brain condition
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2021 ◽  
Vol 13 (4) ◽  
pp. 701-711
Author(s):  
Marco G. Ceppi ◽  
Marlene S. Rauch ◽  
Peter S. Sándor ◽  
Andreas R. Gantenbein ◽  
Shyam Krishnakumar ◽  
...  

Background: Delirium is a brain condition associated with poor outcomes in rehabilitation. It is therefore important to assess delirium incidence in rehabilitation. Purpose: To develop and validate a chart-based method to identify incident delirium episodes within the electronic database of a Swiss rehabilitation clinic, and to identify a study population of validated incident delirium episodes for further research purposes. Design: Retrospective validation study. Settings: Routinely collected inpatient clinical data from ZURZACH Care. Participants: All patients undergoing rehabilitation at ZURZACH Care, Rehaklinik Bad Zurzach between 2015 and 2018 were included. Methods: Within the study population, we identified all rehabilitation stays for which ≥2 delirium-predictive key words (common terms used to describe delirious patients) were recorded in the medical charts. We excluded all prevalent delirium episodes and defined the remaining episodes to be potentially incident. At least two physicians independently confirmed or refuted each potential incident delirium episode by reviewing the patient charts. We calculated the positive predictive value (PPV) with 95% confidence interval (95% CI) for all potential incident delirium episodes and for specific subgroups. Results: Within 10,515 rehabilitation stays we identified 554 potential incident delirium episodes. Overall, 125 potential incident delirium episodes were confirmed by expert review. The PPV of the chart-based method varied from 0.23 (95% CI 0.19–0.26) overall to 0.69 (95% CI 0.56–0.79) in specific subgroups. Conclusions: Our chart-based method was able to capture incident delirium episodes with low to moderate accuracy. By conducting an additional expert review of the medical charts, we identified a study population of validated incident delirium episodes. Our chart-based method contributes towards an automated detection of potential incident delirium episodes that, supplemented with expert review, efficiently yields a validated population of incident delirium episodes for research purposes.


PLoS ONE ◽  
2021 ◽  
Vol 16 (7) ◽  
pp. e0255285
Author(s):  
Keisuke Kokubun ◽  
Juan Cesar D. Pineda ◽  
Yoshinori Yamakawa

Unhealthy lifestyles are damaging to the brain. Previous studies have indicated that body mass index (BMI), alcohol intake, short sleep, smoking, and lack of exercise are negatively associated with gray matter volume (GMV). Living alone has also been found to be related to GMV through lowered subjective happiness. However, to our knowledge, no GMV study has dealt with these unhealthy lifestyles simultaneously. By our analyses based on 142 healthy Japanese participants, BMI, alcohol intake, living alone, and short sleep were negatively associated with the gray-matter brain healthcare quotient (GM-BHQ), an MRI-based normalized GMV, after controlling for age, sex, and facility, not only individually but also when they were entered into a single regression model. Moreover, there were small but significant differences in the proportion of the variance for GM-BHQ explained by variables in a regression model (measured by R squared) between when these unhealthy variables were entered in an equation at the same time and when they were entered separately, with the former larger than the latter. However, smoking and lack of exercise were not significantly associated with GM-BHQ. Results indicate that some kinds of unhealthy lifestyles are somewhat harmful on their own, but may become more noxious to brain condition if practiced simultaneously, although its difference may not be large. To our knowledge, this study is the first to show that overlapping unhealthy lifestyles affects the brains of healthy adults.


Author(s):  
Irena Smaga ◽  
Małgorzata Frankowska ◽  
Małgorzata Filip

AbstractSubstance use disorder (SUD) is a chronic brain condition, with compulsive and uncontrollable drug-seeking that leads to long-lasting and harmful consequences. The factors contributing to the development of SUD, as well as its treatment settings, are not fully understood. Alterations in brain glutamate homeostasis in humans and animals implicate a key role of this neurotransmitter in SUD, while the modulation of glutamate transporters has been pointed as a new strategy to diminish the excitatory glutamatergic transmission observed after drugs of abuse. N-acetylcysteine (NAC), known as a safe mucolytic agent, is involved in the regulation of this system and may be taken into account as a novel pharmacotherapy for SUD. In this paper, we summarize the current knowledge on the ability of NAC to reduce drug-seeking behavior induced by psychostimulants, opioids, cannabinoids, nicotine, and alcohol in animals and humans. Preclinical studies showed a beneficial effect in animal models of SUD, while the clinical efficacy of NAC has not been fully established. In summary, NAC will be a small add-on to usual treatment and/or psychotherapy for SUD, however, further studies are required.


2020 ◽  
Vol 62 (4) ◽  
pp. 111-126
Author(s):  
Philip Clapson

AbstractIt may seem obvious we are conscious for we are certain we see, feel and think, but there is no accepted scientific account of these mental states as a brain condition. And since most neuroscientists assume consciousness and its supposed powers without explaining it, science is brought into question. That consciousness does not exist is here explained. The alternative, the theory of brain-sign, is outlined. It eliminates the quasi-divine knowledge properties of seeing, feeling and thinking. Brain-sign is a means/mechanism enabling collective action between organisms. Brain-sign signifies the shared world of that action. Signs are intrinsically physical and biologically ubiquitous. Brain-signs are derived moment-by-moment from the causal orientation of each brain towards others and the world. Interactive behaviour which is not predetermined (as in passing a cup of coffee) is characteristic of vertebrate species. Causality lies in the electrochemical operation of the brain. But identifying the changing world by brain-signs binds the causal states of those interacting into one unified operation. Brain-signing creatures, including humans, have no ‘sense’ they function this way. The world appears as seen. The ‘sense of seeing’, however, is the brain’s communicative activity in joint behaviour. Similarly for ‘feeling’. Language causality results from the transmission of compression waves or electromagnetic radiation from one brain to another altering the other’s causal orientation. The ‘sense of understanding’ words is the communicative state. The brain understands nothing, knows nothing, believes nothing. By replacing the prescientific notion of consciousness, brain-sign can enable a scientific path for brain science.


2020 ◽  
Vol 10 (1) ◽  
Author(s):  
Keisuke Kokubun ◽  
Yousuke Ogata ◽  
Yasuharu Koike ◽  
Yoshinori Yamakawa

2019 ◽  
Vol 3 (2) ◽  
pp. 102-134
Author(s):  
M Luisetto ◽  
BN Ahmadabadi ◽  
AY Rafa ◽  
RK Sahu ◽  
L Cabianca ◽  
...  

2019 ◽  
Vol 18 (3) ◽  
pp. 237
Author(s):  
Tomislav Breitenfeld ◽  
Drako Breitenfeld ◽  
Hansjörg Bäzner
Keyword(s):  

2018 ◽  
Vol 7 (4.11) ◽  
pp. 44
Author(s):  
S. A. M. Aris1 ◽  
N. A. Bani ◽  
M. N.Muhtazaruddin ◽  
M. N. Taib

A lot of useful information can be obtained through observation of the electroencephalogram (EEG) signal such as the human psychophysiology. It has been proven that EEG is handy in human diagnosis and tools to observe the brain condition. The study aims to establish a calmness index, which can differentiate the calmness level of an individual. Alpha waves were selected as the data features and computed into asymmetry index. The data features were clustered using Fuzzy C-Means (FCM) and resulted in three clusters. Wilcoxon Signed Ranks test was applied to determine the significance of the data features clustered by FCM. The Z-score obtained successfully distinguish three level of calmness index from the lower index until the higher index. With the advancement of signal processing techniques, the feature extractions for calmness index establishment computation is achievable.  


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