The utility of biomarker risk prediction score in patients with chronic heart failure.
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ABSTRACT:
SUBMITTER: Berezin AE
PROVIDER: S-EPMC4787185 | biostudies-other | 2015
REPOSITORIES: biostudies-other
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Project description:BackgroundReliable risk scores in patients undergoing transcatheter edge-to-edge mitral valve repair (TMVR) are lacking. Heart failure is common in these patients, and risk scores derived from heart failure populations might help stratify TMVR patients.MethodsConsecutive patients from three Heart Centers undergoing TMVR were enrolled to investigate the association of the "Get with the Guidelines Heart Failure Risk Score" (comprising the variables systolic blood pressure, urea nitrogen, blood sodium, age, heart rate, race, history of chronic obstructive lung disease) with all-cause mortality.ResultsAmong 815 patients with available data 177 patients died during a median follow-up time of 365 days. Estimated 1-year mortality by quartiles of the score (0-37; 38-42, 43-46 and more than 46 points) was 6%, 10%, 23% and 30%, respectively (p < 0.001), with good concordance between observed and predicted mortality rates (goodness of fit test p = 0.46). Every increase of one score point was associated with a 9% increase in the hazard of mortality (95% CI 1.06-1.11%, p < 0.001). The score was associated with long-term mortality independently of left ventricular ejection fraction, NYHA class and NTproBNP, and was equally predictive in primary and secondary mitral regurgitation.ConclusionThe "Get with the Guidelines Heart Failure Risk Score" showed a strong association with mortality in patients undergoing TMVR with additive information beyond traditional risk factors. Given the routinely available variables included in this score, application is easy and broadly possible.
| S-EPMC8639563 | biostudies-literature
Project description:Prior studies have suggested using a panel of biomarkers that measure diverse biological processes as a prognostic tool in chronic heart failure. Whether this approach improves risk prediction beyond clinical evaluation is unknown.In a multicenter cohort of 1513 chronic systolic heart failure patients, we measured a contemporary biomarker panel consisting of high-sensitivity C-reactive protein, myeloperoxidase, B-type natriuretic peptide, soluble fms-like tyrosine kinase receptor-1, troponin I, soluble toll-like receptor-2, creatinine, and uric acid. From this panel, we calculated a parsimonious multimarker score and assessed its performance in predicting risk of death, cardiac transplantation, or ventricular assist device placement in comparison to an established clinical risk score, the Seattle Heart Failure Model (SHFM). During a median follow-up of 2.5 years, there were 317 outcomes: 187 patients died; 99 were transplanted; and 31 had a ventricular assist device placed. In unadjusted Cox models, patients in the highest tertile of the multimarker score had a 13.7-fold increased risk of adverse outcomes compared with the lowest tertile (95% confidence interval, 8.75-21.5). These effects were independent of the SHFM (adjusted hazard ratio, 6.80; 95% confidence interval, 4.18-11.1). Addition of the multimarker score to the SHFM led to a significantly improved area under the receiver operating characteristic curve of 0.803 versus 0.756 (P=0.003) and appropriately reclassified a significant number of patients who had the outcome into a higher risk category (net reclassification improvement, 25.2%; 95% confidence interval, 14.2-36.2%; P<0.001).In ambulatory chronic heart failure patients, a score derived from multiple biomarkers integrating diverse biological pathways substantially improves prediction of adverse events beyond current metrics.
| S-EPMC3387487 | biostudies-literature
Project description:This review article addresses the question of whether biomarker-guided therapy is ready for clinical implementation in chronic heart failure. The most well-known biomarkers in heart failure are natriuretic peptides, namely B-type natriuretic peptide (BNP) and N-terminal pro-BNP. They are well-established in the diagnostic process of acute heart failure and prediction of disease prognosis. They may also be helpful in screening patients at risk of developing heart failure. Although studied by 11 small- to medium-scale trials resulting in several positive meta-analyses, it is less well-established whether natriuretic peptides are also helpful for guiding chronic heart failure therapy. This uncertainty is expressed by differences in European and American guideline recommendations. In addition to reviewing the evidence surrounding the use of natriuretic peptides to guide chronic heart failure therapy, this article gives an overview of the shortcomings of the trials, how the results may be interpreted and the future directions necessary to fill the current gaps in knowledge. Therapy guidance in chronic heart failure using other biomarkers has not been prospectively tested to date. Emerging biomarkers, such as galectin-3 and soluble ST2, might be useful in this regard, as suggested by several post-hoc analyses.
