Defining Kawasaki disease and pediatric inflammatory multisystem syndrome-temporally associated to SARS-CoV-2 infection during SARS-CoV-2 epidemic in Italy: results from a national, multicenter survey

Background: There is mounting evidence on the existence of a Pediatric Inflammatory Multisystem Syndrome-temporally associated to SARS-CoV-2 infection (PIMS-TS), sharing similarities with Kawasaki Disease (KD). The main outcome of the study were to better characterize the clinical features and the treatment response of PIMS-TS and to explore its relationship with KD determining whether KD and PIMS are two distinct entities. Methods: The Rheumatology Study Group of the Italian Pediatric Society launched a survey to enroll patients diagnosed with KD (Kawasaki Disease Group - KDG) or KD-like (Kawacovid Group - KCG) disease between February 1st 2020, and May 31st 2020. Demographic, clinical, laboratory data, treatment information, and patients' outcome were collected in an online anonymized database (RedCAP®). Relationship between clinical presentation and SARS-CoV-2 infection was also taken into account. Moreover, clinical characteristics of KDG during SARS-CoV-2 epidemic (KDG-CoV2) were compared to Kawasaki Disease patients (KDG-Historical) seen in three different Italian tertiary pediatric hospitals (Institute for Maternal and Child Health, IRCCS "Burlo Garofolo", Trieste; AOU Meyer, Florence; IRCCS Istituto Giannina Gaslini, Genoa) from January 1st 2000 to December 31st 2019. Chi square test or exact Fisher test and non-parametric Wilcoxon Mann-Whitney test were used to study differences between two groups. Results: One-hundred-forty-nine cases were enrolled, (96 KDG and 53 KCG). KCG children were significantly older and presented more frequently from gastrointestinal and respiratory involvement. Cardiac involvement was more common in KCG, with 60,4% of patients with myocarditis. 37,8% of patients among KCG presented hypotension/non-cardiogenic shock. Coronary artery abnormalities (CAA) were more common in the KDG. The risk of ICU admission were higher in KCG. Lymphopenia, higher CRP levels, elevated ferritin and troponin-T characterized KCG. KDG received more frequently immunoglobulins (IVIG) and acetylsalicylic acid (ASA) (81,3% vs 66%; p = 0.04 and 71,9% vs 43,4%; p = 0.001 respectively) as KCG more often received glucocorticoids (56,6% vs 14,6%; p < 0.0001). SARS-CoV-2 assay more often resulted positive in KCG than in KDG (75,5% vs 20%; p < 0.0001). Short-term follow data showed minor complications. Comparing KDG with a KD-Historical Italian cohort (598 patients), no statistical difference was found in terms of clinical manifestations and laboratory data. Conclusion: Our study suggests that SARS-CoV-2 infection might determine two distinct inflammatory diseases in children: KD and PIMS-TS. Older age at onset and clinical peculiarities like the occurrence of myocarditis characterize this multi-inflammatory syndrome. Our patients had an optimal response to treatments and a good outcome, with few complications and no deaths

Load Balancing in Mesh-like Computations using Prediction Binary Trees

We present a load-balancing technique that exploits the temporal coherence, among successive computation phases, in mesh-like computations to be mapped on a cluster of processors. Our method partitions the computation in balanced tasks and distributes them to independent processors through the Prediction Binary Tree (PBT). At each new phase, current PBT is updated by using previous phase computing time (for each task) as (next phase) cost estimate. The PBT is designed so that it balances the load across the tasks as well as reduce dependency among processors for higher performances. Reducing dependency is obtained by using rectangular tiles of the mesh, of almost-square shape (i.e. one dimension is at most twice the other). By reducing dependency, one can reduce inter-processors communication or exploit local dependencies among tasks (such as data locality). Our strategy has been assessed on a significant problem, Parallel Ray Tracing. Our implementation shows a good scalability, and improves over coherence-oblivious implementations. We report different measurements showing that granularity of tasks is a key point for the performances of our decomposition/mapping strategy.

On Estimating the Effectiveness of Temporal and Spatial Coherence in Parallel Ray Tracing

In this paper we estimate the effectiveness of exploiting coherence in Parallel Ray Tracing. We present a loadbalancing technique which divides the original rendering problem in balanced subtasks and distribute them to independent processors through a Prediction Binary Tree (PBT). Furthermore the PBT allows to exploit temporal coherence among successive image frames. At each new frame, it updates the current PBT using a cost function which uses the previous rendering time as cost estimate. We also provide two heuristics which take advantage of data-locality. We assess the effectiveness of the proposed solution by running two experiments. The £rst one aims to investigate the accurancy of predictions made using the PBT. Results show that such predictions are quite accurate even considering a heavily unbalanced scene and a fast moving camera. The second experiment evaluates the two locality-aware heuristics showing a modest improvement

Easy and Efficient Agent-based Simulations with the OpenABL Language and Compiler

Agent-based simulations represent an effective scientific tool, with numerous applications from social sciences to biology, which aims to emulate or predict complex phenomena through a set of simple rules performed by multiple agents. To simulate a large number of agents with complex models, practitioners have developed high-performance parallel implementations, often specialized for particular scenarios and target hardware. It is, however, difficult to obtain portable simulations, which achieve high performance and at the same time are easy to write and to reproduce on different hardware. This article gives a complete presentation of OpenABL, a domain-specific language and a compiler for agent-based simulations that enable users to achieve high-performance parallel and distributed agent simulations with a simple and portable programming environment. OpenABL is comprised of (1) an easy-to-program language, which relies on domain abstractions and explicitly exposes agent parallelism, synchronization and locality, (2) a source-to-source compiler, and (3) a set of pluggable compiler backends, which generate target code for multi-core CPUs, GPUs, and cloud-based systems. We evaluate OpenABL on simulations from different fields. In particular, our analysis includes predator–prey and keratinocyte, two complex simulations with multiple step functions, heterogeneous agent types, and dynamic creation and removal of agents. The results show that OpenABL-generated codes are portable to different platforms, perform similarly to manual target-specific implementations, and require significantly fewer lines of codes