Background: Klebsiella pneumoniae (Kpn) is an important cause of healthcare-associated infections (HAI). In low and middle-income countries, HAI due to Kpn disproportionally affects neonates. In this study, we investigated the genomic changes that occurred during long-term circulation of a Kpn ST39 clone, causing a disproportionate number of infections on the neonatal ward at a tertiary […]
Estimating the sensitivity of non-treponemal and treponemal antibody tests in primary syphilis
Among patients with primary syphilis, sensitivity of TRUST was 55% (6/11) compared to darkfield microscopy (DFM) and 60% (9/15) compared to Treponema pallidum PCR. Sensitivity of RPR was 78% (38/49) and 93% (43/46), respectively. TPPA had a sensitivity of 95% (41/43) compared to DFM and 96% (43/45) compared to PCR.
Genome-Wide Association Study of Risk for Eosinophilic Granulomatosis with Polyangiitis
Eosinophilic granulomatosis with polyangiitis (EGPA) is an anti-neutrophil cytoplasmic antibody-associated vasculitis characterized by the manifestation of asthma and eosinophilia in the early phases. Currently, it is not well understood how underlying genetic risk factors affect EGPA and its comorbidity. To address this question, we aim to identify novel genetic associations with EGPA and investigating their […]
Scaling genetic discovery for organ volumes using machine learning-assisted imputation and bias-corrected GWAS
Background MRI-derived organ and tissue volumes are powerful endophenotypes for studying complex disease, but their availability is limited by cost and throughput. We present a scalable framework that combines machine learning-based phenotypic imputation with probabilistic GWAS (POP-GWAS) to enable robust genetic discovery for imaging-derived phenotypes (IDPs). Results Using 37,589 UK Biobank MRI scans and 382 […]
Ambient Only vs. Longitudinal Data-Enhanced AI Documentation: A Pilot Study Quantifying the Value of Historical Clinical Context in Primary Care
Abstract Background: Ambient artificial intelligence (AI) clinical documentation tools have gained rapid adoption in healthcare to address physician burnout from documentation burden. However, current implementations primarily rely on real-time audio capture without systematically incorporating longitudinal patient data, potentially limiting documentation completeness for chronic disease management. Objective: To compare documentation completeness between ambient audio-only workflows and […]