| S-EPMC5490943 | biostudies-literature
Project description:AimSoluble suppression of tumorigenicity-2 (sST2) is a strong prognostic biomarker in heart failure. The emerging understanding of circadian biology in cardiovascular disease may lead to novel applications in prognosis and diagnosis and may provide insight into mechanistic aspects of the disease-biomarker interaction. So far, it is unknown whether sST2 exhibits a diurnal rhythm. Repeated measurements of sST2 may aid in clinical decision making. The goal of this study was to investigate whether sST2 exhibits diurnal variation in patients with heart failure with reduced ejection fraction (HFrEF) and in control subjects, thereby enhancing its diagnostic and prognostic values.Methods and resultsThe study comprised 32 subjects: 16 HFrEF patients and 16 controls. Blood was collected at seven subsequent time points during a 24 h time period. sST2, N-terminal pro-B-type natriuretic peptide (NT-proBNP), melatonin, and cortisol were measured from serum. Peak values of sST2 clustered at daytime (modal value: 5 p.m.) in 87.6% of all subjects (81.3% of patients, P = 0.021; 93.8% of controls, P = 0.001), and minimum concentrations at night-time (modal value: 5 a.m.) in 84.4% (87.5% of patients, P = 0.004 81.3% of controls, P = 0.021). A cosinor analysis of mean normalized sST2 values revealed significant cosine shaped 24 h oscillations of patients (P = 0.026) and controls (P = 0.037). NT-proBNP in contrast did not show a diurnal rhythm, while melatonin and cortisol patterns were intact in all subjects.ConclusionssST2 exhibits a diurnal rhythm with lower values in the morning than in the late afternoon. This new insight could lead to refinement of its diagnostic and prognostic values through specified and consistent sampling times with repeated measurements. For example, by measuring sST2 during the afternoon, when levels are at their highest, false negatives on prognosis prediction could be avoided.
| S-EPMC7261542 | biostudies-literature
Project description:BackgroundDespite the growing burden of heart failure (HF), there have been no recommendations for use of any of the primary prevention models in the existing guidelines. HF was also not included as an outcome in the American College of Cardiology/American Heart Association (ACC/AHA) risk score.MethodsAmong 2743 men and 3646 women aged ≥ 55 years, free of HF, from the population-based Rotterdam Study cohort, 4 Cox models were fitted using the predictors of the ACC/AHA, ARIC and Health-ABC risk scores. Performance of the models for 10-year HF prediction was evaluated. Afterwards, performance and net reclassification improvement (NRI) for adding NT-proBNP to the ACC/AHA model were assessed.ResultsDuring a median follow-up of 13 years, 429 men and 489 women developed HF. The ARIC model had the highest performance [c-statistic (95% confidence interval [CI]): 0.80 (0.78; 0.83) and 0.80 (0.78; 0.83) in men and women, respectively]. The c-statistic for the ACC/AHA model was 0.76 (0.74; 0.78) in men and 0.77 (0.75; 0.80) in women. Adding NT-proBNP to the ACC/AHA model increased the c-statistic to 0.80 (0.78 to 0.83) in men and 0.81 (0.79 to 0.84) in women. Sensitivity and specificity of the ACC/AHA model did not drastically change after addition of NT-proBNP. NRI(95%CI) was - 23.8% (- 19.2%; - 28.4%) in men and - 27.6% (- 30.7%; - 24.5%) in women for events and 57.9% (54.8%; 61.0%) in men and 52.8% (50.3%; 55.5%) in women for non-events.ConclusionsAcceptable performance of the model based on risk factors included in the ACC/AHA model advocates use of this model for prediction of HF risk in primary prevention setting. Addition of NT-proBNP modestly improved the model performance but did not lead to relevant discrimination improvement in clinical risk reclassification.
