Computational Pressure-Fluid Dynamics Applied to Index of Microcirculatory Resistance, Predicting the Prognosis of Drug-Coated Balloons Compared With Drug-Eluting Stents in STEMI Patients

Yang Duan, Yiwen Wang, Min Zhang, Zhi Li, Lei Chen, Hao Miao, Siyu Pei, Yuan Lu, Zhirong Wang, Yang Duan, Yiwen Wang, Min Zhang, Zhi Li, Lei Chen, Hao Miao, Siyu Pei, Yuan Lu, Zhirong Wang

Abstract

Background: The impairment of microvascular injury on prognosis has increasingly drawn extensive awareness along with the high morbidity and mortality of ST-segment elevation myocardial infarction (STEMI) over recent years. The prognostic significance of computational pressure-fluid dynamics applied to index of microcirculatory resistance, derived from coronary angiography (CPFD-caIMR) in microvascular injury evaluation of STEMI patients remained inconclusive. Methods: A total of 213 patients who met the inclusion criteria were selected retrospectively from 1003 STEMI patients from February 2018 to February 2020. Propensity score matching (PSM) was thereafter finished. CPFD-caIMR of all patients was obtained off-line using the software (FlashAngio, Rainmed Ltd., Suzhou, China) after PPCI. The primary endpoint was to compare the CPFD-caIMR and the incidence of major adverse cardiovascular events (MACEs) between drug-coated balloons (DCB) and drug-eluting stents (DES) groups. The correlation between CPFD-caIMR and MACEs was analyzed, and the prognosis of patients with STEMI was evaluated by CPFD-caIMR by multivariate regression analysis. Results: Totally 213 STEMI patients with successful primary percutaneous coronary intervention (PPCI) were included, of whom 84 patients accepted DCB and 129 patients accepted DES respectively. Baseline characteristics and CPFD-caIMR were comparable between DCB and DES groups after PSM (62 patients in each group). CPFD-caIMR was not significantly different between two groups (DES vs. DCB: mean difference: 2.26, 95% CI -4.05 to 8.57, p = 0.45), and so was it when re-grouped by whether CPFD-caIMR > 40U or not (DES vs. DCB: 34.17% vs. 27.16%, p = 0.29). After a follow-up of 1 year, more MACEs occurred in DES group than DCB group (relative risk: 2.50, 95% CI 1.04 to 6.02, p = 0.04). The predictors of MACEs by multi-variate analysis found that, only time from symptom to balloon (p = 0.03) and time from door to balloon (p < 0.01) were independent predictors of MACEs, independent of treatment with DCB or DES intervention. Furthermore, CPFD-caIMR > 40U became an independent predictor of the combined events including cardiovascular deaths or heart failure readmission irrespective of PSM (odds ratio: 4.07, 95% CI: 1.06 to 7.66, p = 0.04). Conclusion: CPFD-caIMR was a promising method for prognosis, which can predict CV death or heart failure readmission in STEMI patients. DCB was a possible strategy in PPCI of STEMI patients, not inferior to DES based on microvascular injury evaluated by CPFD-caIMR.

Keywords: ST-segment elevation myocardial infarction; computational pressure-fluid dynamics derived index of microcirculatory resistance; drug-coated balloon; major adverse cardiovascular event; primary percutaneous coronary intervention; retrospective study.

Conflict of interest statement

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Copyright © 2022 Duan, Wang, Zhang, Li, Chen, Miao, Pei, Lu and Wang.

