Commercial brain function monitors for depth of anesthesia have been available for more than 2 decades; there are currently more than 10 devices on the market. Advances in this field are evidenced by updated versions of existing monitors, development of new monitors, and increasing research unveiling the mechanisms of anesthesia on the brain. Electroencephalography signal processing forms an integral part of the technology supporting the brain function monitors for derivation of a depth-of-anesthesia index. This article aims to provide a better understanding of the technology and functionality behind these monitors. This review will highlight the general design principles of these devices and the crucial stages in electroencephalography signal processing and classification, with a focus on the key mathematical techniques used in algorithm development for final derivation of the index representing anesthetic state. We will briefly discuss the advantages and limitations of this technology in the clinical setting as a tool in our repertoire used for optimizing individualized patient care. Also included is a table describing 10 available commercial depth-of-anesthesia monitors.

In reviewing the improvement in EEG evaluation after a podcast education module, those with more podcast experience achieved greater gains in EEG evaluation scores. For EEG education, those receiving the podcast education module showed greater increases in scores compared with those receiving didactic teaching without podcasting, as measured by change in a mean EEG evaluation scores.

Objective: Educational methods for residents are shifting toward greater learner independence aided by technological advances. A Web-based program using a podcast was created for resident EEG instruction, replacing conventional didactics. The EEG curriculum also consisted of EEG interpretations under the tutelage of a neurophysiologist. This pilot study aimed to objectively evaluate the effectiveness of the podcast as a new teaching tool. Methods:A podcast for resident EEG instruction was implemented on the Web, replacing the traditional lecture. After Institutional Review Board approval, consent was obtained from the participating residents. Using 25-question evaluation tools, participants were assessed at baseline before any EEG instruction, and reassessed after podcasting and after 10 clinical EEG exposures. Each 25-item evaluation tool contained tracings used for clinical EEG interpretations. Scores after podcast training were also compared to scores after traditional didactic training from a previous study among anesthesiology trainees. Results:Ten anesthesiology residents completed the study. The mean scores with standard deviations are 9.50 Ϯ 2.92 at baseline, 13.40 Ϯ 3.31 (p ϭ 0.034) after the podcast, and 16.20 Ϯ 1.87 (p ϭ 0.019) after interpreting 10 EEGs. No differences were noted between the mean educational tool scores for those who underwent podcasting training compared to those who had undergone traditional didactic training. Conclusion:In this pilot study, podcast training was as effective as the prior conventional lecture in meeting the curricular goals of increasing EEG knowledge after 10 EEG interpretations as measured by assessment tools. Neurology ® 2011;77:e42-e44 GLOSSARY CME ϭ continuing medical education; GME ϭ graduate medical education; IT ϭ Information Technology; UKy ϭ University of Kentucky.Podcasting technology is attractive in graduate medical education (GME) because of its educational potential, low implementation cost, and positive user experiences.1,2 The current technology-savvy millennial generation of residents are a driving force for its growth.3 Podcasting enables faculty to easily provide supplemental didactics in a video podcast format. In this pilot study, podcasting was incorporated into an established EEG curriculum developed by a neurophysiologist and a neurointensivist at the University of Kentucky (UKy). 4,5 The module was taught to anesthesiology residents, pulmonary critical care fellows, neurosurgery residents, and medical students during their neurocritical care rotation. This particular study was addressed to the anesthesiology residents. Conventional didactics were converted to a podcast including slides with lecturer audio, event videos during recordings, and EEG tracings. Topics included monitoring, physiologic basis, and clinical applications. The resident interpreted 10 EEGs with a neurophysiologist (1:1 or 1:2 faculty-to-resident ratio) and participated in video, continuous, and intraoperative EEG monitoring throughout the institution.This study ...

This innovative, collaborative approach using the expertise of the clinical neurophysiologist met the curriculum goals after 10 supervised EEG interpretations, as measured by the study assessment tool.

The obese patient presents many challenges to both anesthesiologist and surgeon. A good understanding of the pathophysiologic effects of obesity and its anesthetic implications in the surgical setting is critical. The anesthesiologist must recognize increased risks and comorbidities inherent to the obese patient and manage accordingly, optimizing multisystem function in the perioperative period that leads to successful outcomes. Addressed from an organ systems approach, the purpose of this review is to provide surgical specialists with an overview of the anesthetic considerations of obesity. Minimally invasive surgery for the obese patient affords improved analgesia, postoperative pulmonary function, and shorter recovery times at the expense of a more challenging intraoperative anesthetic course. The physiologic effects of laparoscopy are discussed in detail. Although laparoscopy's physiologic effects on various organ systems are well recognized, techniques provide means for compensation and reversing such effects, thereby preserving good patient outcomes.

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This educational effort using the department of neurology expertise provided a significant improvement in EEG assessment tool scores.

Long-term retention was significantly improved after 20 compared with 10 EEG interpretations as evaluated by the assessment tools. Potential reasons for better long-term retention may relate to the total number of EEG interpretations with 2 additional spaced interval opportunities and evaluations reinforcing learning.