比亚韦斯托克医科大学

Background and Aims Patients with established atherosclerotic cardiovascular disease (ASCVD) are at high risk of developing heart failure (HF). However, incident HF is not part of the risk assessment of current guideline-recommended models. The aim of this study was to develop and externally validate the SMART2-HF model for prediction of incident HF in patients with ASCVD.Methods SMART2-HF was developed in 7698 individuals with established ASCVD (coronary, cerebrovascular, or peripheral artery disease, or abdominal aortic aneurysm) but without prior HF from the UCC-SMART cohort. Cox proportional hazards models including sex-predictor interactions and with age as the time scale were derived to estimate the 10-year and lifetime risk of incident HF (hospitalization for HF or HF-related death), accounting for competing non-HF mortality. Predictors, limited to routinely available clinical characteristics, were aligned with the SMART2 risk model for recurrent cardiovascular (CV) risk in the same population. External validation was performed in 240 741 patients with ASCVD from six data sources: the Clinical Practice Research Datalink, the HUNT3 study, the SWEDEHEART Registry, the ASCVD-Particles cohort, the Estonian Biobank and the international REACH Registry.Results During a median follow-up of 11.2 years (interquartile range 6.1-16.4 years), 1031 incident HF events (13%) occurred in the UCC-SMART cohort. In the external validation data sources, a total of 24 885 incident HF events (10%) occurred. The pooled C-statistic was .696 (95% confidence interval .674-.717), with consistent performance in subgroups by sex and type of ASCVD. Predicted risks matched observed incidence in external validation.Conclusions The SMART2-HF model enables the prediction of incident HF in patients with ASCVD. Aligned with the guideline-recommended SMART2 model for recurrent CV risk, SMART2-HF can be used as a complementary tool in this population.

BACKGROUND:Guidelines recommend using the SMART2 model, estimating the risk of recurrent cardiovascular (CV) events, to support treatment decisions in patients with established atherosclerotic CV disease (ASCVD). They further outline that adding biomarkers, comorbidities, anthropometric, and social factors may improve these predictions. AIMS:To investigate the added predictive value of guideline-outlined factors including biomarkers, comorbidities, anthropometric, and social factors on top of the SMART2 model using an approach enabling their use as add-on predictors. METHODS:Patients aged 40-80 with ASCVD were included from 11 cohorts (n=179,382 with 25,789 recurrent CV events). Additional factors included biomarkers (troponin I, NT-proBNP, albuminuria), comorbidities (heart failure, atrial fibrillation, coronary multivessel disease), anthropometric measurements (body-mass index, waist and hip circumference), social (employment, education), and other factors (former smoking, parental CV history). Cross-cohort availability of these factors ranged from 2 cohorts for albuminuria to all cohorts for BMI. These factors were assessed as add-on predictors to the SMART2 model using Fine-Gray models with SMART2 coefficients as offset with recurrent CV events as primary outcome (non-fatal myocardial infarction or stroke, or CV death). Added predictive value was assessed through cohort cross validation by change (Δ) in C--statistic, calibration, and net benefit through decision curve analysis. RESULTS:Sub distribution hazard ratios for additional factors ranged from 0.77 [95% confidence interval 0.75-0.80] for employment status to 1.69 [1.63-1.76] for heart failure history. ΔC-statistic was largest for NT-proBNP (0.0127 [0.0060-0.0193]) and troponin I (0.0100 [0.0020-0.0181]), with statistically significant but smaller ΔC-statistics for employment, heart failure, and atrial fibrillation. Calibration was adequate before and after integration of additional factors. Decision curve analysis demonstrated added net benefit beyond SMART2 for NT-proBNP, heart failure history, atrial fibrillation, albuminuria, current employment, coronary multivessel disease, and education level across clinically relevant thresholds up to 40% predicted risk. CONCLUSIONS:The flexible add-on of guideline-outlined factors on top of SMART2 enables more personalised and improved estimation of recurrent CV event risk in patients with established ASCVD.

