Benzodiazepine-Free Cardiac Anesthesia for Reduction of Postoperative Delirium (B-Free): A protocol for a multi-centre randomized cluster crossover trial

Delirium is common after cardiac surgery and is associated with adverse outcomes. Administration of benzodiazepines before and after cardiac surgery is associated with delirium; guidelines recommend minimizing their use. Benzodiazepine administration during cardiac surgery remains common because of its recognized benefits. Th

Differential classification of states of consciousness using envelope- and phase-based functional connectivity

The development of sophisticated computational tools to quantify changes in the brain\u27s oscillatory dynamics across states of consciousness have included both envelope- and phase-based measures of functional connectivity (FC), but there are very few direct comparisons of these techniques using the same dataset. The goal of this study was to compare an envelope-based (i.e. Amplitude Envelope Correlation, AEC) and a phase-based (i.e. weighted Phase Lag Index, wPLI) measure of FC in their classification of states of consciousness. Nine healthy participants underwent a three-hour experimental anesthetic protocol with propofol induction and isoflurane maintenance, in which five minutes of 128-channel electroencephalography were recorded before, during, and after anesthetic-induced unconsciousness, at the following time points: Baseline; light sedation with propofol (Light Sedation); deep unconsciousness following three hours of surgical levels of anesthesia with isoflurane (Unconscious); five minutes prior to the recovery of consciousness (Pre-ROC); and three hours following the recovery of consciousness (Recovery). Support vector machine classification was applied to the source-localized EEG in the alpha (8-13 Hz) frequency band in order to investigate the ability of AEC and wPLI (separately and together) to discriminate i) the four states from Baseline; ii) Unconscious ( deep unconsciousness) vs. Pre-ROC ( light unconsciousness); and iii) responsiveness (Baseline, Light Sedation, Recovery) vs. unresponsiveness (Unconscious, Pre-ROC). AEC and wPLI yielded different patterns of global connectivity across states of consciousness, with AEC showing the strongest network connectivity during the Unconscious epoch, and wPLI showing the strongest connectivity during full consciousness (i.e., Baseline and Recovery). Both measures also demonstrated differential predictive contributions across participants and used different brain regions for classification. AEC showed higher classification accuracy overall, particularly for distinguishing anesthetic-induced unconsciousness from Baseline (83.7 ± 0.8%). AEC also showed stronger classification accuracy than wPLI when distinguishing Unconscious from Pre-ROC (i.e., deep from light unconsciousness) (AEC: 66.3 ± 1.2%; wPLI: 56.2 ± 1.3%), and when distinguishing between responsiveness and unresponsiveness (AEC: 76.0 ± 1.3%; wPLI: 63.6 ± 1.8%). Classification accuracy was not improved compared to AEC when both AEC and wPLI were combined. This analysis of source-localized EEG data demonstrates that envelope- and phase-based FC provide different information about states of consciousness but that, on a group level, AEC is better able to detect relative alterations in brain FC across levels of anesthetic-induced unconsciousness compared to wPLI

Obstructive sleep apnea as an independent predictor of postoperative delirium and pain: Protocol for an observational study of a surgical cohort [version 2; referees: 2 approved]

Introduction: Postoperative delirium and pain are common complications in adults, and are difficult both to prevent and treat. Obstructive sleep apnea (OSA) is prevalent in surgical patients, and has been suggested to be a risk factor for postoperative delirium and pain. OSA also might impact pain perception, and alter pain medication requirements. This protocol describes an observational study, with the primary aim of testing whether OSA is an independent predictor of postoperative complications, focusing on (i) postoperative incident delirium and (ii) acute postoperative pain severity. We secondarily hypothesize that compliance with prescribed treatment for OSA (typically continuous positive airway pressure or CPAP) might decrease the risk of delirium and the severity of pain. Methods and analysis: We will include data from patients who have been enrolled into three prospective studies: ENGAGES, PODCAST, and SATISFY-SOS. All participants underwent general anesthesia for a non-neurosurgical inpatient operation, and had a postoperative hospital stay of at least one day at Barnes Jewish Hospital in St. Louis, Missouri, from February 2013 to May 2018.  Patients included in this study have been assessed for postoperative delirium and pain severity as part of the parent studies. In the current study, determination of delirium diagnosis will be based on the Confusion Assessment Method, and the Visual Analogue Pain Scale will be used for pain severity. Data on OSA diagnosis, OSA risk and compliance with treatment will be obtained from the preoperative assessment record. Other variables that are candidate risk factors for delirium and pain will also be extracted from this record. We will use logistic regression to test whether OSA independently predicts postoperative delirium and linear regression to assess OSAs relationship to acute pain severity. We will conduct secondary analyses with subgroups to explore whether these relationships are modified by compliance with OSA treatment.</ns4:p

