This article looks at the application of complexity theory to risk assessment in child protection practice, and how it may help to give a better understanding of risk in relation to protecting vulnerable children. Within the last 20 years increasing use has been made of the term complexity within the natural sciences. In recent times, some of the key concepts in complexity theory have started to filter through to the social sciences. The article offers an explanation of some of the key concepts in complexity theory and discusses the development of a model of assessing risk in child protection cases.
Aims Oesophageal fistula represents a rare but dreadful complication of atrial fibrillation catheter ablation. Data on its incidence, management and outcome are sparse. Methods and results This international multicenter registry investigates the characteristics of oesophageal fistulae after treatment of atrial fibrillation by catheter ablation. A total of 553,729 catheter ablation procedures (radiofrequency: 62.9%, cryoballoon: 36.2%, other modalities: 0.9%) were performed at 214 centers in 35 countries. In 78 centers 138 patients (0.025%, radiofrequency: 0.038%, cryoballoon: 0.0015% (p<0.0001)) were diagnosed with an oesophageal fistula. Periprocedural data were available for 118 patients (85.5%). Following catheter ablation, the median time to symptoms and the median time to diagnosis were 18 (7.75, 25; range: 0-60) days and 21 (15, 29.5; range: 2-63) days, respectively. The median time from symptom onset to oesophageal fistula diagnosis was 3 (1, 9; range: 0-42) days. The most common initial symptom was fever (59.3%). The diagnosis was established by chest computed tomography in 80.2% of patients. Oesophageal surgery was performed in 47.4% and direct endoscopic treatment in 19.8%, and conservative treatment in 32.8% of patients. The overall mortality was 65.8%. Mortality following surgical (51.9%) or endoscopic treatment (56.5%) was significantly lower as compared to conservative management (89.5%) (odds ratio 7.463 (2.414, 23.072) p<0.001). Conclusions Oesophageal fistula after catheter ablation of atrial fibrillation is rare and occurs mostly with the use of radiofrequency energy rather than cryoenergy. Mortality without surgical or endoscopic intervention is exceedingly high.
Zebrafish, a popular organism for studying embryonic development and for modeling human diseases, has so far lacked a systematic functional annotation program akin to those in other animal models. To address this, we formed the international DANIO-CODE consortium and created a central repository to store and process zebrafish developmental functional genomic data. Our data coordination center (https://danio-code.zfin.org) combines a total of 1,802 sets of unpublished and re-analyzed published genomic data, which we used to improve existing annotations and show its utility in experimental design. We identified over 140,000 cis-regulatory elements throughout development, including classes with distinct features dependent on their activity in time and space. We delineated the distinct distance topology and chromatin features between regulatory elements active during zygotic genome activation and those active during organogenesis. Finally, we matched regulatory elements and epigenomic landscapes between zebrafish and mouse and predicted functional relationships between them beyond sequence similarity, thus extending the utility of zebrafish developmental genomics to mammals.
Information is the most potent protective weapon we have to combat a pandemic, at both the individual and global level. For individuals, information can help us make personal decisions and provide a sense of security. For the global community, information can inform policy decisions and offer critical insights into the epidemic of COVID-19 disease. Fully leveraging the power of information, however, requires large amounts of data and access to it. To achieve this, we are making steps to form an international consortium, Coronavirus Census Collective (CCC, coronaviruscensuscollective.org), that will serve as a hub for integrating information from multiple data sources that can be utilized to understand, monitor, predict, and combat global pandemics. These sources may include self-reported health status through surveys (including mobile apps), results of diagnostic laboratory tests, and other static and real-time geospatial data. This collective effort to track and share information will be invaluable in predicting hotspots of disease outbreak, identifying which factors control the rate of spreading, informing immediate policy decisions, evaluating the effectiveness of measures taken by health organizations on pandemic control, and providing critical insight on the etiology of COVID-19. It will also help individuals stay informed on this rapidly evolving situation and contribute to other global efforts to slow the spread of disease. In the past few weeks, several initiatives across the globe have surfaced to use daily self-reported symptoms as a means to track disease spread, predict outbreak locations, guide population measures and help in the allocation of healthcare resources. The aim of this paper is to put out a call to standardize these efforts and spark a collaborative effort to maximize the global gain while protecting participant privacy.
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