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

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Abstract

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.

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Acknowledgments

This study was financially supported by Bristol Myers Squibb, France. The authors thank Prof. Paulo Lisboa and his team (Liverpool John Moore University, United Kingdom) for the rule extraction methodology and the data management and statistics department of ICTA-PM (Dijon, France).

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Authors and Affiliations

  1. THEMIS-ICTA Group, Bioparc-60 Avenue Rockefeller, Lyon, 69008, France

    Valérie Bourdès & Maryse Berlion

  2. Inserm U558, University Hospital, Toulouse, France

    Jean Ferrières

  3. Rangueil Hospital, Toulouse, France

    Jean Ferrières & Jacques Amar

  4. Bristol-Myers Squibb, Rueil Malmaison, France

    Elisabeth Amelineau

  5. Laboratoire ERIC, Ecole Polytechnique Universitaire, Villeurbanne, France

    Stéphane Bonnevay

  6. Georges Pompidou European Hospital, Paris, France

    Nicolas Danchin

Authors
  1. Valérie Bourdès
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  2. Jean Ferrières
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  3. Jacques Amar
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  4. Elisabeth Amelineau
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  5. Stéphane Bonnevay
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  6. Maryse Berlion
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  7. Nicolas Danchin
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Correspondence to Valérie Bourdès.

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Bourdès, V., Ferrières, J., Amar, J. et al. Prediction of persistence of combined evidence-based cardiovascular medications in patients with acute coronary syndrome after hospital discharge using neural networks. Med Biol Eng Comput 49, 947–955 (2011). https://doi.org/10.1007/s11517-011-0785-4

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  • DOI: https://doi.org/10.1007/s11517-011-0785-4

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