| Literature DB >> 34966798 |
Boris Schnorbus1,2, Kerstin Jurk2, Karl J Lackner3, Caroline Welk1, Thomas Münzel1, Tommaso Gori1,4.
Abstract
Aims: In this pre-specified analysis of the "endothelium, stent and antiplatelet therapy" study, we investigate the impact of antiplatelet therapies on microvascular function in patients undergoing stenting for an acute coronary syndrome. Methods andEntities:
Keywords: antiplatelet; coronary; microvascular (MV); randomized; stent
Year: 2021 PMID: 34966798 PMCID: PMC8710519 DOI: 10.3389/fcvm.2021.780605
Source DB: PubMed Journal: Front Cardiovasc Med ISSN: 2297-055X
Figure 1Study protocol.
Patient characteristics.
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| Age, years | 64 | 55–71 | 61 | 55–65 | 64 | 52–65 | 0.503 |
| Male, | 18 | (75%) | 12 | (80%) | 17 | (81%) | 0.129 |
| BMI | 27 | 26–29 | 29 | 26–31 | 29 | 27–30 | 0.218 |
| Blood pressure, sytolic, mmHg | 130 | 127–145 | 133 | 121–150 | 136 | 120–150 | 0.913 |
| Blood pressure, diastolic, mmHg | 80 | 79–82 | 80 | 66–97 | 80 | 70–94 | 0.969 |
| Clinical presentation, NSTEMI ( | 8 | (40%) | 7 | (47%) | 12 | (57%) | 0.271 |
| Diabetes ( | 2 | (10%) | 2 | (13%) | 6 | (29%) | 0.119 |
| Hyperlipidemia ( | 12 | (60%) | 8 | (53%) | 12 | (57%) | 0.857 |
| Hypertension ( | 13 | (65%) | 12 | (80%) | 15 | (71%) | 0.623 |
| Smoking ( | 6 | (30%) | 4 | (53%) | 10 | (48%) | 0.156 |
| Former smoker | 6 | (30%) | 7 | (47%) | 2 | (9.5%) | |
| Family history ( | 11 | (55%) | 8 | (53%) | 12 | (57%) | 0.974 |
Concomitant medications.
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| ASA, | 20 (100%) | 15 (100%) | 21 (100%) | 1 |
| ACE-inhibitor, | 14 (70%) | 9 (60%) | 15 (71%) | 0.745 |
| ß-Blocker, | 16 (80%) | 9 (60%) | 19 (90%) | 0.283 |
| AT-1-Antagonist, | 5 (25%) | 6 (40%) | 7 (33%) | 0.130 |
| Ca2+-Antagonist, | 4 (20%) | 4 (27%) | 5 (24%) | 0.063 |
| Renin inhibitor, | 1 (5%) | 1 (7%) | 0 (0%) | 0.151 |
| Statins/ | 16 (80%)/4 (20%) | 14 (93%)/ | 16 (76%)/2 (10%) | 0.294 |
| Diuretics, | 11 (55%) | 7 (47%) | 7 (34%) | 0.185 |
| PPIs, | 10 (50%) | 3 (20%) | 7 (33%) | 0.241 |
| L-Thyroxin, | 2 (10%) | 1 (7%) | 3 (14%) | 0.100 |
Platelet aggregation, aggregation units.
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| 51 | 37–86 | 60 | 37–79 | 61 | 35–66 | |
| 0.902 | |||||||
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| 28 | 19–60 | 15 | 11–21 | 20 | 16–27 | |
| 0.009 | |||||||
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| 7/20 | 35% | 1/20 | 5% | 0/20 | 0% | |
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| 13 | 11–18 | 8 | 3–11 | 11 | 8–13 | |
| 0.006 | |||||||
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| 0/20 | 0% | 0/20 | 0% | 0/20 | 0% | |
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| 25 | 18–34 | 16 | 12–19 | 17 | 13–22 | |
| 0.006 | |||||||
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| 2/20 | 10% | 0/20 | 0% | 0/20 | 0% | |
Non-responders are defined as Multiplate ADP >46 aggregation units.
: P = 0.006 for the comparison prasugrel vs. clopidogrel, P = 0.107 for the comparison prasugrel vs. ticagrelor, P = 0.048 for the comparison clopidogrel vs. ticagrelor;
: P = 0.002 for the comparison prasugrel vs. clopidogrel, P = 0.051 for the comparison prasugrel vs. ticagrelor, P = 0.136 for the comparison clopidogrel vs. ticagrelor;
P = 0.009 for the comparison prasugrel vs. clopidogrel, P = 0.657 for the comparison prasugrel vs. ticagrelor, P = 0.009 for the comparison clopidogrel vs. ticagrelor.
Microvascular function data.