| S-EPMC7885616 | biostudies-literature
Project description:AimsThe Cardiac Lipid Panel (CLP) is a newly discovered panel of metabolite-based biomarkers that has shown to improve the diagnostic value of N terminal pro B type natriuretic peptide (NT-proBNP). However, little is known about its usefulness in predicting outcomes. In this study, we developed a risk score for 4-year cardiovascular death in elderly chronic heart failure (CHF) patients using the CLP.Methods and resultsFrom the Cardiac Insufficiency Bisoprolol Study in Elderly trial, we included 280 patients with CHF aged >65 years. A targeted metabolomic analysis of the CLP biomarkers was performed on baseline serum samples. Cox regression was used to determine the association of the biomarkers with the outcome after accounting for established risk factors. A risk score ranging from 0 to 4 was calculated by counting the number of biomarkers above the cut-offs, using Youden index. During the mean (standard deviation) follow-up period of 50 (8) months, 35 (18%) subjects met the primary endpoint of cardiovascular death. The area under the receiver operating curve for the model based on clinical variables was 0.84, the second model with NT-proBNP was 0.86, and the final model with the CLP was 0.90. The categorical net reclassification index was 0.25 using three risk categories: 0-60% (low), 60-85% (intermediate), and >85% (high). The continuous net reclassification index was 0.772, and the integrated discrimination index was 0.104.ConclusionsIn patients with CHF, incorporating a panel of three metabolite-based biomarkers into a risk score improved the prognostic utility of NT-proBNP by predicting long-term cardiovascular death more precisely. This novel approach holds promise to improve clinical risk assessment in CHF patients.
| S-EPMC7524071 | biostudies-literature
Project description:BackgroundThe prevalence and prognostic value of chronic heart failure (CHF) in the setting of Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) infection has seldom been studied. The aim of this study was to analyze the prevalence and prognosis of CHF in this setting.MethodsThis single-center study included 829 consecutive patients with SARS-CoV-2 infection from February to April 2020. Patients with a previous history of CHF were matched 1:2 for age and sex. We analyze the prognostic value of pre-existing CHF. Prognostic implications of N terminal pro brain natriuretic peptide (NT-proBNP) levels on admission in the CHF cohort were explored.ResultsA total of 129 patients (43 CHF and 86 non-CHF) where finally included. All-cause mortality was higher in CHF patients compared to non-CHF patients (51.2% vs. 29.1%, p = 0.014). CHF was independently associated with 30-day mortality (hazard ratio (HR) 2.3, confidence interval (CI) 95%: 1.26-2.4). Patients with CHF and high-sensitivity troponin T < 14 ng/L showed excellent prognosis. An NT-proBNP level > 2598 pg/mL on admission was associated with higher 30-day mortality in patients with CHF.ConclusionsAll-cause mortality in CHF patients hospitalized due to SARS-CoV-2 infection was 51.2%. CHF was independently associated with all-cause mortality (HR 2.3, CI 95% 1.26-4.2). NT-proBNP levels could be used for stratification risk purposes to guide medical decisions if larger studies confirm this finding.
| S-EPMC7829899 | biostudies-literature
Project description:AimThe purpose of this study was to explore the utility of two single-item self-report (SR) questions to assess physical inactivity in patients with heart failure (HF).Methods and resultsThis is a cross-sectional study using data from 106 patients with HF equipped with accelerometers for 1 week each. Two SR items relating to physical activity were also collected. Correlations between accelerometer activity counts and the SR items were analysed. Patients were classified as physically active or inactive on the basis of accelerometer counts, and the SR items were used to try to predict that classification. Finally, patients were classified as having high self-reported physical activity or low self-reported physical activity, on the basis of the SR items, and the resulting groups were analysed for differences in actual physical activity. There were significant but weak correlations between the SR items and accelerometer counts: ρ = 0.24, P = 0.016 for SR1 and ρ = 0.21, P = 0.033 for SR2. Using SR items to predict whether a patient was physically active or inactive produced an area under the curve of 0.62 for SR1, with a specificity of 92% and a sensitivity of 30%. When dividing patients into groups on the basis of SR1, there was a significant difference of 1583 steps per day, or 49% more steps in the high self-reported physical activity group (P < 0.001).ConclusionsThere might be utility in the single SR question for high-specificity screening of large populations to identify physically inactive patients in order to assign therapeutic interventions efficiently where resources are limited.
