinical data of the studied groups

Click here to view


We compared the urine output in response to FST between those patients that progressed and did not progress to higher AKI stages. Progressors had a worse urine output response (10.7% responded to FST with >200 ml urine output) compared with nonprogressors (93.8% responded to FST with >200 ml urine output) (P<0.001) ([Table 6] and [Figure 6]).
Table 6 Relation between serum cystatin c and outcome in total sample (n=60)

Click here to view
Figure 6 Relation between FST and outcome in each group and in all AKI patients. AKI, acute kidney injury; FST, furosemide stress test.

Click here to view


We also assessed the sensitivity and specificity of various 2-h urine volumes to predict the outcomes. The 2-h urine output of 200 ml or less had the best sensitivity (89.29%) and specificity (93.75%) to predict the outcome of AKI ([Table 7] and Figure 7).
Table 7 Agreement (sensitivity, specificity) for serum cystatin c to predict progression of AKI

Click here to view



  Discussion Top


AKI is a common complication which occurs with sepsis in ICU patients as a part of multiorgan failure and is significantly associated with high mortality rates. The early detection of AKI and the prediction of its progression will have prognostic and therapeutic implications. In addition, with the development of new therapeutic modalities for AKI, an accurate prediction of AKI progression and severity may help to define high-risk patients and those most likely to benefit from such a treatment [19].

Several AKI biomarkers, including serum cystatin C, tissue inhibitor of metalloproteinases-2, insulin-like growth factor-binding protein 7, IL-18, and plasma NGAL, have been demonstrated to predict AKI progression. These biomarkers were expected to help in the early detection of patients at risk of AKI in various clinical settings, but most of them were insensitive and nonspecific [20]. Recently, FST was suggested to be a significant predictor of progression to AKI.

The mean value of serum cystatin C was higher in patients who progressed to higher AKI stages than its level in nonprogressors in groups I, II, and IV (P=0.021, 0.001, and 0.014, respectively).

The mean value of serum cystatin C (4.27±1.69 mg/l) in patients with less than 200 ml urine after FST was higher than the mean value of serum cystatin C (2.34±1.15 mg/l) in patients with more than 200 ml urine after FST with a statistically significant difference between two groups (P<0.001). So, higher levels of cystatin C were associated with poor response to FST.

Our data demonstrated that serum cystatin C had a value for the prediction of AKI and its progression with a sensitivity of 82.14% and with a specificity of 31.25% (AUC=0.742 and P=0.001), which coincide with the findings of Yong et al. [21]. Their study included 982 patients and showed that cystatin C had high predictive power for all-cause AKI and the AUC was 0.89.

Nakhjavan-Shahraki et al. [22] reported a systemic review of a total of 24 articles, which included 1302 non-AKI children and 645 AKI cases. Their results showed that AUC of cystatin C in the prediction of AKI were 0.83 [95% confidence interval (CI), 0.80–0.86). The best sensitivity (value = 0.85; 95% CI, 0.78–0.90) and specificity (value = 0.61; 95% CI, 0.48–0.73) were observed in the cutoff points between 0.4 and 1.0 mg/l.

Similar to our study, Safdar et al. [23] published a prospective study that was undertaken in the pediatric ICU at King Abdulaziz University Hospital and studied the role of serum cystatin in predicting the occurrence and progression of AKI. The AUC for serum cystatin C was 0.825 (95% CI, 0.694–0.956), with a sensitivity of 94% but a low specificity of 57% at a cutoff of 0.645 mg/l.

Our study also reported that serum cystatin C had low specificity (31.25%) in predicting the occurrence and progression of AKI. The cause may be that serum cystatin C is affected by factors other than GFR as was reported by Stevens et al. [24]. Their study demonstrated that high serum cystatin C was associated with high white blood cell count, hypoalbuminemia, and all markers of sepsis, which were elevated in our cohort of septic patients. In addition, serum cystatin C level is affected by age, sex, race, muscle mass, thyroid functions [25], steroid treatment [26], growth hormone [27], and insulin [28].

