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 >1.81 mg/dl, AUC is 0.787 (95% CI 0.71–0.85, p<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.

Abstract 13758: The Value of Plasma Neutrophil Gelatinase Associated Lipocalin in the Diagnosis of Cardiorenal Syndrome Type 1

Circulation ◽  
2020 ◽  
Vol 142 (Suppl_3) ◽  
Author(s):  
Hao T Phan
Keyword(s):  
Heart Failure ◽  
Positive Predictive Value ◽  
Negative Predictive Value ◽  
Acute Heart Failure ◽  
Predictive Value ◽  
Cardiorenal Syndrome ◽  
Syndrome Type ◽  
Neutrophil Gelatinase Associated Lipocalin ◽  
Neutrophil Gelatinase

Introduction: 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). Neutrophil gelatinase-associated lipocalin (NGAL) in the blood and urine is one of the earliest markers of acute kidney damage due to anemia or nephrotoxicity. Hypothesis: Plasma NGAL has good value in the diagnosis of cardiorenal syndrome type 1. Methods: There were 139 patients with acute heart failure or acute decompensated heart failure (ADHF) in the Department of cardiovascular resuscitation and Interventional cardiology at our 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 for diagnosing NGAL CRS1 is > 353.23 ng/ml, AUC is 0.732 (95% CI 0.65-0.80, p <0.001), sensitivity 74.47%, specificity 68.48%, positive predictive value 54.7%, negative predictive value 84%. Building the optimal regression model by the BMA (Bayesian Model Average) method with 2 variables NGAL and creatinin day 1: Odds Ratio= e^y while y = - 2.39 + 0.0037 x NGAL + 0.17 x CreatininD1. Moreover, a nomogram with 2 variables NGAL and creatinin day 1 was designed to predict the likelihood of CRS1 with AUC 0.79 and validated on a testing set (consiting of 40 % of the data) by 10-cross-validation method with accuracy 79.82%. Ultimately, a confusion matrix was constructed to determine model accuracy 75.93%, sensitivity 76.74%, specificity 72.73%, positive predictive value 91.67%, negative predictive value 44.44%. Conclusions: Plasma NGAL is quite good value in the diagnosis of CRS1 in patients with acute heart failure or ADHF. A predictive model based on NGAL may help early diagnose CRS1 in patients with acute heart failure or ADHF.

Antibodies against NALP5 and it’s role in hypoparathyroidism in autoimmune polyglandular syndrome type 1

2016 ◽  
Vol 62 (2) ◽  
pp. 25-30
Author(s):  
Leila S. Sozaeva ◽  
Elizaveta M. Orlova ◽  
Bergithe Oftedal ◽  
Maria A. Kareva ◽  
Valentina A. Peterkova ◽  
...  
Keyword(s):  
Positive Predictive Value ◽  
Negative Predictive Value ◽  
Predictive Value ◽  
Parathyroid Glands ◽  
Syndrome Type ◽  
Positive Correlation ◽  
Autoimmune Polyglandular Syndrome ◽  
Autoimmune Polyglandular Syndrome Type ◽  
Immune Assay

Hypoparathyroidism is one of major components of autoimmune polyglandular syndrome type 1 (APS type 1) with a prevalence 73—83%. The protein NALP5 has been described previously as an antigen of parathyroid glands. Aim — to investigate antibodies against NALP5 in patients with APS type 1. Material and methods. Seventy nine patients with APS type 1 were included in the study. Radio-immune assay was used for detecting antibodies against NALP5. Results. The correlation between hypoparathyroidism and high levels of antibodies against NALP5 was found (p<0.001). Sensitivity of the method was 69,4%, specificity — 83,3%, positive predictive value — 93,5%, negative predictive value — 44,1%. Correlations between other components of the disease and high levels of the antibodies were not found. Conclusions. We found a positive correlation between antibodies against NALP5 and hypoparathyroidism in APS type 1 patients. We did not find correlations between antibodies against NALP5 and other components of APS type 1.

scholarly journals Nomogram Model to Predict Cardiorenal Syndrome Type 1 in Patients with Acute Heart Failure

2018 ◽  
Vol 43 (6) ◽  
pp. 1832-1841 ◽  
Author(s):  
Zeyuan Fan ◽  
Yang Li ◽  
Hanhua Ji ◽  
Xinwen Jian
Keyword(s):  
Heart Failure ◽  
Acute Heart Failure ◽  
Cardiorenal Syndrome ◽  
Syndrome Type

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 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.

scholarly journals Levels of Proinflammatory Cytokines, Oxidative Stress, and Tissue Damage Markers in Patients with Acute Heart Failure with and without Cardiorenal Syndrome Type 1

