scholarly journals Value of Plasma NGAL and Creatinine on First Day of Admission in the Diagnosis of Cardiorenal Syndrome Type 1

2020 ◽  
Vol 2020 ◽  
pp. 1-9
Author(s):  
Hao Phan Thai ◽  
Bao Hoang Bui ◽  
Tien Hoang Anh ◽  
Minh Huynh Van
Keyword(s):  
Heart Failure ◽  
Acute Kidney Injury ◽  
Predictive Value ◽  
Kidney Injury ◽  
Cardiorenal Syndrome ◽  
Admission Diagnosis ◽  
Multivariable Logistic Regression Analysis ◽  
Plasma Ngal ◽  
Model Average ◽  
Study Results

Background. The presence of acute kidney injury in the setting of acute heart failure (AHF) or acute decompensated heart failure (ADHF) is a very common occurrence and was termed cardiorenal syndrome 1 (CRS1). Neutrophil gelatinase-associated lipocalin (NGAL) in the blood and urine is one of the earliest biomarkers of acute kidney injury due to ischemia or renal toxicity. This study was aimed to evaluate the diagnostic efficacy of plasma NGAL in the diagnosis of CRS1. Methods. There were 139 patients with AHF or ADHF in the department of Cardiovascular Resuscitation and Interventional Cardiology at Ho Chi Minh City 115 People Hospital from September 2018 to March 2019. This was a prospective cohort study. Results. There were 48 cases (rate 34.5%) with CRS1, mean age was 66.12 ± 15.77 and men accounted for 50.4%. There were no significant differences of vital signs at admission, diagnosis, and EF-based heart failure between CRS1 and non-CRS1 groups. The urea, creatinine on first day (creatinine D1) and third day (creatinine D3), NT-proBNP, and NGAL levels were higher in the CRS1 group than the non-CRS1 group, p < 0.05 . The optimal cutoff plasma NGAL for diagnosing CRS1 was >353.23 ng/ml, area under curve (AUC) 0.732 (95% CI 0.65–0.80, p < 0.001 ), sensitivity 74.47%, specificity 68.48%, positive predictive value 54.7%, and negative predictive value 84%. Multivariable logistic regression analysis eGFRCKDEPID1 remained the strongest independent predictor of CRS1. Building the optimal regression model (without eGFRCKDEPID1) by the BMA (Bayesian model average) method with two variables NGAL and Creatinine D1, we had the equation: odds ratio = ey while y = −2.39 + 0.0037 × NGAL + 0.17 × Creatinine D1. The nomogram (without eGFRCKDEPID1) was designed to predict the likelihood of CRS1 with AUC 0.79. Conclusions. The combination of plasma NGAL and creatinine D1 on the first day at admission had a high accuracy of predictive model for CRS1.

Acute kidney injury in heart failure

2015 ◽  
Author(s):  
Dinna N. Cruz ◽  
Anna Giuliani ◽  
Claudio Ronco
Keyword(s):  
Heart Failure ◽  
Acute Kidney Injury ◽  
Kidney Injury ◽  
Volume Overload ◽  
Bioelectrical Impedance ◽  
Impedance Analysis ◽  
Cardiorenal Syndrome ◽  
Renal Diseases ◽  
Consensus Definition ◽  
Short And Long Term

Acute kidney injury (AKI) occurring during heart failure (HF) has been labelled cardiorenal syndrome (CRS) type 1. CRS is defined as a group of ‘disorders of the heart and kidneys whereby acute or chronic dysfunction in one organ may induce acute or chronic dysfunction of the other’. This consensus definition was proposed by the Acute Dialysis Quality Initiative, with the aim to standardize those disorders where cardiac and renal diseases coexist. Five subtypes have been proposed, according to which organ is affected first (cardiac vs renal) and whether the dysfunction is acute or chronic. Another subtype which includes systemic conditions leading to both heart and kidney dysfunction is also described.The term ‘worsening renal function’ has been regularly used to describe the acute and/or subacute changes that occur in the kidneys following HF. However, the AKI classification according to the current consensus definition better represents the entire spectrum of AKI in the setting of HF.The pathophysiology of heart–kidney interaction is complex and still poorly understood. Factors beyond the classic haemodynamic mechanisms appear to be involved: neurohormonal activation, venous congestion, and inflammation have all been implicated.Diuretics are still a cornerstone in the management of HF. Intravenous administration by bolus or continuous infusion appears to be equally efficacious. Biomarkers and bioelectrical impedance analysis can be helpful in estimating the real volume overload and may be useful to predict and avoid AKI. The role of ultrafiltration remains controversial, and it is currently recommended only for diuretic-resistant patients as it has not been associated with better outcomes. The occurrence of AKI during HF is associated with substantially greater short- and long-term mortality.