The present study aimed to assess the performance of the FST in the diagnosis and prediction of the severity and outcome of AKI and to compare it to serum cystatin C in septic ICU patients. In this study, we have demonstrated that the FST is a practical and well-tolerated tool to be used in critically ill patients with AKI. Some complications may occur after furosemide administration like vasodilation and hypotension, but we did not observe any of these complications during our study. We took careful measures to decrease these potential adverse effects by choosing well-resuscitated patients and when appropriate isovolemic replacement of urine output with isotonic fluids was performed. This explains why we did not observe any adverse events.

We assessed the urine output in response to furosemide within the first 2 h after its administration. We compared the urine output in response to FST between those patients that progressed and did not progress to AKI higher stages. Progressors had a lower UOP response (10.7% responded to FST with >200 ml UOP) compared with nonprogressors (93.8% responded to FST with more than 200 ml UOP) (P<0.001). FST had 89.29% sensitivity and 93.75% specificity in the prediction of AKI outcome.

These data coincide with the findings of Chawla et al. [29]. They created and validated a standardized approach to using furosemide to assess progression to more advanced AKI stages. They gave AKI patients 1 mg/kg of furosemide i.v. or 1.5 mg/kg if the patient was with prior furosemide exposure in the previous 7 days. At a cutoff of 200 ml at 2 h, the sensitivity and specificity of the FST is 87.1 and 84.1%, respectively [29].

Koyner et al. [30] compared FST to a group of renal biomarkers for predicting the progression of AKI. The primary outcome measure was progression to stage 3 AKI. In this study, an extensive list of biomarkers including: urine NGAL, urine IL-18, urine kidney injury molecule 1, and plasma NGAL was compared with the previously described FST results. None of these biomarkers significantly improved on the FST for predicting progression to stage 3 AKI, the need for RRT, or inpatient mortality. In the subset of patients with elevated AKI biomarkers, the performance of FST further improved the prediction of outcome (AUC=0.90) [30]. In addition, the study did not find any statistically improved risk prediction when a biomarker was added to FST results, but when FST was combined with other biomarkers of AKI there was an improvement in risk prediction for all outcomes.

Although FST was recently reintroduced by Chawla and colleagues, the role of furosemide in AKI assessment has been raised before. Baek et al. [31] assessed 15 patients who did not have AKI at the time of admission, subjected them to a FST, and then evaluated the patients’ free water clearance (CH2O). They found that CH2O is near zero and a poor response to furosemide signaled that ‘acute renal failure was imminent.’

Van der Voort et al. [32], studied 25 patients that subsequently developed AKI and found they had lower urine output 2 h following administration of furosemide compared with 52 patients that did not develop AKI. Besides their study to predict the occurrence of AKI based on the renal response to FST, this study used to predict successful recovery of renal function after continuous RRT in critically ill patients recovering from AKI. They demonstrated good performance of the FST with an AUC of 0.84 for assessing renal recovery after AKI and continuous RRT. This serves as a proof of concept that the FST not only has a role in predicting the development of AKI but also a role in predicting its recovery.

Recently Matsuura et al. [33] evaluated FST in predicting severe AKI. This study included 95 adult critically ill patients in the medical–surgical mixed ICU at the University of Tokyo Hospital. The aim of this study was not only to evaluate FST, but also to evaluate the response to different doses of furosemide and to define the role of combining FST and plasma NGAL for the prediction of development of severe AKI. The receiver-operating curve analysis revealed that the AUC values of FST and plasma NGAL were 0.87 (0.73–0.94) and 0.80 (0.67–0.88) for AKI progression, respectively. In addition, FST was associated with an AUC of 0.84 (0.67–0.94) for AKI progression in patients with high NGAL levels more than 142 ng/ml. This suggested that FST revealed favorable efficacy for predicting AKI progression even in patients with high plasma NGAL levels and that a combination of FST and other biomarkers like plasma NGAL can stratify the risk of AKI progression in a clinical setting.

We were the first study to compare the performance of FST to serum cystatin C in predicting the occurrence and progression of septic AKI and in both studies [30],[33], FST performed better than other biomarkers. Our data demonstrate that urine output in the first 2 h after FST outperforms the level of serum cystatin C for the prediction of AKI progression and future requirement of RRT. FST had 89.29% sensitivity and 93.75% specificity in the prediction of AKI outcome, while serum cystatin C had 82.14% sensitivity and 31.25% specificity in the prediction of AKI outcome (AUC=0.742).

