Pacing in hypertrophic obstructive cardiomyopathy: A randomized crossover study

Background Uncontrolled studies have shown that short atrioventricular delay dual chamber pacing reduces outflow tract obstruction in hypertrophic obstructive cardiomyopathy. Although the exact mechanism of this beneficial effect is unclear, this seems a promising potential new treatment for hypertrophic obstructive cardiomyopathy. Method In order to evaluate the impact of pacing therapy, we performed a randomized multicentre double-blind crossover (pacemaker activated vs non activated) study to investigate modification of echocardiography, exercise tolerance, angina, dyspnoea and quality of life in 83 patients with a mean age of 53 (range 22-87) years with symptoms refractory or intolerant to classical drug treatment. Results After 12 weeks of activated or inactivated pacing, independent of which phase was first, the pressure gradient fell from 59±36 mmHg to 30±25 mmHg (P<0·001) with active pacing. Exercise tolerance improved by 21% in those patients who at baseline tolerated less than 10 min of Bruce protocol; symptoms of dyspnoea and angina also improved significantly from NYHA class 2·4 to 1·4 and 1·0 to 0·4, respectively (P<0·007). Quality of life assessment with a validated questionnaire objectivated the subjective improvement. Conclusion Pacemaker therapy is of clinical and haemodynamic benefit for patients with hypertrophic obstructive cardiomyopathy, left ventricular outflow gradient at rest over 30 mmHg who are symptomatic despite drug treatmen

Adipocyte Turnover: Relevance to Human Adipose Tissue Morphology

International audienceOBJECTIVE: Adipose tissue may contain few large adipocytes (hypertrophy) or many small adipocytes (hyperplasia). We investigated factors of putative importance for adipose tissue morphology. RESEARCH DESIGN AND METHODS: Subcutaneous adipocyte size and total fat mass were compared in 764 subjects with BMI 18-60 kg/m(2). A morphology value was defined as the difference between the measured adipocyte volume and the expected volume given by a curved-line fit for a given body fat mass and was related to insulin values. In 35 subjects, in vivo adipocyte turnover was measured by exploiting incorporation of atmospheric (14)C into DNA. RESULTS: Occurrence of hyperplasia (negative morphology value) or hypertrophy (positive morphology value) was independent of sex and body weight but correlated with fasting plasma insulin levels and insulin sensitivity, independent of adipocyte volume (beta-coefficient = 0.3, P < 0.0001). Total adipocyte number and morphology were negatively related (r = -0.66); i.e., the total adipocyte number was greatest in pronounced hyperplasia and smallest in pronounced hypertrophy. The absolute number of new adipocytes generated each year was 70% lower (P < 0.001) in hypertrophy than in hyperplasia, and individual values for adipocyte generation and morphology were strongly related (r = 0.7, P < 0.001). The relative death rate (approximately 10% per year) or mean age of adipocytes (approximately 10 years) was not correlated with morphology. CONCLUSIONS: Adipose tissue morphology correlates with insulin measures and is linked to the total adipocyte number independently of sex and body fat level. Low generation rates of adipocytes associate with adipose tissue hypertrophy, whereas high generation rates associate with adipose hyperplasia

The Prognostic Value of Fasting Plasma Glucose, Two-Hour Postload Glucose, and HbA 1c in Patients With Coronary Artery Disease: A Report From EUROASPIRE IV

OBJECTIVE Three tests are recommended for identifying dysglycemia: fasting glucose (FPG), 2-h postload glucose (2h-PG) from an oral glucose tolerance test (OGTT), and glycated hemoglobin A1c (HbA1c). This study explored the prognostic value of these screening tests in patients with coronary artery disease (CAD). RESEARCH DESIGN AND METHODS FPG, 2h-PG, and HbA1c were used to screen 4,004 CAD patients without a history of diabetes (age 18–80 years) for dysglycemia. The prognostic value of these tests was studied after 2 years of follow-up. The primary end point included cardiovascular mortality, nonfatal myocardial infarction, stroke, or hospitalization for heart failure and a secondary end point of incident diabetes. RESULTS Complete information including all three glycemic parameters was available in 3,775 patients (94.3%), of whom 246 (6.5%) experienced the primary end point. Neither FPG nor HbA1c predicted the primary outcome, whereas the 2h-PG, dichotomized as <7.8 vs. ≥7.8 mmol/L, was a significant predictor (hazard ratio 1.38, 95% CI 1.07–1.78; P = 0.01). During follow-up, diabetes developed in 78 of the 2,609 patients (3.0%) without diabetes at baseline. An FPG between 6.1 and 6.9 mmol/L did not predict incident diabetes, whereas HbA1c 5.7–6.5% and 2h-PG 7.8–11.0 mmol/L were both significant independent predictors. CONCLUSIONS The 2h-PG, in contrast to FPG and HbA1c, provides significant prognostic information regarding cardiovascular events in patients with CAD. Furthermore, elevated 2h-PG and HbA1c are significant prognostic indicators of an increased risk of incident diabetes

RNA sequencing-based single sample predictors of molecular subtype and risk of recurrence for clinical assessment of early-stage breast cancer

