Detecting and monitoring arrhythmia recurrence following catheter ablation of atrial fibrillation.

Atrial fibrillation (AF) is the most common arrhythmia prompting clinical presentation, is associated with significant morbidity and mortality. The incidence and prevalence of this arrhythmia is expected to grow significantly in the coming decades. Of the available pharmacologic and non-pharmacologic treatment options, the fastest growing and most intensely studied is catheter-based ablation therapy for AF. Given the varying success rates for AF ablation, the increasingly complex factors that need to be taken into account when deciding to proceed with ablation, as well as varying definitions of procedural success, accurate detection of arrhythmia recurrence and its burden is of significance. Detecting and monitoring AF recurrence following catheter ablation is therefore an important consideration. Multiple studies have demonstrated the close relationship between the intensity of rhythm monitoring with wearable ambulatory cardiac monitors, or implantable cardiac rhythm monitors and the detection of arrhythmia recurrence. Other studies have employed algorithms dependent on intensive monitoring and arrhythmia detection in the decision tree on whether to proceed with repeat ablation or medical therapy. In this review, we discuss these considerations, types of monitoring devices, and implications for monitoring AF recurrence following catheter ablation

Using facial feature extraction to enhance the creation of 3D human models

The creation of personalised 3D characters has evolved to provide a high degree of realism in both appearance and animation. Further to the creation of generic characters the capabilities exist to create a personalised character from images of an individual. This provides the possibility of immersing an individual into a virtual world. Feature detection, particularly on the face, can be used to greatly enhance the realism of the model. To address this innovative contour based templates are used to extract an individual from four orthogonal views providing localisation of the face. Then adaptive facial feature extraction from multiple views is used to enhance the realism of the model

Monomorphic Ventricular Arrhythmias in Athletes.

Ventricular arrhythmias are challenging to manage in athletes with concern for an elevated risk of sudden cardiac death (SCD) during sports competition. Monomorphic ventricular arrhythmias (MMVA), while often benign in athletes with a structurally normal heart, are also associated with a unique subset of idiopathic and malignant substrates that must be clearly defined. A comprehensive evaluation for structural and/or electrical heart disease is required in order to exclude cardiac conditions that increase risk of SCD with exercise, such as hypertrophic cardiomyopathy and arrhythmogenic right ventricular cardiomyopathy. Unique issues for physicians who manage this population include navigating athletes through the decision of whether they can safely continue their chosen sport. In the absence of structural heart disease, therapies such as radiofrequency catheter ablation are very effective for certain arrhythmias and may allow for return to competitive sports participation. In this comprehensive review, we summarise the recommendations for evaluating and managing athletes with MMVA

Integrating monitor alarms with laboratory test results to enhance patient deterioration prediction

AbstractPatient monitors in modern hospitals have become ubiquitous but they generate an excessive number of false alarms causing alarm fatigue. Our previous work showed that combinations of frequently co-occurring monitor alarms, called SuperAlarm patterns, were capable of predicting in-hospital code blue events at a lower alarm frequency. In the present study, we extend the conceptual domain of a SuperAlarm to incorporate laboratory test results along with monitor alarms so as to build an integrated data set to mine SuperAlarm patterns. We propose two approaches to integrate monitor alarms with laboratory test results and use a maximal frequent itemsets mining algorithm to find SuperAlarm patterns. Under an acceptable false positive rate FPRmax, optimal parameters including the minimum support threshold and the length of time window for the algorithm to find the combinations of monitor alarms and laboratory test results are determined based on a 10-fold cross-validation set. SuperAlarm candidates are generated under these optimal parameters. The final SuperAlarm patterns are obtained by further removing the candidates with false positive rate>FPRmax. The performance of SuperAlarm patterns are assessed using an independent test data set. First, we calculate the sensitivity with respect to prediction window and the sensitivity with respect to lead time. Second, we calculate the false SuperAlarm ratio (ratio of the hourly number of SuperAlarm triggers for control patients to that of the monitor alarms, or that of regular monitor alarms plus laboratory test results if the SuperAlarm patterns contain laboratory test results) and the work-up to detection ratio, WDR (ratio of the number of patients triggering any SuperAlarm patterns to that of code blue patients triggering any SuperAlarm patterns). The experiment results demonstrate that when varying FPRmax between 0.02 and 0.15, the SuperAlarm patterns composed of monitor alarms along with the last two laboratory test results are triggered at least once for [56.7–93.3%] of code blue patients within an 1-h prediction window before code blue events and for [43.3–90.0%] of code blue patients at least 1-h ahead of code blue events. However, the hourly number of these SuperAlarm patterns occurring in control patients is only [2.0–14.8%] of that of regular monitor alarms with WDR varying between 2.1 and 6.5 in a 12-h window. For a given FPRmax threshold, the SuperAlarm set generated from the integrated data set has higher sensitivity and lower WDR than the SuperAlarm set generated from the regular monitor alarm data set. In addition, the McNemar’s test also shows that the performance of the SuperAlarm set from the integrated data set is significantly different from that of the SuperAlarm set from the regular monitor alarm data set. We therefore conclude that the SuperAlarm patterns generated from the integrated data set are better at predicting code blue events