Figures

FIGURE 1
FIGURE 1
(A), pre-surgery angiography; (B), post-surgery of DCB; (C), the patient’s post-operative caFFR was normal and caIMR was high (caFFR = 0.92, caIMR = 42.1). After 6 months of follow-up, the patient had myocardial infarction again.; (D), pre-surgery angiography; (E), post-surgery of DES; (F), the patient’s postoperative caFFR and caIMR (caFFR = 0.91, caIMR = 22.8) were normal and no MACEs events occurred in 1.5 years of follow-up. Abbreviations: caFFR, coronary angiography-derived fractional flow reserve; caIMR, coronary-angiography-derived index of microcirculatory resistance; DES, drug-eluting stents; DCB, drug-coated balloons; MACE, major adverse cardiovascular events.
FIGURE 2
FIGURE 2
The flow-chart of the study in detail. Abbreviations: STEMI, ST-segment elevation myocardial infarction; PCI, percutaneous coronary intervention; CPFD, computational pressure-fluid dynamics; caIMR, coronary-angiography-derived index of microcirculatory resistance; DES, drug-eluting stents; DCB, drug-coated balloons; MACE, major adverse cardiovascular events.
FIGURE 3
FIGURE 3
MACEs comparing DES and DCB groups. (A). MACEs comparing DES and DCB groups before propensity score matching. (B). MACEs comparing DES and DCB groups after propensity score matching. (C). MACEs comparing caIMR ≤ 40U and caIMR >40U in group DES. (D). MACEs comparing caIMR ≤ 40U and caIMR >40U in group DCB. Abbreviations: DES, drug-eluting stents; DCB, drug-coated balloons; caIMR, coronary-angiography-derived index of microcirculatory resistance; MACE, major adverse cardiovascular events; CV, cardiovascular; HF, heart failure; AMI, acute myocardial infarction; UA, unstable angina; CI, confidence interval.
FIGURE 4
FIGURE 4
Binary logistic regression analysis. Shown are odds ratios for MACEs among patients. (A) Binary logistic regression analysis before propensity score matching. Shown are odds ratios for MACEs among patients before propensity score matching. The size of the square corresponds to the number of patients in two groups. (B) Binary logistic regression analysis after propensity score matching. Shown are odds ratios for MACEs among patients after propensity score matching. The size of the square corresponds to the number of patients in two groups. Abbreviations: MACE, major adverse cardiovascular events; PCI, percutaneous coronary intervention; DCB, drug-coated balloons; DES, drug-eluting stents; S to B, time from symptom to balloon; D to B, time from door to balloon; caIMR, coronary-angiography-derived index of microcirculatory resistance; LVEF, Left ventricular ejection fraction; CK-MB, MB isoenzyme of creatine kinase; IV diuretics, Intravenous diuretics; SD, standard deviation; IQR, inter-quartile range; CI, confidence interval.
FIGURE 5
FIGURE 5
ROC curve of STOB and DTOB predicting MACEs before (A) and after (B) propensity score matching. Abbreviations: S to B, time from symptom to balloon; D to B, time from door to balloon; ROC, Receiver Operating characteristic; AUC, Area under curve.
FIGURE 6
FIGURE 6
Binary logistic regression analysis. Shown are odds ratios for CorH event among patients. (A) Binary logistic regression analysis of predicting the event group including CV deaths or heart failure readmission (CorH) before propensity score matching. Shown are odds ratios for CorH event among patients before propensity score matching. The size of the square corresponds to the number of patients in two groups. (B) Binary logistic regression analysis of predicting the event group including CV deaths or heart failure readmission (CorH) after propensity score matching. Shown are odds ratios for CorH event among patients after propensity score matching. The size of the square corresponds to the number of patients in two groups. Abbreviations: S to B, time from symptom to balloon; D to B, time from door to balloon; caIMR, coronary-angiography-derived index of microcirculatory resistance; LVEF, Left ventricular ejection fraction; CK-MB, MB isoenzyme of creatine kinase; SD, standard deviation; IQR, inter-quartile range; CI, confidence interval.
FIGURE 7
FIGURE 7
ROC curve of CPFD-caIMR predicting the event group including CV deaths or heart failure readmission (CorH) before (A) and after (B) propensity score matching. Abbreviations: CPFD, computational pressure-fluid dynamics; caIMR, coronary-angiography-derived index of microcirculatory resistance; CV, cardiovascular; ROC, Receiver Operating characteristic; AUC, Area under curve.

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