Objective: In this study, electroencephalography activity recorded during monotonous driving was investigated to examine the predictive capability of monopolar EEG analysis for fatigue/sleepiness in ...a cohort of train drivers. Approach: Sixty-three train drivers participated in the study, where 32- lead monopolar EEG data was recorded during a monotonous driving task. Participant sleepiness was assessed using the Pittsburgh sleep quality index (PSQI), the Epworth sleepiness scale (ESS), the Karolinksa sleepiness scale (KSS) and the checklist of individual strength 20 (CIS20). Main results: Self-reported fatigue/sleepiness scores of the train driver cohort were primarily associated with EEG delta, theta, and alpha variables; however, some beta and gamma associations were also implicated. Furthermore, general linear models informed by these EEG variables were able to predict self-reported scores with varying degrees of success, representing between 48% and 54% of variance in fatigue scores. Significance: Self-reported fatigue/sleepiness scores of train drivers were predicted with varying degrees of success (dependent upon the self-reported fatigue/sleepiness measure) by alterations to monopolar delta, theta, and alpha band activity variables, indicating EEG as a potential indicator for fatigue/sleepiness in train drivers.
Diabetes mellitus (DM) is a global metabolic epidemic associated with numerous adverse complications. Invasive finger prick tests or invasive monitors are currently the most common means of ...monitoring and controlling blood glucose levels (BGLs). Heart rate variability (HRV) is a noninvasive measure of the autonomic nervous system, and its dynamic physiological nature may provide an alternative means of blood glucose monitoring. However, the relationship between BGL and HRV parameters remains relatively unknown.
Thirty-two participants with diabetes (39.97 ± 17.21 years of age) and 31 without diabetes (27.87 ± 10.55 years of age) participated in the current study. Fasting preceded a 10-min three-lead electrocardiogram (ECG), which was followed by a finger prick blood glucose assessment. Following this, a regular meal was consumed, and 30 min after ingestion, a second postprandial 10-min ECG was obtained, and blood glucose assessment was conducted.
Low-frequency (LF) power, high-frequency (HF) power, and total power (TP) of HRV were negatively associated with BGL in participants with DM. Additionally, the ratio of LF to HF was positively correlated with BGL. Duration of DM was also associated with multiple HRV parameters, with negative associations to both LF and HF parameters as well as TP.
This study demonstrates links between specific HRV variables and BGL. In the future the dynamic nature of HRV could provide a unique and real-time method for monitoring BGL, for continuous noninvasive prediction and/or management of DM.
Due to their ease of isolation, differentiation capabilities, and immunomodulatory properties, the therapeutic potential of mesenchymal stem cells (MSCs) has been assessed in numerous pre-clinical ...and clinical settings. Currently, whole pancreas or islet transplantation is the only cure for people with type 1 diabetes (T1D) and, due to the autoimmune nature of the disease, MSCs have been utilised either natively or transdifferentiated into insulin-producing cells (IPCs) as an alternative treatment. However, the initial success in pre-clinical animal models has not translated into successful clinical outcomes. Thus, this review will summarise the current state of MSC-derived therapies for the treatment of T1D in both the pre-clinical and clinical setting, in particular their use as an immunomodulatory therapy and targets for the generation of IPCs via gene modification. In this review, we highlight the limitations of current clinical trials of MSCs for the treatment of T1D, and suggest the novel clustered regularly interspaced short palindromic repeat (CRISPR) gene-editing technology and improved clinical trial design as strategies to translate pre-clinical success to the clinical setting.
Aim
To explore the role of coping moderators in self‐management of breathlessness crises by people with advanced respiratory disease.
Design
A secondary analysis of semi‐structured interview data.
...Methods
Interviews with patients who had advanced respiratory disease, chronic breathlessness and at least one experience where they considered presenting to Emergency but self‐managed instead (a “near miss”). Participants were recruited from New South Wales, Queensland, Victoria, South Australia or Tasmania. Eligible caregivers were those who contributed to Emergency‐related decision‐making. Interviews were coded inductively and then deductively against the coping moderators social support and dispositional coping style, defined by the Transactional Model of Stress and Coping.
