Atrioventricular (AV) delay optimization in sequential and biventricular (BiV) pacing, although widely recommended, is often poorly performed in clinical practice as an improper setting can reduce the success of the stimulation. Despite the several methods proposed, the AV delay is frequently programmed in an empirical way or left to a predefined value (usually the manufacturer's setting), without considering the different variables involved in this context, concerning the intra- and interindividual variability of the electromechanical events, the peculiarities of the several cardiopathies, the spontaneous interatrial and AV conduction, the pharmacological therapy, and the pacing mode. The manuscript illustrates the physiological bases of the optimization, describes why and how to programme the best AV delay at rest and during daily activities and discusses critically all methods proposed, divided into three groups: predefined formulas, iterative attempts, and automatic settings. The manuscript is not only a review because it tries to clarify this complex topic, stating the fundamental concept in BiV pacing; the optimal AV delay should be short enough to have always a pre-exitated stimulation and contemporary an optimal left ventricular filling. The paper suggests new purposes and new solutions for this goal, it shows the limits of the actual guidelines and the disappointing results obtained in several studies by automatic methods, goading to find new algorithms.
Twenty-three patients affected by severe, refractory angina were submitted to permanent spinal cord stimulation (SCS) and then followed in our outpatient clinic for 24 months. During the follow-up period, the number of weekly angina episodes drastically dropped from 9.2 (preimplant) to 1.8 in the 3rd, 2.5 in the 6th, 4.5 in the 12th, and 4.2 in the 24th month, with a statistically significant difference (P < 0.01) between the first and last values. A significant increase in the average exercise time from 320 +/- 120 seconds (in baseline condition) to 410 +/- 115 seconds (during SCS) was observed at the treadmill stress test (P < 0.01). SCS was well tolerated by all the patients. However, 7 patients died during follow-up (3 myocardial infarctions, 2 noncardiac deaths, and 2 sudden deaths). Three generators were replaced because of battery depletion after 15, 17, and 21 months. No serious complication was observed. In conclusion, in patients with otherwise intractable angina or already submitted to myocardial revascularization, SCS is very effective in reducing the number of angina episodes. The time of the work during exercise stress test is also significantly prolonged.
factor for cardiovascular diseases. The high rate of morbidity and mortality in obese patients recognises metabolic, haemodynamic, endothelial and endocrine mechanisms as influencing factors. Insulin resistance and the resulting hyperinsulinaemia represents one of the most relevant elements for developing visceral obesity, which is involved in volume overload, sympathetic hyperactivity, increased vascular sensitivity and tone, stable hypertension, left ventricular hypertrophy and atherogenic dyslipidaemia. On the other hand, hypertension, hyperinsulinaemia, and sympathetic and renin-angiotensin hyperactivity may promote the structural changes in cardiac geometry, defined as remodelling, concentric and eccentric hypertrophy, and diastolic and systolic dysfunction and failure. In this view, the adipose tissue has to be considered not only as a deposit tissue, but also as an endocrine organ. Several molecules produced by adipocytes act by an endocrine, paracrine and autocrine function on different tissues. Leptin, adiponectin, tumour necrosis factor-α and interleukin-6 are some of these molecules, which are involved in glucose and lipid metabolism in the atherosclerosis process and in thrombosis and haemodynamic homeostasis.In summary, visceral obesity, as an independent risk factor, may result in insulin resistance, hypertension, cardiovascular remodelling, endothelial dysfunction, dyslipidaemia and consequent atherosclerosis.
Aim:To assess the usefulness of ambulatory blood pressure monitoring (ABPM) in the prognostic stratification of patients with a recent myocardial infarction. Method: The study population included 75 patients consecutively admitted at our institution for acute ST-segment elevation myocardial infarction (STEMI). All patients underwent ABPM 3 weeks after discharge and were subsequently followed for 12 months. Results: The age (Y), mean 24-hour diastolic blood pressure (mDBP) and mean 24-hour beat-to-beat interval (mBBI) values were found to be independent predictors of the combined endpoint of cardiac death and symptomatic left ventricular dysfunction during the follow-up period. A prognostic index was then developed from such variables, according to the formula (mDBP + mBBI/10) -Y. This index, when considered as a categorical variable, in its 'low' figures (cut-off <88), showed a significant prognostic value (p < 0.0001). The predictive value of the index for the combined endpoint was higher than left ventricular ejection fraction (50% versus 36%).
To propose a clinical prognostic index for death and heart failure in patients with ischemic cardiomyopathy implanted with an ICD. This prospective study included 192 consecutive patients (age 68 ± 10) recruited from 2004 to 2009 and implanted with an ICD for MADIT II criteria. All patients performed 24-h ambulatory blood pressure monitoring after discharge and common haematological samples. The prognostic index (PI) was built according to the formula: 120 - age + mean 24 h systolic blood pressure--(creatinine 9 10). Other variables were assessed: EF, haemoglobin concentration, mean 24 h heart rate and diastolic blood pressure, sodium level, pacing mode and diabetes. Non-arrhythmic cardiac death and new hospitalizations for heart failure during 1-year follow-up were the combined end point. A total of 48 events (25%) occurred during the follow-up: 7 cardiac deaths and 41 hospitalizations for acute heart failure. Cox proportional hazards model showed that PI was the only predictor of events (HR = 0.96; CI 95% 0.944–0.976, p < 0.0001). ROC curve showed that PI best cut-off was 144, with AUC 0.79, p < 0.0001; sensitivity 77%, specificity 74%, positive predictive value 50%, negative predictive value 90%. PI was predictive of events in a clinical setting where EF had no predictive value. PI works according to the rule ‘‘the lower the worse’’. The high negative predictive value (90%) of PI allows to identify subjects at lower risk for death and heart failure. PI can be a practical tool to stratify risk in ischemic cardiomyopathy.
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