Thoracic Epidural Anesthesia Can Be Effective for the Short‐Term Management of Ventricular Tachycardia Storm

Background Novel therapies aimed at modulating the autonomic nervous system, including thoracic epidural anesthesia (TEA), have been shown in small case series to be beneficial in treating medically refractory ventricular tachycardia (VT) storm. However, it is not clear when these options should be considered. We reviewed a multicenter experience with TEA in the management of VT storm to determine its optimal therapeutic use.Methods and Results Data for 11 patients in whom TEA was instituted for VT storm between July 2005 and March 2016 were reviewed to determine the clinical characteristics, outcomes, and role in management. The clinical presentation was incessant VT in 7 (64%), with polymorphic VT in 3 (27%) and monomorphic VT in 8 (73%). The underlying conditions were nonischemic cardiomyopathy in 5 (45%), ischemic cardiomyopathy in 3 (27%), and hypertrophic cardiomyopathy, Brugada syndrome, and cardiac lipoma in 1 (9%) each. Five (45%) had a complete and 1 (9%) had a partial response to TEA; 4 of the complete responders had incessant VT. All 4 patients with a documented response to deep sedation demonstrated a complete response to TEA.Conclusions More than half of the patients with VT storm in our series responded to TEA. TEA may be effective and should be considered as a therapeutic option in patients with VT storm, especially incessant VT, who are refractory to initial management. Improvement in VT burden with deep sedation may suggest that sympathoexcitation plays a key role in perpetuating VT and predict a positive response to TEA

Desperately seeking niches: Grassroots innovations and niche development in the community currency field

The sustainability transitions literature seeks to explain the conditions under which technological innovations can diffuse and disrupt existing socio-technical systems through the successful scaling up of experimental ‘niches’; but recent research on ‘grassroots innovations’ argues that civil society is a promising but under-researched site of innovation for sustainability, albeit one with very different characteristics to the market-based innovation normally considered in the literature. This paper aims to address that research gap by exploring the relevance of niche development theories in a civil society context. To do this, we examine a growing grassroots innovation – the international field of community currencies – which comprises a range of new socio-technical configurations of systems of exchange which have emerged from civil society over the last 30 years, intended to provide more environmentally and socially sustainable forms of money and finance. We draw on new empirical research from an international study of these initiatives comprising primary and secondary data and documentary sources, elite interviews and participant observation in the field. We describe the global diffusion of community currencies, and then conduct a niche analysis to evaluate the utility of niche theories for explaining the development of the community currency movement. We find that some niche-building processes identified in the existing literature are relevant in a grassroots context: the importance of building networks, managing expectations and the significance of external ‘landscape’ pressures, particularly at the level of national-type. However, our findings suggest that existing theories do not fully capture the complexity of this type of innovation: we find a diverse field addressing a range of societal systems (money, welfare, education, health, consumerism), and showing increasing fragmentation (as opposed to consolidation and standardisation); furthermore, there is little evidence of formalised learning taking place but this has not hampered movement growth. We conclude that grassroots innovations develop and diffuse in quite different ways to conventional innovations, and that niche theories require adaptation to the civil society context

Marbling Texture Has No Effect on Collagen Characteristics

Objective: The objective of this study was to determine the effects of marbling texture on collagen traits and adipocyte cross-sectional area. Study Description: Beef strip loins (n = 117) from three U.S. Department of Agriculture quality grades (Top Choice, Low Choice, and Select) with three marbling textures (fine, medium, and coarse) were selected using visual appraisal. Strip loins were taken to the Kansas State University meat laboratory, Manhattan, KS, fabricated into 1-in steaks, vacuum packaged, and aged for 21 days at 40°F. Following aging, steaks were analyzed for collagen and adipocyte staining, imaging, and peak thermal transition temperature. The Bottom Line: These results indicate that marbling texture has no effect on collagen traits and any potential tenderness differences among beef varying in marbling texture are not related to these traits