Department of Intensive Care, Radboud University Nijmegen Medical Centre, Nijmegen, PO box 9101, Nijmegen 6500HB, the Netherlands.
Crit Care. 2010;14(4):R146. doi: 10.1186/cc9214. Epub 2010 Aug 3.
Predictive models, such as acute physiology and chronic health evaluation II (APACHE-II), are widely used in intensive care units (ICUs) to estimate mortality. Although the presence of delirium is associated with a higher mortality in ICU patients, delirium is not part of the APACHE-II model. The aim of the current study was to evaluate whether delirium, present within 24 hours after ICU admission, improves the predictive value of the APACHE-II score.
In a prospective cohort study 2116 adult patients admitted between February 2008 and February 2009 were screened for delirium with the confusion assessment method-ICU (CAM-ICU). Exclusion criteria were sustained coma and unable to understand Dutch. Logistic regression analysis was used to estimate the predicted probabilities in the model with and without delirium. Calibration plots and the Hosmer-Lemeshow test (HL-test) were used to assess calibration. The discriminatory power of the models was analyzed by the area under the receiver operating characteristics curve (AUC) and AUCs were compared using the Z-test.
1740 patients met the inclusion criteria, of which 332 (19%) were delirious at the time of ICU admission or within 24 hours after admission. Delirium was associated with in-hospital mortality in unadjusted models, odds ratio (OR): 3.22 (95% confidence interval [CI]: 2.23 - 4.66). The OR between the APACHE-II and in-hospital mortality was 1.15 (95% CI 1.12 - 1.19) per point. The predictive accuracy of the APACHE-II did not improve after adding delirium, both in the total group as well as in the subgroup without cardiac surgery patients. The AUC of the APACHE model without delirium was 0.77 (0.73 - 0.81) and 0.78 (0.74 - 0.82) when delirium was added to the model. The z-value was 0.92 indicating no improvement in discriminative power, and the HL-test and calibration plots indicated no improvement in calibration.
Although delirium is a significant predictor of mortality in ICU patients, adding delirium as an additional variable to the APACHE-II model does not result in an improvement in its predictive estimates.
预测模型,如急性生理学和慢性健康评估 II (APACHE-II),广泛用于重症监护病房(ICU)来估计死亡率。虽然 ICU 患者的谵妄与更高的死亡率有关,但谵妄并不属于 APACHE-II 模型的一部分。本研究的目的是评估 ICU 入院后 24 小时内出现的谵妄是否可以提高 APACHE-II 评分的预测价值。
在一项前瞻性队列研究中,对 2008 年 2 月至 2009 年 2 月期间入院的 2116 名成年患者使用 ICU 意识模糊评估法(CAM-ICU)筛查谵妄。排除标准为持续昏迷和无法理解荷兰语。使用逻辑回归分析来估计有和无谵妄的模型中的预测概率。校准图和 Hosmer-Lemeshow 检验(HL 检验)用于评估校准。通过接收者操作特征曲线下的面积(AUC)来分析模型的区分能力,并使用 Z 检验比较 AUCs。
1740 名患者符合纳入标准,其中 332 名(19%)在 ICU 入院时或入院后 24 小时内出现谵妄。在未调整的模型中,谵妄与住院死亡率相关,比值比(OR):3.22(95%置信区间[CI]:2.23 - 4.66)。APACHE-II 与住院死亡率之间的 OR 为每增加 1 分 1.15(95%CI 1.12 - 1.19)。在不包括心脏手术患者的总组和亚组中,添加谵妄后,APACHE-II 的预测准确性并未提高。无谵妄的 APACHE 模型的 AUC 为 0.77(0.73 - 0.81),当将谵妄添加到模型中时为 0.78(0.74 - 0.82)。Z 值为 0.92,表明判别能力无改善,HL 检验和校准图表明校准无改善。
尽管谵妄是 ICU 患者死亡率的重要预测指标,但将谵妄作为附加变量添加到 APACHE-II 模型中并不会提高其预测估计。