A clinical risk score to identify patients at high risk of very late stent thrombosis. (22nd February 2018)

• Record Type: Journal Article
• Authors: Godschalk, Thea C.; Gimbel, Marieke E.; Nolet, Wouter W.; van Kessel, Dionne J.; Amoroso, Giovanni; Dewilde, Willem J.; Wykrzykowska, Joanna J.; Janssen, Paul W.; Bergmeijer, Thomas O.; Kelder, Johannes C.; Heestermans, Ton; ten Berg, Jurriën M.
• Is Part Of: Journal of interventional cardiology. Volume 31:Number 2(2018:Apr.)
• Page Start: 159
• Page End: 169
• Publication Date: 2018-02-22
• Subjects: dual antiplatelet therapy -- prediction model -- very late stent thrombosis; Cardiology -- Periodicals; Heart -- Diseases -- Periodicals; 616.1206
• DOI: 10.1111/joic.12494
• Languages: English
• ISSNs: 0896-4327

Abstract

Abstract : Objectives: The aim of this study was to determine predictors of very late stent thrombosis (VLST; >1 year after stenting), and to evaluate whether addition of these predictors to the dual antiplatelet therapy (DAPT) score would improve the ability to identify patients at high risk of VLST who might benefit from DAPT. Background: VLST is a severe complication of percutaneous coronary intervention (PCI). Extended knowledge about the predictors of VLST is needed to prevent this life‐threatening complication. Recent data showed a reduction in VLST after treatment with prolonged DAPT. The DAPT study developed a prediction score to identify patients after PCI who might benefit from prolonged DAPT duration. Methods: The Dutch stent thrombosis study is a multi‐center case‐control study. Consecutive patients with definite VLST were included between 2007 and 2014. Baseline characteristics from the index PCI were collected. Independent predictors of VLST were identified and added to the DAPT score to develop the VLST score. Results: In total, 155 VLST cases and 155 matched controls were included. Suboptimal result of stenting, right coronary artery as target vessel, and diffuse coronary artery ectasia were independent predictors of VLST, and added to the DAPT score. The power of the VLST score to identify patients who experienced VLST was increased (AUC, 95%CI; DAPT score: 0.64, 0.57‐0.70; VLST score: 0.70, 0.63‐0.76, P = 0.010). Conclusions: Addition of newly identified independent predictors of VLST resulted in a prediction model with a higher ability to identify patients at high risk of VLST who might benefit from prolonged DAPT.