Classification and Regression Trees on Aggregate Data Modeling : An Application in Acute Myocardial Infarction
Joint Authors
Quantin, Catherine
Zeller, M.
Le Teuff, G.
Cottin, Y.
Billard, L.
Afonso, F.
Andreu, N.
Diday, E.
Battaglia, G.
Touati, M.
Seck, D.
Source
Journal of Probability and Statistics
Issue
Vol. 2011, Issue 2011 (31 Dec. 2011), pp.1-19, 19 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2011-09-05
Country of Publication
Egypt
No. of Pages
19
Main Subjects
Abstract EN
Cardiologists are interested in determining whether the type of hospital pathway followed by a patient is predictive of survival.
The study objective was to determine whether accounting for hospital pathways in the selection of prognostic factors of one-year survival after acute myocardial infarction (AMI) provided a more informative analysis than that obtained by the use of a standard regression tree analysis (CART method).
Information on AMI was collected for 1095 hospitalized patients over an 18-month period.
The construction of pathways followed by patients produced symbolic-valued observations requiring a symbolic regression tree analysis.
This analysis was compared with the standard CART analysis using patients as statistical units described by standard data selected TIMI score as the primary predictor variable.
For the 1011 (84, resp.) patients with a lower (higher) TIMI score, the pathway variable did not appear as a diagnostic variable until the third (second) stage of the tree construction.
For an ecological analysis, again TIMI score was the first predictor variable.
However, in a symbolic regression tree analysis using hospital pathways as statistical units, the type of pathway followed was the key predictor variable, showing in particular that pathways involving early admission to cardiology units produced high one-year survival rates.
American Psychological Association (APA)
Quantin, Catherine& Billard, L.& Touati, M.& Andreu, N.& Cottin, Y.& Zeller, M.…[et al.]. 2011. Classification and Regression Trees on Aggregate Data Modeling : An Application in Acute Myocardial Infarction. Journal of Probability and Statistics،Vol. 2011, no. 2011, pp.1-19.
https://search.emarefa.net/detail/BIM-478475
Modern Language Association (MLA)
Quantin, Catherine…[et al.]. Classification and Regression Trees on Aggregate Data Modeling : An Application in Acute Myocardial Infarction. Journal of Probability and Statistics No. 2011 (2011), pp.1-19.
https://search.emarefa.net/detail/BIM-478475
American Medical Association (AMA)
Quantin, Catherine& Billard, L.& Touati, M.& Andreu, N.& Cottin, Y.& Zeller, M.…[et al.]. Classification and Regression Trees on Aggregate Data Modeling : An Application in Acute Myocardial Infarction. Journal of Probability and Statistics. 2011. Vol. 2011, no. 2011, pp.1-19.
https://search.emarefa.net/detail/BIM-478475
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-478475