| Titre : | A logistic regression model when some events precede treatment : The effect of thrombolytic therapy for acute myocardial infarction on the risk of cardiac arrest. (1997) |
| Auteurs : | C.H. SCHMID ; J.R. BESHANSKY ; R.B. D'AGOSTINO ; J.L. GRIFFITH ; H.P. SELKER ; Division of Clinical Care Research. Department of Medicine. New England Medical Center. And Tufts University School of Medicine. Boston Massachusetts. USA |
| Type de document : | Article |
| Dans : | Journal of clinical epidemiology (vol. 50, n° 11, 1997) |
| Pagination : | 1219-1229 |
| Langues: | Anglais |
| Mots-clés : | Infarctus ; Myocarde ; Thérapeutique médicamenteuse ; Thérapeutique ; Modèle ; Homme ; Appareil circulatoire [pathologie] ; Cardiopathie coronaire ; Myocarde [pathologie] |
| Résumé : | [BDSP. Notice produite par INIST LcVR0xEZ. Diffusion soumise à autorisation]. When outcomes occur in clinical trials before treatment can be given, neither intent-to-treat nor according-to-protocol analyses give optimal estimates of the treatment effect. A better approach employs a time-dependent variable for treatment. Intent-to-treat analyses are conservative, biasing against treatment ; according-to-protocol analyses bias in favor of treatment. We show how to measure the effect of a time-dependent variable in a logistic regression using person-time intervals as units of measurement and describe appropriate methods for reporting model performance. The method is applied to develop a model to predict the probability that a patient with a myocardial infarction will have a sudden cardiac arrest within 48 hours of presentation to emergency medical services both when treated with thrombolysis and when not treated. We use a time-dependent treatment variable because many patients went into cardiac arrest while awaiting treatment. This technique has been programmed into an electricardiograph for real-time use in an emergency department. |
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