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Clinical Evaluation of Heart Failure: Agreement among Tests.

ABSTRACT: Methods commonly used clinically to assess cardiac function in patients with heart failure include ejection fraction (EF), exercise treadmill testing (ETT), and symptom evaluation. Although these approaches are useful in evaluating patients with heart failure, there are at times substantial mismatches between individual assessments. For example, ETT results are often discordant with EF, and patients with minimal symptoms sometimes have surprisingly low EFs. To better define the relationship of these methods of assessment, we studied 56 patients with heart failure with reduced EF (HFrEF) who underwent measurement of ETT duration, EF by echocardiography, quantitative symptom evaluation, and LV peak dP/dt (rate of left ventricular pressure development and decline, measured invasively). Correlations were determined among these four tests in order to assess the relationship of EF, ETT, and symptoms against LV peak dP/dt. In addition, we sought to determine whether EF, ETT, and symptoms correlated with each other. Overall, correlations were poor. Only 15 of 63 total correlations (24%) were significant (p < 0.05). EF correlated most closely with LV peak -dP/dt. Linear regression analysis indicated that EF, ETT, and symptoms taken together predicted LV peak dP/dt better than any one measure alone. We conclude that clinical tests used to assess LV function in patients with HFrEF may not be as accurate or correlate as well as expected. All three clinical measures considered together may be the best representation of cardiac function in HFrEF patients currently available.

SUBMITTER: Pandey AK

PROVIDER: S-EPMC4990285 | biostudies-literature | 2016

REPOSITORIES: biostudies-literature

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Clinical Evaluation of Heart Failure: Agreement among Tests.

Pandey Amit K AK Penny William F WF Bhargava Valmik V Lai N Chin NC Xu Ronghui R Hammond H Kirk HK

PloS one 20160818 8

Methods commonly used clinically to assess cardiac function in patients with heart failure include ejection fraction (EF), exercise treadmill testing (ETT), and symptom evaluation. Although these approaches are useful in evaluating patients with heart failure, there are at times substantial mismatches between individual assessments. For example, ETT results are often discordant with EF, and patients with minimal symptoms sometimes have surprisingly low EFs. To better define the relationship of t ...[more]

PMID: 27537778

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Project description:The metabolic changes that accompany changes in Cardiopulmonary testing (CPET) and heart failure biomarkers (HFbio) are not well known. We undertook metabolomic and lipidomic phenotyping of a cohort of heart failure (HF) patients and utilized Multiple Regression Analysis (MRA) to identify associations to CPET and HFBio test performance (peak oxygen consumption (Peak VO2), oxygen uptake efficiency slope (OUES), exercise duration, and minute ventilation-carbon dioxide production slope (VE/VCO2 slope), as well as the established HF biomarkers of inflammation C-reactive protein (CRP), beta-galactoside-binding protein (galectin-3), and N-terminal prohormone of brain natriuretic peptide (NT-proBNP)). A cohort of 49 patients with a left ventricular ejection fraction < 50%, predominantly males African American, presenting a high frequency of diabetes, hyperlipidemia, and hypertension were used in the study. MRA revealed that metabolic models for VE/VCO2 and Peak VO2 were the most fitted models, and the highest predictors' coefficients were from Acylcarnitine C18:2, palmitic acid, citric acid, asparagine, and 3-hydroxybutiric acid. Metabolic Pathway Analysis (MetPA) used predictors to identify the most relevant metabolic pathways associated to the study, aminoacyl-tRNA and amino acid biosynthesis, amino acid metabolism, nitrogen metabolism, pantothenate and CoA biosynthesis, sphingolipid and glycerolipid metabolism, fatty acid biosynthesis, glutathione metabolism, and pentose phosphate pathway (PPP). Metabolite Set Enrichment Analysis (MSEA) found associations of our findings with pre-existing biological knowledge from studies of human plasma metabolism as brain dysfunction and enzyme deficiencies associated with lactic acidosis. Our results indicate a profile of oxidative stress, lactic acidosis, and metabolic syndrome coupled with mitochondria dysfunction in patients with HF tests poor performance. The insights resulting from this study coincides with what has previously been discussed in existing literature thereby supporting the validity of our findings while at the same time characterizing the metabolic underpinning of CPET and HFBio.

Project description:BackgroundMalnutrition is common in patients with chronic heart failure (CHF) and is associated with adverse outcome, but few data exist.ObjectivesThe objective of this study was to compare the agreement and classification performance of 6 malnutrition tools in patients with CHF.MethodsWe evaluated the performance of 6 malnutrition tools: COntrolling NUTritional Status Index (CONUT), Geriatric Nutritional Risk Index (GNRI), Prognostic Nutritional Index (PNI), Malnutrition Universal Screening Tool (MUST), Mini Nutritional Assessment-Short Form (MNA-SF), and Subjective Global Assessment (SGA), in 467 consecutive patients with CHF who attended our clinic for follow-up. We used Venn diagrams and Kappa statistics to study the agreement of different tools. Because there is no "gold standard" for malnutrition evaluation, for each of the malnutrition tools, we used the results of the other 5 tools to produce a standard combined index for evaluating at least moderate malnutrition. Subjects were considered as having at least moderate malnutrition if so identified by ?3/5 tools. We evaluated the sensitivity, specificity, and predictive values of different tools in identifying significant malnutrition as defined by the combined index.ResultsMen comprised 67% of patients, median age was 76 years, and median N-terminal pro-B-type natriuretic peptide (NTproBNP) was 1156 ng/L. The prevalence of any degree and at least moderate malnutrition ranged between 6-60% and 3-9%, respectively, with CONUT classifying the highest proportion of subjects as malnourished. Malnourished patients tended to be older and have worse symptoms, higher NTproBNP, and more comorbidities. CONUT had the highest sensitivity (80%), MNA-SF and SGA had the highest specificity (99%), and MNA-SF had the lowest misclassification rate (2%) in identifying at least moderate malnutrition as defined by the combined index.ConclusionsMalnutrition is common in patients with CHF. The prevalence of malnutrition varies depending on the tool used. Among the 6 malnutrition tools studied, MNA-SF has the best classification performance in identifying significant malnutrition as defined by the combined index.

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Clinical Evaluation of Heart Failure: Agreement among Tests.

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Clinical Evaluation of Heart Failure: Agreement among Tests.

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