How can we improve management of syncope in the Emergency Department?

Syncope is a common and challenging presenting complaint to the Emergency Department (ED). Despite substantial research efforts, there is still considerable uncertainty about the optimal ED management of syncope. There is continued interest among clinicians and researchers in improving diagnostic algorithms and optimizing resource utilization. In this paper, we discuss 4 strategies to improve the emergency care of syncope patients: (1) Development of accurate and consistent risk-stratification, (2) Increased use of syncope observation protocols, (3) Evaluation of a discharge with ambulatory monitoring pathway, (4) Use of shared decision-making for disposition decisions. Since current risk-stratification tools have fallen short with regard to subsequent validation and implementation into clinical practice, we outline key factors for future risk-stratification research. We propose that observation units have the potential to safely decrease length-of-stay and hospital costs for hemodynamically stable, intermediate risk patients without adversely affecting clinical outcomes. For appropriate patients with a negative ED evaluation, we recommend consideration of direct discharge, with ambulatory monitoring and expedited follow-up, as a means of decreasing costs and reducing iatrogenic harms. Finally, we advocate for the use of shared decision-making regarding the ultimate disposition of select, intermediate risk patients who have not had a serious condition revealed in the ED. If properly implemented, these four strategies could significantly improve the care of ED syncope patients by helping clinicians identify truly high-risk patients, decreasing unnecessary hospitalizations, and increasing patient satisfaction.

Learning-based Perception Contracts and Applications

Perception modules are integral in many modern autonomous systems, but their accuracy can be subject to the vagaries of the environment. In this paper, we propose a learning-based approach that can automatically characterize the error of a perception module from data and use this for safe control. The proposed approach constructs a {\em perception contract (PC)\/} which generates a set that contains the ground-truth value that is being estimated by the perception module, with high probability. We apply the proposed approach to study a vision pipeline deployed on a quadcopter. With the proposed approach, we successfully constructed a PC for the vision pipeline. We then designed a control algorithm that utilizes the learned PC, with the goal of landing the quadcopter safely on a landing pad. Experiments show that with the learned PC, the control algorithm safely landed the quadcopter despite the error from the perception module, while the baseline algorithm without using the learned PC failed to do so

Preoperative Assessment of Anomalous Right Coronary Artery Arising from the Main Pulmonary Artery

Anomalous origin of the right coronary artery from the pulmonary artery is a rare condition. Two cases are presented in this paper. One case was treated by ligation and coronary artery bypass. The other was treated by direct reimplantation of the anomalous coronary artery into the aorta

Preliminary prediction of individual response to electroconvulsive therapy using whole-brain functional magnetic resonance imaging data.

Electroconvulsive therapy (ECT) works rapidly and has been widely used to treat depressive disorders (DEP). However, identifying biomarkers predictive of response to ECT remains a priority to individually tailor treatment and understand treatment mechanisms. This study used a connectome-based predictive modeling (CPM) approach in 122 patients with DEP to determine if pre-ECT whole-brain functional connectivity (FC) predicts depressive rating changes and remission status after ECT (47 of 122 total subjects or 38.5% of sample), and whether pre-ECT and longitudinal changes (pre/post-ECT) in regional brain network biomarkers are associated with treatment-related changes in depression ratings. Results show the networks with the best predictive performance of ECT response were negative (anti-correlated) FC networks, which predict the post-ECT depression severity (continuous measure) with a 76.23% accuracy for remission prediction. FC networks with the greatest predictive power were concentrated in the prefrontal and temporal cortices and subcortical nuclei, and include the inferior frontal (IFG), superior frontal (SFG), superior temporal (STG), inferior temporal gyri (ITG), basal ganglia (BG), and thalamus (Tha). Several of these brain regions were also identified as nodes in the FC networks that show significant change pre-/post-ECT, but these networks were not related to treatment response. This study design has limitations regarding the longitudinal design and the absence of a control group that limit the causal inference regarding mechanism of post-treatment status. Though predictive biomarkers remained below the threshold of those recommended for potential translation, the analysis methods and results demonstrate the promise and generalizability of biomarkers for advancing personalized treatment strategies

