National Heart Foundation of Australia & Cardiac Society of Australia and New Zealand: Comprehensive Australian Clinical Guideline for Diagnosing and Managing Acute Coronary Syndromes 2025
Bibliographic record
Abstract
Scope: This guideline makes recommendations for: assessing adults aged 18 years and older with suspected ACS managing confirmed ACS recovery after ACS and secondary prevention of future vascular events. The definition of myocardial infarction (MI) has been refined from the Fourth universal definition of myocardial infarction to align more closely with the clinical syndromes that characterise occlusive and non-occlusive MI. This guideline adopts the term acute coronary occlusion myocardial infarction which includes both atherosclerotic and non-atherosclerotic causes. The guideline predominantly focuses on managing people with MI due to atherosclerotic plaque rupture, ulceration, fissure, or erosion. Some recommendations presented in this guideline may be relevant to other types of MI (e.g. type 2MI), particularly with respect to initial acute treatment and post-hospital care. Specific recommendations are presented in some cases for MI due to non-atherosclerotic causes (e.g. spontaneous coronary artery dissection [SCAD]) (Figure 1).The guideline does not cover management of non-ACS presentations and non-cardiac chest pain. It does not include detailed guidance on managing related clinical conditions, such as heart failure, or comorbidities such as cancer or diabetes. Healthcare professionals should refer to existing guidance, where available.
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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 | 0.010 | 0.037 |
| Meta-epidemiology (narrow) | 0.001 | 0.002 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.003 | 0.004 |
| Research integrity | 0.008 | 0.010 |
| Insufficient payload (model declined to judge) | 0.004 | 0.004 |
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".