scholarly journals CARDIORENAL SYNDROME IN PATIENTS WITH CHRONIC HEART FAILURE AS A STAGE OF THE CARDIORENAL CONTINUUM (PART I): DEFINITION, CLASSIFICATION, PATHOGENESIS, DIAGNOSIS, EPIDEMIOLOGY

2019 ◽  
Vol 9 (1) ◽  
pp. 5-22 ◽  
Author(s):  
E. V. Reznik ◽  
I. G. Nikitin
Keyword(s):  
Heart Failure ◽  
Acute Kidney Injury ◽  
Chronic Heart Failure ◽  
Impaired Renal Function ◽  
Prognostic Value ◽  
Kidney Injury ◽  
Cardiorenal Syndrome ◽  
Syndrome Type ◽  
Patients With Heart Failure

The combination of heart failure and renal failure is called cardiorenal syndrome. It is a stage of the cardiorenal continuum and, possibly, a small link of the cardiorenal-cerebral-metabolic axis. Despite the fact that the phrase “cardiorenal syndrome” and its five types have become a part of the medical lexicon, many aspects of this problem are still not clear. Cardiorenal syndrome can be diagnosed in 32-90.3% of patients with heart failure. Cardiorenal syndrome type 1 or 2 develops in most cases of heart failure: cardiorenal syndrome presents with the development ofchronic kidney disease in patients with chronic heart failure and acute kidney injury in patients with acute heart failure. Impaired renal function has an unfavorable prognostic value. It leads to an increase in the mortality of patients with heart failure. It is necessary to timely diagnose the presence of cardiorenal syndrome and take into account its presence when managing patients with heart failure. Further researches are needed on ways toprevent the development and prevent the progression of kidney damage in patients with heart failure, to which the efforts of the multidisciplinary team should be directed. The first part of this review examines the currently definition, classification, pathogenesis, epidemiology and prognosis of cardiorenal syndrome in patients with heart failure.

scholarly journals Markers of renal function and acute kidney injury in acute heart failure: definitions and impact on outcomes of the cardiorenal syndrome

2010 ◽  
Vol 31 (22) ◽  
pp. 2791-2798 ◽  
Author(s):  
J. P. E. Lassus ◽  
M. S. Nieminen ◽  
K. Peuhkurinen ◽  
K. Pulkki ◽  
K. Siirila-Waris ◽  
...  
Keyword(s):  
Heart Failure ◽  
Acute Kidney Injury ◽  
Renal Function ◽  
Acute Heart Failure ◽  
Kidney Injury ◽  
Cardiorenal Syndrome

scholarly journals Acute Cardiorenal Syndrome: Models and Heart-Kidney Connectors

Nephron ◽  
2020 ◽  
Vol 144 (12) ◽  
pp. 629-633 ◽  
Author(s):  
Yoshio Funahashi ◽  
Sheuli Chowdhury ◽  
Mahaba B. Eiwaz ◽  
Michael P. Hutchens
Keyword(s):  
Heart Failure ◽  
Cell Culture ◽  
Acute Kidney Injury ◽  
Renal Function ◽  
Kidney Injury ◽  
Cardiorenal Syndrome ◽  
Syndrome Type ◽  
Culture Models ◽  
Cell Culture Models

Cardiorenal syndrome type 1 (CRS-1) is an acute kidney injury (AKI) due to acute worsening of cardiac function. More than 20% of patients with acute heart failure develop AKI, and AKI predicts poor outcome. Although a number of potential pathways have been suggested as heart-kidney connectors which might drive the syndrome, there are significant barriers to investigation, such as a paucity of animal models, a lack of specific biomarkers, and an inconsistent temporal and causal relationship between changes in cardiac flow and development of renal dysfunction. Thus, mechanisms of heart-kidney interaction are still unclear, and there is no specific or effective therapy for CRS-1. This review, therefore, focuses on mitigating these challenges in the investigation of CRS-1. We review the available models and focus on mechanistic insights gained from those models. In particular, we focus on non-flow and endocrine mediators of CRS-1 such as heart-derived messengers which alter renal function and which may represent targetable pathways in this syndrome. As precise connectors of heart-kidney interaction remain unclear, the establishment of animal and relevant cell-culture models and further investigation are required.

scholarly journals The value of Cystatin C in the diagnosis of cardiorenal syndrome type 1