Furosemide is a loop diuretic which has properties that allow it to be used as a functional tool. Furosemide is not effectively filtered by the glomerulus in contrast to other drugs cleared by the kidney. Besides its ability to measure the tubule’s secretion capacity, FST was also used to assess the integration of renal function. Diuretic action of furosemide starts by its active secretion into the proximal lumen, and the functions of the thick ascending limb, luminal patency, and collecting duct must all be intact to increase urine output [34]. Once in the tubular lumen, furosemide blocks luminal cation–chloride cotransport throughout the thick ascending limb of Henle, thereby preventing sodium reabsorption and resulting in natriuresis and increased urine flow. Because furosemide is only eliminated by exclusive secretion in the proximal tubule and not filtered by the glomerulus, the measurement of the amount of furosemide secreted in the urine after an intravenous administration might allow the separation of urine output response from the proximal tubular function [35]. Based on these properties, furosemide-induced increases in urine output represent a good tool to assess the integrity of the renal tubular function in AKI.

In addition to its role in AKI, recent studies are focusing on the role of FST to predict the progression of CKD to end-stage renal disease, which would help to prepare patients for dialysis as early as possible. Improved prognostic utilities can also avoid the unnecessary placement of vascular access and arteriovenous fistula. This technique could also be applicable to patients with kidney transplants as a way to predict delayed graft function and long-term allograft survival [36].

In summary, in patients with sepsis with or without early AKI stable enough to undergo FST, 2-h urine output serves as a promising tool for the assessment of occurrence and progression of AKI. The FST is a feasible, cheap, and well-tolerated tool in critically ill patients with sepsis to identify those patients who will progress to advanced AKI stages and the need of RRT. FST was superior to serum cystatin C as a functional biomarker of AKI. Improving risk prediction in those with early AKI is likely to alter clinical decision-making and patient care, as well as facilitate enrollment into future therapeutic AKI trials.

Limitations of the study

Our study had some limitations included; first, the small number of patients. Second, we did not compare FST to well-established biomarkers. Third, we did not combine its prognostic ability with other biomarkers. Fourth, we only assessed the progression but not other outcomes like mortality or need for RRT. Finally, we only included patients with septic AKI, so our results cannot be generalized to other cases of AKI including cases with resistance to diuretics, for example, patients with decompensated heart failure or nephrotic syndrome.


  Conclusion Top


In our study FST was superior to serum cystatin C as a functional biomarker of AKI.

Financial support and sponsorship

Nil.

Conflicts of interest

There are no conflicts of interest.



 
  References Top

1.
Mandelbaum T, Scott DJ, Lee J, Mark RG, Malhotra A, Waikar SS et al. Outcome of critically ill patients with acute kidney injury using the Acute Kidney Injury Network criteria. Crit Care Med 2011; 39:2659–2664.  Back to cited text no. 1
    
2.
Bellomo R, Ronco C, Kellum JA, Mehta RL, Palevsky P. Acute Dialysis Quality Initiative workgroup. Acute renal failure - definition, outcome measures, animal models, fluid therapy and information technology ne eds the Second International Consensus Conference of the Acute Dialysis Quality Initiative (ADQI) Group. Crit Care 2004; 8:R204–R212.  Back to cited text no. 2
    
3.
Mehta RL, Kellum JA, Shah SV, Molitoris BA, Ronco C, Warnock DG, Levin A, Acute Kidney Injury Network. Acute Kidney Injury Network: report of an initiative to improve outcomes in acute kidney injury. Crit Care 2007; 11:R31.  Back to cited text no. 3
    
4.
Rangel-Frausto MS, Pittet D, Costigan M, Hwang T, Davis CS, Wenzel RP. The natural history of the systemic inflammatory response syndrome (SIRS): a prospective study. JAMA 1995; 273:117–123.  Back to cited text no. 4
    
5.
Reddy BMP. Acute renal failure. In: Hall JB, Schmidt GA editor. Principles of critical care 3rd ed. New York: McGraw-Hill 2005;1139–1160  Back to cited text no. 5
    
6.
Singer M, Deutschman CS, Seymour CW, Shankar-Hari M, Annane D, Bauer M et al. The Third International Consensus Definitions for Sepsis and Septic Shock (Sepsis-3). JAMA 2016; 315:801–810.  Back to cited text no. 6
    
