Patients with type 2 MI and NIMI were older, with higher proportion of women and more comorbidities than patients with type 1 MI. Absolute mortality and the adjusted risk for all-cause mortality in both groups were significantly higher than that of patients with type 1 MI (39.7%, HR: 1.41 95% CI 1.02 to 1.94, p=0.038 and 40.0%, HR: 1.54 95% CI 1.16 to 2.04, p=0.002, respectively). Patients with type 2 MI and NIMI tended to present more readmissions due to heart failure (16.5%, HR: 1.55 95% CI 0.87 to 2.76, p=0.133 and 12.3%, HR: 1.15 95% CI 0.70 to 1.90, p=0.580) and less readmission rates due to acute coronary syndrome (ACS) than patients with type 1 MI (2.1%, HR: 0.11 95% CI 0.04 to 0.31, p<0.001 and 4.3%, HR: 0.22 95% CI 0.12 to 0.41, p<0.001), CONCLUSIONS: Patients diagnosed with type 2 MI and NIMI have higher rates of mortality and lower readmission rates for ACS compared with patients with type 1 MI.

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AimsBetter management of heart failure (HF) over the past two decades has improved survival, mainly by reducing the incidence of death due to cardiovascular (CV) causes. Deaths due to non-CV causes, particularly cancer, may be increasing. This study explored the modes of death of consecutive patients who attended a HF clinic over A total of 935 deaths were ascertained from 2002 to 2018 among 1876 patients (mean age 65.8 ± 12.5 years, 75% men, left ventricular ejection fraction < 50%) admitted to our HF clinic. Median follow-up was 4.2 years [1.9-7.8].Mode of death was curated from patient health records and verified by the Catalan and Spanish health system databases. Trends for every mode of death were assessed by polynomial regression. Two trends were observed: a significant reduction in sudden death (P = 0.03) without changes in HF progression as mode of death (P = 0.26), and a significant increase in non-CV modes of death (P < 0.001). Non-CV deaths accounted for 17.4% of deaths in 2002 and 65.8% of deaths in 2018. A total 138 deaths were due to cancer (37% of non-CV deaths). A significant trend was observed towards a progressive increase in cancer deaths over time (P = 0.002).

Important differences in comorbidities and clinical characteristics exist between women and men with heart failure (HF). In particular, differences in the kinetics of biological circulating biomarkers—a critical component of cardiovascular care—are highly relevant. Most circulating HF biomarkers are assessed daily by clinicians without taking sex into account, despite the multiple gender-related differences observed in plasma concentrations. Even in health, compared to men, women tend to exhibit higher levels of natriuretic peptides and galectin-3 and lower levels of cardiac troponins and the cardiac stress marker, soluble ST2. Many biological factors can provide a reliable explanation for these differences, like body composition, fat distribution, or menopausal status. Notwithstanding, these sex-specific differences in biomarker levels do not reflect different pathobiological mechanisms in HF between women and men, and they do not necessarily imply a need to use different diagnostic cut-off levels in clinical practice. To date, the sex-specific prognostic value of HF biomarkers for risk stratification is an unresolved issue that future research must elucidate. This review outlines current evidence regarding gender-related differences in circulating biomarkers widely used in HF, the pathophysiological mechanisms underlying these differences, and their clinical relevance.

Patients with cardiovascular risk factors or established cardiovascular disease have an increased risk of developing coronavirus disease 19 and have a worse outcome when infected, but translating this notion into effective action is challenging. At present it is unclear whether cardiovascular therapies may reduce the likelihood of infection, or improve the survival of infected patients. Given the crucial importance of this issue for clinical cardiologists and all specialists dealing with coronavirus disease 19, we tried to recapitulate the current evidence and provide some practical recommendations.

