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Predicting mortality, thrombus recurrence and persistence in patients with post-acute myocardial infarction left ventricular thrombus

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Abstract

Left ventricular thrombus (LVT) is a common complication of acute myocardial infarction and is associated with morbidity from embolic complications. Predicting which patients will develop death or persistent LVT despite anticoagulation may help clinicians identify high-risk patients. We developed a random forest (RF) model that predicts death or persistent LVT and evaluated its performance. This was a single-center retrospective cohort study in an academic tertiary center. We included 244 patients with LVT in our study. Patients who did not receive anticoagulation (n = 8) or had unknown (n = 31) outcomes were excluded. The primary outcome was a composite outcome of death, recurrent LVT and persistent LVT. We selected a total of 31 predictors collected at the point of LVT diagnosis based on clinical relevance. We compared conventional regularized logistic regression with the RF algorithm. There were 156 patients who had resolution of LVT and 88 patients who experienced the composite outcome. The RF model achieved better performance and had an AUROC of 0.700 (95% CI 0.553–0.863) on a validation dataset. The most important predictors for the composite outcome were receiving a revascularization procedure, lower visual ejection fraction (EF), higher creatinine, global wall motion abnormality, higher prothrombin time, higher body mass index, higher activated partial thromboplastin time, older age, lower lymphocyte count and higher neutrophil count. The RF model accurately identified patients with post-AMI LVT who developed the composite outcome. Further studies are needed to validate its use in clinical practice.

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Funding

CHS was supported by the Singapore Population Health Improvement Centre (SPHERiC) Fellowship. This research is supported by the Singapore Ministry of Health’s National Medical Research Council under the Fellowship Programme by Singapore Population Health Improvement Centre (NMRC/CG/C026/2017_NUHS). CHS was also supported by the National University of Singapore Yong Loo Lin School of Medicine’s Junior Academic Faculty Scheme.

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Author notes

  1. Wesley Yeung and Ching-Hui Sia have contributed equally.

Authors and Affiliations

  1. University Medicine Cluster, National University Hospital, 5 Lower Kent Ridge Road, Singapore, 119074, Singapore

    Wesley Yeung & Aloysius Sheng-Ting Leow

  2. Department of Cardiology, National University Heart Centre Singapore, Singapore, Singapore

    Ching-Hui Sia, Rajinderdeep Kaur, Tiong-Cheng Yeo, Edgar Lik-Wui Tay, Mark Yan-Yee Chan & Joshua Ping-Yun Loh

  3. Department of Medicine, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore

    Ching-Hui Sia, Tiong-Cheng Yeo, Edgar Lik-Wui Tay, Mark Yan-Yee Chan & Joshua Ping-Yun Loh

  4. Laboratory for Computational Physiology, Harvard-MIT Health Sciences & Technology, Massachusetts Institute of Technology, Cambridge, MA, USA

    Wesley Yeung & Tom Pollard

  5. Yong Loo Lin School of Medicine, National University Singapore, Singapore, Singapore

    Benjamin Yong-Qiang Tan & Leonard Leong-Litt Yeo

  6. Division of Neurology, Department of Medicine, National University Health System, Singapore, Singapore

    Benjamin Yong-Qiang Tan & Leonard Leong-Litt Yeo

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  1. Wesley Yeung
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Contributions

WY and CHS conceived of the presented idea. WY developed the theory and performed the computations. TP provided technical assistance during the analysis. MC, JL, BT and LY supervised the findings of this work. All authors discussed the results and contributed to the final manuscript.

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Correspondence to Wesley Yeung.

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Yeung, W., Sia, CH., Pollard, T. et al. Predicting mortality, thrombus recurrence and persistence in patients with post-acute myocardial infarction left ventricular thrombus. J Thromb Thrombolysis 52, 654–661 (2021). https://doi.org/10.1007/s11239-020-02368-1

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