233 resultados para Heart


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Objectives: This study sought to investigate the effect of a multiple micronutrient supplement on left ventricular ejection fraction (LVEF) in patients with heart failure. Background: Observational studies suggest that patients with heart failure have reduced intake and lower concentrations of a number of micronutrients. However, there have been very few intervention studies investigating the effect of micronutrient supplementation in patients with heart failure. Methods: This was a randomized, double-blind, placebo-controlled, parallel-group study involving 74 patients with chronic stable heart failure that compared multiple micronutrient supplementation taken once daily versus placebo for 12 months. The primary endpoint was LVEF assessed by cardiovascular magnetic resonance imaging or 3-dimensional echocardiography. Secondary endpoints were Minnesota Living With Heart Failure Questionnaire score, 6-min walk test distance, blood concentrations of N-terminal prohormone of brain natriuretic peptide, C-reactive protein, tumor necrosis factor alpha, interleukin-6, interleukin-10, and urinary levels of 8-iso-prostaglandin F2 alpha. Results: Blood concentrations of a number of micronutrients increased significantly in the micronutrient supplement group, indicating excellent compliance with the intervention. There was no significant difference in mean LVEF at 12 months between treatment groups after adjusting for baseline (mean difference: 1.6%, 95% confidence interval: -2.6 to 5.8, p = 0.441). There was also no significant difference in any of the secondary endpoints at 12 months between treatment groups. Conclusions: This study provides no evidence to support the routine treatment of patients with chronic stable heart failure with a multiple micronutrient supplement. (Micronutrient Supplementation in Patients With Heart Failure [MINT-HF]; NCT01005303).

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Objective
To examine age and gender specific trends in coronary heart disease (CHD) and stroke mortality in two neighbouring countries, the Republic of Ireland (ROI) and Northern Ireland (NI). Design Epidemiological study of time trends in CHD and stroke mortality.

Setting/patients
The populations of the ROI and NI, 1985–2010.

Interventions
None.

Main outcome measures
Directly age standardised CHD and stroke mortality rates were calculated and analysed using joinpoint regression to identify years where the slope of the linear trend changed significantly. This was performed separately for specific age groups (25–54, 55–64, 65–74 and 75–84 years) and by gender. Annual percentage change (APC) and 95% CIs are presented.

Results
There was a striking similarity between the two countries, with percentage change between 1985 and 1989 and between 2006 and 2010 of 67% and 69% in
CHD mortality, and 64% and 62% in stroke mortality for the ROI and NI, respectively. However, joinpoint analysis identified differences in the pace of change between the two countries. There was an accelerated pace of decline (negative APC) in mortality for both CHD and stroke in both countries from the mid-1990s (APC ROI −8% (95% CI −9.5 to 6.5) and NI −6.6% (−6.9 to −6.3)), but the accelerated decrease started later for CHD mortality in the ROI. In recent years, a levelling off in CHD mortality was observed in the 25–54 year age group in NI and in stroke mortality for men and women in the ROI.

Conclusions
While differences in the pace of change in mortality were observed at different time points, similar, substantial decreases in CHD and stroke mortality were achieved between 1985 and 1989 and between 2006 and 2010 in the ROI and NI despite important differences in health service structures. There is evidence of a levelling in mortality rates in some groups in recent years.

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In this paper, a low complexity system for spectral analysis of heart rate variability (HRV) is presented. The main idea of the proposed approach is the implementation of the Fast-Lomb periodogram that is a ubiquitous tool in spectral analysis, using a wavelet based Fast Fourier transform. Interestingly we show that the proposed approach enables the classification of processed data into more and less significant based on their contribution to output quality. Based on such a classification a percentage of less-significant data is being pruned leading to a significant reduction of algorithmic complexity with minimal quality degradation. Indeed, our results indicate that the proposed system can achieve up-to 45% reduction in number of computations with only 4.9% average error in the output quality compared to a conventional FFT based HRV system.

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Background

Chronic kidney disease is now regarded as a risk factor for cardiovascular disease. The impact of occupational or non-occupational physical activity (PA) on moderate decreases of renal function is uncertain.

Objectives

We aimed to identify the potential association of PA (occupational and leisure-time) on early decline of estimated glomerular filtration rate (eGFR) and to determine the potential mediating effect of PA on the relationship between eGFR and heart disease.

Methods

From the PRIME study analyses were conducted in 1058 employed men. Energy expended during leisure, work and commuting was calculated. Linear regression analyses were used to determine the link between types of PA and moderate decrements of eGFR determined with the KDIGO guideline at the baseline assessment. Cox proportional hazards analyses were used to explore the potential effect of PA on the relationship between eGFR and heart disease, ascertained during follow-up over 10 years.

Results

For these employed men, and after adjustment for known confounders of GFR change, more time spent sitting at work was associated with increased risk of moderate decline in kidney function, while carrying objects or being active at work was associated with decreased risk. In contrast, no significant link with leisure PA was apparent. No potential mediating effect of occupational PA was found for the relationship between eGFR and coronary heart disease.

Conclusion

Occupational PA (potential modifiable factors) could provide a dual role on early impairment of renal function, without influence on the relationship between early decrease of e-GFR and CHD risk.

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Commentary on

Rautiainen S, Levitan EB, Mittleman MA, et al. Total antioxidant capacity of diet and risk of heart failure: a population-based prospective cohort of women. Am J Med 2013;126:494–500.

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Background

Although life expectancy continues to increase in the Republic of Ireland (ROI) and Northern Ireland (NI), coronary heart disease (CHD) remains a leading cause of death and disability in older adults. Some, but not all, of the socioeconomic inequality in cardiovascular disability can be explained by a social gradient in conventional risk factors. The aims of the research were to assess CHD-related disability, and to establish the prevalence and population attributable fractions (PAFs) of risk factors for CHD-related disability across gender and socioeconomic groups in older adults in NI and ROI.

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Today there is a growing interest in the integration of health monitoring applications in portable devices necessitating the development of methods that improve the energy efficiency of such systems. In this paper, we present a systematic approach that enables energy-quality trade-offs in spectral analysis systems for bio-signals, which are useful in monitoring various health conditions as those associated with the heart-rate. To enable such trade-offs, the processed signals are expressed initially in a basis in which significant components that carry most of the relevant information can be easily distinguished from the parts that influence the output to a lesser extent. Such a classification allows the pruning of operations associated with the less significant signal components leading to power savings with minor quality loss since only less useful parts are pruned under the given requirements. To exploit the attributes of the modified spectral analysis system, thresholding rules are determined and adopted at design- and run-time, allowing the static or dynamic pruning of less-useful operations based on the accuracy and energy requirements. The proposed algorithm is implemented on a typical sensor node simulator and results show up-to 82% energy savings when static pruning is combined with voltage and frequency scaling, compared to the conventional algorithm in which such trade-offs were not available. In addition, experiments with numerous cardiac samples of various patients show that such energy savings come with a 4.9% average accuracy loss, which does not affect the system detection capability of sinus-arrhythmia which was used as a test case.