Coronary Computed Tomography Angiography to Exclude Acute Coronary Syndrome in Low-Risk Chest Pain Patients
Bibliographic record
Abstract
BACKGROUND: Coronary computed tomography angiography (CCTA) is a non-invasive imaging tool used predominantly in suspected chronic coronary artery disease (CAD) patients, due to its high negative predictive value. However, increasing focus has been placed on CCTA to manage and risk stratify acute chest pain patients in emergency departments (ED). OBJECTIVE: This scoping review summarizes the available evidence on the role of CCTA to exclude acute coronary syndrome (ACS) in low-risk acute chest pain patients, focusing on its diagnostic accuracy, safety, and application in the context of high sensitivity cardiac troponin assays (hs-cTn). METHODS: Articles published between January 2015 and March 2025 investigating CCTA use in low-risk acute chest pain patients were retrieved from Medline, Embase, Emcare, and Web of Science databases. RESULTS: 22 articles (13,617 patients) were retrieved. CCTA had strong diagnostic performance, with an excellent negative predictive value (99.8-100%) and sensitivity (94-100%) for ACS diagnosis and prediction of major adverse cardiovascular events. Specificity and positive predictive values were lower and less consistent. When combined with hs-cTn, the diagnostic accuracy of CCTA for ACS was improved significantly. CCTA was associated with low rates of ACS at follow-up (0-3.5%), which were lower than or comparable to the safety outcomes of standard care and stress testing.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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 teacher head, 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".