Sequential Pattern Mining of Longitudinal Adverse Events After Left Ventricular Assist Device Implant.

Pubmed ID: 31831453

Pubmed Central ID: PMC8462525

Journal: IEEE journal of biomedical and health informatics

Publication Date: Aug. 1, 2020

Link: https://ieeexplore.ieee.org/ielx7/6221020/6363502/08930032.pdf?tp=&arnumber=8930032&isnumber=6363502&ref=&link_time=2024-04-26_16:33:34.666082

MeSH Terms: Humans, Male, Female, Cardiovascular Diseases, Medical Informatics, Pattern Recognition, Automated, Middle Aged, Models, Statistical, Cluster Analysis, Markov Chains, Respiratory Insufficiency, Hemorrhage, Data Mining, Heart-Assist Devices, Equipment Failure

Grants: R01 HL122639

Authors: Zhang Y, Movahedi F, Kormos RL, Lohmueller L, Seese L, Kanwar M, Murali S, Padman R, Antaki JF

Cite As: Movahedi F, Kormos RL, Lohmueller L, Seese L, Kanwar M, Murali S, Zhang Y, Padman R, Antaki JF. Sequential Pattern Mining of Longitudinal Adverse Events After Left Ventricular Assist Device Implant. IEEE J Biomed Health Inform 2020 Aug;24(8):2347-2358. Epub 2019 Dec 9.

Studies:

Abstract

Left ventricular assist devices (LVADs) are an increasingly common therapy for patients with advanced heart failure. However, implantation of the LVAD increases the risk of stroke, infection, bleeding, and other serious adverse events (AEs). Most post-LVAD AEs studies have focused on individual AEs in isolation, neglecting the possible interrelation, or causality between AEs. This study is the first to conduct an exploratory analysis to discover common sequential chains of AEs following LVAD implantation that are correlated with important clinical outcomes. This analysis was derived from 58,575 recorded AEs for 13,192 patients in International Registry for Mechanical Circulatory Support (INTERMACS) who received a continuous-flow LVAD between 2006 and 2015. The pattern mining procedure involved three main steps: (1) creating a bank of AE sequences by converting the AEs for each patient into a single, chronologically sequenced record, (2) grouping patients with similar AE sequences using hierarchical clustering, and (3) extracting temporal chains of AEs for each group of patients using Markov modeling. The mined results indicate the existence of seven groups of sequential chains of AEs, characterized by common types of AEs that occurred in a unique order. The groups were identified as: GRP1: Recurrent bleeding, GRP2: Trajectory of device malfunction & explant, GRP3: Infection, GRP4: Trajectories to transplant, GRP5: Cardiac arrhythmia, GRP6: Trajectory of neurological dysfunction & death, and GRP7: Trajectory of respiratory failure, renal dysfunction & death. These patterns of sequential post-LVAD AEs disclose potential interdependence between AEs and may aid prediction, and prevention, of subsequent AEs in future studies.