King L G, Wohl J S, Manning A M, Hackner S G, Raffe M R, Maislin G
Department of Clinical Studies, School of Veterinary Medicine, University of Pennsylvania, Philadelphia 19104-6010, USA.
Am J Vet Res. 2001 Jun;62(6):948-54. doi: 10.2460/ajvr.2001.62.948.
To prospectively evaluate a survival prediction index (SPI) in dogs admitted to intensive care units (ICU) and to generate and test an improved SPI (ie, SPI2).
Medical records of 624 critically ill dogs admitted to an ICU.
Data were collected from dogs within 24 hours after admission to an ICU. Variables recorded reflected function of vital organ systems, severity of underlying physiologic derangement, and extent of physiologic reserve; outcome was defined as dogs that survived or did not survive until 30 days after admission to the ICU. Probabilities of survival were calculated, using an established model (SPI). We then performed another logistic regression analysis, thereby reestimating the variables to create the new SPI2. Cross-validation of the models obtained was performed by randomly assigning the total sample of 624 dogs into an estimation group of 499 dogs and validation group of 125 dogs.
Testing of SPI resulted in an area under the curve (AUC) of 0.723. Testing of SPI2 revealed an AUC of 0.773. A backwards-elimination procedure was used to create a model containing fewer variables, and variables were sequentially eliminated. The AUC for the reduced model of SPI2 was 0.76, indicating little loss in predictive accuracy.
The new SPI2 objectively stratified clinical patients into groups according to severity of disease. This index could provide an important tool for clinical research.
前瞻性评估入住重症监护病房(ICU)的犬类的生存预测指数(SPI),并生成和测试改进后的SPI(即SPI2)。
624只入住ICU的重症病犬的病历。
在犬类入住ICU后24小时内收集数据。记录的变量反映了重要器官系统的功能、潜在生理紊乱的严重程度以及生理储备程度;结局定义为入住ICU后存活或未存活至30天的犬类。使用既定模型(SPI)计算生存概率。然后我们进行了另一项逻辑回归分析,从而重新估计变量以创建新的SPI2。通过将624只犬的总样本随机分为499只犬的估计组和125只犬的验证组,对所得模型进行交叉验证。
SPI测试得出曲线下面积(AUC)为0.723。SPI2测试显示AUC为0.773。采用向后淘汰程序创建一个包含较少变量的模型,并依次消除变量。SPI2简化模型的AUC为0.76,表明预测准确性几乎没有损失。
新的SPI2根据疾病严重程度将临床患者客观地分层分组。该指数可为临床研究提供重要工具。