Merli Koitmäe

Abstract Computed tomography (CT) is widely used in diagnosing acute mesenteric ischemia (AMI), but robust identification of distinctive subtypes and stages of progression is lacking. Systematic literature search in PubMed, Cochrane Library, Web of Science and Scopus was conducted in May 2024. Studies including at least 10 adult patients and reporting radiological diagnosis of AMI versus no AMI or transmural ischemia versus no transmural ischemia were included.

Abstract This study focuses on key methodological challenges in genome-wide association studies (GWAS) of biobank data with time-to-event outcomes, analyzed using the Cox proportional hazards (CPH) model. We address four primary issues: left-truncation of the data, computational inefficiency of standard model-fitting algorithms, relatedness among individuals, and model misspecification.

Abstract We address issues frequently encountered in the genome-wide association studies (GWAS) on biobank data with time to event outcomes, using the Cox proportional hazards (CPH) model: left-truncation of the outcomes, relative slowness of the conventional model-fitting algorithm, relatedness of individuals and model misspecification. To account for left-truncation, it is conventional to use age as timescale, whereas individuals enter the risk set at the age at biobank recruitment.