BackgroundMultigene expression assays for molecular subtypes and biomarkers can aid clinical management of early invasive breast cancer. Based on RNA-sequencing we aimed to develop single-sample predictor (SSP) models for conventional clinical markers, molecular intrinsic subtype and risk of recurrence (ROR).MethodsA uniformly accrued breast cancer cohort of 7743 patients with RNA-sequencing data from fresh tissue was divided into a training set and a reserved test set. We trained SSPs for PAM50 molecular subtypes and ROR assigned by nearest-centroid (NC) and SSPs for conventional clinical markers from histopathology data. Additionally, SSP classifications were compared with Prosigna® in two external cohorts. Prognostic value was assessed using distant recurrence-free interval.ResultsIn the test set, agreement between SSP and NC classifications for PAM50 (five subtypes) and Subtype (four subtypes) was high (85%, Kappa=0.78) and very high (90%, Kappa=0.84) respectively. Accuracy for ROR risk category was high (84%, Kappa=0.75, weighted Kappa=0.90). The prognostic value for SSP and NC was assessed as equivalent. Agreement for SSP and histopathology was very high or high for receptor status, while moderate and poor for Ki67 status and Nottingham histological grade, respectively. SSP concordance with Prosigna® was high for subtype and moderate and high for ROR risk category. In pooled analysis, concordance between SSP and Prosigna® for emulated treatment recommendation for chemotherapy (yes vs. no) was high (85%, Kappa=0.66). In postmenopausal ER+/HER2-/N0 patients SSP application suggested changed treatment recommendations for up to 17% of patients, with nearly balanced escalation and de-escalation of chemotherapy.ConclusionsSSP models for histopathological variables, PAM50, and ROR classifications can be derived from RNA-sequencing that closely matches clinical tests. Agreement and outcome analyses suggest that NC and SSP models are interchangeable on a group-level and nearly so on a patient level. Retrospective evaluation in postmenopausal ER+/HER2-/N0 patients suggested that molecular testing could lead to a changed therapy recommendation for almost one-fifth of patients

Undetected dysglycaemia common in primary care patients treated for hypertension and/or dyslipidaemia: On the need for a screening strategy in clinical practice. A report from EUROASPIRE IV a registry from the EuroObservational Research Programme of the European Society of Cardiology

Background: Dysglycaemia defined as type 2 diabetes (T2DM) and impaired glucose tolerance (IGT), increases the risk of cardiovascular disease (CVD). The negative impact is more apparent in the presence of hypertension and/or dyslipidaemia. Thus, it seems reasonable to screen for dysglycaemia in patients treated for hypertension and/or dyslipidaemia. A simple screening algorithm would enhance the adoption of such strategy in clinical practice. Objectives: To test the hypotheses (1) that dysglycaemia is common in patients with hypertension and/or dyslipidaemia and (2) that initial screening with the Finnish Diabetes Risk Score (FINDRISC) will decrease the need for laboratory based tests. Methods: 2395 patients (age 18-80 years) without (i) a history of CVD or TDM2, (ii) prescribed blood pressure and/or lipid lowering drugs answered the FINDRISC questionnaire and had an oral glucose tolerance test (OGTT) and HbA1c measured. Results: According to the OGTT 934 (39%) had previously undetected dysglycaemia (T2DM 19%, IGT 20%). Of patients, who according to FINDRISC had a low, moderate or slightly elevated risk 20, 34 and 41% and of those in the high and very high-risk category 49 and 71% had IGT or T2DM respectively. The OGTT identified 92% of patients with T2DM, FPG + HbA1c 90%, FPG 80%, 2hPG 29% and HbA1c 22%. Conclusions: (1) The prevalence of dysglycaemia was high in patients treated for hypertension and/or dyslipidaemia. (2) Due to the high proportion of dysglycaemia in patients with low to moderate FINDRISC risk scores its initial use did not decrease the need for subsequent glucose tests. (3) FPG was the best test for detecting T2DM. Its isolated use is limited by the inability to disclose IGT. A pragmatic strategy, decreasing the demand for an OGTT, would be to screen all patients with FPG followed by OGTT in patients with IFG

An integral method for solving nonlinear eigenvalue problems

We propose a numerical method for computing all eigenvalues (and the corresponding eigenvectors) of a nonlinear holomorphic eigenvalue problem that lie within a given contour in the complex plane. The method uses complex integrals of the resolvent operator, applied to at least $k$ column vectors, where $k$ is the number of eigenvalues inside the contour. The theorem of Keldysh is employed to show that the original nonlinear eigenvalue problem reduces to a linear eigenvalue problem of dimension $k$. No initial approximations of eigenvalues and eigenvectors are needed. The method is particularly suitable for moderately large eigenvalue problems where $k$ is much smaller than the matrix dimension. We also give an extension of the method to the case where $k$ is larger than the matrix dimension. The quadrature errors caused by the trapezoid sum are discussed for the case of analytic closed contours. Using well known techniques it is shown that the error decays exponentially with an exponent given by the product of the number of quadrature points and the minimal distance of the eigenvalues to the contour