Université de Montréal

About: Université de Montréal is a education organization based out in Montreal, Quebec, Canada. It is known for research contribution in the topics: Population & Context (language use). The organization has 45641 authors who have published 100476 publications receiving 4004007 citations. The organization is also known as: University of Montreal & UdeM.

Arrhythmia Burden in Adults With Surgically Repaired Tetralogy of Fallot A Multi-Institutional Study

Abstract: Background— The arrhythmia burden in tetralogy of Fallot, types of arrhythmias encountered, and risk profile may change as the population ages. Methods and Results— The Alliance for Adult Research in Congenital Cardiology (AARCC) conducted a multicenter cross-sectional study to quantify the arrhythmia burden in tetralogy of Fallot, to characterize age-related trends, and to identify associated factors. A total of 556 patients, 54.0% female, 36.8±12.0 years of age were recruited from 11 centers. Overall, 43.3% had a sustained arrhythmia or arrhythmia intervention. Prevalence of atrial tachyarrhythmias was 20.1%. Factors associated with intraatrial reentrant tachycardia in multivariable analyses were right atrial enlargement (odds ratio [OR], 6.2; 95% confidence interval [CI], 2.8 to 13.6), hypertension (OR, 2.3; 95% CI, 1.1 to 4.6), and number of cardiac surgeries (OR, 1.4; 95% CI, 1.2 to 1.6). Older age (OR, 1.09 per year; 95% CI, 1.05 to 1.12), lower left ventricular ejection fraction (OR, 0.93 per unit;...

Associations between sleep duration patterns and behavioral/cognitive functioning at school entry.

Abstract: Objective: The aim of the study was to investigate the associations between longitudinal sleep duration patterns and behavioral/cognitive functioning at school entry. Design, Setting, and Participants: Hyperactivity-impulsivity (HI), inattention, and daytime sleepiness scores were measured by questionnaire at 6 years of age in a sample of births from 1997 to 1998 in a Canadian province (N=1492). The Peabody Picture Vocabulary Test - Revised (PPVT-R) was administered at 5 years of age and the Block Design subtest (WISCIII) was administered at 6 years of age. Sleep duration was reported yearly by the children’s mothers from age 2.5 to 6 years. A group-based semiparametric mixture model was used to estimate developmental patterns of sleep duration. The relationships between sleep duration patterns and both behavioral items and neurodevelopmental tasks were tested using weighted multivariate logistic regression models to control for potentially confounding psychosocial factors. Results: Four sleep duration patterns were identified: short persistent (6.0%), short increasing (4.8%),10-hour persistent (50.3%), and 11-hour persistent (38.9%). The association of short sleep duration patterns with high HI scores (P=0.001), low PPVT-R performance (P=0.002), and low Block Design subtest performance (P=0.004) remained significant after adjusting for potentially confounding variables. Conclusions: Shortened sleep duration, especially before the age of 41 months, is associated with externalizing problems such as HI and lower cognitive performance on neurodevelopmental tests. Results highlight the importance of giving a child the opportunity to sleep at least 10 hours per night throughout early childhood.

The Importance of Skip Connections in Biomedical Image Segmentation

Abstract: In this paper, we study the influence of both long and short skip connections on Fully Convolutional Networks (FCN) for biomedical image segmentation. In standard FCNs, only long skip connections are used to skip features from the contracting path to the expanding path in order to recover spatial information lost during downsampling. We extend FCNs by adding short skip connections, that are similar to the ones introduced in residual networks, in order to build very deep FCNs (of hundreds of layers). A review of the gradient flow confirms that for a very deep FCN it is beneficial to have both long and short skip connections. Finally, we show that a very deep FCN can achieve near-to-state-of-the-art results on the EM dataset without any further post-processing.