2018 ◽  
Vol 8 (4) ◽  
pp. 321-331 ◽  
Author(s):  
Grazia Maria Virzì ◽  
Andrea Breglia ◽  
Alessandra Brocca ◽  
Massimo de Cal ◽  
Chiara Bolin ◽  
...  
Keyword(s):  
Oxidative Stress ◽  
Heart Failure ◽  
Proinflammatory Cytokines ◽  
Tissue Damage ◽  
Cardiorenal Syndrome ◽  
Syndrome Type ◽  
Spearman's Rho ◽  
Spearman’S Rho ◽  
And Oxidative Stress

Background: Cardiorenal syndrome type 1 (CRS type 1) is characterized by a rapid worsening of cardiac function leading to acute kidney injury (AKI). Inflammation and oxidative stress seem to play a pivotal role in its pathophysiology. In this in vivo study, we examined the putative role of inflammation and humoral markers in the pathogenesis of the CRS type 1. Methods: We enrolled 53 patients with acute heart failure (AHF); 17 of them developed AKI (CRS type 1). The cause of AKI was presumed to be related to cardiac dysfunction after having excluded other causes. We assessed the plasma levels of proinflammatory cytokines (TNF-α, IL-6, IL-18, sICAM, RANTES, GMCSF), oxidative stress marker (myeloperoxidase, MPO), brain natriuretic peptide (BNP), and neutrophil gelatinase-associated lipocalin (NGAL) in AHF and CRS type 1 patients. Results: We observed a significant increase in IL-6, IL-18, and MPO levels in CRS type 1 group compared to AHF (p < 0.001). We found higher NGAL at admission in the CRS type 1 group compared to the AHF group (p = 0.008) and a positive correlation between NGAL and IL-6 (Spearman’s rho = 0.45, p = 0.003) and between IL-6 and BNP (Spearman’s rho = 0.43, p = 0.004). We observed lower hemoglobin levels in CRS type 1 patients compared to AHF patients (p < 0.05) and inverse correlation between hemoglobin and cytokines (IL-6: Spearman’s rho = –0.38, p = 0.005; IL-18: Spearman’s rho = –0.32, p = 0.02). Conclusion: Patients affected by CRS type 1 present increased levels of proinflammatory cytokines and oxidative stress markers, increased levels of tissue damage markers, and lower hemoglobin levels. All these factors may be implicated in the pathophysiology of CRS type 1 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.

The validity of heart failure diagnoses in the Finnish Hospital Discharge Register

2019 ◽  
Vol 48 (1) ◽  
pp. 20-28 ◽  
Author(s):  
Matti A. Vuori ◽  
Jari A. Laukkanen ◽  
Arto Pietilä ◽  
Aki S. Havulinna ◽  
Mika Kähönen ◽  
...  
Keyword(s):  
Heart Failure ◽  
Ejection Fraction ◽  
Positive Predictive Value ◽  
Negative Predictive Value ◽  
Hospital Discharge ◽  
Predictive Value ◽  
Medical Records ◽  
Register Data ◽  
Preserved Ejection Fraction ◽  
Hospital Discharge Register

Background: Contemporary validation studies of register-based heart failure diagnoses based on current guidelines and complete clinical data are lacking in Finland and internationally. Our objective was to assess the positive and negative predictive values of heart failure diagnoses in a nationwide hospital discharge register. Methods: Using Finnish Hospital Discharge Register data from 2013–2015, we obtained the medical records for 120 patients with a register-based diagnosis for heart failure (cases) and for 120 patients with a predisposing condition for heart failure, but without a heart failure diagnosis (controls). The medical records of all patients were assessed by a physician who categorized each individual as having heart failure (with reduced or preserved ejection fraction) or no heart failure, based on the definition of current European Society of Cardiology heart failure guidelines. Unclear cases were assessed by a panel of three physicians. This classification was considered as the clinical gold standard, against which the registers were assessed. Results: Register-based heart failure diagnoses had a positive predictive value of 0.85 (95% CI 0.77–0.91) and a negative predictive value of 0.83 (95% CI 0.75–0.90). The positive predictive value decreased when we classified patients with transient heart failure (duration <6 months), dialysis/lung disease or heart failure with preserved ejection fraction as not having heart failure. Conclusions: Heart failure diagnoses of the Finnish Hospital Discharge Register have good positive predictive value and negative predictive value, even when patients with pre-existing heart conditions are used as healthy controls. Our results suggest that heart failure diagnoses based on register data can be reliably used for research purposes.

Sign in / Sign up

Export Citation Format

Share Document