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Updated: Sep 14, 2025

Interventional Diagnostic Procedure: A Practical Guide for the Assessment of Coronary Vascular Function
Published on: March 15, 2022
Prognostic impact of type 2 diabetes mellitus and coronary microvascular dysfunction in patients undergoing
Lijun Feng1,2,3,4, Yuxuan Zhang1,2,3,4, Chenyun Zhang1,2,3,4
1Department of Cardiology of The Second Affiliated Hospital, School of Medicine, Zhejiang University, Hangzhou, China.
Background:
The combined predictive value of type 2 diabetes mellitus (T2DM) and coronary microvascular dysfunction (CMD) in rotational atherectomy (RA) patients during the PCI remains unclear. The study examined whether the co-occurrence of DM and CMD, determined by angiography-derived index of microcirculatory resistance in RA patients influences clinical outcomes.
Methods:
This was a retrospective, multicenter, observational study involving 452 patients at 3 medical centers. The primary endpoint was the occurrence of major adverse cardiac events (MACEs) at 24 months after the procedure, encompassing cardiac death, myocardial infarction, target vessel revascularization, and readmission for unstable angina.
Results:
The post-PCI angio-IMR was lower in the non-DM group compared to the DM group (17.40 [13.86-21.34] vs. 18.53 [14.63-23.01], p = 0.037). Patients with DM had a higher risk of MACEs at 24 months than those without DM (17.42% vs. 9.49%, p = 0.011). CMD was defined as post-PCI angio-IMR ≧ 25.Patients with CMD demonstrated a statistically significant elevated risk of MACEs at the 24-month follow-up, when compared to individuals without CMD (26.77% vs. 10.54%, p < 0.001). In comparison to others, patients with both DM and CMD had the highest incidence of MACEs. Specifically, DM combined with CMD was the strongest independent predictor of MACEs (DM + CMD; HR: 5.61, 95% CI, 2.606-12.083, p < 0.001).
Conclusion:
This study reveals that both T2DM and CMD are associated with the risk of MACEs in RA patients during the PCI. Combing T2DM and CMD can further improve the accessibility to predict the risk of MACEs.
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