BACKGROUND AND AIMS:Heart failure (HF) with preserved ejection fraction (HFpEF) constitutes a heterogeneous disease with varying prognosis. Given the rising incidence of HFpEF, accurate risk prediction for these patients is needed to identify high-risk individuals, who may benefit the most from preventive treatments. The LIFE-Preserved model was developed and validated for the prediction of individual short-term and lifetime risk for HF hospitalization or cardiovascular (CV) death in patients with HFpEF. METHODS:LIFE-Preserved was derived in 20 332 patients aged 40-90 years with a left ventricular ejection fraction ≥ 50% from the Swedish HF Registry. Cause- and sex-specific Cox models were derived to predict the risk of HF hospitalization or CV death using 14 routinely available predictors. Use of age as the timescale allowed for predictions beyond the maximum follow-up duration in the derivation data, adjusted for competing risks. External validation was performed in two trials (EMPEROR-Preserved and TOPCAT-Americas) and three registries (NHS England Secure Data Environment, Veterans Affairs, and HF-Particles). Model performance was assessed by discrimination and calibration. RESULTS:During a median follow-up of 1.8 years (interquartile range .6-4.2, maximum 19 years), 9341 first HF hospitalizations or CV deaths (46%) were observed in Swedish HF Registry. External validation included data from 28 062 patients with HFpEF [9930 (35%) first HF hospitalizations or CV deaths]. Pooled C-statistics were .714 (95% confidence interval .652-.775) in trials and .658 (95% confidence interval .599-.717 in registries, with adequate calibration in all external validation sources. Performance was similar in men and women. An interactive calculator of the LIFE-Preserved model has been made available here. CONCLUSIONS:The LIFE-Preserved model enables prediction of short-term and lifetime risk of HF hospitalization or CV death in patients with HFpEF. The model could serve as a tool to identify high-risk HFpEF patients, guiding clinical management and shared decision-making.

Foodborne pathogens, including Salmonella enterica serovar Typhimurium (S. Typhimurium), pose a significant threat to both human health and livestock productivity. The pandemic S. Typhimurium ST34 clone acquired a genomic island (SGI-4) conferring high copper resistance, an adaptation relevant in the context of the widespread use of copper sulphate at therapeutic levels in pig farming. We investigated how high dietary copper influences the piglet gut microbiota and Salmonella-microbiota interactions that may explain the global spread of S. Typhimurium ST34. An on-farm study combined with faecal shotgun metagenomics revealed that several potential Salmonella competitor species, including Bifidobacterium, Escherichia, and Lactobacillus, were less abundant in piglets on high-copper diets. Anaerobic and aerobic culturing alongside whole genome sequencing of 131 species and copper sulphate susceptibility testing identified copper resistance gene acquisition in selected microbes, particularly within Escherichia. Niche competition assays demonstrated that copper resistance is critical for inter-species competition under high-copper conditions, with Salmonella’s Type VI Secretion System providing a distinct advantage over Escherichia in the copper-modified niche. Our findings suggest that copper supplementation alters the piglet gut environment, impacting competitive dynamics between pathogenic and commensal bacteria, likely to influence the zoonotic transmission of pathogens.

Introduction: Sauna bathing, traditionally associated with relaxation in Nordic countries, is increasingly regarded as a tool supporting cardiovascular prevention and post-exercise recovery. As its use becomes more widespread, questions arise about the safety of this form of heat exposure, the mechanisms by which it affects the cardiovascular system and autonomic regulation, and how it can be integrated into training programmes for athletes and physically active individuals. Aim: The aim of this narrative review is to organize current knowledge on the acute and chronic effects of sauna bathing on haemodynamic parameters, sympathetic–parasympathetic balance and post-exercise recovery, with particular emphasis on potential benefits, risks, contraindications and practical aspects of dosing the thermal stimulus. State of knowledge: Available studies indicate that a single sauna session induces predictable circulatory changes – peripheral vasodilation, an increase in heart rate and cardiac output with a moderate reduction in arterial blood pressure, and transient hypovolaemia. Regular sauna bathing has been associated in long-term observations with a more favourable cardiovascular profile, improvement in selected indices of sinus rhythm variability, better subjective well-being and improved exercise tolerance. In athletic populations, sauna may support the perception of recovery, promote muscle relaxation and facilitate glycogen resynthesis, provided that it is used with adequate attention to hydration and appropriate dosing of heat stress. Conclusions: Sauna appears to be a valuable and relatively simple adjunct to cardiovascular prevention strategies and recovery programmes, but it does not replace physical activity or causal treatment. Further interventional studies are needed to refine optimal protocols of sauna bathing in the general population and in elite sport, and to better define groups in whom the benefits outweigh the risks.