Distributed lag models for retrospective cohort data with application to a study of built environment and body weight.

Distributed lag models (DLMs) estimate the health effects of exposure over multiple time lags prior to the outcome and are widely used in time series studies. Applying DLMs to retrospective cohort studies is challenging due to inconsistent lengths of exposure history across participants, which is common when using electronic health record databases. A standard approach is to define subcohorts of individuals with some minimum exposure history, but this limits power and may amplify selection bias.

CAGI6 ID panel challenge: assessment of phenotype and variant predictions in 415 children with neurodevelopmental disorders (NDDs).

The Genetics of Neurodevelopmental Disorders Lab in Padua provided a new intellectual disability (ID) Panel challenge for computational methods to predict patient phenotypes and their causal variants in the context of the Critical Assessment of the Genome Interpretation, 6th edition (CAGI6). Eight research teams submitted a total of 30 models to predict phenotypes based on the sequences of 74 genes (VCF format) in 415 pediatric patients affected by Neurodevelopmental Disorders (NDDs). NDDs are clinically and genetically heterogeneous conditions, with onset in infant age.

Amplifying adolescent and emerging adult voices: Development of a pediatric-to-adult transition research advisory council.

Background: Adolescents and emerging adults (AEA) with chronic health conditions may face numerous challenges when undergoing the transition from pediatric to adult health care. Despite the need for engagement with AEA in health research, little is known about how researchers operationalize this engagement. In an effort to enhance transparency in the practices of patient engagement, this commentary details the process of developing a pediatric-adult transition-specific youth advisory council in Alberta: the Transition Research Advisory Council (TRAC).

ClinValAI: A framework for developing Cloud-based infrastructures for the External Clinical Validation of AI in Medical Imaging.

Artificial Intelligence (AI) algorithms showcase the potential to steer a paradigm shift in clinical medicine, especially medical imaging. Concerns associated with model generalizability and biases necessitate rigorous external validation of AI algorithms prior to their adoption into clinical workflows. To address the barriers associated with patient privacy, intellectual property, and diverse model requirements, we introduce ClinValAI, a framework for establishing robust cloud-based infrastructures to clinically validate AI algorithms in medical imaging.

Association between neighborhood walkability and physical activity in a community-based twin sample.

We investigated associations between neighborhood walkability and physical activity using twins (5477 monozygotic and same-sex dizygotic pairs) as "quasi-experimental" controls of genetic and shared environment (familial) factors that would otherwise confound exposure-outcome associations. Walkability comprised intersection density, population density, and destination accessibility. Outcomes included self-reported weekly minutes of neighborhood walking and moderate-to-vigorous physical activity (MVPA) and days per week using transit services (eg, bus, commuter rail).