Prediction of persistence of combined evidence-based cardiovascular medications in patients with acute coronary syndrome after hospital discharge using neural networks.

Valérie Bourdès (1) , Jean Ferrières (2, 3) , Jacques Amar (4) , Elisabeth Amelineau (5) , Stéphane Bonnevay (6) , Maryse Berlion (7) , Nicolas Danchin (8)

1 THEMIS-ICTA Group
2 LEASP - Epidémiologie et analyses en santé publique : risques, maladies chroniques et handicaps
3 Service Cardiologie [CHU Toulouse]
4 HTA et thérapeutique - Service d'hypertension artérielle et thérapeutique [CHU Toulouse]
5 Britol-Myers Squibb
6 ERIC - Equipe de Recherche en Ingénierie des Connaissances
7 ICTA - Institute of Animal Science and Technology
8 Service de Cardiologie [CHU Rouen]

In the PREVENIR-5 study, artificial neural networks (NN) were applied to a large sample of patients with recent first acute coronary syndrome (ACS) to identify determinants of persistence of evidence-based cardiovascular medications (EBCM: antithrombotic + beta-blocker + statin + angiotensin converting enzyme inhibitor-ACEI and/or angiotensin-II receptor blocker-ARB). From October 2006 to April 2007, 1,811 general practitioners recruited 4,850 patients with a mean time of ACS occurrence of 24 months. Patient profile for EBCM persistence was determined using automatic rule generation from NN. The prediction accuracy of NN was compared with that of logistic regression (LR) using Area Under Receiver-Operating Characteristics-AUROC. At hospital discharge, EBCM was prescribed to 2,132 patients (44%). EBCM persistence rate, 24 months after ACS, was 86.7%. EBCM persistence profile combined overweight, hypercholesterolemia, no coronary artery bypass grafting and low educational level (Positive Predictive Value = 0.958). AUROC curves showed better predictive accuracy for NN compared to LR models.

Mots clés: artificial neural networks; Acute coronary syndrome; evidence-based medical therapy; long-term persistence; artificial neural networks.

Domaines: Imagerie médicale; Cardiologie et système cardiovasculaire

Valérie Bourdès, Jean Ferrières, Jacques Amar, Elisabeth Amelineau, Stéphane Bonnevay, et al.. Prediction of persistence of combined evidence-based cardiovascular medications in patients with acute coronary syndrome after hospital discharge using neural networks.. Medical and Biological Engineering and Computing, 2011, 49 (8), pp.947-55. ⟨10.1007/s11517-011-0785-4⟩. ⟨hal-00624080⟩