Cardoso Luciana Gonzaga dos Santos, Chiavone Paulo Antonio
Santa Casa de São Paulo, Faculdade de Ciências Médicas, São Paulo, SP, Brazil.
Rev Lat Am Enfermagem. 2013 May-Jun;21(3):811-9. doi: 10.1590/S0104-11692013000300022.
to analyze the performance of the Acute Physiology and Chronic Health Evaluation (APACHE II), measured based on the data from the last 24 hours of hospitalization in ICU, for patients transferred to the wards.
an observational, prospective and quantitative study using the data from 355 patients admitted to the ICU between January and July 2010, who were transferred to the wards.
the discriminatory power of the AII-OUT prognostic index showed a statistically significant area beneath the ROC curve. The mortality observed in the sample was slightly greater than that predicted by the AII-OUT, with a Standardized Mortality Ratio of 1.12. In the calibration curve the linear regression analysis showed the R2 value to be statistically significant.
the AII-OUT could predict mortality after discharge from ICU, with the observed mortality being slightly greater than that predicted, which shows good discrimination and good calibration. This system was shown to be useful for stratifying the patients at greater risk of death after discharge from ICU. This fact deserves special attention from health professionals, particularly nurses, in managing human and technological resources for this group of patients.
基于重症监护病房（ICU）住院最后24小时的数据，分析急性生理与慢性健康状况评分系统（APACHE II）对转入普通病房患者的评估表现。
采用一项观察性、前瞻性定量研究，数据来源于2010年1月至7月间入住ICU并转入普通病房的355例患者。
AII - OUT预后指数的鉴别能力在ROC曲线下面积显示具有统计学意义。样本中观察到的死亡率略高于AII - OUT预测的死亡率，标准化死亡率为1.12。在校准曲线中，线性回归分析显示R2值具有统计学意义。
AII - OUT能够预测ICU出院后的死亡率，观察到的死亡率略高于预测值，显示出良好的鉴别能力和校准性。该系统对于对ICU出院后死亡风险较高的患者进行分层很有用。这一事实值得医护人员，尤其是护士，在为这类患者管理人力和技术资源时给予特别关注。