Results
Interviews were conducted between October 2015 ‐ April 2016 with 20 patients and three caregivers. Social networks offered emotional and practical support but also had potential for conflict with patients' ‘hardy’ coping style. Patient hardiness (characterized by a sense of ‘commitment’ and ‘challenge’) promoted a proactive approach to self‐management but made some patients less willing to accept support. Information‐seeking tendencies varied between patients and were sometimes shared with caregivers. An optimistic coping style appeared to be less equivocally beneficial.
Conclusion
This study shows that social support and coping style may influence how people self‐manage through their breathlessness crises and identified ways coping moderators can facilitate or hinder effective self‐management.
Impact
This study confers insights into how social‐support and coping style can be supported and optimized to facilitate breathlessness self‐management. Acknowledging coping moderator interactions is beneficial for developing resources and strategies that recognise patient mastery.
目的
探讨应对调节者在晚期呼吸系统疾病患者呼吸困难危机自我管理中的作用。
设计
半结构化访谈数据的二次分析。
方法
采访患有晚期呼吸系统疾病、慢性呼吸困难的患者,至少有一次他们考虑过紧急情况下自我管理的经历(“相近差错”)。参与者来自新南威尔士、昆士兰、维多利亚、南澳大利亚或塔斯马尼亚。合格的护理人员是那些参与紧急相关决策的人。
访谈以应激和应对的交互模型为基础,对应对调节者的社会支持和倾向性应对方式进行归纳和演绎编码。
结果
在2015年10月至2016年4月期间,对20名患者和3名护理人员进行了访谈。社交网络提供了情感和实际支持,但也有可能与患者的“坚强”应对方式发生冲突。患者的意志力(以“承诺”和“挑战”为特征)促进了积极主动的自我管理方法,但使一些患者不愿意接受支持。患者之间的信息寻求倾向各不相同,有时与护理人员分享。乐观的应对方式看来有明显的好处。
结论
本研究表明,社会支持和应对方式可能影响人们如何通过呼吸困难的危机自我管理,并确定应对调解人可以促进或阻碍有效的自我管理的方式。
影响
本研究探讨如何支持和优化社会支持和应对方式,以促进呼吸困难的自我管理。认识到应对调节者的相互作用有助于开发认识到患者掌握情况的资源和策略。
ABSTRACT
To describe sleep quality using repeated subjective assessment and the ongoing use of sleep‐promoting interventions in intensive care. It is well known that the critically ill experience ...sleep disruption while receiving treatment in the intensive care unit. Both the measurement and promotion of sleep is challenging in the complex environment of intensive care unit. Repeated subjective assessment of patients' sleep in the intensive care unit and use of sleep‐promoting interventions has not been widely reported. An observational study was conducted in a 58‐bed adult intensive care unit. Sleep quality was assessed using the Richards‐Campbell Sleep Questionnaire (RCSQ) each morning. intensive care unit audit sleep‐promoting intervention data were compared to data obtained prior to the implementation of a sleep guideline. Patients answered open‐ended questions about the facilitators and deterrents of their sleep in intensive care unit. The sample (n = 50) was predominately male (76%) with a mean age: 62.6±16.9 years. Sleep quality was assessed on 2 days or more for 21 patients. The majority of patients (98%) received sleep‐promoting interventions. Sleep quality had not improved significantly since the guideline was first implemented. The mean Richards‐Campbell Sleep Questionnaire score was 47.9±24.1 mm. The main sleep deterrents were discomfort and noise. Frequently cited facilitators were nothing (i.e. nothing helped) and analgesia. The Richards‐Campbell Sleep Questionnaire was used on repeated occasions, and sleep‐promoting interventions were used extensively. There was no evidence of improvement in sleep quality since the implementation of a sleep guideline. The use of the Richards‐Campbell Sleep Questionnaire for the subjective self‐assessment of sleep quality in intensive care unit patients and the implementation of simple‐promoting interventions by intensive care unit clinicians is both feasible and may be the most practical way to assess sleep in the intensive care unit context.