Ketamine infusion for patients receiving extracorporeal membrane oxygenation support: A case series

The use of ketamine infusion for sedation/analgesia in patients receiving extracorporeal membrane oxygenation (ECMO) therapy has not been described. The aims of this retrospective cohort study were to explore whether ketamine infusion for patients requiring ECMO therapy was associated with altered RASS scores, decreased concurrent sedative or opioid use, or with changes in vasopressor requirements.  All patients on ECMO who received ketamine infusions in addition to sedative and/or opioid infusions between December 2013 and October 2014 at Barnes-Jewish Hospital in St. Louis were retrospectively identified. Patient characteristics and process of care data were collected. A total of 26 ECMO patients receiving ketamine infusion were identified. The median (inter quartile range [range]) age was 40 years (30-52 [25-66]) with 62% male. The median starting infusion rate of ketamine was 50 mg/hr (30-50 [6-150]) and it was continued for a median duration of 9 days (4-14 [0.2-21]). Prior to ketamine, 14/26 patients were receiving vasopressor infusions to maintain hemodynamic stability. Ketamine initiation was associated with a decrease in vasopressor requirement in 11/26  patients within two hours, and 0/26 required an increase (p<0.001). All patients were receiving sedative and/or opioid infusions at the time of ketamine initiation; 9/26 had a decrease in these infusions within two hours of ketamine initiation, and 1/26 had an increase (p=0.02; odds ratio for decrease to increase = 9; 95% CI, 1.14 to 71.04). The median (IQR[range]) RASS score 24 hours before ketamine initiation was -4 (-3 to -5, [0 to -5]) and after ketamine was -4 (-3 to -4 [-1 to -5]) ( P = 0.614). Ketamine infusion can be used as an adjunctive sedative agent in patients receiving ECMO and may decrease concurrent sedative and/or opioid infusions without altering RASS scores. The hemodynamic effects of ketamine may provide the benefit of decreasing vasopressor requirements

SCOOP: Self-Supervised Correspondence and Optimization-Based Scene Flow

Scene flow estimation is a long-standing problem in computer vision, where the goal is to find the 3D motion of a scene from its consecutive observations. Recently, there have been efforts to compute the scene flow from 3D point clouds. A common approach is to train a regression model that consumes source and target point clouds and outputs the per-point translation vectors. An alternative is to learn point matches between the point clouds concurrently with regressing a refinement of the initial correspondence flow. In both cases, the learning task is very challenging since the flow regression is done in the free 3D space, and a typical solution is to resort to a large annotated synthetic dataset. We introduce SCOOP, a new method for scene flow estimation that can be learned on a small amount of data without employing ground-truth flow supervision. In contrast to previous work, we train a pure correspondence model focused on learning point feature representation and initialize the flow as the difference between a source point and its softly corresponding target point. Then, in the run-time phase, we directly optimize a flow refinement component with a self-supervised objective, which leads to a coherent and accurate flow field between the point clouds. Experiments on widespread datasets demonstrate the performance gains achieved by our method compared to existing leading techniques while using a fraction of the training data. Our code is publicly available at https://github.com/itailang/SCOOP

Prevention of awareness during general anesthesia

Awareness during general anesthesia with subsequent explicit recall is a serious and frequently preventable problem that is gaining attention from clinicians and patients alike. Cost-effective interventions that increase vigilance should be implemented to decrease the likelihood of this complication

\u3ci\u3eTalking Foreign Policy\u3c/i\u3e: The Iran Nuclear Accord

Talking Foreign Policy is a one-hour radio program, hosted by Case Western Reserve University School of Law Co-Dean Michael Scharf, in which experts discuss the salient foreign policy issues of the day. Dean Scharf created Talking Foreign Policy to break down complex foreign policy topics that are prominent in the day-to-day news cycles yet difficult to understand. This broadcast featured: Milena Sterio, Associate Dean and Professor of Law at Cleveland-Marshall College of Law. Sterio is also one of six permanent editors of the IntLawGrrls blog and an expert in the field of international law Avidan Cover, Director of the Institute for Global Law & Policy at Case Western Reserve University School of Law and an expert in national security law. Cover has also litigated national security cases in federal and state courts Paul Williams, who is President and co-founder of the Public International Law & Policy Group and has advised parties to treaty negotiations around the world Col. Mike Newton, Professor of Practice at Vanderbilt University School of Law. Newton has published more than 80 books, articles, and book chapters and is an expert on transnational justice and conduct of hostilities issue