Prognostic Value of Cardiovascular Biomarkers in the Population.

Importance: Identification of individuals at high risk for atherosclerotic cardiovascular disease within the population is important to inform primary prevention strategies. Objective: To evaluate the prognostic value of routinely available cardiovascular biomarkers when added to established risk factors. Design, Setting, and Participants: Individual-level analysis including data on cardiovascular biomarkers from 28 general population-based cohorts from 12 countries and 4 continents with assessments by participant age. The median follow-up was 11.8 years. Exposure: Measurement of high-sensitivity cardiac troponin I, high-sensitivity cardiac troponin T, N-terminal pro-B-type natriuretic peptide, B-type natriuretic peptide, or high-sensitivity C-reactive protein. Main Outcomes and Measures: The primary outcome was incident atherosclerotic cardiovascular disease, which included all fatal and nonfatal events. The secondary outcomes were all-cause mortality, heart failure, ischemic stroke, and myocardial infarction. Subdistribution hazard ratios (HRs) for the association of biomarkers and outcomes were calculated after adjustment for established risk factors. The additional predictive value of the biomarkers was assessed using the C statistic and reclassification analyses. Results: The analyses included 164 054 individuals (median age, 53.1 years [IQR, 42.7-62.9 years] and 52.4% were women). There were 17 211 incident atherosclerotic cardiovascular disease events. All biomarkers were significantly associated with incident atherosclerotic cardiovascular disease (subdistribution HR per 1-SD change, 1.13 [95% CI, 1.11-1.16] for high-sensitivity cardiac troponin I; 1.18 [95% CI, 1.12-1.23] for high-sensitivity cardiac troponin T; 1.21 [95% CI, 1.18-1.24] for N-terminal pro-B-type natriuretic peptide; 1.14 [95% CI, 1.08-1.22] for B-type natriuretic peptide; and 1.14 [95% CI, 1.12-1.16] for high-sensitivity C-reactive protein) and all secondary outcomes. The addition of each single biomarker to a model that included established risk factors improved the C statistic. For 10-year incident atherosclerotic cardiovascular disease in younger people (aged <65 years), the combination of high-sensitivity cardiac troponin I, N-terminal pro-B-type natriuretic peptide, and high-sensitivity C-reactive protein resulted in a C statistic improvement from 0.812 (95% CI, 0.8021-0.8208) to 0.8194 (95% CI, 0.8089-0.8277). The combination of these biomarkers also improved reclassification compared with the conventional model. Improvements in risk prediction were most pronounced for the secondary outcomes of heart failure and all-cause mortality. The incremental value of biomarkers was greater in people aged 65 years or older vs younger people. Conclusions and Relevance: Cardiovascular biomarkers were strongly associated with fatal and nonfatal cardiovascular events and mortality. The addition of biomarkers to established risk factors led to only a small improvement in risk prediction metrics for atherosclerotic cardiovascular disease, but was more favorable for heart failure and mortality.

A multistate model of health transitions in older people: a secondary analysis of ASPREE clinical trial data.

BACKGROUND: Understanding the nature of transitions from a healthy state to chronic diseases and death is important for planning health-care system requirements and interventions. We aimed to quantify the trajectories of disease and disability in a population of healthy older people. METHODS: We conducted a secondary analysis of data from the ASPREE trial, which was done in 50 sites in Australia and the USA and recruited community-dwelling, healthy individuals who were aged 70 years or older (≥65 years for Black and Hispanic people in the USA) between March 10, 2010, and Dec 24, 2014. Participants were followed up with annual face-to-face visits, biennial assessments of cognitive function, and biannual visits for physical function until death or June 12, 2017, whichever occurred first. We used multistate models to examine transitions from a healthy state to first intermediate disease events (ie, cancer events, stroke events, cardiac events, and physical disability or dementia) and, ultimately, to death. We also examined the effects of age and sex on transition rates using Cox proportional hazards regression models. FINDINGS: 19 114 participants with a median age of 74·0 years (IQR 71·6-77·7) were included in our analyses. During a median follow-up of 4·7 years (IQR 3·6-5·7), 1933 (10·1%) of 19 114 participants had an incident cancer event, 487 (2·5%) had an incident cardiac event, 398 (2·1%) had an incident stroke event, 924 (4·8%) developed persistent physical disability or dementia, and 1052 (5·5%) died. 15 398 (80·6%) individuals did not have any of these events during follow-up. The highest proportion of deaths followed incident cancer (501 [47·6%] of 1052) and 129 (12·3%) participants transitioned from disability or dementia to death. Among 12 postulated transitions, transitions from the intermediate states to death had much higher rates than transitions from a healthy state to death. The progression rates to death were 158 events per 1000 person-years (95% CI 144-172) from cancer, 112 events per 1000 person-years (86-145) from stroke, 88 events per 1000 person-years (68-111) from cardiac disease, 69 events per 1000 person-years (58-82) from disability or dementia, and four events per 1000 person-years (4-5) from a healthy state. Age was significantly associated with an accelerated rate for most transitions. Male sex (vs female sex) was significantly associated with an accelerate rate for five of 12 transitions. INTERPRETATION: We describe a multistate model in a healthy older population in whom the most common transition was from a healthy state to cancer. Our findings provide unique insights into the frequency of events, their transition rates, and the impact of age and sex. These results have implications for preventive health interventions and planning for appropriate levels of residential care in healthy ageing populations. FUNDING: The National Institutes of Health.

Cognitive Decline and Risk of Dementia in Individuals With Heart Failure: A Systematic Review and Meta-analysis.