Monocytes are a heterogeneous population of effector cells with key roles in tissue integrity restoration and maintenance. Here, we explore the association of monocyte subsets and prognosis in patients with ambulatory heart failure (HF). Monocyte subsets were classified as classical (CD14++/CD16–), intermediate (CD14++/CD16+), or non-classical (CD14+/CD16++). Percentage distribution and absolute cell count were assessed in each subset, and multivariable Cox regression analyses were performed with all-cause death, HF-related hospitalization, and the composite end-point of both as dependent variables. 400 patients were consecutively included (72.8% male, age 69.4±12.2 years, 45.5% from ischemic aetiology, left ventricle ejection fraction (LVEF) 41.6% ±14.5, New York Heart Association (NYHA) class II 62.8% and III 30.8%). During a mean follow-up of 2.6±0.9 years, 107 patients died, 99 had a HF-related hospitalization and 160 suffered the composite end-point of all-cause death or HF-related hospitalization. Monocyte subsets assessed in percentages were not independently associated to any of the end-points. When considering number of cells/μL, intermediate subset was independently associated with an increase of all-cause death (HR 1.25 [95% CI 1,02–1.52], p = 0.03), and the composite end-point HR 1.20 [95% CI 1,03–1.40], p = 0.02). The presented findings show that absolute cell count of monocyte subsets was preferred over monocyte percentage for prognosis stratification for outpatients with HF. The intermediate monocyte subset provides information on increased risk of all-cause death and the composite end-point.

BackgroundHeart failure (HF) is associated with a high rate of readmissions within 30 days post-discharge and in the following year, especially in frail elderly patients. Biomarker data are scarce in this high-risk population. This study assessed the value of early post-discharge circulating levels of ST2, NT-proBNP, CA125, and hs-TnI for predicting 30-day and 1-year outcomes in comorbid frail elderly patients with HF with mainly preserved ejection fraction (HFpEF).MethodsBlood samples were obtained at the first visit shortly after discharge (4.9 ± 2 days). The primary endpoint was the composite of all-cause mortality or HF-related rehospitalization at 30 days and at 1 year. All-cause mortality alone at one year was also a major endpoint. HF-related rehospitalizations alone were secondary end-points.ResultsFrom February 2014 to November 2016, 522 consecutive patients attending the STOP-HF Clinic were included (57.1% women, age 82 ± 8.7 years, mean Barthel index 70 ± 25, mean Charlson comorbidity index 5.6 ± 2.2). The composite endpoint occurred in 8.6% patients at 30 days and in 38.5% at 1 year. In multivariable analysis, ST2 [hazard ratio (HR) 1.53; 95% CI 1.19–1.97; p = 0.001] was the only predictive biomarker at 30 days; at 1 year, both ST2 (HR 1.34; 95% CI 1.15–1.56; p < 0.001) and NT-proBNP (HR 1.19; 95% CI 1.02–1.40; p = 0.03) remained significant. The addition of ST2 and NT-proBNP into a clinical predictive model increased the AUC from 0.70 to 0.75 at 30 days (p = 0.02) and from 0.71 to 0.74 at 1 year (p < 0.05). For all-cause death at 1 year, ST2 (HR 1.50; 95% CI 1.26–1.80; p < 0.001), and CA125 (HR 1.41; 95% CI 1.21–1.63; p < 0.001) remained independent predictors in multivariable analysis. The addition of ST2 and CA125 into a clinical predictive model increased the AUC from 0.74 to 0.78 (p = 0.03). For HF-related hospitalizations, ST2 was the only predictive biomarker in multivariable analyses, both at 30 days and at 1 year.ConclusionsIn a comorbid frail elderly population with HFpEF, ST2 outperformed NT-proBNP for predicting the risk of all-cause mortality or HF-related rehospitalization. ST2, a surrogate marker of inflammation and fibrosis, may be a better predictive marker in high-risk HFpEF.Electronic supplementary materialThe online version of this article (10.1186/s12877-018-0807-2) contains supplementary material, which is available to authorized users.

Several heart failure (HF) web-based risk scores are currently used in clinical practice. Currently, we lack head-to-head comparison of the accuracy of risk scores. This study aimed to assess correlation and mortality prediction performance of Meta-Analysis Global Group in Chronic Heart Failure (MAGGIC-HF) risk score, which includes clinical variables + medications; Seattle Heart Failure Model (SHFM), which includes clinical variables + treatments + analytes; PARADIGM Risk of Events and Death in the Contemporary Treatment of Heart Failure (PREDICT-HF) and Barcelona Bio-Heart Failure (BCN-Bio-HF) risk calculator, which also include biomarkers, like N-terminal pro B-type natriuretic peptide (NT-proBNP).