Diagnostic accuracy of a machine learning algorithm using point-of-care high-sensitivity cardiac troponin I for rapid rule-out of myocardial infarction: a retrospective study.

Background: Point-of-care (POC) high-sensitivity cardiac troponin (hs-cTn) assays have been shown to provide similar analytical precision despite substantially shorter turnaround times compared with laboratory-based hs-cTn assays. We applied the previously developed machine learning based personalised Artificial Intelligence in Suspected Myocardial Infarction Study (ARTEMIS) algorithm, which can predict the individual probability of myocardial infarction, with a single POC hs-cTn measurement, and compared its diagnostic performance with standard-of-care pathways for rapid rule-out of myocardial infarction.

Methods: We retrospectively analysed pooled data from consecutive patients of two prospective observational cohorts in geographically distinct regions (the Safe Emergency Department Discharge Rate cohort from the USA and the Suspected Acute Myocardial Infarction in Emergency cohort from Australia) who presented to the emergency department with suspected myocardial infarction.

Severe Eosinophilic Asthma or Eosinophilic Granulomatosis With Polyangiitis: Potential Biomarkers for Novel Diagnostic Strategies.

Background: Severe eosinophilic asthma (SEA) may be the prodromal phase of eosinophilic granulomatosis with polyangiitis (EGPA). Nevertheless, few studies have tried to recognize EGPA in the early stages of the disease.

Objective: To identify a panel of clinical and biological markers to detect which severe asthmatic patient might be considered in a prodromal phase of EGPA and crafting a strategy for diagnostic decision-making.

Unrecognized myocardial scar by late-gadolinium-enhancement cardiovascular magnetic resonance: Insights from the population-based Hamburg City Health Study.

Background: The presence of myocardial scar is associated with poor prognosis in several underlying diseases. Late-gadolinium-enhancement (LGE) cardiovascular magnetic resonance (CMR) imaging reveals clinically silent "unrecognized myocardial scar" (UMS), but the etiology of UMS often remains unclear. This population-based CMR study evaluated prevalence, localization, patterns, and risk factors of UMS.

Personalized diagnosis in suspected myocardial infarction.

Background: In suspected myocardial infarction (MI), guidelines recommend using high-sensitivity cardiac troponin (hs-cTn)-based approaches. These require fixed assay-specific thresholds and timepoints, without directly integrating clinical information. Using machine-learning techniques including hs-cTn and clinical routine variables, we aimed to build a digital tool to directly estimate the individual probability of MI, allowing for numerous hs-cTn assays.

Impact of Sex and Cardiovascular Risk Factors on Myocardial T1, Extracellular Volume Fraction, and T2 at 3 Tesla: Results From the Population-Based, Hamburg City Health Study.

Background: Reliable reference intervals are crucial for clinical application of myocardial T1 and T2 mapping cardiovascular magnetic resonance imaging. This study evaluated the impact of sex and cardiovascular risk factors on myocardial T1, extracellular volume fraction (ECV), and T2 at 3T in the population-based HCHS (Hamburg City Health Study).

Methods: The final study sample consisted of 1576 consecutive HCHS participants between 46 and 78 years without prevalent heart disease, including 1020 (67.