LVEF trajectories vary in HF depending on a number of disease modifiers, but an inverted U-shaped pattern with lower LVEF at both ends of the distribution emerged. A declining LVEF in the preceding period was associated with higher mortality.
Background: Long-term trajectories of left ventricular ejection fraction (LVEF) in heart failure (HF) patients with preserved EF (HFpEF) remain unclear. Our objective was to assess long-term longitudinal trajectories in consecutive HFpEF patients and the prognostic impact of LVEF dynamic changes over time. Methods and Results: Consecutive ambulatory HFpEF patients admitted to a multidisciplinary HF Unit were prospectively evaluated by 2-dimensional echocardiography at baseline and at 1, 3, 5, 7, 9, and 11 years of follow-up. Exclusion criteria were patients having a previous known LVEF <50%, patients undergoing only 1 echocardiogram study, and those with a diagnosis of dilated, noncompaction, alcoholic, or toxic cardiomyopathy. One hundred twenty-six patients (age, 71±13 years; 63% women) were included. The main pathogeneses were valvular disease (36%) and hypertension (28%). Atrial fibrillation was present in 67 patients (53%). The mean number of echocardiographies performed was 3±1.2 per patient. Locally weighted error sum of squares curves showed a smooth decrease of LVEF during the 11-year follow-up that was statistically significant in linear mixed-effects modeling ( P =0.01). Ischemic patients showed a higher decrease than nonischemics. The great majority (88.9%) of patients remained in the HFpEF category during follow-up; 9.5% evolved toward HF with midrange LVEF, and only 1.6% dropped to HF with reduced LVEF. No significant relationship was found between LVEF dynamics in the immediate preceding period and mortality. Conclusions: LVEF remained ≥50% in the majority of patients with HFpEF for ≤11 years. Only 1.6% of patients evolved to HF with reduced LVEF. Dynamic LVEF changes were not associated with mortality.
Systolic pulmonary artery pressure (SPAP), tricuspid annular plane systolic excursion (TAPSE), and TAPSE/SPAP ratio trajectories are not fully characterized in chronic heart failure (HF). We assessed very long-term longitudinal SPAP, TAPSE and TAPSE/SPAP trajectories in HF patients, and their dynamic changes in outcomes.
on behalf of the Do CHANGE consortium The importance of modifying lifestyle factors in order to improve prognosis in cardiac patients is well-known. Current study aims to evaluate the effects of a lifestyle intervention on changes in lifestyle-and health data derived from wearable devices. Cardiac patients from Spain (n = 34) and The Netherlands (n = 36) were included in the current analysis. Data were collected for 210 days, using the Fitbit activity tracker, Beddit sleep tracker, Moves app (GPS tracker), and the Careportal home monitoring system. Locally Weighted Error Sum of Squares regression assessed trajectories of outcome variables. Linear Mixed Effects regression analysis was used to find relevant predictors of improvement deterioration of outcome measures. Analysis showed that Number of Steps and Activity Level significantly changed over time (F = 58.21, p < 0.001; F = 6.33, p = 0.01). No significant changes were observed on blood pressure, weight, and sleep efficiency. Secondary analysis revealed that being male was associated with higher activity levels (F = 12.53, p < 0.001) and higher number of steps (F = 8.44, p < 0.01). Secondary analysis revealed demographic (gender, nationality, marital status), clinical (co-morbidities, heart failure), and psychological (anxiety, depression) profiles that were associated with lifestyle measures. In conclusion results showed that physical activity increased over time and that certain subgroups of patients were more likely to have a better lifestyle behaviors based on their demographic, clinical, and psychological profile. This advocates a personalized approach in future studies in order to change lifestyle in cardiac patients.
Incipient Alzheimer’s Disease (AD) is characterized by a slow onset of clinical symptoms, with pathological brain changes starting several years earlier. Consequently, it is necessary to first understand and differentiate age-related changes in brain regions in the absence of disease, and then to support early and accurate AD diagnosis. However, there is poor understanding of the initial stage of AD; seemingly healthy elderly brains lose matter in regions related to AD, but similar changes can also be found in non-demented subjects having mild cognitive impairment (MCI). By using a Linear Mixed Effects approach, we modelled the change of 166 Magnetic Resonance Imaging (MRI)-based biomarkers available at a 5-year follow up on healthy elderly control (HC, n = 46) subjects. We hypothesized that, by identifying their significant variant (vr) and quasi-variant (qvr) brain regions over time, it would be possible to obtain an age-based null model, which would characterize their normal atrophy and growth patterns as well as the correlation between these two regions. By using the null model on those subjects who had been clinically diagnosed as HC (n = 161), MCI (n = 209) and AD (n = 331), normal age-related changes were estimated and deviation scores (residuals) from the observed MRI-based biomarkers were computed. Subject classification, as well as the early prediction of conversion to MCI and AD, were addressed through residual-based Support Vector Machines (SVM) modelling. We found reductions in most cortical volumes and thicknesses (with evident gender differences) as well as in sub-cortical regions, including greater atrophy in the hippocampus. The average accuracies (ACC) recorded for men and women were: AD-HC: 94.11%, MCI-HC: 83.77% and MCI converted to AD (cAD)-MCI non-converter (sMCI): 76.72%. Likewise, as compared to standard clinical diagnosis methods, SVM classifiers predicted the conversion of cAD to be 1.9 years earlier for females (ACC:72.5%) and 1.4 years earlier for males (ACC:69.0%).
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