2021 ◽  
Vol 42 (Supplement_1) ◽  
Author(s):  
H A O Phan
Keyword(s):  
Heart Failure ◽  
Positive Predictive Value ◽  
Negative Predictive Value ◽  
Acute Heart Failure ◽  
Cystatin C ◽  
Predictive Value ◽  
Cardiorenal Syndrome ◽  
Syndrome Type ◽  
Model Average

Abstract Background The presence of acute kidney injury in the setting of acute heart failure is very common occurrence and was termed cardiorenal syndrome 1 (CRS1). In CRS1 the diagnosis of acute kidney damage is often delayed by creatinine and urine output following KDIGO standards (Kidney Disease Improving Global Outcomes). Cystatin C is one of the earliest markers of worsening renal function. We studied the value of plasma Cystatin C in the diagnosis of cardiorenal syndrome type 1. Purpose This study was aimed: (1) to decribe clinical, subclinical characteristics, prevalence of CRS1; (2) to evaluate the diagnostic efficacy of Cystatin C in diagnosis of CRS1. Materials and method There were 139 patients with acute heart failure or acute decompensated heart failure (ADHF) in the Department of cardiovascular resuscitation and Interventional cardiology at 115 Ho Chi Minh City People's Hospital from September 2018 to June 2019. This is a prospective cohort study. Results There were 48 cases (rate 34.5%) with CRS1, medium age 66.12±15.77, men accounted for 50.4%. The optimal cut-off Cystatin C for diagnosing CRS1 is &gt;1.81 mg/dl, AUC is 0.787 (95% CI 0.71–0.85, p&lt;0.001), sensitivity 75%, specificity 83.52%, positive predictive value 70.6%, negative predictive value 86.4%. Building the optimal regression model by the BMA (Bayesian Model Average) method with only one variable Cystatin C: Odds Ratio = ey, while y = −2.75 + 1.11x Cystatin C. Moreover, a nomogram with variable Cystatin C was designed to predict the likelihood of CRS1 with AUC 0.842. Ultimately, a confusion matrix was constructed to determine model accuracy 81.82%, sensitivity 78.26%, specificity 100%, positive predictive value 100%, negative predictive value 47.37%. Conclusions Cystatin C is quite good value in the diagnosis of CRS1 in patients with acute heart failure or ADHF. A predictive model based on Cystatin C may help early diagnose CRS1 in patients with acute heart failure or ADHF. FUNDunding Acknowledgement Type of funding sources: None.

scholarly journals The Role of Endothelial Dysfunction in Development of Acute Kidney Injury in Patients With Acute Decompensated Heart Failure

2020 ◽  
Author(s):  
Shu-Min Lin ◽  
Chih-Hsiang Chang ◽  
Ting-Yu Lin ◽  
Allen Chung-Cheng Huang ◽  
Chiung-Hung Lin ◽  
...  
Keyword(s):  
Heart Failure ◽  
Acute Kidney Injury ◽  
Plasma Levels ◽  
Acute Decompensated Heart Failure ◽  
Kidney Injury ◽  
Roc Curves ◽  
Decompensated Heart Failure ◽  
Cardiorenal Syndrome ◽  
Type I ◽  
Soluble Thrombomodulin

Abstract Objective: Cardiorenal syndrome type I (CRS I) is defined as the development of acute kidney injury (AKI) following acute decompensated heart failure (ADHF). Note that the clinical significance of endothelial markers in ADHF-associated AKI has yet to be clarified. This study investigated the biological processes linking ADHF and AKI to determine whether plasma markers of endothelial injury and activation could serve as predictors for AKI in patients with ADHF. Methods: The study prospectively recruited 125 consecutive patients admitted to a coronary critical unit due to ADHF. Patients with and without AKI were compared in terms of plasma levels of soluble thrombomodulin (sTM), angiopoietin (Ang)-1 and 2, and baseline characteristics. Results: Among the study population, 14 (11.2%) patients developed CRS within 7 days after admission. The hemoglobin levels (11.4 ± 2.1 vs. 13.3 ± 2.2 g/dL, p =0.003) and baseline eGFR (65.7 ± 34.5 vs. 85.5 ± 35.0 mL/minute/1.73m2, p = 0.048) of patients with CRS were lower than those of patients without CRS. Patients with CRS also presented elevated plasma levels of BNP (1,797.2 ± 1,649.1 vs. 687.8 ± 976.6 pg/mL, p = 0.008), Ang-2 (7,524.7 ± 8,485.5 vs. 3,325.3 ± 4,7409 pg/mL, p = 0.006), and sTM (7,763.8 ± 3,803.7 vs. 4,661.3 ± 1,896.8 ng/mL, p < 0.001) compared to patients without CRS. Areas under the ROC curves (AUROC) revealed that Ang-2 and TM plasma levels had significantly discriminative powers pertaining to the development of CRS (0.704, 95% CI 0.55-0.859, p =0.013; and 0.789, 95% CI 0.675-0.903, p <0.001, respectively). Conclusion: These biomarkers suggest a novel avenue for kidney injury in the context of ADHF and indicate that baseline biomarker profiles could potential be used to identify individuals at risk of developing AKI.

