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Die Lifespan-Forschung untersucht die Entwicklung von Individuen über den gesamten Lebenslauf. Die medizinische Rehabilitation hat nach geltendem Sozialrecht die Aufgabe, chronische Krankheiten abzuwenden, zu beseitigen, zu mindern, auszugleichen, eine Verschlimmerung zu verhüten und Negativfolgen für die Lebensführung zu reduzieren. Dies erfordert in wissenschaftlicher wie in praxisbezogener Hinsicht die Entwicklung einer Lebensspannenperspektive als Voraussetzung für die Klassifikation und Diagnostik chronischer Erkrankungen, die Beschreibung von verlaufsbeeinflussenden Faktoren, kritischen Lebensphasen und Critical Incidents (kritische Verlaufszeitpunkte), die Durchführung von prophylaktischen Maßnahmen, die Entwicklung von Assessmentverfahren zur Erfassung und Bewertung von Verläufen oder Vorbehandlungen, die Auswahl und Priorisierung von Interventionen, eine Behandlungs- und Behandlerkoordination auf der Zeitachse, die Präzisierung der Aufgabenstellung für spezialisierte Rehabilitationsmaßnahmen, wie beispielsweise Rehabilitationskliniken, und als Grundlage für die Sozialmedizin. Aufgrund der Vielfalt der individuellen Risikokonstellationen, Krankheitsverläufe und Behandlungssituationen über die Lebensspanne hinweg, bedarf es in der medizinischen Rehabilitation in besonderer Weise einer personalisierten Medizin, die zugleich rehabilitationsförderliche und -behindernde Umweltfaktoren im Rehabilitationsverlauf berücksichtigt.
Moving Beyond ERP Components
(2018)
Relationships between neuroimaging measures and behavior provide important clues about brain function and cognition in healthy and clinical populations. While electroencephalography (EEG) provides a portable, low cost measure of brain dynamics, it has been somewhat underrepresented in the emerging field of model-based inference. We seek to address this gap in this article by highlighting the utility of linking EEG and behavior, with an emphasis on approaches for EEG analysis that move beyond focusing on peaks or "components" derived from averaging EEG responses across trials and subjects (generating the event-related potential, ERP). First, we review methods for deriving features from EEG in order to enhance the signal within single-trials. These methods include filtering based on user-defined features (i.e., frequency decomposition, time-frequency decomposition), filtering based on data-driven properties (i.e., blind source separation, BSS), and generating more abstract representations of data (e.g., using deep learning). We then review cognitive models which extract latent variables from experimental tasks, including the drift diffusion model (DDM) and reinforcement learning (RL) approaches. Next, we discuss ways to access associations among these measures, including statistical models, data-driven joint models and cognitive joint modeling using hierarchical Bayesian models (HBMs). We think that these methodological tools are likely to contribute to theoretical advancements, and will help inform our understandings of brain dynamics that contribute to moment-to-moment cognitive function.
Purpose: Postoperative cognitive dysfunction (POCD) appears in up to 30% of patients suffering from postoperative delirium (POD). Both are associated with higher mortality and postoperative complications, prolonged hospital stays, and increased costs. Multi-modal models with pre-admission risk reduction counselling, perioperative monitoring, and training of multidisciplinary patient care providers have been shown to decrease the prevalence of both. The aim of our study is to understand how far those measures are known and implemented in routine care and to detect potential gaps in the current practice regarding risk communication and information flow between involved caregivers for patients at risk for POD/POCD. Patients and Methods: As part of a multicenter study, seven semi-structured focus group (FG) discussions with nurses and physicians from tertiary care hospitals (surgery, anesthesiology, and orthopedics, n=31) and general practitioners (GPs) in private practice (n=7) were performed. Transcribed discussions were analyzed using qualitative content analysis. Results: POD is present above all in the daily work of nurses, whereas physicians do not perceive it as a relevant problem. Physicians report that no regular risk assessment or risk communication was performed prior to elective surgery. Information about POD often gets lost during hand-offs and is not regularly reported in discharge letters. Thus, persisting cognitive dysfunction is often missed. The importance of standardized documentation and continuous education concerning risks, screening, and treatment was emphasized. The often-suggested pre-OP medication adjustment was seen as less important; in contrast, avoiding withdrawal was regarded as far more important. Conclusion: Altogether, it seems that standards and available best practice concepts are rarely implemented. In contrast to physicians, nurses are highly aware of delirium and ask for standardized procedures and more responsibility. Therefore, raising awareness regarding risks, screening tools, and effective preventive measures for POD/POCD seems an urgent goal. Nurses should have a central role in coordination and care of POD to prevent the risk for POCD.
Stress plays a key role in modulating addictive behavior and can cause relapse following periods of abstinence. Common effects of stress and alcohol on the dopaminergic system have been suggested, although the precise mechanisms are unclear. Here, we investigated 20 detoxified alcohol-dependent patients and 19 matched healthy controls and assessed striatal D2/D3 availability using [F-18]-fallypride positron emission tomography and stressful life events. We found a strong association between striatal D2/D3 availability and stress in patients, but not in healthy controls. Interestingly, we found increased D2/D3 receptor availability in patients with higher stress levels. This mirrors complex interactions between stress and alcohol intake in animal studies and emphasizes the importance to investigate stress exposure in neurobiological studies of addiction.
Background Uptake of self-testing and self-management of oral coagulation has remained inconsistent, despite good evidence of their effectiveness. To clarify the value of self-monitoring of oral anticoagulation, we did a meta-analysis of individual patient data addressing several important gaps in the evidence, including an estimate of the effect on time to death, first major haemorrhage, and thromboembolism.
Methods We searched Ovid versions of Embase (1980-2009) and Medline (1966-2009), limiting searches to randomised trials with a maximally sensitive strategy. We approached all authors of included trials and requested individual patient data: primary outcomes were time to death, first major haemorrhage, and first thromboembolic event. We did prespecified subgroup analyses according to age, type of control-group care (anticoagulation-clinic care vs primary care), self-testing alone versus self-management, and sex. We analysed patients with mechanical heart valves or atrial fibrillation separately. We used a random-effect model method to calculate pooled hazard ratios and did tests for interaction and heterogeneity, and calculated a time-specific number needed to treat.
Findings Of 1357 abstracts, we included 11 trials with data for 6417 participants and 12 800 person-years of follow-up. We reported a significant reduction in thromboembolic events in the self-monitoring group (hazard ratio 0.51; 95% CI 0.31-0.85) but not for major haemorrhagic events (0.88, 0.74-1.06) or death (0.82, 0.62-1.09). Participants younger than 55 years showed a striking reduction in thrombotic events (hazard ratio 0.33, 95% CI 0.17-0.66), as did participants with mechanical heart valve (0.52, 0.35-0.77). Analysis of major outcomes in the very elderly (age >= 85 years, n=99) showed no significant adverse effects of the intervention for all outcomes.
Interpretation Our analysis showed that self-monitoring and self-management of oral coagulation is a safe option for suitable patients of all ages. Patients should also be offered the option to self-manage their disease with suitable health-care support as back-up.