Cipriano L E, Steinberg M L, Gazelle G S, González R G
Institute for Technology Assessment, Massachusetts General Hospital, Boston, Mass. 02114, USA.
AJNR Am J Neuroradiol. 2009 Apr;30(4):703-9. doi: 10.3174/ajnr.A1441. Epub 2009 Jan 22.
A neuroimaging-based ischemic stroke classification system that predicts costs and outcomes would be useful for clinical prognostication and hospital resource planning. The Boston Acute Stroke Imaging Scale (BASIS), a neuroimaging-based ischemic stroke classification system, was tested to determine whether it was able to predict the costs and clinical outcomes of patients with stroke at an urban academic medical center.
Patients with ischemic stroke who presented in the emergency department in 2000 (230 patients) and 2005 (250 patients) were classified by using BASIS as having either a major or minor stroke. Compared outcomes included death, length of hospitalization, discharge disposition, use of imaging and intensive care unit (ICU) resources, and total in-hospital cost. Continuous variables were compared by univariate analysis by using the Student t test or the Satterthwaite test adjusted for unequal variances. Categoric variables were tested with the chi(2) test. Multiple regression analyses related total hospital cost (dependent variable) to stroke severity (major versus minor), sex, age, presence of comorbidities, and death during hospitalization. Logistic regression analysis was applied to identify the significant predictive variables indicating a greater likelihood of discharge home.
In both years, individuals with strokes classified as major had a significantly longer length of stay, spent more days in the ICU, and had a higher cost of hospitalization than patients with minor strokes (all outcomes, P < .0001). All deaths (8 in 2000, 26 in 2005) occurred in patients with major stroke. Whereas 73% of patients with minor stroke were discharged home, only 12.2% of patients with major stroke were discharged home (P < .0001); 61% of patients with major stroke were discharged to a rehabilitation or skilled nursing facility. Patients with major stroke cost 4.4 times and 3.0 times that of patients with minor stroke in 2000 and 2005, respectively. Making up less than one third of all patients, patients with major stroke accounted for 60% of the total in-hospital cost of acute stroke care.
BASIS, a neuroimaging-based stroke classification system, is highly effective at predicting in-hospital resource use, acute-hospitalization cost, and outcome. Predictive ability was maintained across the years studied.
一种基于神经影像学的缺血性卒中分类系统,若能预测成本和预后,将有助于临床预后评估和医院资源规划。对基于神经影像学的缺血性卒中分类系统——波士顿急性卒中影像量表(BASIS)进行了测试,以确定其能否预测一家城市学术医疗中心卒中患者的成本和临床预后。
将2000年(230例患者)和2005年(250例患者)在急诊科就诊的缺血性卒中患者,使用BASIS分类为重度或轻度卒中。比较的预后指标包括死亡、住院时间、出院去向、影像学检查和重症监护病房(ICU)资源的使用情况以及住院总费用。连续变量采用单因素分析,使用Student t检验或针对不等方差调整后的Satterthwaite检验进行比较。分类变量采用卡方检验。多元回归分析将住院总费用(因变量)与卒中严重程度(重度与轻度)、性别、年龄、合并症的存在情况以及住院期间的死亡情况相关联。应用逻辑回归分析确定表明出院回家可能性更大的显著预测变量。
在这两年中,被分类为重度卒中的患者住院时间显著更长,在ICU的天数更多,住院费用也高于轻度卒中患者(所有预后指标,P <.0001)。所有死亡患者(2000年8例,2005年26例)均为重度卒中患者。轻度卒中患者中有73%出院回家,而重度卒中患者中只有12.2%出院回家(P <.0001);61%的重度卒中患者出院后前往康复机构或专业护理机构。2000年和2005年,重度卒中患者的费用分别是轻度卒中患者的4.4倍和3.0倍。重度卒中患者占所有患者不到三分之一,但却占急性卒中护理住院总费用的60%。
BASIS,一种基于神经影像学的卒中分类系统,在预测住院资源使用、急性住院费用和预后方面非常有效。在研究的这些年份中,其预测能力保持稳定。