Bisoprolol compared with carvedilol and metoprolol succinate in the treatment of patients with chronic heart failure

© 2017, Springer-Verlag Berlin Heidelberg. Aims: Beta-blockers are recommended for the treatment of chronic heart failure (CHF). However, it is disputed whether beta-blockers exert a class effect or whether there are differences in efficacy between agents. Methods and results: 6010 out-patients with stable CHF and a reduced left ventricular ejection fraction prescribed either bisoprolol, carvedilol or metoprolol succinate were identified from three registries in Norway, England, and Germany. In three separate matching procedures, patients were individually matched with respect to both dose equivalents and the respective propensity scores for beta-blocker treatment. During a follow-up of 26,963 patient-years, 302 (29.5%), 637 (37.0%), and 1232 (37.7%) patients died amongst those prescribed bisoprolol, carvedilol, and metoprolol, respectively. In univariable analysis of the general sample, bisoprolol and carvedilol were both associated with lower mortality as compared with metoprolol succinate (HR 0.80, 95% CI 0.71–0.91, p  <  0.01, and HR 0.86, 95% CI 0.78–0.94, p  <  0.01, respectively). Patients prescribed bisoprolol or carvedilol had similar mortality (HR 0.94, 95% CI 0.82–1.08, p = 0.37). However, there was no significant association between beta-blocker choice and all-cause mortality in any of the matched samples (HR 0.90; 95% CI 0.76–1.06; p = 0.20; HR 1.10, 95% CI 0.93–1.31, p = 0.24; and HR 1.08, 95% CI 0.95–1.22, p = 0.26 for bisoprolol vs. carvedilol, bisoprolol vs. metoprolol succinate, and carvedilol vs. metoprolol succinate, respectively). Results were confirmed in a number of important subgroups. Conclusion: Our results suggest that the three beta-blockers investigated have similar effects on mortality amongst patients with CHF

Inter-hemispheric EEG coherence analysis in Parkinson's disease : Assessing brain activity during emotion processing

Parkinson’s disease (PD) is not only characterized by its prominent motor symptoms but also associated with disturbances in cognitive and emotional functioning. The objective of the present study was to investigate the influence of emotion processing on inter-hemispheric electroencephalography (EEG) coherence in PD. Multimodal emotional stimuli (happiness, sadness, fear, anger, surprise, and disgust) were presented to 20 PD patients and 30 age-, education level-, and gender-matched healthy controls (HC) while EEG was recorded. Inter-hemispheric coherence was computed from seven homologous EEG electrode pairs (AF3–AF4, F7–F8, F3–F4, FC5–FC6, T7–T8, P7–P8, and O1–O2) for delta, theta, alpha, beta, and gamma frequency bands. In addition, subjective ratings were obtained for a representative of emotional stimuli. Interhemispherically, PD patients showed significantly lower coherence in theta, alpha, beta, and gamma frequency bands than HC during emotion processing. No significant changes were found in the delta frequency band coherence. We also found that PD patients were more impaired in recognizing negative emotions (sadness, fear, anger, and disgust) than relatively positive emotions (happiness and surprise). Behaviorally, PD patients did not show impairment in emotion recognition as measured by subjective ratings. These findings suggest that PD patients may have an impairment of inter-hemispheric functional connectivity (i.e., a decline in cortical connectivity) during emotion processing. This study may increase the awareness of EEG emotional response studies in clinical practice to uncover potential neurophysiologic abnormalities

Evaluation of TV commercials using neurophysiological responses

Background: In recent years, neuroscientific knowledge has been applied to marketing as a novel and efficient means to comprehend the cognitive and behavioral aspects of consumers. A number of studies have attempted to evaluate media contents, especially TV commercials using various neuroimaging techniques such as electroencephalography (EEG). Yet neurophysiological examination of detailed cognitive and affective responses in viewers is still required to provide practical information to marketers. Here, this study develops a method to analyze temporal patterns of EEG data and extract affective and cognitive indices such as happiness, surprise, and attention for TV commercial evaluation. Methods: Twenty participants participated in the study. We developed the neurophysiological indices for TV commercial evaluation using classification model. Specifically, these model-based indices were customized using individual EEG features. We used a video game for developing the index of attention and four video clips for developing indices of happiness and surprise. Statistical processes including one-way analyses of variance (ANOVA) and the cross validation scheme were used to select EEG features for each index. The EEG features were composed of the combinations of spectral power at selected channels from the cross validation for each individual. The Fisher&apos;s linear discriminant classifier (FLDA) was used to estimate each neurophysiological index during viewing four different TV commercials. Post hoc behavioral responses of preference, short-term memory, and recall were measured. Results: Behavioral results showed significant differences for all preference, short-term memory rates, and recall rates between commercials, leading to a &apos;high-ranked&apos; commercial group and a &apos;low-ranked&apos; group (P &lt; 0.05). Neural estimation of happiness results revealed a significant difference between the high-ranked and the low-ranked commercials in happiness index (P &lt; 0.01). The order of rankings based on happiness and attention matched well with the order of behavioral response rankings. In the elapsed-time analysis of the highest-ranked commercial, we could point to visual and auditory semantic structures of the commercial that induced increases in the happiness index. Conclusions: Our results demonstrated that the neurophysiological indices developed in this study may provide a useful tool for evaluating TV commercialsclose0

USING CALIBRATED RGB IMAGERY FROM LOW-COST UAVS FOR GRASSLAND MONITORING: CASE STUDY AT THE RENGEN GRASSLAND EXPERIMENT (RGE), GERMANY

Monitoring the spectral response of intensively managed grassland throughout the growing season allows optimizing fertilizer inputs by monitoring plant growth. For example, site-specific fertilizer application as part of precision agriculture (PA) management requires information within short time. But, this requires field-based measurements with hyper- or multispectral sensors, which may not be feasible on a day to day farming practice. Exploiting the information of RGB images from consumer grade cameras mounted on unmanned aerial vehicles (UAV) can offer cost-efficient as well as near-real time analysis of grasslands with high temporal and spatial resolution. The potential of RGB imagery-based vegetation indices (VI) from consumer grade cameras mounted on UAVs has been explored recently in several. However, for multitemporal analyses it is desirable to calibrate the digital numbers (DN) of RGB-images to physical units. In this study, we explored the comparability of the RGBVI from a consumer grade camera mounted on a low-cost UAV to well established vegetation indices from hyperspectral field measurements for applications in grassland. The study was conducted in 2014 on the Rengen Grassland Experiment (RGE) in Germany. Image DN values were calibrated into reflectance by using the Empirical Line Method (Smith & Milton 1999). Depending on sampling date and VI the correlation between the UAV-based RGBVI and VIs such as the NDVI resulted in varying R2 values from no correlation to up to 0.9. These results indicate, that calibrated RGB-based VIs have the potential to support or substitute hyperspectral field measurements to facilitate management decisions on grasslands