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Coronary artery disease is detectable by multi-slice computed tomography in most asymptomatic type 2 diabetic patients at high cardiovascular risk

  • Rodolfo Nasti
  • , Ornella Carbonara
  • , Maria L.Mangoni Di Santo Stefano
  • , Roberta Auriemma
  • , Sabato Esposito
  • , Giuseppe Picardi
  • , Nadia Lascar
  • , Antonio Pagano
  • , Roberto Ruggiero
  • , Roberto Torella
  • , Ferdinando C. Sasso*
  • *Corresponding author for this work
    • Seconda Università degli Studi di Napoli
    • S. Maria della Pietà Hospital

    Research output: Contribution to journal › Article › peer-review

    Abstract

    Objective: Non-invasive testing often does not identify coronary artery disease (CAD) in diabetic subjects. This study was designed in order to examine the prevalence of CAD in a cohort of asymptomatic type 2 diabetic patients at high cardiovascular risk and negative nuclear imaging, using multi-slice computed tomography (MSCT) angiography. Methods: In total, 770 type 2 diabetic patients were screened from January 2008 through July 2010. Of these, 132 Caucasians with diabetic nephropathy and asymptomatic for angina were eligible for a cross-sectional study. Patients underwent MSCT after ischaemia was excluded by myocardial Single Photon Emission Computed Tomography (SPECT) at rest and after dynamic exercise. When obstructive plaques were found (≥50% lumen narrowing), patients were sent to conventional coronary angiography (CCA).Results: Six subjects were not included in the analysis because of motion artefacts. MSCT was positive for CAD in 114 patients (90%). Within patients with positive MSCT, 60 (48% of all) showed one or more obstructive plaques. CCA confirmed significant stenosis (≥50%) in 48 of these 60 patients (80%). Some 21 (35%) showed stenosis ≥75% and were submitted to the revascularisation procedure.Conclusion: MSCT seems to better identify CAD than myocardial SPECT in asymptomatic patients with type 2 diabetes and diabetic nephropathy.

    Original languageEnglish
    Pages (from-to)10-17
    Number of pages8
    JournalDiabetes and Vascular Disease Research
    Volume9
    Issue number1
    DOIs
    Publication statusPublished - Jan 2012

    Bibliographical note

    Funding Information:
    Grant from Italian Ministry of University and Research (PRIN).

    Funding

    Grant from Italian Ministry of University and Research (PRIN).

    UN SDGs

    This output contributes to the following UN Sustainable Development Goals (SDGs)

    1. SDG 3 - Good Health and Well-being
      SDG 3 Good Health and Well-being

    Keywords

    • CAD
    • diabetes
    • imaging
    • nephropathy

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