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Prediction of Length of Stay Following Elective Percutaneous Coronary Intervention

机译:择期经皮冠状动脉介入治疗后的住院时间预测

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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.
机译:已经发表了风险分层方法来预测经皮冠状动脉介入治疗(PCI)后的并发症。但是,目前尚缺乏对此类方法进行预测住院时间(LOS)的正式评估。因此,我们试图评估一种易于使用的树状结构预后分类模型在预测选择性PCI患者中的LOS方面的性能。该研究基于纽约州PCI数据库。该模型是根据1999-2000年的数据开发的,包括67,766个程序。关于LOS的验证是使用2001-2002年数据进行的,包括79,545个程序。通过模型确定的风险组表现出较长的LOS的相对风险模式呈强而逐步增加的趋势。预计的平均LOS为3到9天。该模型的性能可与其他已发布的风险评分相媲美。总之,树状结构的预后分类是一个模型,可以很容易地用于在决策过程中尽早地帮助从业者,以解决在PCI后管理更复杂患者所需的额外资源的需求,或为付款人证明额外的合理性PCI后需要长期观察和护理的患者管理所需的费用。

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