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| 44 | 28–74 | 39 | 27–68 | 61 | 20–135 | |
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| 0.440 | ||||||
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| 119 | 71–173 | 108 | 64–146 | 124 | 84–197 | 0.363 |
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| 156 | 65–229 | 146 | 86–224 | 88 | 40–265 | 0.502 |
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| 45 | 29–83 | 29 | 19–48 | 50 | 19–116 | |
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| 0.158 | ||||||
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| 111 | 75–160 | 112 | 64–148 | 133 | 73–198 | 0.572 |
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| 140 | 70–180 | 216 | 159–457 | 159 | 58–342 | 0.022 |
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| 59 | 40–80 | 31 | 23–52 | 40 | 25–82 | |
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| 0.091 | ||||||
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| 138 | 89–179 | 102 | 66–136 | 92 | 84–172 | 0.437 |
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| 101 | 47–177 | 110 | 82–303 | 139 | 95–264 | 0.287 |
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| 30 | 17–60 | 49 | 20–75 | 33 | 21–75 | |
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| 0.490 | ||||||
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| 94 | 81–135 | 116 | 88–192 | 120 | 67–173 | 0.599 |
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| 193 | 113–327 | 135 | 86–298 | 224 | 90–352 | 0.726 |
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| 49 | 27–81 | 57 | 30–71 | 57 | 26–95 | |
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| 0.609 | ||||||
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| 119 | 96–140 | 119 | 91–130 | 134 | 9–175 | 0.436 |
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| 152 | 46–233 | 106 | 100–184 | 125 | 65–175 | 0.894 |
: P = 0.015 among groups for the change in %PORH between screening and following oral loading (P = 0.007 for the comparison clopidogrel vs. prasugrel; P = 0.329 for the comparison prasugrel vs. ticagrelor and P = 0.042 for the comparison clopidogrel vs. ticagrelor);
: P = 0.003 for the comparison prasugrel vs. clopidogrel, P = 0.117 for the comparison prasugrel vs. ticagrelor, P = 0.415 for the comparison clopidogrel vs. ticagrelor;
= 0.026 for the comparison with immediately after loading.
Microvascular conductance.
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| 0.449 | 0.259–0.819 | 0.360 | 0.272–0.638 | 0.750 | 0.243–1.504 | |
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| 0.262 | ||||||
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| 1.263 | 0.933–1.578 | 1.095 | 0.576–1.627 | 1.373 | 0.856–2.097 | 0.210 |
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| 154.1 | 61.4–241.2 | 138.2 | 72.5–227.2 | 89.0 | 39.7–264.8 | 0.545 |
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| 0.560 | 0.345–0.805 | 0.273 | 0.190–0.478 | 0.578 | 0.239–1.233 | |
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| 0.05 | ||||||
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| 1.263 | 0.933–1.578 | 1.095 | 0.576–1.627 | 1.373 | 0.856–2.097 | 0.446 |
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| 140.3 | 73.8–178.4 | 209.9 | 153.7–473.9 | 158.7 | 57.9–342.0 | 0.022 |
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| 0.616 | 0.454–0.960 | 0.275 | 0.245–0.592 | 0.418 | 0.305–0.820 | |
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| 1.261 | 0.993–1.855 | 1.061 | 0.626–1.261 | 1.088 | 0.835–1.727 | 0.200 |
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| 97.9 | 43.4–167.2 | 107.5 | 79.4–297.3 | 138.9 | 95.2–264.9 | 0.186 |
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| 0.338 | 0.190–0.623 | 0.590 | 0.354–0.763 | 0.416 | 0.230–0.786 | |
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| 0.438 | ||||||
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| 1.023 | 0.750–1.670 | 1.152 | 1.020–2.255 | 1.362 | 0.882–1.979 | 0.458 |
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| 225.0 | 107.4–338.9 | 134.7 | 94.1–255.5 | 220.7 | 78.6–328.6 | 0.725 |
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| 0.493 | 0.291–0.988 | 0.530 | 0.279–0.668 | 0.633 | 0.306–0.974 | |
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| 0.545 | ||||||
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| 1.307 | 0.969–1.601 | 1.250 | 0.956–1.336 | 1.290 | 0.990–1.838 | 0.320 |
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| 148.3 | 45.0–215.5 | 106.5 | 97.8–211.5 | 124.9 | 64.6–175.3 | 0.865 |
P = 0.011 for the post-hoc comparison with clopidogrel, P = 0.122 for the comparison with ticagrelor. P = 0.224 for the comparison ticagrelor and clopidogrel.
P = 0.020 and
= 0.5 for the comparison with immediately after loading.
Figure 2The impact of the three study medications on microvascular function. PORH (post-occlusion reactive hyperemia) was improved acutely after loading by prasugrel, however this effect was lost after percutaneous intervention.
Figure 3Correlation between platelet activity and PORH.