22 research outputs found
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A Single Visualization Technique for Displaying Multiple Metabolite-Phenotype Associations.
To assist with management and interpretation of human metabolomics data, which are rapidly increasing in quantity and complexity, we need better visualization tools. Using a dataset of several hundred metabolite measures profiled in a cohort of ~1500 individuals sampled from a population-based community study, we performed association analyses with eight demographic and clinical traits and outcomes. We compared frequently used existing graphical approaches with a novel 'rain plot' approach to display the results of these analyses. The 'rain plot' combines features of a raindrop plot and a conventional heatmap to convey results of multiple association analyses. A rain plot can simultaneously indicate effect size, directionality, and statistical significance of associations between metabolites and several traits. This approach enables visual comparison features of all metabolites examined with a given trait. The rain plot extends prior approaches and offers complementary information for data interpretation. Additional work is needed in data visualizations for metabolomics to assist investigators in the process of understanding and convey large-scale analysis results effectively, feasibly, and practically
Joint influences of obesity, diabetes, and hypertension on indices of ventricular remodeling: Findings from the community-based Framingham Heart Study.
IntroductionObesity, hypertension, and diabetes are independently associated with cardiac remodeling and frequently co-cluster. The conjoint and separate influences of these conditions on cardiac remodeling have not been investigated.Materials and methodsWe evaluated 5,741 Framingham Study participants (mean age 50 years, 55% women) who underwent echocardiographic measurements of left ventricular (LV) mass (LVM), LV ejection fraction (LVEF), global longitudinal strain (GLS), mitral E/e', left atrial end-systolic (peak) dimension (LASD) and emptying fraction (LAEF). We used multivariable generalized linear models to estimate the adjusted-least square means of these measures according to cross-classified categories of body mass index (BMI; normal, overweight and obese), hypertension (yes/no), and diabetes (yes/no).ResultsWe observed statistically significant interactions of BMI category, hypertension, and diabetes with LVM, LVEF, GLS, and LAEF (p for all 3-way interactions ConclusionsObesity, hypertension, and diabetes interact synergistically to influence cardiac remodeling. These findings may explain the markedly heightened risk of heart failure and cardiovascular disease when these factors co-cluster
Bone marrow and plasma FGF‐23 in heart failure patients : novel insights into the heart–bone axis
Aims: Fibroblast growth factor 23 (FGF‐23) is known to be elevated in patients with congestive heart failure (CHF). As FGF‐23 is expressed in the bone but can also be expressed in the myocardium, the origin of serum FGF‐23 in CHF remains unclear. It is also unclear if FGF‐23 expressed in the bone is associated with outcome in CHF. The aim of the present study was to investigate FGF‐23 levels measured in bone marrow plasma (FGF‐23‐BM) and in peripheral blood (FGF‐23‐P) in CHF patients to gain further insights into the heart–bone axis of FGF‐23 expression. We also investigated possible associations between FGF‐23‐BM as well as FGF‐23‐P and outcome in CHF patients.
Methods and results: We determined FGF‐23‐P and FGF‐23‐BM levels in 203 CHF patients (85% male, mean age 61.3 years) with a left ventricular ejection fraction (LVEF) ≤45% and compared them with those of 48 healthy controls (48% male, mean age 39.2 years). We investigated the association between FGF‐23‐BM and FGF‐23‐P with all‐cause mortality in CHF patients, 32 events, median follow‐up 1673 days, interquartile range [923, 1828]. FGF‐23‐P (median 60.3 vs. 22.0 RU/mL, P < 0.001) and FGF‐23‐BM (median 130.7 vs. 93.1 RU/mL, P < 0.001) levels were higher in CHF patients compared with healthy controls. FGF‐23‐BM levels were significantly higher than FGF‐23‐P levels in both CHF patients and in healthy controls (P < 0.001). FGF‐23‐P and FGF‐23‐BM correlated significantly with LVEF (r = −0.37 and r = −0.33, respectively), N terminal pro brain natriuretic peptide levels (r = 0.57 and r = 0.6, respectively), New York Heart Association status (r = 0.28 and r = 0.25, respectively), and estimated glomerular filtration rate (r = −0.43 and r = −0.41, respectively) (P for all <0.001) and were independently associated with all‐cause mortality in CHF patients after adjustment for LVEF, estimated glomerular filtration rate, New York Heart Association status, and N terminal pro brain natriuretic peptide, hazard ratio 2.71 [confidence interval: 1.18–6.20], P = 0.018, and hazard ratio 2.80 [confidence interval: 1.19–6.57], P = 0.018, respectively.
