Using AI to Identify Unremarkable Chest Radiographs for Automatic Reporting.

Background Radiology practices have a high volume of unremarkable chest radiographs and artificial intelligence (AI) could possibly improve workflow by providing an automatic report. Purpose To estimate the proportion of unremarkable chest radiographs, where AI can correctly exclude pathology (ie, specificity) without increasing diagnostic errors. Materials and Methods In this retrospective study, consecutive chest radiographs in unique adult patients (≥18 years of age) were obtained January 1-12, 2020, at four Danish hospitals.

Hemodialysis and biomarkers of myocardial infarction - a cohort study.

Objectives: End-stage renal disease is associated with a high risk of cardiovascular disease. We compared the concentration and prognostic ability of high sensitivity cardiac troponin T (hs-cTnT) and I (hs-cTnI) and cardiac myosin-binding protein C (cMyC) among stable hemodialysis patients.

Methods: Patients were sampled before and after hemodialysis.

Autonomous Chest Radiograph Reporting Using AI: Estimation of Clinical Impact.

Background Automated interpretation of normal chest radiographs could alleviate the workload of radiologists. However, the performance of such an artificial intelligence (AI) tool compared with clinical radiology reports has not been established. Purpose To perform an external evaluation of a commercially available AI tool for the number of chest radiographs autonomously reported, the sensitivity for AI detection of abnormal chest radiographs, and the performance of AI compared with that of the clinical radiology reports.

Hemodialysis leads to plasma depletion of lectin complement pathway initiator molecule ficolin-2.

Introduction: This study aimed to investigate changes in complement system-related molecules in patients undergoing hemodialysis.

Methods: Patients >18 years of age on maintenance hemodialysis were included. Using enzyme-linked immunosorbent assays (ELISA) methods complement related molecules ficolin-1, ficolin-2, ficolin-3 mannose-binding lectin, long pentraxin 3, complement activation products C3c, and complement activation potentials were measured before and after a single hemodialysis treatment.

Mid-regional pro-atrial natriuretic peptide levels before and after hemodialysis predict long-term prognosis.

Background: Mid-regional pro-atrial natriuretic peptide (MR-proANP) is a strong prognostic biomarker in cardiovascular disease but there is limited data for its use among patients undergoing dialysis.

Methods: This was a cohort study of patients receiving maintenance hemodialysis from two Danish centers. Blood sampling and echocardiography were performed before and after a dialysis session.