F1000Prime Recommended Article: The benefits of statins in people without established cardiovascular disease but with cardiovascular risk factors: meta-analysis of randomised controlled trials.

Telemonitoring modalities in heart failure (HF) have been proposed as being essential for future organization and transition of HF care, however, efficacy has not been proven. A comprehensive meta-analysis of studies on home telemonitoring systems (hTMS) in HF and the effect on clinical outcomes are provided. A systematic literature search was performed in four bibliographic databases, including randomized trials and observational studies that were published during January 1996–July 2022. A random-effects meta-analysis was carried out comparing hTMS with standard of care. All-cause mortality, first HF hospitalization, and total HF hospitalizations were evaluated as study endpoints. Sixty-five non-invasive hTMS studies and 27 invasive hTMS studies enrolled 36 549 HF patients, with a mean follow-up of 11.5 months. In patients using hTMS compared with standard of care, a significant 16% reduction in all-cause mortality was observed [pooled odds ratio (OR): 0.84, 95% confidence interval (CI): 0.77–0.93, I²: 24%], as well as a significant 19% reduction in first HF hospitalization (OR: 0.81, 95% CI 0.74–0.88, I²: 22%) and a 15% reduction in total HF hospitalizations (pooled incidence rate ratio: 0.85, 95% CI 0.76–0.96, I²: 70%). These results are an advocacy for the use of hTMS in HF patients to reduce all-cause mortality and HF-related hospitalizations. Still, the methods of hTMS remain diverse, so future research should strive to standardize modes of effective hTMS. Summary results for all-cause mortality, first heart failure hospitalization, and total/recurrent heart failure hospitalizations divided in invasive home telemonitoring systems and non-invasive home telemonitoring systems and total. I² represents heterogeneity between studies. CI, confidence interval.

Background and Aims: Heart failure (HF) is a major public health issue, imposing substantial costs on healthcare systems and societies. This study aimed to provide a contemporary overview of its global economic impact. Methods: A systematic search of four databases was conducted according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines. Studies reporting direct cost (DC) and/or indirect cost (IC) associated with HF were included. DC and IC were expressed as a percentage of current healthcare expenditure (CHE) and gross domestic product (GDP), which were obtained for 2021 from the World Health Organization Global Health Expenditure Database. Countries were categorized by their Human Development Index (HDI), and weighted group means were calculated to estimate costs based on their 2021 expenditure. Results: Thirty-two studies met the inclusion criteria. In 2021, the estimated economic burden of HF was $284.17 billion across 179 countries. This included $136.86 billion (48.16%) in DC and $147.31 (51.84%) billion in IC. Very high HDI countries account for most absolute HF spending, but HF comprises a smaller share of CHE and GDP (1.07% DC, 0.09% IC) compared with low HDI countries (8.85% DC, 0.29% IC). Conclusions: The global economic burden of HF is substantial, increasing, and varies across countries. Although very high and high HDI countries carry most of the absolute costs, low HDI countries bear a disproportionate burden relative to their total healthcare expenditure or GDP. Data scarcity in these settings further impedes accurate burden estimates. To address this growing challenge, proactive and cost-effective measures tailored to each country’s healthcare system are crucial in optimizing HF care worldwide.

Adjustment of treatment based on remote monitoring of pulmonary artery (PA) pressure may reduce the risk of hospital admission for heart failure (HF). We have conducted a meta-analysis of large randomized trials investigating this question. A systematic literature search was performed for randomized clinical trials with PA pressure monitoring devices in patients with HF. The primary outcome of interest was the total number of HF hospitalizations. Other outcomes assessed were urgent visits leading to treatment with intravenous diuretics, all-cause mortality, and composites. Treatment effects are expressed as hazard ratios, and pooled effect estimates were obtained applying random effects meta-analyses. Three eligible randomized clinical trials were identified that included 1898 outpatients in New York Heart Association functional classes II–IV, either hospitalized for HF in the prior 12 months or with elevated plasma NT-proBNP concentrations. The mean follow-up was 14.7 months, 67.8% of the patients were men, and 65.8% had an ejection fraction ≤40%. Compared to patients in the control group, the hazard ratio (95% confidence interval) for total HF hospitalizations in those randomized to PA pressure monitoring was 0.70 (0.58–0.86) (P = .0005). The corresponding hazard ratio for the composite of total HF hospitalizations, urgent visits and all-cause mortality was 0.75 (0.61–0.91; P = .0037) and for all-cause mortality 0.92 (0.73–1.16). Subgroup analyses, including ejection fraction phenotype, revealed no evidence of heterogeneity in the treatment effect. The use of remote PA pressure monitoring to guide treatment of patients with HF reduces episodes of worsening HF and subsequent hospitalizations. The upper part of the figure shows the characteristics of the included RCTs at the sides, and the pulmonary artery sensor, patient electronics system, and the pulmonary artery pressure database in the middle. In the lower part of the figure, the x axis presents the risk ratio, the y axis presents the data points of clinical endpoints as addressed, the dot is the point estimate of the hazard ratio pooled estimate, and the bars correspond to the 95% confidence interval. CI, confidence interval; EF, ejection fraction; HR, hazard ratio; HF, heart failure; HFH, heart failure hospitalization; M, months; NT-proBNP, N-terminal pro-B-type natriuretic peptide; NYHA, New York Heart Association; PA, pulmonary artery.

The efficacy of angiotensin-converting enzyme (ACE)-inhibitors in stable coronary artery disease (CAD) may be increased by targeting the therapy to those patients most likely to benefit. However, these patients cannot be identified by clinical characteristics. We developed a genetic profile to predict the treatment benefit of ACE-inhibitors exist and to optimize therapy with ACE-inhibitors. In 8907 stable CAD patients participating in the randomized placebo-controlled EUROPA-trial, we analysed 12 candidate genes within the pharmacodynamic pathway of ACE-inhibitors, using 52 haplotype-tagging-single nucleotide polymorphisms (SNPs). The primary outcome was the reduction in cardiovascular mortality, non-fatal myocardial infarction, and resuscitated cardiac arrest during 4.2 years of follow-up. Multivariate Cox regression was performed with multiple testing corrections using permutation analysis. Three polymorphisms, located in the angiotensin-II type I receptor and bradykinin type I receptor genes, were significantly associated with the treatment benefit of perindopril after multivariate adjustment for confounders and correction for multiple testing. A pharmacogenetic score, combining these three SNPs, demonstrated a stepwise reduction of risk in the placebo group and a stepwise decrease in treatment benefit of perindopril with an increasing scores (interaction P < 0.0001). A pronounced treatment benefit was observed in a subgroup of 73.5% of the patients [hazard ratio (HR) 0.67; 95% confidence interval (CI) 0.56–0.79], whereas no benefit was apparent in the remaining 26.5% (HR 1.26; 95% CI 0.97–1.67) with a trend towards a harmful effect. In 1051 patients with cerebrovascular disease from the PROGRESS-trial, treated with perindopril or placebo, an interaction effect of similar direction and magnitude, although not statistically significant, was observed. The current study is the first to identify genetic determinants of treatment benefit of ACE-inhibitor therapy. We developed a genetic profile which predicts the treatment benefit of ACE-inhibitors and which could be used to optimize therapy.