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  1. Comparison of analytic models for estimating the effect of clinical factors on the cost of coronary artery bypass graft surgery.

    Article - En anglais

    The cost of treating disease depends on patient characteristics, but standard tools for analyzing the clinical predictors of cost have deficiencies.

    To explore whether survival analysis techniques might overcome some of these deficiencies in the analysis of cost data, we compared ordinary least square (OLS) linear regression (with and without transformation of the data) and binary logistic regression with two survival models: the Cox proportional hazards model and a parametric model assuming a Weibull distribution.

    Each model was applied to data from 155 patients undergoing coronary artery bypass grafting.

    We examined the effects of age, sex, ejection fraction, unstable angina, and number of diseased vessels on univariable and multivariable predictions of costs.

    Mots-clés Pascal : Dérivation, Aortocoronaire, Analyse coût, Chirurgie, Traitement, Appareil circulatoire pathologie, Homme, Modèle statistique, Méthodologie, Etude comparative, Economie santé, Méthode statistique

    Mots-clés Pascal anglais : Bypass, Aortocoronary, Cost analysis, Surgery, Treatment, Cardiovascular disease, Human, Statistical model, Methodology, Comparative study, Health economy, Statistical method

    Logo du centre Notice produite par :
    Inist-CNRS - Institut de l'Information Scientifique et Technique

    Cote : 93-0343014

    Code Inist : 002B25E. Création : 199406.