American heart journal · 2001
Predictors of length of stay after coronary stenting.
СтатьяНазвание и аннотация: Перевод пока не подготовлен
Обработка статьи · этапы, ошибки и управление
Загрузка состояния…
Ошибки и ограничения
История · было → стало
Состояние обновляется каждые 5 секунд, пока блок открыт. Процент показывается только там, где известен объём работы. Пауза останавливает продолжение этапа; текущий запрос к источнику может завершиться.
Aronow H D, Peyser P A, Eagle K A, Bates E R, Werns S W, Russman P L, Crum M A, Harris K, Moscucci M
Аннотация
BACKGROUND: Postprocedure length of stay (LOS) remains an important determinant of medical costs after coronary stenting. Variables that predict LOS in this setting have not been well characterized.
METHODS: We evaluated 359 consecutive patients who underwent coronary stenting with antiplatelet therapy. Sequential multiple linear regression (MLR) models were constructed with use of 4 types of variables to predict log-transformed LOS: preprocedure, intraprocedure, and postprocedure factors and adverse outcomes.
RESULTS: Preprocedure factors alone explained more than one third of the variability in postprocedure LOS (adjusted R(2) = 0.37). The addition of procedural variables added little to the model (adjusted R(2) = 0.39). Entering nonoutcome postprocedure variables significantly enhanced the predictive capacity of the model, explaining more than half the variability in postprocedure LOS (adjusted R(2) = 0.54). In the final model, addition of outcome variables increased its predictive capacity only slightly (adjusted R(2) = 0.61). In this model, significant preprocedure factors included: myocardial infarction (MI) within 24 hours, MI within 1 to 30 days, women with peripheral vascular disease, intravenous heparin, and chronic atrial fibrillation. High-risk intervention was the only significant intraprocedure variable. Significant postprocedure factors included periprocedure ischemia; cerebrovascular accident or transient ischemic attack; treatment with intravenous heparin or nitroglycerin or intra-aortic balloon pump; and need for blood transfusion. Significant adverse outcomes included contrast nephropathy, gastrointestinal bleeding, arrhythmia, vascular complication, and repeat angiography.
CONCLUSION: This prediction model identifies a number of potentially reversible factors responsible for prolonging LOS and may enable the development of more accurate risk-adjusted methods with which to improve or compare care.
METHODS: We evaluated 359 consecutive patients who underwent coronary stenting with antiplatelet therapy. Sequential multiple linear regression (MLR) models were constructed with use of 4 types of variables to predict log-transformed LOS: preprocedure, intraprocedure, and postprocedure factors and adverse outcomes.
RESULTS: Preprocedure factors alone explained more than one third of the variability in postprocedure LOS (adjusted R(2) = 0.37). The addition of procedural variables added little to the model (adjusted R(2) = 0.39). Entering nonoutcome postprocedure variables significantly enhanced the predictive capacity of the model, explaining more than half the variability in postprocedure LOS (adjusted R(2) = 0.54). In the final model, addition of outcome variables increased its predictive capacity only slightly (adjusted R(2) = 0.61). In this model, significant preprocedure factors included: myocardial infarction (MI) within 24 hours, MI within 1 to 30 days, women with peripheral vascular disease, intravenous heparin, and chronic atrial fibrillation. High-risk intervention was the only significant intraprocedure variable. Significant postprocedure factors included periprocedure ischemia; cerebrovascular accident or transient ischemic attack; treatment with intravenous heparin or nitroglycerin or intra-aortic balloon pump; and need for blood transfusion. Significant adverse outcomes included contrast nephropathy, gastrointestinal bleeding, arrhythmia, vascular complication, and repeat angiography.
CONCLUSION: This prediction model identifies a number of potentially reversible factors responsible for prolonging LOS and may enable the development of more accurate risk-adjusted methods with which to improve or compare care.