7.
Seymour CW, Liu VX, Iwashyna TJ, Brunkhorst FM, Rea TD, Scherag A et al. Assessment of clinical criteria for sepsis: for the Third International Consensus Definitions for Sepsis and Septic Shock (Sepsis-3). JAMA 2016; 315:762–774.  Back to cited text no. 7
    
8.
Vincent JL, Martin GS, Levy MM. qSOFA does not replace SIRS in the definition of sepsis. Crit Care 2016; 20:210.  Back to cited text no. 8
    
9.
Bennett MR, Devarajan P. Characteristics of an ideal biomarker of kidney diseases. In: Edelstein CL editor. Biomarkers of kidney disease. 2nd ed. Colorado, USA: Academic Press; 2017. 1–20.  Back to cited text no. 9
    
10.
Parikh CR, Koyner JL. Biomarkers in acute and chronic kidney diseases. In: Skorecki K, Chertow GM, Marsden PA, Taal MW, Yu ASL editors. Brenner & Rector’s the kidney 10th ed. Philadelphia: Elsevier Inc.; 2016. 1:926.  Back to cited text no. 10
    
11.
Charlton JR, Portilla D, Okusa MD. A basic science view of acute kidney injury biomarkers. Nephrol Dial Transplant 2014; 29:1301–1311.  Back to cited text no. 11
    
12.
Kashani K, Cheungpasitporn W, Ronco C. Biomarkers of acute kidney injury: the pathway from discovery to clinical adoption. Clin Chem Lab Med 2017; 55:1074–1089.  Back to cited text no. 12
    
13.
Koyner JL, Davison DL, Brasha-Mitchell E, Chalikonda DM, Arthur JM, Shaw AD et al. Furosemide stress test and biomarkers for the prediction of AKI severity. J Am Soc Nephrol 2015; 26:2023–2031.  Back to cited text no. 13
    
14.
Williams JM, Greenslade JH, McKenzie JV, Chu K, Brown AFT, Lipman J. et al... SIRS, qSOFA and organ dysfunction: insights from a prospective database of emergency department patients with infection. Chest 2017; 151:586–596.  Back to cited text no. 14
    
15.
Kidney Disease: Improving Global Outcomes (KDIGO) Acute Kidney Injury Work Group. KDIGO clinical practice guideline for acute kidney injury. Kidney Int 2012; 2 (Suppl):1–138.  Back to cited text no. 15
    
16.
Inker LA, Schmid CH, Tighiouart H et al. Estimating glomerular filtration rate from serum creatinine and cystatin C. N Engl J Med 2012; 367:20–29.  Back to cited text no. 16
    
17.
Kotz S, Balakrishnan N, Read CB, Vidakovic B. Encyclopedia of statistical sciences 2nd ed. Hoboken, NJ: Wiley-Interscience 2006.  Back to cited text no. 17
    
18.
Kirkpatrick LA, Feeney BC. A simple guide to IBM SPSS statistics for version 21.0, Student In: Belmont CS, editor. Wadsworth: Cengage Learning; 2015. 1–25.  Back to cited text no. 18
    
19.
Russell JA, Singer J, Bernard GR, Wheeler A, Fulkerson W, Hudson L et al. Changing pattern of organ dysfunction in early human sepsis is related to mortality. Crit Care Med 2000; 28:3405–3411.  Back to cited text no. 19
    
20.
Arthur JM, Hill EG, Alge JL, Lewis EC, Neely BA, Janech MG et al. Evaluation of 32 urine biomarkers to predict the progression of acute kidney injury after cardiac surgery. Kidney Int 2014; 85:431–438.  Back to cited text no. 20
    
21.
Yong Z, Pei X, Zhu B, Yuan H, Zhao W. Predictive value of serum cystatin C for acute kidney injury in adults: a meta-analysis of prospective cohort trials. Sci Rep 2017; 7:410–412.  Back to cited text no. 21
    
22.
Nakhjavan-Shahraki B, Mahmoud Y, Neamatollah A, Masoud B, Fatemeh A, Behnaz B et al. Accuracy of cystatin C in prediction of acute kidney injury in children; serum or urine levels: which one works better? a systematic review and meta-analysis. BMC Nephrol 2017; 18:120.  Back to cited text no. 22
    
