Accession Site Does Not Influence the Risk of Stroke after Diagnostic Coronary Angiography or Intervention: Results from a Large Prospective Registry

INTRODUCTION: Periprocedural stroke represents a rare but serious complication of cardiac catheterization. Pooled data from randomized trials evaluating the risk of stroke following cardiac catheterization via transradial versus transfemoral access showed no difference. On the other hand, a significant difference in stroke rates favoring transradial access was found in a recent meta-analysis of observational studies. Our aim was to determine if there is a difference in stroke risk after transradial versus transfemoral catheterization within a contemporary real-world registry. METHODS: Data from 14,139 patients included in a single-center prospective registry between 2009 and 2016 were used to determine the odds of periprocedural transient ischemic attack (TIA) and stroke for radial versus femoral catheterization via multivariate logistic regression with Firth's correction. RESULTS: A total of 10,931 patients underwent transradial and 3,208 underwent transfemoral catheterization. Periprocedural TIA/stroke occurred in 41 (0.29%) patients. Age was the only significant predictor of TIA/stroke in multivariate analysis, with each additional year representing an odds ratio (OR) = 1.09 (CI 1.05-1.13, p < 0.000). The choice of accession site had no impact on the risk of periprocedural TIA/stroke (OR = 0.81; CI 0.38-1.72, p = 0.577). CONCLUSION: Observational data from a large prospective registry indicate that accession site has no influence on the risk of periprocedural TIA/stroke after cardiac catheterization

GPU-based Parallelization for Schedule Optimization with Uncertainty

This paper presents an application of Graphics Processing Units (GPU) technology for speeding up a sched-ule optimization problem under uncertainty and provides a fast decision support algorithm to solve an air traffic management problem. In terminal airspace, integrated departure and arrival operations using shared resources have the potential to increase operations efficiency. However, results and benefits from integrated operations might be sensitive to flight time uncertainty. In previous work, a scheduling algorithm was pro-posed for a model of the Los Angeles terminal airspace. Uncertainty was introduced in the flight times and the uncertainty cost computation was handled by Monte Carlo simulations. The original implementation was carried out on sequential processors, but a 30-minute scenario ran in 6.5 hours, which prohibits applying the algorithm in real-time. This paper presents a GPU-based implementation of the scheduling optimization with uncertainty achieving a 637x speedup in Monte Carlo simulations and a 154x speedup for the entire algorithm compared to a sequential implementation. The runtime of the GPU-based code for the same 30-minute sce-nario is about 2.5 minutes. This significant speedup allows a large range of experiments to be explored and hundreds of simulations to be run. Two types of experiments are designed and they explore different values of traffic densities and arrival-to-departure ratios. The results demonstrate that there exist trade-off solutions between computed delays and number of controller interventions. The variation of total number of aircraft showed a larger impact on the controller’s workload than the variation of arrival-to-departure ratios. When the traffic density is increased, compromise solutions can be identified to reduce the number of controller interventions and achieve low delays. I