SAIMSARA Journal

Machine Generated Science • ISSN 3054-3991

Aortic Dissection Diagnosis: Scoping Review with ☸️SAIMSARA.

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Cardiac & Vascular Health

Issue 1, Volume 1, 2026

DOI: 10.62487/saimsarace693bab

Editorial note
• Last update: 2026-04-28 10:37:16
What is this paper about
This review shows that aortic dissection diagnosis is no longer just “CTA or miss it” — the strongest modern pathway combines ADD-RS, D-dimer, ECG-gated CTA, bedside ultrasound, and selective AI/biomarker triage. The full paper is worth reading because it maps exactly where diagnosis still fails — atypical symptoms, stroke-like presentations, intramural hematoma, transfer misinterpretation — and which tools can realistically close those gaps.
Human-verified editorial review Verified by World ID proof-of-human. This editorial layer was submitted from a SAIMSARA account verified as a unique human.


Abstract: The aim of this paper is to synthesize evidence regarding the diagnostic accuracy, clinical utility, and technological advancements in the identification of aortic dissection across various clinical settings and patient populations. The review utilises 164 references. The mapped evidence indicates that combining the Aortic Dissection Detection Risk Score with D-dimer at a 500 ng/mL threshold offers a robust rule-out signal for acute aortic syndromes, with reported sensitivities of 96.7% to 100% and failure rates as low as 0% to 0.3% in low-to-intermediate risk populations. Computed tomography angiography remained the dominant confirmatory modality across cohorts, with electrocardiogram-gated acquisition consistently improving assessment of the ascending aorta and coronary origins, while transesophageal echocardiography retained a complementary bedside role with sensitivities of 97.5% to 100% in unstable patients. Persistent diagnostic gaps are evident, including initial misdiagnosis rates of 17.6% to 45.3% in emergency and transfer cohorts and more than 60% of dissection deaths undiagnosed before death at autopsy. Emerging signals from deep learning models on non-contrast computed tomography, chest radiography, and electrocardiograms, together with novel biomarkers such as soluble ST2, smooth muscle myosin heavy chain, and circulating microRNAs, suggest expanding options for early triage and differentiation from acute coronary syndromes. Practically, the synthesis supports embedding standardized clinical risk scores with D-dimer and electrocardiogram-gated computed tomography angiography into emergency pathways, while maintaining vigilance for atypical, painless, neurological, and peripartum presentations. Future research should prioritize prospective multicenter validation of artificial intelligence triage tools and multimarker panels in real-world workflows, alongside dedicated diagnostic studies for intramural hematoma where current D-dimer thresholds appear less reliable.

Keywords: Acute aortic dissection; D-dimer; Aortic Dissection Risk Score; Transesophageal echocardiography; Computed tomography angiography; Deep learning; Radiomics; Myosin heavy chain assay; Aortic elongation; Diagnostic delay

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Reference Index (164)