scholarly journals Acute kidney injury in patients with chronic heart failure

2021 ◽  
Vol 2 (3) ◽  
pp. 6-17
Author(s):  
A. G. Arutyunov ◽  
R. A. Bashkinov ◽  
T. I. Batluk ◽  
E. S. Melnikov ◽  
A. N. Ermilova
Keyword(s):  
Heart Failure ◽  
Acute Kidney Injury ◽  
Chronic Heart Failure ◽  
Negative Impact ◽  
Kidney Injury ◽  
Cardiorenal Syndrome ◽  
Pathological Process ◽  
Reduced Ejection Fraction ◽  
Coronavirus Infection

The problem of chronic heart failure (CHF) and especially CHF with reduced ejection fraction is one of the most significant for modern healthcare systems. This is due to the high mortality rate, reduced quality of life, frequent hospitalizations and marked comorbidity of patients with this pathology. Involvement of the kidneys in the pathological process is one of the most common comorbid conditions in cardiovascular disease. There are a large number of pathogenetic mechanisms of mutually negative impact of heart failure and renal dysfunction, reflected in the concept of «Cardiorenal syndrome». Moreover, drug therapy of CHF can be one of the causes of kidney damage. Episodes of acute circulatory decompensation as well as a new coronavirus infection (COVID-19) are particularly threatening conditions. The aim of this review is to consolidate the international literature on the problem of acute kidney injury in patients with CHF.

scholarly journals Frailty status among older critically ill patients with severe acute kidney injury

Critical Care ◽  
2021 ◽  
Vol 25 (1) ◽  
Author(s):  
William Beaubien-Souligny ◽  
Alan Yang ◽  
Gerald Lebovic ◽  
Ron Wald ◽  
Sean M. Bagshaw
Keyword(s):  
Acute Kidney Injury ◽  
Critically Ill ◽  
Critically Ill Patients ◽  
Multivariable Analysis ◽  
Kidney Injury ◽  
Multivariable Logistic Regression Analysis ◽  
Clinical Frailty Scale ◽  
Factors Associated ◽  
Frailty Status ◽  
Physiological Variables

Abstract Background Frailty status among critically ill patients with acute kidney injury (AKI) is not well described despite its importance for prognostication and informed decision-making on life-sustaining therapies. In this study, we aim to describe the epidemiology of frailty in a cohort of older critically ill patients with severe AKI, the outcomes of patients with pre-existing frailty before AKI and the factors associated with a worsening frailty status among survivors. Methods This was a secondary analysis of a prospective multicentre observational study that enrolled older (age > 65 years) critically ill patients with AKI. The clinical frailty scale (CFS) score was captured at baseline, at 6 months and at 12 months among survivors. Frailty was defined as a CFS score of ≥ 5. Demographic, clinical and physiological variables associated with frailty as baseline were described. Multivariable Cox proportional hazard models were constructed to describe the association between frailty and 90-day mortality. Demographic and clinical factors associated with worsening frailty status at 6 months and 12 months were described using multivariable logistic regression analysis and multistate models. Results Among the 462 patients in our cohort, median (IQR) baseline CFS score was 4 (3–5), with 141 (31%) patients considered frail. Pre-existing frailty was associated with greater hazard of 90-day mortality (59% (n = 83) for frail vs. 31% (n = 100) for non-frail; adjusted hazards ratio [HR] 1.49; 95% CI 1.11–2.01, p = 0.008). At 6 months, 68 patients (28% of survivors) were frail. Of these, 57% (n = 39) were not classified as frail at baseline. Between 6 and 12 months of follow-up, 9 (4% of survivors) patients transitioned from a frail to a not frail status while 10 (4% of survivors) patients became frail and 11 (5% of survivors) patients died. In multivariable analysis, age was independently associated with worsening CFS score from baseline to 6 months (adjusted odds ratio [OR] 1.08; 95% CI 1.03–1.13, p = 0.003). Conclusions Pre-existing frailty is an independent risk factor for mortality among older critically ill patients with severe AKI. A substantial proportion of survivors experience declining function and worsened frailty status within one year.

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