BACKGROUND: We sought to determine the association between heart failure (HF) and cognitive change and dementia. METHODS AND RESULTS: Systematic search of three electronic databases was performed and 29 eligible studies involving approximately 3 million participants were identified. Twelve studies examined dementia and 20 cognitive change, but only a subset of studies could be included in the meta-analysis. These findings indicated that HF was not significantly associated with dementia (n = 8, hazard ratio 1.18, 95% confidence interval 0.93-1.50), but increased the risk of cognitive impairment (n = 3, hazard ratio 1.80, 95% confidence interval 1.14-2.86) . Additionally, HF was associated with poorer mean cognitive performance in global cognition (Hedges' g -0.73, 95% confidence interval -1.12 to -0.35), memory (Hedges' g -0.57, 95% confidence interval -0.72 to -0.42), executive function (Hedges' g -0.58, 95% confidence interval -0.72 to -0.43), attention/speed (Hedges' g -0.50, 95% confidence interval -0.63 to -0.37) and language (Hedges' g -0.61, 95% confidence interval -1.05 to -0.17). CONCLUSIONS: Patients with HF perform worse on all cognitive tests and have an increased risk of cognitive impairment. These findings highlight the need for clinicians to consider cognition as part of routine care for patients with HF.

Non-Invasive Risk Prediction Based on Right Ventricular Function in Patients with Pulmonary Arterial Hypertension.

BACKGROUND: Right ventricular dysfunction is a major determinant of outcome in pulmonary arterial hypertension (PAH). We aimed to identify echocardiographic right heart parameters associated with adverse outcome and to develop a non-invasive, echocardiography-based risk score for PAH patients. METHODS AND RESULTS: In 254 PAH patients we analyzed functional status, laboratory results, and echocardiographic parameters. We included these parameters to estimate all-cause death or lung transplantation using Cox regression models. The analyses included a conventional model using guideline-recommended variables and an extended echocardiographic model. Based on the final model a 12-point risk score was derived, indicating the association with the primary outcome within five years. During a median follow-up time of 4.2 years 74 patients died or underwent lung transplantation. The conventional model resulted in a C-Index of 0.539, whereas the extended echocardiographic model improved the discrimination (C-index 0.639, p-value 0.017). Ultimately, the newly developed risk score included WHO functional class, 6-min walking distance, N-terminal brain natriuretic peptide concentrations, pericardial effusion, right atrial area, tricuspid annular plane systolic excursion, and fractional area change. CONCLUSION: Integrating right heart function assessed by echocardiography improves prediction of death or lung transplantation in PAH patients. Independent validation of this finding is warranted.

Discrimination of patients with type 2 myocardial infarction.

AIMS: The differentiation of type 1 and type 2 myocardial infarction (T1MI, T2MI) is important, but challenging in the emergency department. We aimed to investigate the clinical characteristics and cardiovascular outcome of T2MI patients and to develop a clinical decision tool to differentiate T1MI and T2MI patients. METHODS AND RESULTS: We prospectively enrolled 1548 patients with suspected MI. All patients were followed for up to 2 years to assess mortality. We used logistic regression with backward step-down selection to determine the most important predictors of T2MI. Based on these regression coefficients, we developed a diagnostic prediction model (score) to diagnose T2MI. T2MI was the final diagnosis of 99 patients. Patients with T2MI showed a high 1-year mortality rate (13.8%), which equals that of T1MI patients (9.4%). Female sex (Beta 1.27 [95% confidence interval; CI 0.67-1.90]), not having radiating chest pain (Beta 1.62 [CI 0.96-2.34]) and a baseline high-sensitivity troponin I concentration ≤ 40.8 ng/L (Beta 1.30 [CI 0.74-1.89]) were the strongest predictors for T2MI. Their combination resulted in an area under the curve of 0.71 to discriminate T1MI and T2MI. The binary score based on this model assigns one point to each of the predictors. Patients with the highest score value of 3 had a 72% probability of T2MI. CONCLUSION: T2MI patients are a heterogeneous population with high-cardiovascular risk. A score based on laboratory and clinical parameters might help to differentiate T1MI and T2MI patients. The additional use of this score in clinical routine needs to be investigated prospectively. TRIAL REGISTRATION: www.clinicaltrials.gov (NCT02355457).

Measurement of homoarginine in human and mouse plasma by LC-MS/MS and ELISA: a comparison and a biological application.

Homoarginine (hArg) is a non-essential amino acid that was identified as a risk marker for cardiovascular disease. Several analytical methods have been described for the quantification of hArg in biological samples. The aim of this study was to compare a liquid chromatography-tandem mass spectrometric (LC-MS/MS) approach with a commercially available enzyme-linked immunosorbent assay (ELISA). Determination of hArg concentrations in ELISA calibration standards measured by both methods revealed a correlation coefficient r (2) of 0.99, for LC-MS/MS calibrators r (2) was 0.997. However, linear regression analysis between the two assays for hArg concentrations in human plasma samples revealed a correlation coefficient r (2) of 0.78. Plasma concentrations obtained from LC-MS/MS are on average 29 % higher than those by ELISA. We investigated the hArg-isobaric N (ε)-trimethyllysine as potential source for the higher observed values, but evaluation of mass spectra indicated that N (ε)-trimethyllysine did not interfere with hArg quantification in our LC-MS/MS method. Both quantification methods were applied to measure hArg in (1) a case-control study of acute coronary syndrome and (2) L-arginine:glycine amidinotransferase-deficient mice. Our LC-MS/MS and the commercially available ELISA assay are suitable for hArg measurement in human and mouse plasma, but different reference values for each method need to be considered.