| S-EPMC7373918 | biostudies-literature
Project description:Measuring genome-wide changes in transcript abundance in circulating peripheral whole blood cells is a useful way to study disease pathobiology and may help elucidate biomarkers and molecular mechanisms of disease. The sensitivity and interpretability of analyses carried out in this complex tissue, however, are significantly affected by its heterogeneity. It is therefore desirable to quantify this heterogeneity, either to account for it or to better model interactions that may be present between the abundance of certain transcripts, some cell types and some indication. Accurate enumeration of the many component cell types that make up peripheral whole blood can be costly, however, and may further complicate the sample collection process. Many approaches have been developed to infer the composition of a sample from high-dimensional transcriptomic and, more recently, epigenetic data. These approaches rely on the availability of isolated expression profiles for the cell types to be enumerated. These profiles are platform-specific, suitable datasets are rare, and generating them is expensive. No such dataset exists on the Affymetrix Gene ST platform. We present a freely-available, and open-source, multiresponse Gaussian model capable of accurately inferring the composition of peripheral whole blood samples from Affymetrix Gene ST expression profiles. The model was developed on a cohort of patients with chronic obtructive pulmonary disease and tested in chronic heart failure patients.
2016-05-25 | GSE77343 | GEO
Project description:Background:Chronic heart failure (CHF) is a global health burden. Despite advances in treatment, there remain well-recognised morbidity and mortality. Risk stratification requires the identification and validation of biomarkers, old and new. Hyponatremia has re-emerged as a prognostic marker in CHF patients. Methods:This is a retrospective cohort study on 241 CHF patients recruited from King Fahd Hospital of the University, Al-Khobar, Saudi Arabia (January 2005-December 2016). Their serum sodium and biochemical parameters were measured at baseline, along with 2-D echocardiographic assessments of left ventricular mass and ejection fraction. The primary endpoint was the association between hyponatremia and all-cause mortality (ACM) after a follow-up period of 24 months. Results:Mean age of patients was 60.61 ± 12.63 (SD) years; 65.1% were males, and type 2 diabetes mellitus (DM) was present in 71%. Baseline serum sodium was 138.00 (136, 140) (median and interquartile range). Hyponatremia (<135 meq/L) was present in 14.1%. After follow-up, 46 deaths had occurred. Multivariate Cox-proportional hazard model showed that type 2 DM, New York Heart Association (NYHA) class (III-IV vs I-II), age, and left ventricular mass index (LVMI) were significant and independent predictors of ACM, with HR 3.03 (95% CI; 1.13, 8.16) (P=0.028), HR 2.31 (95% CI; 1.11, 4.82) (P=0.026), HR 1.06 (95% CI; 1.03, 1.09) (P<0.001), and HR 1.01 (95% CI; 1.00, 1.02) (P=0.039), respectively. Estimated glomerular filtration rate (eGFR) was not a significant predictor. Kaplan-Meier survival analysis was used for the analysis of NYHA class and hyponatremia interactions and showed that hyponatremia had an association with poorer survival in patients with NYHA class III-IV rather than I-II (Log-rank test, P= 0.0009). Conclusion:Hyponatremia was a feature in CHF patients, and ACM was predicted by type 2 DM, NYHA class, age, and LVMI. Hyponatremia impact on survival was in patients with more advanced disease.
| S-EPMC7381090 | biostudies-literature