angiotensinogen has been researched along with Cardio-Renal-Syndrome* in 3 studies
1 review(s) available for angiotensinogen and Cardio-Renal-Syndrome
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An Expanded View of Progressive Cardiorenal Disorders.
Chronic renal diseases and congestive heart failure are progressive disorders, which cannot be completely controlled by established therapies. It has been argued that intracrine biology involving the formation of self-sustaining intracrine regulatory loops accounts for the progression of these disorders and for the inability of standard therapies to stop disease spread. The renin-angiotensin system is a prime candidate to be involved in any such process, and an amplifying role for mineralocorticoid activation is also consistent with this view. Here, the notion of intracrine participation in congestive heart failure and chronic renal disease is expanded to include consideration of the participation of other intracrines including transforming growth factor beta 1, parathyroid hormone-related protein and vascular endothelial growth factor among others. The possibility that intracrine expression patterns account for disease phenotypes is explored. The therapeutic implications of this view are discussed. Topics: Angiotensin II; Angiotensinogen; Cardio-Renal Syndrome; Disease Progression; Heart Failure; Humans; Parathyroid Hormone-Related Protein; Peptidyl-Dipeptidase A; Renal Insufficiency, Chronic; Renin; Renin-Angiotensin System; Signal Transduction; Transforming Growth Factor beta1; Vascular Endothelial Growth Factor A | 2016 |
2 other study(ies) available for angiotensinogen and Cardio-Renal-Syndrome
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Urinary Biomarkers at the Time of AKI Diagnosis as Predictors of Progression of AKI among Patients with Acute Cardiorenal Syndrome.
A major challenge in early treatment of acute cardiorenal syndrome (CRS) is the lack of predictors for progression of AKI. We aim to investigate the utility of urinary angiotensinogen and other renal injury biomarkers in predicting AKI progression in CRS.. In this prospective, multicenter study, we screened 732 adults who admitted for acute decompensated heart failure from September 2011 to December 2014, and evaluated whether renal injury biomarkers measured at time of AKI diagnosis can predict worsening of AKI. In 213 patients who developed Kidney Disease Improving Global Outcomes stage 1 or 2 AKI, six renal injury biomarkers, including urinary angiotensinogen (uAGT), urinary neutrophil gelatinase-associated lipocalin (uNGAL), plasma neutrophil gelatinase-associated lipocalin, urinary IL-18 (uIL-18), urinary kidney injury molecule-1, and urinary albumin-to-creatinine ratio, were measured at time of AKI diagnosis. The primary outcome was AKI progression defined by worsening of AKI stage (50 patients). The secondary outcome was AKI progression with subsequent death (18 patients).. After multivariable adjustment, the highest tertile of three urinary biomarkers remained associated with AKI progression compared with the lowest tertile: uAGT (odds ratio [OR], 10.8; 95% confidence interval [95% CI], 3.4 to 34.7), uNGAL (OR, 4.7; 95% CI, 1.7 to 13.4), and uIL-18 (OR, 3.6; 95% CI, 1.4 to 9.5). uAGT was the best predictor for both primary and secondary outcomes with area under the receiver operating curve of 0.78 and 0.85. These three biomarkers improved risk reclassification compared with the clinical model alone, with uAGT performing the best (category-free net reclassification improvement for primary and secondary outcomes of 0.76 [95% CI, 0.46 to 1.06] and 0.93 [95% CI, 0.50 to 1.36]; P<0.001). Excellent performance of uAGT was further confirmed with bootstrap internal validation.. uAGT, uNGAL, and uIL-18 measured at time of AKI diagnosis improved risk stratification and identified CRS patients at highest risk of adverse outcomes. Topics: Acute Disease; Acute Kidney Injury; Aged; Aged, 80 and over; Albuminuria; Angiotensinogen; Biomarkers; Cardio-Renal Syndrome; Creatinine; Disease Progression; Female; Hepatitis A Virus Cellular Receptor 1; Humans; Interleukin-18; Lipocalin-2; Male; Middle Aged; Prospective Studies; Risk Assessment; Time Factors | 2016 |
Development and Validation of a Risk Score for Prediction of Acute Kidney Injury in Patients With Acute Decompensated Heart Failure: A Prospective Cohort Study in China.
Although several risk factors for acute kidney injury (AKI) have been identified, early detection of AKI in acute decompensated heart failure patients remains a challenge. The aim of this study was to develop and validate a risk score for early prediction of AKI in acute decompensated heart failure patients.. A total of 676 consecutive acute decompensated heart failure participants were prospectively enrolled from 6 regional central hospitals. Data from 507 participants were analyzed. Participants from 4 of the 6 hospitals (n=321) were used to develop a risk score and conduct internal validation. External validation of the developed risk score was conducted in participants from the other 2 hospitals (n=186). Sequential logistic regression was used to develop and validate the risk score. The c statistic and calibration plot were used to assess the discrimination and calibration of the proposed risk score. The overall occurrence of AKI was 33.1% (168/507). The risk score, ranging from 0 to 55, demonstrated good discriminative power with an optimism-corrected c statistic of 0.859. Similar results were obtained from external validation with c statistic of 0.847 (95% CI 0.819-0.927). The risk score had good calibration with no apparent over- or under-prediction observed from calibration plots.. The novel risk score is a simple and accurate tool that can help clinicians assess the risk of AKI in acute decompensated heart failure patients, which in turn helps them plan and initiate the most appropriate disease management for patients in time. Topics: Acute Disease; Acute Kidney Injury; Aged; Aged, 80 and over; Angiotensinogen; Cardio-Renal Syndrome; China; Cohort Studies; Female; Heart Failure; Humans; Lipocalin-2; Logistic Models; Male; Middle Aged; Prospective Studies; Renal Insufficiency, Chronic; Reproducibility of Results; Risk Assessment; Risk Factors | 2016 |