Initial experience with off-pump left ventricular assist device implantation in single center: retrospective analysis

<p>Abstract</p> <p>Background</p> <p>We hypothesize that implantation of left ventricular assist device through off-pump technique is feasible and has a comparable result to implantation on cardiopulmonary bypass and could improve one-year survival.</p> <p>Methods</p> <p>This retrospective, observational, single-center study was conducted on 29 consecutive patients at our institution who underwent off-pump left ventricular assist device implantation by a single surgeon.</p> <p>Results</p> <p>Twenty-seven procedures were performed successfully using the off-pump technique. The survival rate was 92% at 30 days, 76% at 90 days, and 67% at one year. We compared the one-year survival of different implantation periods, and divided our study into three time intervals (2004-2005, 2006, and 2007). There was a trend in reduction in number of deaths over one year that demonstrated a decrease in death rate from 50% to 17%, as well as improvement in our experience over time. However, this trend is not statistically significant (p = 0.08) due to limited sample size.</p> <p>Conclusions</p> <p>Based upon our findings, off-pump left ventricular assist device implantation is a feasible surgical technique, and combining this technique with improved device technology in the future may provide even greater improvement in patient outcomes.</p

SEGUE-2 Limits on Metal-Rich Old-Population Hypervelocity Stars In the Galactic Halo

We present new limits on the ejection of metal-rich old-population hypervelocity stars from the Galactic center (GC) as probed by the SEGUE-2 survey. Our limits are a factor of 3-10 more stringent than previously reported, depending on stellar type. Compared to the known population of B-star ejectees, there can be no more than 30 times more metal-rich old-population F/G stars ejected from the GC. Because B stars comprise a tiny fraction of a normal stellar population, this places significant limits on a combination of the GC mass function and the ejection mechanism for hypervelocity stars. In the presence of a normal GC mass function, our results require an ejection mechanism that is about 5.5 times more efficient at ejecting B-stars compared to low-mass F/G stars.Comment: 18 pages including 5 figures; Submitted to Ap

Initial United States experience with the Paracor HeartNet⁎⁎Paracor Medical, Inc, Sunnyvale, Calif. myocardial constraint device for heart failure

ObjectiveThis study was undertaken to review the initial results and surgical safety data for the US Food and Drug Administration safety and feasibility trial of the Paracor HeartNet (Paracor Medical, Inc, Sunnyvale, Calif.) myocardial constraint device.MethodsPatients with New York Heart Association functional class II or III heart failure underwent device implantation (n = 21) through a left minithoracotomy.ResultsThe average age was 53 years (31–72 years). There were 18 men and 3 women, and 17 patients had nonischemic etiology of heart failure. Mean heart failure duration was 8.3 years (1.4-18.8 years). Average ejection fraction was 22% (11%-33%), with an average left ventricular end-diastolic dimension of 74 mm (55-94 mm). Previous medical therapy included angiotensin-converting enzyme inhibitors, β-blockers, diuretics, digoxin, and aldosterone receptor blockers. At implantation, 17 patients had implantable electronic devices: 1 biventricular pacemaker, 11 biventricular pacemakers with cardioverter-defibrillators, and 5 implantable cardioverter-defibrillators. Patient comorbidities included hypertension in 10 cases, diabetes mellitus in 8, myocardial infarction in 1, and ventricular tachycardia in 8. Mean operative time was 68 minutes (42–102 minutes), and implantation time averaged 15 minutes (5–51 minutes). The average time to ambulation was 1.6 days (1–4 days). The intensive care unit stay averaged 3.3 days (1–16 days), and hospital stay averaged 6.3 days (4–16 days). Atrial fibrillation occurred in 2 patients, and there were 2 in-hospital deaths.ConclusionsThe Paracor device can be implanted in patients with heart failure and reduced left ventricular function with a high degree of success. Significant surgical complications were infrequent. The initial US experience supports the conduct of a randomized, controlled, pivotal trial