Conclusions: In CHF patients, FGF‐23 is elevated in bone marrow plasma and is independently associated with heart failure severity and all‐cause mortality. The failing heart seems to interact via FGF‐23 within a heart–bone axis
Bone marrow and plasma FGF‐23 in heart failure patients: novel insights into the heart–bone axis
Aims: Fibroblast growth factor 23 (FGF‐23) is known to be elevated in patients with congestive heart failure (CHF). As FGF‐23 is expressed in the bone but can also be expressed in the myocardium, the origin of serum FGF‐23 in CHF remains unclear. It is also unclear if FGF‐23 expressed in the bone is associated with outcome in CHF. The aim of the present study was to investigate FGF‐23 levels measured in bone marrow plasma (FGF‐23‐BM) and in peripheral blood (FGF‐23‐P) in CHF patients to gain further insights into the heart–bone axis of FGF‐23 expression. We also investigated possible associations between FGF‐23‐BM as well as FGF‐23‐P and outcome in CHF patients.
Methods and results: We determined FGF‐23‐P and FGF‐23‐BM levels in 203 CHF patients (85% male, mean age 61.3 years) with a left ventricular ejection fraction (LVEF) ≤45% and compared them with those of 48 healthy controls (48% male, mean age 39.2 years). We investigated the association between FGF‐23‐BM and FGF‐23‐P with all‐cause mortality in CHF patients, 32 events, median follow‐up 1673 days, interquartile range [923, 1828]. FGF‐23‐P (median 60.3 vs. 22.0 RU/mL, P < 0.001) and FGF‐23‐BM (median 130.7 vs. 93.1 RU/mL, P < 0.001) levels were higher in CHF patients compared with healthy controls. FGF‐23‐BM levels were significantly higher than FGF‐23‐P levels in both CHF patients and in healthy controls (P < 0.001). FGF‐23‐P and FGF‐23‐BM correlated significantly with LVEF (r = −0.37 and r = −0.33, respectively), N terminal pro brain natriuretic peptide levels (r = 0.57 and r = 0.6, respectively), New York Heart Association status (r = 0.28 and r = 0.25, respectively), and estimated glomerular filtration rate (r = −0.43 and r = −0.41, respectively) (P for all <0.001) and were independently associated with all‐cause mortality in CHF patients after adjustment for LVEF, estimated glomerular filtration rate, New York Heart Association status, and N terminal pro brain natriuretic peptide, hazard ratio 2.71 [confidence interval: 1.18–6.20], P = 0.018, and hazard ratio 2.80 [confidence interval: 1.19–6.57], P = 0.018, respectively.
Conclusions: In CHF patients, FGF‐23 is elevated in bone marrow plasma and is independently associated with heart failure severity and all‐cause mortality. The failing heart seems to interact via FGF‐23 within a heart–bone axis
Troponin I Assay for Identification of a Significant Coronary Stenosis in Patients with Suspected Acute Myocardial Infarction and Wide QRS Complex
Background Common ECG criteria such as ST-segment changes are of limited value in patients with suspected acute myocardial infarction (AMI) and bundle branch block or wide QRS complex. A large proportion of these patients do not suffer from an AMI, whereas those with ST-elevation myocardial infarction (STEMI) equivalent AMI benefit from an aggressive treatment. Aim of the present study was to evaluate the diagnostic information of cardiac troponin I (cTnI) in hemodynamically stable patients with wide QRS complex and suspected AMI. Methods In 417 out of 1818 patients presenting consecutively between 01/2007 and 12/2008 in a prospective multicenter observational study with suspected AMI a prolonged QRS duration was observed. Of these, n = 117 showed significant obstructive coronary artery disease (CAD) used as diagnostic outcome variable. cTnI was determined at admission. Results Patients with significant CAD had higher cTnI levels compared to individuals without (median 250ng/L vs. 11ng/L; p<0.01). To identify patients needing a coronary intervention, cTnI yielded an area under the receiver operator characteristics curve of 0.849. Optimized cut-offs with respect to a sensitivity driven rule-out and specificity driven rule-in strategy were established (40ng/L/96ng/L). Application of the specificity optimized cut-off value led to a positive predictive value of 71% compared to 59% if using the 99th percentile cut-off. The sensitivity optimized cut-off value was associated with a negative predictive value of 93% compared to 89% provided by application of the 99th percentile threshold. Conclusion cTnI determined in hemodynamically stable patients with suspected AMI and wide QRS complex using optimized diagnostic thresholds improves rule-in and rule-out with respect to presence of a significant obstructive CAD
Estimation of Values below the Limit of Detection of a Contemporary Sensitive Troponin I Assay Improves Diagnosis of Acute Myocardial Infarction
