Paul E, Bailey M, Kasza J, Pilcher D V
PhD student, Australian and New Zealand Intensive Care Research Centre, Department of Epidemiology and Preventive Medicine, School of Public Health and Preventive Medicine, Monash University, Melbourne, Victoria.
Professor, Australian and New Zealand Intensive Care Research Centre, Department of Epidemiology and Preventive Medicine, School of Public Health and Preventive Medicine, Monash University, Melbourne, Victoria.
Anaesth Intensive Care. 2017 May;45(3):326-343. doi: 10.1177/0310057X1704500308.
The Australian and New Zealand Risk of Death (ANZROD) model currently used for benchmarking intensive care units (ICUs) in Australia and New Zealand utilises physiological data collected up to 24 hours after ICU admission to estimate the risk of hospital mortality. This study aimed to develop the Australian and New Zealand Risk of Death admission (ANZROD) model to predict hospital mortality using data available at presentation to ICU and compare its performance with the ANZROD in Australian and New Zealand hospitals. Data pertaining to all ICU admissions between 1 January 2006 and 31 December 2015 were extracted from the Australian and New Zealand Intensive Care Society Adult Patient Database. Hospital mortality was modelled using logistic regression with development (two-thirds) and validation (one-third) datasets. All predictor variables available at ICU admission were considered for inclusion in the ANZROD model. Model performance was assessed using Brier score, standardised mortality ratio and area under the receiver operating characteristic curve. The relationship between ANZROD and ANZROD predicted risk of death was assessed using linear regression. After standard exclusions, 1,097,416 patients were available for model development and validation. Observed mortality was 9.5%. Model performance measures (Brier score, standardised mortality ratio and area under the receiver operating characteristic curve) for the ANZROD and ANZROD in the validation dataset were 0.069, 1.0 and 0.853; 0.057, 1.0 and 0.909, respectively. There was a strong positive correlation between the mortality predictions with an overall R of 0.73. We found that the ANZROD model had acceptable calibration and discrimination. Predictions from the models had high correlations in all major diagnostic groups, with the exception of cardiac surgery and possibly trauma and sepsis.
目前用于对澳大利亚和新西兰的重症监护病房（ICU）进行基准评估的澳大利亚和新西兰死亡风险（ANZROD）模型，利用ICU入院后24小时内收集的生理数据来估计医院死亡风险。本研究旨在开发澳大利亚和新西兰入院死亡风险（ANZROD）模型，以使用ICU入院时可用的数据预测医院死亡率，并将其性能与澳大利亚和新西兰医院的ANZROD模型进行比较。从澳大利亚和新西兰重症监护学会成人患者数据库中提取了2006年1月1日至2015年12月31日期间所有ICU入院患者的数据。使用逻辑回归对医院死亡率进行建模，分为开发数据集（三分之二）和验证数据集（三分之一）。考虑将ICU入院时所有可用的预测变量纳入ANZROD模型。使用Brier评分、标准化死亡率和受试者工作特征曲线下面积评估模型性能。使用线性回归评估ANZROD与预测死亡风险之间的关系。经过标准排除后，有1,097,416名患者可用于模型开发和验证。观察到的死亡率为9.5%。验证数据集中ANZROD和ANZROD的模型性能指标（Brier评分、标准化死亡率和受试者工作特征曲线下面积）分别为0.069、1.0和0.853；0.057、1.0和0.909。死亡率预测之间存在很强的正相关性，总体R为0.73。我们发现ANZROD模型具有可接受的校准和区分能力。除心脏手术以及可能的创伤和脓毒症外，模型预测在所有主要诊断组中都具有高度相关性。
