Develop and Apply Electrocardiography-Based Risk Score to Identify Community-Based Elderly Individuals at High-Risk of Mortality

With an aging world population, risk stratification of community-based, elderly population is required for primary prevention. This study proposes a combined score developed using electrocardiographic (ECG) parameters and determines its long-term prognostic value for predicting risk of cardiovascular mortality. A cohort-study, conducted from December 2008 to April 2019, enrolled 5,380 subjects in Taiwan, who were examined, using three-serial-12-lead ECGs, and their health/demographic information were recorded. To understand the predictive effects of ECG parameters on overall-survival, Cox hazard regression analysis were performed. The mean age at enrollment was 69.04 ± 8.14 years, and 47.4% were males. ECG abnormalities, LVH [hazard ratio (HR) = 1.39, 95% confidence intervals (CI) = (1.16–1.67), P = 0.0003], QTc [HR = 1.31, CI = (1.07–1.61), P = 0.007] and PR interval [HR = 1.40, CI = (1.01–1.95), P = 0.04], were significantly associated with primary outcome all-cause death. Furthermore, LVH [HR = 2.37, CI = (1.48–3.79), P = 0.0003] was significantly associated with cardiovascular death, while PR interval [HR = 2.63, CI = (1.24– 5.57), P = 0.01] with unexplained death. ECG abnormality (EA) score was defined based on the number of abnormal ECG parameters for each patient, which was used to divide all patients into sub-groups. Competing risk survival analysis using EA score were performed by using the Gray's test, which reported that high-risk EA groups showed significantly higher cumulative incidence for all three outcomes. Prognostic models using the EA score as predictor were developed and a 10-fold cross validation design was adopted to conduct calibration and discrimination analysis, to establish the efficacy of the proposed models. Overall, ECG model could successfully predict people, susceptible to all three death outcomes (P < 0.05), with high efficacy. Statistically significant (P < 0.001) improvement of the c-indices further demonstrated the robustness of the prediction model with ECG parameters, as opposed to a traditional model with no EA predictor. The EA score is highly associated with increased risk of mortality in elderly population and may be successfully used in clinical practice.

The Role of Brief Global Cognitive Tests and Neuropsychological Expertise in the Detection and Differential Diagnosis of Dementia

Dementia is a global public health problem and its impact is bound to increase in the next decades, with a rapidly aging world population. Dementia is by no means an obligatory outcome of aging, although its incidence increases exponentially in old age, and its onset may be insidious. In the absence of unequivocal biomarkers, the accuracy of cognitive profiling plays a fundamental role in the diagnosis of this condition. In this Perspective article, we highlight the utility of brief global cognitive tests in the diagnostic process, from the initial detection stage for which they are designed, through the differential diagnosis of dementia. We also argue that neuropsychological training and expertise are critical in order for the information gathered from these omnibus cognitive tests to be used in an efficient and effective way, and thus, ultimately, for them to fulfill their potential.

Bayer

A growing and aging world population and the increasing strain on nature's ecosystems are among the major challenges facing humanity. As a global leader in health and nutrition, Bayer is able to play a key role in devising solutions to tackle these challenges. Guided by its purpose "Science for a better life," it delivers breakthrough innovations in health care and agriculture. It contributes to a world in which diseases are not only treated but effectively prevented or cured, in which people can take better care of their own health needs, and in which enough agriculture products are produced while respecting the planet's natural resources. That is because at Bayer, it is believed that growth and sustainability should go hand in hand. In short, they are working to make their vision "Health for all, hunger for none" a reality.

A System for Neuromotor Based Rehabilitation on a Passive Robotic Aid

In the aging world population, the occurrence of neuromotor deficits arising from stroke and other medical conditions is expected to grow, demanding the design of new and more effective approaches to rehabilitation. In this paper, we show how the combination of robotic technologies with progress in exergaming methodologies may lead to the creation of new rehabilitation protocols favoring motor re-learning. To this end, we introduce the Track-Hold system for neuromotor rehabilitation based on a passive robotic arm and integrated software. A special configuration of weights on the robotic arm fully balances the weight of the patients’ arm, allowing them to perform a purely neurological task, overcoming the muscular effort of similar free-hand exercises. A set of adaptive and configurable exercises are proposed to patients through a large display and a graphical user interface. Common everyday tasks are also proposed for patients to learn again the associated actions in a persistent way, thus improving life independence. A data analysis module was also designed to monitor progress and compute indices of post-stroke neurological damage and Parkinsonian-type disorders. The system was tested in the lab and in a pilot project involving five patients in the post-stroke chronic stage with partial paralysis of the right upper limb, showing encouraging preliminary results.

Acute versus Chronic Exposures to Inhaled Particulate Matter and Neurocognitive Dysfunction: Pathways to Alzheimer’s Disease or a Related Dementia

An estimated 92% of the world’s population live in regions where people are regularly exposed to high levels of anthropogenic air pollution. Historically, research on the effects of air pollution have focused extensively on cardiovascular and pulmonary health. However, emerging evidence from animal and human studies has suggested that chronic exposures to air pollution detrimentally change the functioning of the central nervous system with the result being proteinopathy, neurocognitive impairment, and neurodegenerative disease. Case analyses of aging World Trade Center responders suggests that a single severe exposure may also induce a neuropathologic response. The goal of this report was to explore the neuroscientific support for the hypothesis that inhaled particulate matter might cause an Alzheimer’s-like neurodegenerative disease, in order to consider proposed mechanisms and latency periods linking inhaled particulate matter and neurodegeneration, and to propose new directions in this line of research.