scholarly journals Combination Treatment with a Calcium Channel Blocker and an Angiotensin Blocker in a Rat Systolic Heart Failure Model with Hypertension.

2002 ◽  
Vol 25 (3) ◽  
pp. 461-466 ◽  
Author(s):  
Masashi NAMBA ◽  
Shokei KIM ◽  
Yumei ZHAN ◽  
Takafumi NAKAO ◽  
Hiroshi IWAO
Keyword(s):  
Heart Failure ◽  
Calcium Channel ◽  
Calcium Channel Blocker ◽  
Combination Treatment ◽  
Channel Blocker ◽  
Systolic Heart Failure ◽  
Failure Model ◽  
Heart Failure Model

scholarly journals Additive Beneficial Effects of the Combination of a Calcium Channel Blocker and an Angiotensin Blocker on a Hypertensive Rat-Heart Failure Model

2004 ◽  
Vol 27 (10) ◽  
pp. 771-779 ◽  
Author(s):  
Shokei KIM-MITSUYAMA ◽  
Yasukatsu IZUMI ◽  
Yasuhiro IZUMIYA ◽  
Kaoru YOSHIDA ◽  
Minoru YOSHIYAMA ◽  
...  
Keyword(s):  
Heart Failure ◽  
Calcium Channel ◽  
Calcium Channel Blocker ◽  
Rat Heart ◽  
Channel Blocker ◽  
Failure Model ◽  
Beneficial Effects ◽  
Hypertensive Rat ◽  
Heart Failure Model

N-terminal fraction of pro-B-type natriuretic peptide versus clinical risk scores for prognostic stratification in chronic systolic heart failure

2018 ◽  
Vol 25 (8) ◽  
pp. 889-895 ◽  
Author(s):  
Chiara Arzilli ◽  
Alberto Aimo ◽  
Giuseppe Vergaro ◽  
Andrea Ripoli ◽  
Michele Senni ◽  
...  
Keyword(s):  
Heart Failure ◽  
Natriuretic Peptide ◽  
Systolic Heart Failure ◽  
Cardiovascular Death ◽  
Risk Scores ◽  
Failure Model ◽  
Model Data ◽  
Available N ◽  
One Year ◽  
Heart Failure Model

Background The Seattle heart failure model or the cardiac and comorbid conditions (3C-HF) scores may help define patient risk in heart failure. Direct comparisons between them or versus N-terminal fraction of pro-B-type natriuretic peptide (NT-proBNP) have never been performed. Methods Data from consecutive patients with stable systolic heart failure and 3C-HF data were examined. A subgroup of patients had the Seattle heart failure model data available. The endpoints were one year all-cause or cardiovascular death. Results The population included 2023 patients, aged 68 ± 12 years, 75% were men. At the one year time-point, 198 deaths were recorded (10%), 124 of them (63%) from cardiovascular causes. While areas under the curve were not significantly different, NT-proBNP displayed better reclassification capability than the 3C-HF score for the prediction of one year all-cause and cardiovascular death. Adding NT-proBNP to the 3C-HF score resulted in a significant improvement in risk prediction. Among patients with Seattle heart failure model data available ( n = 798), the area under the curve values for all-cause and cardiovascular death were similar for the Seattle heart failure model score (0.790 and 0.820), NT-proBNP (0.783 and 0.803), and the 3C-HF score (0.770 and 0.800). The combination of the 3C-HF score and NT-proBNP displayed a similar prognostic performance to the Seattle heart failure model score for both endpoints. Adding NT-proBNP to the Seattle heart failure model score performed better than the Seattle heart failure model alone in terms of reclassification, but not discrimination. Conclusions Among systolic heart failure patients, NT-proBNP levels had better reclassification capability for all-cause and cardiovascular death than the 3C-HF score. The inclusion of NT-proBNP to the 3C-HF and Seattle heart failure model score resulted in significantly better risk stratification.

Abstract 134: Influence of Predictive Modeling in Implementing Optimal Heart Failure Therapy in Inpatient setting

2014 ◽  
Vol 7 (suppl_1) ◽  
Author(s):  
Hari Prasad ◽  
Gujan Choudhary ◽  
Ali Fahad ◽  
Dwight Stapleton
Keyword(s):  
Heart Failure ◽  
Medical Therapy ◽  
Systolic Heart Failure ◽  
Left Ventricular ◽  
Left Ventricular Ejection ◽  
Failure Model ◽  
Heart Failure Therapy ◽  
Device Therapy ◽  
Predictive Tool ◽  
Heart Failure Model

Background: A gap remains between evidence-based guidelines in the treatment of heart failure and current pharmacologic and device therapy. The Seattle Heart Failure Model is an accurate predictive tool that allows the clinician to quantitatively assess the influence of pharmacologic and device therapy on heart failure that has been validated in outpatient setting. We attempt to use the Seattle Heart Failure Model in optimizing the heart failure therapy. Methods: We examined 405 patients’ charts who were admitted with a diagnosis of acute systolic heart failure or acute on chronic systolic heart failure with left ventricular ejection fraction ≤ 40%. Twenty-one data elements were entered into the Seattle Heart Failure Model to create a survival estimate before and after implementation of interventions known to be beneficial, both pharmacologic (addition of ACE/ARB, statin, β-blocker, aldosterone blocker) and device-based (consideration for AICD, BiV pacer, BiV ICD). Results: The mean age of the population examined was 77 ± 9 years. The cohort was comprised of 72 % males, mean weight 89 ± 22.5kg, with NYHA class 2.4 ± 0.6 symptoms. Ischemic etiology was identified in 86% with a mean left ventricular EF of 29.8 ± 9 %. Laboratory data included mean Hgb 10.1 ±1.5g/dL with 15 ± 8% lymphocytes, mean total cholesterol of 176 ± 42mg/dL and mean sodium of 133 ± 3.5mmol/L. The one year all-cause mortality rates were 19.5 % reflecting advanced heart failure population. In the 405 patients examined, we were able to alter therapy (medical or device) in 86%. This included advancement of medical therapy in 56%, consideration for device referral in 11%, or both (medical therapy and device referral) in 19 %. This augmentation of therapy resulted in an increase in estimated mean life expectancy from 6.6 years to 9.6 years (p < 0.001). Conclusion: Use of the Seattle Heart Failure Model significantly helps in intensification of heart failure therapy when applied at time of discharge or in first follow up visit post discharge.

Sign in / Sign up

Export Citation Format

Share Document