Academic Journal
Machine-learning-based prediction of fractional flow reserve after percutaneous coronary intervention.
| العنوان: | Machine-learning-based prediction of fractional flow reserve after percutaneous coronary intervention. |
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| المؤلفون: | Hamaya, R., Goto, S., Hwang, D., Zhang, J., Yang, S., Lee, J.M., Hoshino, M., Nam, C.W., Shin, E.S., Doh, J.H., Chen, S.L., Toth, G.G., Piroth, Z., Hakeem, A., Uretsky, B.F., Hokama, Y., Tanaka, N., Lim, H.S., Ito, T., Matsuo, A., Azzalini, L., Leesar, M.A., Collet, C., Koo, B.K., De Bruyne, B., Kakuta, T. |
| المصدر: | Atherosclerosis, vol. 383, pp. 117310 |
| سنة النشر: | 2023 |
| المجموعة: | Université de Lausanne (UNIL): Serval - Serveur académique lausannois |
| مصطلحات موضوعية: | Humans, Coronary Artery Disease/diagnosis, Coronary Artery Disease/therapy, Fractional Flow Reserve, Myocardial, Treatment Outcome, Percutaneous Coronary Intervention, Coronary Angiography, Predictive Value of Tests, Machine-learning |
| الوصف: | Post-percutaneous coronary intervention (PCI) fractional flow reserve (FFR) reflects residual atherosclerotic burden and is associated with future events. How much post-PCI FFR can be predicted based on baseline basic information and the clinical relevance have not been investigated. We compiled a multicenter registry of patients undergoing pre- and post-PCI FFR. Machine-learning (ML) algorithms were designed to predict post-PCI FFR levels from baseline demographics, quantitative coronary angiography, and pre-PCI FFR. FFR deviation was defined as actual minus ML-predicted post-PCI FFR levels, and its association with incident target vessel failure (TVF) was evaluated. Median (IQR) pre- and post-PCI FFR values were 0.71 (0.61, 0.77) and 0.88 (0.84, 0.93), respectively. The Spearman correlation coefficient of the actual and predicted post-PCI FFR was 0.54 (95% CI: 0.52, 0.57). FFR deviation was non-linearly associated with incident TVF (HR [95% CI] with Q3 as reference: 1.65 [1.14, 2.39] in Q1, 1.42 [0.98, 2.08] in Q2, 0.81 [0.53, 1.26] in Q4, and 1.04 [0.69, 1.56] in Q5). A model with polynomial function of continuous FFR deviation indicated increasing TVF risk for FFR deviation ≤0 but plateau risk with FFR deviation >0. An ML-based algorithm using baseline data moderately predicted post-PCI FFR. The deviation of post-PCI FFR from the predicted value was associated with higher vessel-oriented event. |
| نوع الوثيقة: | article in journal/newspaper |
| اللغة: | English |
| Relation: | info:eu-repo/semantics/altIdentifier/pmid/37797507; info:eu-repo/semantics/altIdentifier/eissn/1879-1484; https://serval.unil.ch/notice/serval:BIB_D5749FCE06CA |
| DOI: | 10.1016/j.atherosclerosis.2023.117310 |
| الاتاحة: | https://serval.unil.ch/notice/serval:BIB_D5749FCE06CA https://doi.org/10.1016/j.atherosclerosis.2023.117310 |
| رقم الانضمام: | edsbas.BCEF18D1 |
| قاعدة البيانات: | BASE |
| DOI: | 10.1016/j.atherosclerosis.2023.117310 |
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