101 resultados para Cardiac


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Cardiac surgery often generates oxidative stress leading to ischemia reperfusion injury (I-R). Antioxidants have been shown to prevent this injury and have been added to cardioplegic solutions to assist in recovery. In this study, we tested the effectiveness of sodium selenite in protecting against ischemia reperfusion injury and investigated the mechanisms behind this protection. Hearts from male Wistar rats were subjected to ischemia reperfusion using the Langendorf model. Krebs-Henseleit perfusion solutions were supplemented with 0,0.1, 0.5, 1.0, and 10μM sodium selenite. Hearts were perfused for 30 min and then subjected to 22.5 min of global ischemia followed by 45 min reperfusion. Heart rate, ischemic contracture, end diastolic pressure, and developed ventricular pressure were monitored. At the completion of the experiment, hearts were homogenized and tissue extracts were assayed for glutathione peroxidase (GSH-Px) and thioredoxin reductase (Thx-Red) activity. Sodium selenite, at a concentration of 0.5 μM, demonstrated a protective effect on the recovery of cardiac function following I-R, as evidenced by a lower end diastolic pressure and enhanced recovery of rate pressure product. There was no beneficial effect observed in hearts perfused with 0.1 μM sodium selenite-supplemented buffer, whereas poorer functional recovery was observed in hearts perfused with 10 μM sodium selenite-supplemented buffer. The beneficial effect of sodium selenite was not mediated through increased activity of GSH-Px or Thx-Red. This study demonstrates that the addition of sodium selenite to reperfusion solutions, at an optimal concentration of 0.5 μM, assists in cardiac recovery following ischemia reperfusion.

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Objective To investigate whether attendance at cardiac rehabilitation (CR) independently predicts all-cause mortality over 14 years and whether there is a dose–response relationship between the proportion of CR sessions attended and long-term mortality.

Design Retrospective cohort study.

Setting CR programmes in Victoria, Australia

Patients The sample comprised 544 men and women eligible for CR following myocardial infarction, coronary artery bypass surgery or percutaneous interventions. Participants were tracked 4 months after hospital discharge to ascertain CR attendance status.

Main outcome measures All-cause mortality at 14 years ascertained through linkage to the Australian National Death Index.

Results In total, 281 (52%) men and women attended at least one CR session. There were few significant differences between non-attenders and attenders. After adjustment for age, sex, diagnosis, employment, diabetes and family history, the mortality risk for non-attenders was 58% greater than for attenders (HR=1.58, 95% CI 1.16 to 2.15). Participants who attended <25% of sessions had a mortality risk more than twice that of participants attending ≥75% of sessions (OR=2.57, 95% CI 1.04 to 6.38). This association was attenuated after adjusting for current smoking (OR=2.06, 95% CI 0.80 to 5.29).

Conclusions This study provides further evidence for the long-term benefits of CR in a contemporary, heterogeneous population. While a dose–response relationship may exist between the number of sessions attended and long-term mortality, this relationship does not occur independently of smoking differences. CR practitioners should encourage smokers to attend CR and provide support for smoking cessation.

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This article is devoted to an empirical investigation of per- formance of several new large multi-tier ensembles for the detection of cardiac autonomic neuropathy (CAN) in diabetes patients using subsets of the Ewing features. We used new data collected by the diabetes screening research initiative (DiScRi) project, which is more than ten times larger than the data set originally used by Ewing in the investigation of CAN. The results show that new multi-tier ensembles achieved better performance compared with the outcomes published in the literature previously. The best accuracy 97.74% of the detection of CAN has been achieved by the novel multi-tier combination of AdaBoost and Bagging, where AdaBoost is used at the top tier and Bagging is used at the middle tier, for the set consisting of the following four Ewing features: the deep breathing heart rate change, the Valsalva manoeuvre heart rate change, the hand grip blood pressure change and the lying to standing blood pressure change.

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This paper is devoted to empirical investigation of novel multi-level ensemble meta classifiers for the detection and monitoring of progression of cardiac autonomic neuropathy, CAN, in diabetes patients. Our experiments relied on an extensive database and concentrated on ensembles of ensembles, or multi-level meta classifiers, for the classification of cardiac autonomic neuropathy progression. First, we carried out a thorough investigation comparing the performance of various base classifiers for several known sets of the most essential features in this database and determined that Random Forest significantly and consistently outperforms all other base classifiers in this new application. Second, we used feature selection and ranking implemented in Random Forest. It was able to identify a new set of features, which has turned out better than all other sets considered for this large and well-known database previously. Random Forest remained the very best classier for the new set of features too. Third, we investigated meta classifiers and new multi-level meta classifiers based on Random Forest, which have improved its performance. The results obtained show that novel multi-level meta classifiers achieved further improvement and obtained new outcomes that are significantly better compared with the outcomes published in the literature previously for cardiac autonomic neuropathy.