BACKGROUND: The limit of detection (LoD) is the minimal amount of a substance that can be consistently detected. In the diagnosis of acute myocardial infarction (AMI) many patients present with troponin concentrations below the LoD of contemporary sensitive cardiac troponin I (cs-cTnI) assays. These censored values below the LoD influence the diagnostic performance of these assays compared to highly sensitive cTnI (hs-cTnI) assays. Therefore we assessed the impact of a new approach for interpolation of the left-censored data of a cs-cTnI assay in the evaluation of patients with suspected AMI. METHODS: Our posthoc analysis used a real world cohort of 1818 patients with suspected MI. Data on cs-cTnI was available in 1786 patients. As a comparator the hs-cTnI version of the assay was used. To reconstruct quantities below the LoD of the cs-cTnI assay, a gamma regression approach incorporating the GRACE (Global Registry of Acute Coronary Events) score variables was used. RESULTS: Censoring of cs-cTnI data below the LoD yielded weaker diagnostic information [area under the curve (AUC), 0.781; 95% CI, 0.731-0.831] regarding AMI compared to the hs-cTnI assay (AUC, 0.949; CI, 0.936-0.961). Use of our model to estimate cs-cTnI values below the LoD showed an AUC improvement to 0.921 (CI, 0.902-0.940). The cs-cTnI LoD concentration had a negative predictive value (NPV) of 0.950. An estimated concentration that was to be undercut by 25% of patients presenting with suspected AMI was associated with an improvement of the NPV to 0.979. CONCLUSIONS: Estimation of values below the LoD of a cs-cTnI assay with this new approach improves the diagnostic performance in evaluation of patients with suspected AMI. (C) 2015 American Association for Clinical Chemistr
Urinary neutrophil gelatinase-associated lipocalin and cystatin C compared to the estimated glomerular filtration rate to predict risk in patients with suspected acute myocardial infarction
Introduction: Impaired renal function, reflected by estimated glomerular filtration rate (eGFR) or cystatin C, is a strong risk predictor in the presence of acute myocardial infarction (AMI). Urinary neutrophil gelatinase associated lipocalin (uNGAL) is an early marker of acute kidney injury. uNGAL might also be a good predictor of outcome in patients with cardiovascular disease. Aim of the present study was to evaluate the prognostic value of uNGAL compared to eGFR and cystatin C in patients with suspected AMI. Methods: 1818 patients were enrolled with suspected AMI. Follow-up information on the combined endpoint of death or non-fatal myocardial infarction was obtained 6 months after enrolment and was available in 1804 patients. 63 events (3.5%) were registered. Results: While cystatin C and eGFR were strong risk predictors for the primary endpoint even adjusted for several variables, uNGAL was not independently associated with outcome: When applied continuously uNGAL was associated with outcome but did not remain a statistically significant predictor after several adjustments (i.e. eGFR). By adding cystatin C or uNGAL to GRACE risk score variables, only cystatin C could improve the predictive value while uNGAL showed no improvement. Conclusion: We could show that cystatin C is an independent risk predictor in patients with suspected AMI and cystatin C can add improvement to the commonly used GRACE risk score. In contrast uNGAL is not independently associated with outcome and seems not to add further prognostic information to GRACE risk score. (C) 2017 Elsevier B.V. All rights reserved
Recommended from our members
A Single Visualization Technique for Displaying Multiple Metabolite-Phenotype Associations.
To assist with management and interpretation of human metabolomics data, which are rapidly increasing in quantity and complexity, we need better visualization tools. Using a dataset of several hundred metabolite measures profiled in a cohort of ~1500 individuals sampled from a population-based community study, we performed association analyses with eight demographic and clinical traits and outcomes. We compared frequently used existing graphical approaches with a novel 'rain plot' approach to display the results of these analyses. The 'rain plot' combines features of a raindrop plot and a conventional heatmap to convey results of multiple association analyses. A rain plot can simultaneously indicate effect size, directionality, and statistical significance of associations between metabolites and several traits. This approach enables visual comparison features of all metabolites examined with a given trait. The rain plot extends prior approaches and offers complementary information for data interpretation. Additional work is needed in data visualizations for metabolomics to assist investigators in the process of understanding and convey large-scale analysis results effectively, feasibly, and practically