This month: from groundbreaking insights to global conversations—we are just one step away from Florence! Join the leading edge of Acute Cardiovascular Care!
Bibliographic record
Abstract
As cardiovascular care evolves at a rapid pace, so too does our understanding of the intricacies surrounding the diagnosis, treatment, and prognosis of patients with acute cardiovascular conditions. In the March issue of the European Heart Journal—Acute Cardiovascular Care, we delve into a collection of pivotal studies and expert perspectives that may help reshape our approach to managing acute myocardial infarction (AMI), myocardial injury, and chronic coronary syndromes. Boeddinghaus et al.1 present a groundbreaking prospective cohort study, offering a new classification system for Type 2 myocardial infarction (MI) based on cardiac imaging with coronary angiography and cardiac magnetic resonance imaging (MRI). This classification challenges traditional diagnostic thresholds, separating out those without obstructive coronary disease or myocardial abnormality and seeking to provide clearer pathways to understanding the underlying pathology, with crucial implications for patient outcomes and preventive therapies. The study’s findings emphasize the value of imaging in refining diagnoses and risk assessment in suspected Type 2 MI. In a different vein, Restan et al.2 offer an important validation study on the Siemens Atellica IM high-sensitivity cardiac troponin I assay. This study provides compelling evidence for the assay’s potential to optimize cardiac evaluations in emergency departments globally, bringing clarity to the decision-making process for patients presenting with non–ST-elevation MI (NSTEMI). Their findings underscore the potential of rapid, high-sensitivity assays to transform acute care settings and improve patient outcomes. Alaoui-Ismaili et al.3 investigates a niche but important intersection between post-cardiac neuroprognostication in AMICS (Acute myocardial infarction complicated by cardiogenic shock) patients supported by the Impella micro-axial flow pump, revealing the confounding impact of haemolysis on neuron-specific enolase (NSE) levels. The study calls for caution in interpreting NSE levels, highlighting the complexity of prognostic markers in this patient population. These findings have significant implications for patient management and the interpretation of biomarkers in acute cardiovascular care. Additionally, our Perspectives section explores the 2024 European Society of Cardiology guidelines for chronic coronary syndromes, with an in-depth focus on ischaemia with non-obstructive coronary arteries (INOCAs)4 and antithrombotic therapy, providing expert insights into these complex conditions.5 Furthermore, Hickman et al.’s6 educational paper critiques the evolving role of the 99th percentile in cardiac troponin assays, stressing the importance of context and understanding the limitations of this threshold in clinical decision-making. Finally, Verbeeck et al.7 present a timely examination of the shift towards patient-centric outcomes in clinical trial design, advocating for the increasing importance of superiority trials over non-inferiority designs. This shift is exemplified by the REC-CAGEFREEI trial, which provides critical insights into how we assess and improve therapies aimed at enhancing patient safety and well-being. Finally, we like to take this opportunity and warmly invite you to explore the latest advancements in acute cardiovascular and intensive care at this year’s Annual Conference in Florence. This event promises to be an extraordinary gathering of experts, where cutting-edge research, transformative treatment approaches, and practical solutions to the most pressing challenges in cardiovascular care will be shared. Join us for an inspiring experience that will enhance your knowledge, broaden your perspective, and strengthen your network. Whether you are a clinician, researcher, or healthcare professional, this conference is an opportunity to stay at the forefront of your field and engage with peers who share your passion for improving patient outcomes. Do not miss out on the chance to be part of this pivotal event—discover more, connect with the best, and shape the future of acute cardiovascular and intensive care! Pascal Vranckx (writing—original draft: lead), David Morrow (writing—original draft: supporting), Sean van Diepen (writing—original draft: supporting), and Frederik H. Verbrugge (writing—original draft: supporting) There is no external funding for this article. No new data were generated or analysed in support of this research.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.013 | 0.050 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.010 | 0.009 |
| Scholarly communication | 0.025 | 0.033 |
| Open science | 0.002 | 0.014 |
| Research integrity | 0.014 | 0.037 |
| Insufficient payload (model declined to judge) | 0.058 | 0.028 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".