A Novel Serum Biomarker Model to Discriminate Aortic Dissection from Coronary Artery Disease

Dis Markers. 2022 Jul 20:2022:9716424. doi: 10.1155/2022/9716424. eCollection 2022.

Abstract

Background: The misdiagnosis of aortic dissection (AD) can lead to a catastrophic prognosis. There is currently a lack of stable serological indicators with excellent efficacy for the differential diagnosis of AD and coronary artery disease (CAD). A recent study has shown an association between AD and iron metabolism. Thus, we investigated whether iron metabolism could discriminate AD from CAD.

Methods: This retrospective and multicenter cross-sectional study investigated the efficacy of biomarkers of iron metabolism for the differential diagnosis of AD. We collected biomarkers of iron metabolism, liver function, kidney function, and other biochemistry test, and further, logistic regression analysis was applied.

Results: Between Oct. 8, 2020, and Mar. 1, 2021, we recruited 521 patients diagnosed with AD, CAD, and other cardiovascular diseases (OCDs) with the main symptoms of chest and back pain and assigned them to discovery set (n = 330) or validation set (n = 191). We found that six serum biomarkers, including serum iron, low-density lipoprotein, uric acid, transferrin, high-density lipoprotein, and estimated glomerular filtration rate, can serve as a novel comprehensive indicator (named FLUTHE) for the differential diagnosis of AD and CAD with a sensitivity of 0.954 and specificity of 0.905 to differentially diagnose AD and CAD more than 72 h past symptom onset.

Conclusion: Our findings provide insight into the role of iron metabolism in diagnosing and distinguishing AD, which might in the future be a key component in AD diagnosis. Furthermore, we establish a novel model named "FLUTHE" with higher efficiency, safety, and economy, especially for patients with chest pain for more than 72 h.

Publication types

  • Multicenter Study

MeSH terms

  • Aortic Dissection* / diagnosis
  • Biomarkers
  • Coronary Artery Disease* / diagnosis
  • Cross-Sectional Studies
  • Humans
  • Iron / metabolism
  • Retrospective Studies

Substances

  • Biomarkers
  • Iron