23.
Safdar OY, Shalaby M, Khathlan N, Elattal B, Bin Joubah M, Bukahri E et al. Serum cystatin is a useful marker for the diagnosis of acute kidney injury in critically ill children: prospective cohort study. BMC Nephrol 2016; 17 (1):130.  Back to cited text no. 23
    
24.
Stevens LA, Schmid CH, Greene T, Li L, Beck GJ, Joffe MM et al. Factors other than GFR affecting serum cystatin C levels. Kidney Int 2009; 75:652–660.  Back to cited text no. 24
    
25.
Ye Y, Gai X, Xie H, Jiao L, Zhang S. Impact of thyroid function on serum cystatin C and estimated glomerular filtration rate: a cross-sectional study. Endocr Pract 2013; 19:397–403.  Back to cited text no. 25
    
26.
Yamawaki C, Takahashi M, Takara K, Kume M, Hirai M, Yasui H et al. Effect of dexamethasone on extracellular secretion of cystatin C in cancer cell lines. Biomed Rep 2013; 1:115–118.  Back to cited text no. 26
    
27.
Sze L, Bernays RL, Zwimpfer C, Wiesli P, Brändle M, Schmid C. Impact of growth hormone on cystatin C. Nephron Extra 2013; 3:118–124.  Back to cited text no. 27
    
28.
Yokoyama H, Inoue T, Node K. Effect of insulin-unstimulated diabetic therapy with miglitol on serum cystatin C level and its clinical significance. Diabetes Res Clin Pract 2009; 83:77–82.  Back to cited text no. 28
    
29.
Chawla LS, Davison DL, Brasha-Mitchell E, Koyner JL, Arthur JM, Shaw AD et al. Development and standardization of a furosemide stress test to predict the severity of acute kidney injury. Crit Care. 2013; 17:R207.  Back to cited text no. 29
    
30.
Koyner JL, Davison DL, Brasha-Mitchell E, Chalikonda DM, Arthur JM, Shaw AD et al. Furosemide stress test and biomarkers for the prediction of AKI severity. J Am Soc Nephrol 2015; 26:2023–2031.  Back to cited text no. 30
    
31.
Baek SM, Brown RS, Shoemaker WC: Early prediction of acute renal failure and recovery. I. Sequential measurements of free water clearance. Ann Surg 1973; 177:253-258.  Back to cited text no. 31
    
32.
Van der Voort PHJ, Boerma EC, Pickkers P. The furosemide stress test to predict renal function after continuous renal replacement therapy. Crit Care 2014; 18:429.  Back to cited text no. 32
    
33.
Matsuura R, Yohei K, Yoshihisa M, Teruhiko Y, Kohei Y, Rei I et al. Response to different furosemide doses predicts AKI progression in ICU patients with elevated plasma NGAL levels. Ann Intensive Care 2018; 8:8.  Back to cited text no. 33
    
34.
Bowman RH. Renal secretion of [35-S] furosemide and depression by albumin binding. Am J Physiol 1975; 229:93–98.  Back to cited text no. 34
    
35.
Burg M, Stoner L, Cardinal J, Green N. Furosemide effect on isolated perfused tubules. Am J Physiol 1973; 225:119–124.  Back to cited text no. 35
    
36.
McMahon BA, Koyner JL, Novick T, Menez S, Moran RA, Lonze BE et al. The prognostic value of the furosemide stress test in predicting delayed graft function following deceased donor kidney transplantation. Biomarkers 2018; 23:61–69.  Back to cited text no. 36
    


    Figures

  [Figure 1], [Figure 2], [Figure 3], [Figure 4], [Figure 5], [Figure 6]
 
 
    Tables

  [Table 1], [Table 2], [Table 3], [Table 4], [Table 5], [Table 6], [Table 7]



 

Top
 
 
  Search
 
Similar in PUBMED
   Search Pubmed for
   Search in Google Scholar for
 Related articles
Access Statistics
Email Alert *
Add to My List *
* Registration required (free)

 
  In this article
   Abstract
  Introduction
  Patients and methods
  Results
  Discussion
  Conclusion
   References
   Article Figures
   Article Tables

 Article Access Statistics
    Viewed166    
    Printed21    
    Emailed0    
    PDF Downloaded33    
    Comments [Add]    

Recommend this journal


[TAG2]
[TAG3]
[TAG4]