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BACKGROUND:
Intraoperative electroencephalography (EEG) signatures related to the development of postoperative delirium (POD) in older patients are frequently studied. However, a broad analysis of the EEG dynamics including preoperative, postinduction, intraoperative and postoperative scenarios and its correlation to POD development is still lacking. We explored the relationship between perioperative EEG spectra-derived parameters and POD development, aiming to ascertain the diagnostic utility of these parameters to detect patients developing POD.
METHODS:
Patients aged ≥65 years undergoing elective surgeries that were expected to last more than 60 minutes were included in this prospective, observational single center study (Biomarker Development for Postoperative Cognitive Impairment [BioCog] study). Frontal EEGs were recorded, starting before induction of anesthesia and lasting until recovery of consciousness. EEG data were analyzed based on raw EEG files and downloaded excel data files. We performed multitaper spectral analyses of relevant EEG epochs and further used multitaper spectral estimate to calculate a corresponding spectral parameter. POD assessments were performed twice daily up to the seventh postoperative day. Our primary aim was to analyze the relation between the perioperative spectral edge frequency (SEF) and the development of POD.
RESULTS:
Of the 237 included patients, 41 (17%) patients developed POD. The preoperative EEG in POD patients was associated with lower values in both SEF (POD 13.1 ± 4.6 Hz versus no postoperative delirium [NoPOD] 17.4 ± 6.9 Hz; P = .002) and corresponding γ-band power (POD −24.33 ± 2.8 dB versus NoPOD −17.9 ± 4.81 dB), as well as reduced postinduction absolute α-band power (POD −7.37 ± 4.52 dB versus NoPOD −5 ± 5.03 dB). The ratio of SEF from the preoperative to postinduction state (SEF ratio) was ~1 in POD patients, whereas NoPOD patients showed a SEF ratio >1, thus indicating a slowing of EEG with loss of unconscious. Preoperative SEF, preoperative γ-band power, and SEF ratio were independently associated with POD (P = .025; odds ratio [OR] = 0.892, 95% confidence interval [CI], 0.808–0.986; P = .029; OR = 0.568, 95% CI, 0.342–0.944; and P = .009; OR = 0.108, 95% CI, 0.021–0.568, respectively).
CONCLUSIONS:
Lower preoperative SEF, absence of slowing in EEG while transitioning from preoperative state to unconscious state, and lower EEG power in relevant frequency bands in both these states are related to POD development. These findings may suggest an underlying pathophysiology and might be used as EEG-based marker for early identification of patients at risk to develop POD.
Die vorliegende Bachelorarbeit behandelt das Thema das betriebliche Ideenmanagement. Das Ziel ist den Prozess zur Einreichung, Evaluierung und Umsetzung von Ideen weiterzuentwickeln und zu digitalisieren.
Um das Ziel zu erreichen, werden Primärdaten mit Hilfe von fünf qualitativen Interviews und einer quantitativen Umfrage mit 50 Mitarbeitern erhoben. Abgesehen davon wurden auch Daten aus der Sekundärforschung erfasst, deren Bestandteile die internen Unterlagen zum bestehenden Ideenmanagement dem Status quo, und wissenschaftliche Quellen sind.
"The limits of my language are the limits of my mind. All I know is what I have words for" (Wittgenstein). When learning something completely new, we connect the unknown term to an already existing part of our knowledge. We can only build new ideas and insights upon an existing conceptual foundation. In the field of statistics, we educators frequently find ourselves met with great confusion when teaching novices. These students, entirely unfamiliar with even basic statistics, must connect the introduced statistical terms within their personal existing networks of largely non-statistical knowledge. Lecturers, on the other hand, who are well versed in statistics, have deeply internalized the content to be taught and its relevant context. The juxtaposition of the two roles may produce amusement in a lecturer upon gaining insight into the word associations made by the statistical novices. For example, a ‘logistic regression’ does not involve the ‘shipping of goods in economically difficult times,’ though this might seem entirely reasonable and intuitive to the statistics learner. Other times, these different perspectives can lead to headaches and frustration for both learners and their lecturers. In this article, we illustrate how simple statistical terms are initially connected to a student’s pre-exiting knowledge and how these associations change after completing an introductory course in applied statistics. Furthermore, we emphasize the important difference between “term”, “approach”, and “context”. Understanding this fundamental distinction may help improve the communication between the lecturer and the learner. We offer a collection of practical tools for instructors to help promote students’ conceptual understanding in a supportive, mutually-beneficial learning environment.
In diesem Buch sind Lehrbeispiele gesammelt, die Dozierenden wertvolle Anregungen für ihre eigene Lehre liefern: Es werden Ideen für einzelne Übungen, Unterrichtseinheiten, Prüfungen oder ganze Kurse vorgestellt. Die benötigten Materialien sind für die Nutzer online frei verfügbar, um die Anwendung zu vereinfachen.
Alle Beiträge dieses Buches wurden 2020 für den Preis für das beste Health-Data-Science-Lehrmaterial eingereicht, der von der Arbeitsgruppe Lehre und Didaktik der Biometrie der Deutschen Region der Internationalen Biometrischen Gesellschaft und der GMDS ausgeschrieben wurde. So entstand ein breiter Querschnitt an Beiträgen für lebendige Lehre in Biometrie, Epidemiologie, Public Health und ähnlichen Gebieten.
Das Buch knüpft damit an die beiden Bände Zeig mir Biostatistik! und Zeig mir mehr Biostatistik! an, denen ähnliche Ausschreibungen vorausgingen.
Die Herausgeber unterrichten Biometrie als Haupt- oder Nebenfach an verschiedenen Universitäten bzw. Hochschulen. Es verbindet sie das gemeinsame Ziel, den Austausch von Ideen und ausgereiftem Unterrichtsmaterial im Bereich Health Data Science zu fördern.
Die funktionale Wiedervernetzung von Ökosystemen ist ein notwendiger und entscheidender Beitrag zur nachhaltigen Sicherung der Artenvielfalt. In der nationalen Strategie zur Biologischen Vielfalt 2007 ist formuliert, dass von Verkehrswegen bis 2020 in der Regel keine erheblichen Beeinträchtigungen des Biotopverbundsystems ausgehen (sollen). In der EU-Biodiversitätsstrategie 2030 ist formuliert, dass es für ein wirklich kohärentes und resilientes transeuropäisches Naturschutznetz wichtig sein wird, ökologische Korridore zu schaffen, um eine genetische Isolierung zu verhindern, die Migration von Arten zu ermöglichen und gesunde Ökosysteme zu erhalten und zu verbessern.