Department of Anesthesiology, Kansai Medical University, Osaka, Japan.
J Anesth. 2013 Aug;27(4):541-9. doi: 10.1007/s00540-013-1557-0. Epub 2013 Mar 9.
To develop an equation model of in-hospital mortality for mechanically ventilated patients in adult intensive care using administrative data for the purpose of retrospective performance comparison among intensive care units (ICUs).
Two models were developed using the split-half method, in which one test dataset and two validation datasets were used to develop and validate the prediction model, respectively. Nine candidate variables (demographics: age; gender; clinical factors hospital admission course; primary diagnosis; reason for ICU entry; Charlson score; number of organ failures; procedures and therapies administered at any time during ICU admission: renal replacement therapy; pressors/vasoconstrictors) were used for developing the equation model.
In acute-care teaching hospitals in Japan: 282 ICUs in 2008, 310 ICUs in 2009, and 364 ICUs in 2010.
Mechanically ventilated adult patients discharged from an ICU from July 1 to December 31 in 2008, 2009, and 2010.
The test dataset consisted of 5,807 patients in 2008, and the validation datasets consisted of 10,610 patients in 2009 and 7,576 patients in 2010. Two models were developed: Model 1 (using independent variables of demographics and clinical factors), Model 2 (using procedures and therapies administered at any time during ICU admission in addition to the variables in Model 1). Using the test dataset, 8 variables (except for gender) were included in multiple logistic regression analysis with in-hospital mortality as the dependent variable, and the mortality prediction equation was constructed. Coefficients from the equation were then tested in the validation model.
Hosmer-Lemeshow χ(2) are values for the test dataset in Model 1 and Model 2, and were 11.9 (P = 0.15) and 15.6 (P = 0.05), respectively; C-statistics for the test dataset in Model 1and Model 2 were 0.70 and 0.78, respectively. In-hospital mortality prediction for the validation datasets showed low and moderate accuracy in Model 1 and Model 2, respectively.
Model 2 may potentially serve as an alternative model for predicting mortality in mechanically ventilated patients, who have so far required physiological data for the accurate prediction of outcomes. Model 2 may facilitate the comparative evaluation of in-hospital mortality in multicenter analyses based on administrative data for mechanically ventilated patients.
利用行政数据为成人重症监护病房机械通气患者建立住院死亡率方程模型，以便对重症监护病房（ICU）进行回顾性绩效比较。
使用分半法建立了两个模型，其中一个测试数据集和两个验证数据集分别用于开发和验证预测模型。九个候选变量（人口统计学：年龄；性别；临床因素：住院过程；主要诊断；入住 ICU 的原因；Charlson 评分；器官衰竭的数量；在 ICU 住院期间任何时候进行的程序和治疗：肾脏替代治疗；升压药/血管收缩剂）用于建立方程模型。
日本急性护理教学医院：2008 年 282 个 ICU、2009 年 310 个 ICU 和 2010 年 364 个 ICU。
2008 年 7 月 1 日至 12 月 31 日从 ICU 出院的机械通气成年患者。
测试数据集由 2008 年的 5807 名患者组成，验证数据集由 2009 年的 10610 名患者和 2010 年的 7576 名患者组成。建立了两个模型：模型 1（使用人口统计学和临床因素的独立变量），模型 2（在 ICU 住院期间任何时候进行的程序和治疗的基础上，使用模型 1 中的变量）。使用测试数据集，将住院死亡率作为因变量，对 8 个变量（除性别外）进行多元逻辑回归分析，构建死亡率预测方程。然后在验证模型中检验方程的系数。
模型 1 和模型 2 的测试数据集 Hosmer-Lemeshow χ(2)值分别为 11.9（P=0.15）和 15.6（P=0.05）；模型 1 和模型 2 的测试数据集 C 统计量分别为 0.70 和 0.78。验证数据集的住院死亡率预测显示，模型 1 和模型 2 的准确性较低和中等。
模型 2 可能是预测机械通气患者死亡率的替代模型，迄今为止，该模型需要生理数据来准确预测结果。模型 2 可能有助于基于机械通气患者的行政数据进行多中心分析中对住院死亡率的比较评估。
