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Curso de Atualização em Medicina Cardiovascular 2019
Reunião Anual Conjunta dos Grupos de Estudo de Cirurgia Cardíaca, Doenças Valvulares e Ecocardiografia da SPC
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Acute coronary syndromes in the young: Using machine-learning and artificial intelligence to ban bare metal stents
Session:
CO9 - Doença Coronária
Speaker:
João André Ferreira
Congress:
CPC 2019
Topic:
E. Coronary Artery Disease, Acute Coronary Syndromes, Acute Cardiac Care
Theme:
13. Acute Coronary Syndromes
Subtheme:
13.4 Acute Coronary Syndromes – Treatment
Session Type:
Comunicações Orais
FP Number:
---
Authors:
João André Ferreira; James Milner; José Almeida; Sofia S. Martinho; Sílvia Monteiro; Pedro Monteiro; He M; C. Simpson; Zaslavskiy M.; Balazard F; L. Li; A. Rousset; S. Schopf; D. Dellamonica; Lino Gonçalves
Abstract
<p><u>Background:</u> Acute coronary syndromes (ACS) remain an important cause of morbidity and mortality in all age groups. However, less is known about the impact of ACS in younger patients. New risk prediction tools are important to better identify and risk stratify high risk patients within this important ACS subpopulation.</p> <p><u>Aim:</u> The aim of this study was to identify the best predictors of a new ACS, in a single-center database of ACS, resorting to machine learning and artificial intelligence, and to compare the relevance of the type of stent used (bare metal stent – BMS – versus drug eluting stent – DES) for risk discrimination in a general ACS population versus a subpopulation of young (<50 years) patients.</p> <p><u>Methods:</u> In a single center, 5977 patients admitted due to ACS between 2004 and 2017 and alive at discharge were studied. In the subpopulation of younger patients (n=660), each covariate present in the database was analyzed separately with a Cox proportional hazard model with three terms – subpopulation belonging indicator, covariate, interaction term. The p-value of the interaction term was used to rank variables. The more significant the interaction term, the stronger the change in relationship between patients in the subpopulation and the risk of a new ACS, compared to the one in the general population.</p> <p><u>Results:</u> During long term follow-up, 13% of patients (n=771) experienced a second event. Kaplan-Meier curve represents how ACS free-survival depends on the type of stent and group of interest. The solid lines represent Kaplan-Meier curves for younger patients, and the dotted lines in the general population. Pink or grey colour of the curves represent the stratification level of the covariate.</p> <p><u>Conclusions:</u> In our model, the type of stent was found to be a better discriminator of risk of further ACS in younger patients than in the general ACS population. Strikingly, younger patients treated with bare-metal stents had a higher rate of readmission for ACS. This finding reinforces the importance of systematically using DES in young ACS patients, making sure that they are closely followed and submitted to optimal risk factor management, in order to improve their post-ACS prognosis.</p>
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