Mass Activated Droplet Sorting (MADS) Enables Highâ Throughput Screening of Enzymatic Reactions at Nanoliter Scale

Microfluidic droplet sorting enables the highâ throughput screening and selection of waterâ inâ oil microreactors at speeds and volumes unparalleled by traditional wellâ plate approaches. Most such systems sort using fluorescent reporters on modified substrates or reactions that are rarely industrially relevant. We describe a microfluidic system for highâ throughput sorting of nanoliter droplets based on direct detection using electrospray ionization mass spectrometry (ESIâ MS). Droplets are split, one portion is analyzed by ESIâ MS, and the second portion is sorted based on the MS result. Throughput of 0.7â samplesâ sâ 1 is achieved with 98â % accuracy using a selfâ correcting and adaptive sorting algorithm. We use the system to screen â 15â 000â samples in 6â h and demonstrate its utility by sorting 25â nL droplets containing transaminase expressed in vitro. Labelâ free ESIâ MS droplet screening expands the toolbox for droplet detection and recovery, improving the applicability of droplet sorting to protein engineering, drug discovery, and diagnostic workflows.A microfluidic system for sorting nanoliter droplets based on mass spectrometry is presented. Fully automated, labelâ free sorting at 0.7â samplesâ sâ 1 is achieved with 98â % accuracy. In vitro transcription and translation (ivTT) of a transaminase enzyme in ca.â 25â nL samples is demonstrated and samples are sorted on the basis of enzyme activity.Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/154315/1/anie201913203.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/154315/2/anie201913203-sup-0001-misc_information.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/154315/3/anie201913203_am.pd

Long-term intake of gluten and cognitive function among US women

Importance: Gluten avoidance has been suggested as having a benefit to cognitive health among the general population, given the link between gluten and cognitive impairment in patients with celiac disease. However, data are lacking in individuals without celiac disease. Objective: To examine whether gluten intake is associated with cognitive function in women without celiac disease. Design, Setting, and Participants: This cohort study included US women who participated in the longitudinal, population-based Nurses\u27 Health Study II and had not previously or subsequently been diagnosed with celiac disease. Dietary data were collected from 1991 to 2015, and data on cognitive function were collected from 2014 to 2019. Data analysis was conducted from October 2020 to April 2021. Exposures: Energy-adjusted gluten intake, cumulatively averaged across questionnaire cycles prior to cognitive assessment. Main Outcomes and Measures: Three standardized cognitive scores assessed by the validated Cogstate Brief Battery: (1) psychomotor speed and attention score, (2) learning and working memory score, and (3) global cognition score. Higher scores indicated better performance. Results: The cohort included 13 494 women (mean [SD] age, 60.6 [4.6] years). The mean (SD) gluten intake was 6.3 (1.6) g/d. After controlling for demographic and lifestyle risk factors in linear regression, no significant differences in standardized cognitive scores (mean [SD], 0 [1]) by quintile of gluten intake were found across highest and lowest quintiles of gluten intake (psychomotor speed and attention: -0.02; 95% CI, -0.07 to 0.03; P for trend = .22; learning and working memory: 0.02; 95% CI, -0.03 to 0.07; P for trend = .30; global cognition: -0.002; 95% CI, -0.05 to 0.05; P for trend = .78). The null associations persisted after additional adjustment for major sources of dietary gluten (ie, refined grains or whole grains), comparing decile categories of gluten intake, using gluten intake updated at each previous questionnaire cycle, or modeling changes in gluten intake. Similarly, these associations were not materially altered in sensitivity analyses that excluded women who had reported cancer or dementia diagnosis or had not completed all dietary assessments. Conclusions and Relevance: In this study, long-term gluten intake was not associated with cognitive scores in middle-aged women without celiac disease. Our results do not support recommendations to restrict dietary gluten to maintain cognitive function in the absence of celiac disease or established gluten sensitivity