title: Prediction of length of stay following elective percutaneous coronary intervention.
abstract: There have been published risk stratification approaches to predict complications following percutaneous coronary interventions (PCI). However, a formal assessment of such approaches with respect to predicting length of stay (LOS) is lacking. Therefore, we sought to assess the performance of, an easy-to-use, tree-structured prognostic classification model in predicting LOS among patients with elective PCI. The study is based on the New York State PCI database. The model was developed on data for 1999-2000, consisting of 67,766 procedures. Validation was carried out, with respect to LOS, using data for 2001-2002, consisting of 79,545 procedures. The risk groups identified by the model exhibited a strong progressively increasing relative risk pattern of longer LOS. The predicted average LOS ranged from 3 to 9 days. The performance of this model was comparable to other published risk scores. In conclusion, the tree-structured prognostic classification is a model which can be easily applied to aid practitioners early on in their decision process regarding the need for extra resources required for the management of more complicated patients following PCI, or to justify to payors the extra costs required for the management of patients who have required extended observation and care after PCI.
authors.affiliation: Division of Biostatistics, Department of Epidemiology and Population Health, Albert Einstein College of Medicine, 1300 Morris Park, Mazer 220, Bronx, New York, NY 10461, USA.
authors.forename: Abdissa
authors.initials: A
authors.lastname: Negassa
authors.forename: E Scott
authors.initials: ES
authors.lastname: Monrad
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