The current study investigated the effect of monotonous driving on inter-hemispheric electroencephalography (EEG) coherence. Twenty-four non-professional drivers were recruited to perform a fatigue ...instigating monotonous driving task while 30 channels of EEG were simultaneously recorded. The EEG recordings were then divided into 5 equal sections over the entire driving period for analysis. Inter-hemispheric coherence was computed from 5 homologous EEG electrode pairs (FP1–FP2, C3–C4, T7–T8, P7–P8, and O1–O2) for delta, theta, alpha and beta frequency bands. Results showed that frontal and occipital inter-hemispheric coherence values were significantly higher than central, parietal, and temporal sites for all four frequency bands (
p
<
0.0001). In the alpha frequency band, significant difference was found between earlier and later driving sections (
p
=
0.02). The coherence values in all EEG frequency bands were slightly increased at the end of the driving session, except for FP1–FP2 electrode pair, which showed no significant change in coherence in the beta frequency band at the end of the driving session.
Context: Diabetes is a growing global metabolic epidemic. Current research is focussing on exploring how the biological processes and clinical outcomes of diabetes are related and developing novel ...biomarkers to measure these relationships, as this can subsequently improve diagnostic, therapeutic and management capacity.
Objective: The objective of this study is to identify the most recent advances in molecular biomarkers of diabetes and directions that warrant further research.
Methods: Using a systematic search strategy, the MEDLINE, CINAHL and OVID MEDLINE databases were canvassed for articles that investigated molecular biomarkers for diabetes. Initial selections were made based on article title, whilst final inclusion was informed by a critical appraisal of the full text of each article.
Results: The systematic search returned 246 records, of which 113 were unique. Following screening, 29 records were included in the final review. Three main research strategies (the development of novel technologies, broad biomarker panels, and targeted approaches) identified a number of potential biomarkers for diabetes including miR-126, C-reactive protein, 2-aminoadipic acid and betatrophin.
Conclusion: The most promising research avenue identified is the detection and quantification of micro RNA. Further, the utilisation of functionalised electrodes as a means to detect biomarker compounds also warrants attention.
Celotno besedilo
Dostopno za:
DOBA, IJS, IZUM, KILJ, NUK, PILJ, PNG, SAZU, UILJ, UKNU, UL, UM, UPUK
Driver drowsiness is reported as one of the main causal factors in many traffic accidents as it progressively impairs the driver's awareness about external events. Drowsiness detection can be ...approached through monitoring physiological signals while driving to correlate drowsiness with the change in the corresponding patterns of the Electroencephalogram (EEG), Electrooculogram (EOG), and Electrocardiogram (ECG) signals. The main challenge in such an approach is to extract a set of features that can highly discriminate between the different drowsiness levels. This paper proposes a new Fuzzy Neighborhood Preserving Analysis (FNPA) feature projection method that is used to extract the discriminant information relevant to the loss of attention caused by drowsiness. Unlike existing methods, FNPA considers the fuzzy memberships of the input measurements into the different classes while constructing the graph Laplacian. Thus, it is able to identify both the discriminant and the geometrical structure of the input data while accounting for the overlapping nature of the drowsiness patterns. Furthermore, in order to address the singularity problem that occurs in many real world problems, the singular value decomposition (SVD), and later the QR-Decomposition, are utilized to extract a set of statistically uncorrelated features presenting the Uncorrelated FNPA (UFNPA). In the current preliminary study with datasets collected from 31 subjects only, while performing a driving simulation task, the proposed method is capable of accurately classifying the drowsiness levels using a small number of features with an average accuracy of ≈93%. On the other hand, the possibility of developing a subject-independent drowsiness recognition system is also investigated when the problem is converted into a binary classification task, as imposed by the number of drowsiness levels exhibited by the drivers, with accuracies ranging from 82%-to-84%.
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