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DOI: 10.1160/TH16-10-0785
Platelet turnover predicts outcome after coronary intervention
Publication History
Received:
18 October 2016
Accepted after major revision:
25 January 2017
Publication Date:
28 November 2017 (online)
![](https://www.thieme-connect.de/media/10.1055-s-00035024/201705/lookinside/thumbnails/10-1160-th16-10-0785-1.jpg)
Summary
Elevated platelet turnover contributes to high platelet reactivity. High platelet reactivity after percutaneous coronary intervention (PCI) is associated with major adverse cardiovascular events (MACE). The purpose of this study was to determine the prognostic value of platelet turnover and function with regard to MACE after PCI with stent implantation. In this prospective observational study, 486 consecutive patients after PCI on aspirin and clopidogrel were included to determine platelet turnover (mean platelet volume (MPV), reticulated platelet fraction (RPF)) and platelet function (multiple electrode aggregometry (MEA), vasodilator-stimulated phosphoprotein-phosphorylation (VASP-P) assay). At six-months follow-up, MACE occurred in 10.7 % of patients. RPF (odds ratio [OR]=1.173 (95% confidence interval [CI 95 %] 1.040–1.324), p=0.009) and MPV (OR=1.459 (CI 95 % 1.059–2.008), p=0.021) were univariable predictors of MACE, whereas VASP-P (OR=1.016 (CI 95 % 1.000–1.032), p=0.052) and MEA (OR=0.999 (CI 95 % 0.980–1.017), p=0.895) failed to predict MACE. RPF remained the only platelet variable independently associated with MACE. The best model to predict MACE included: troponin I (OR=1.007 (CI 95 % 1.002–1.012), p=0.009), RPF (OR=1.136 (CI 95 % 1.001–1.288), p=0.048), CRP (OR=1.008 (CI 95 % 1.001–1.014), p=0.023) and history of myocardial infarction (OR=2.039 (CI 95 % 1.093–3.806), p=0.025). RPF (OR=1.211 (CI 95 % 1.042–1.406), p=0.012) was also independently associated with in-hospital bleedings. In conclusion, RPF as index of platelet turnover is an independent predictor of MACE and bleeding events in PCI patients on dual antiplatelet therapy. Since RPF can reliably be quantified along with routine haemograms, RPF might easily be applied in the setting of cardiovascular risk prediction.
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