Georgiou Andy, Turner Nicholas, Serrano Ruiz Alfredo, Wadman Harry, Saunsbury Emma, Laver Stephen, Maybin Rob
Intensive Care Unit, Royal United Hospital Bath NHS Foundation Trust, Bath, UK.
Bristol Randomised Trials Collaboration, University of Bristol, Bristol, UK.
J Intensive Care Soc. 2023 Feb;24(1):16-23. doi: 10.1177/17511437221096287. Epub 2022 May 4.
This study aims to identify any effect of frailty in altering the risk of death or poor outcome already associated with receipt of organ support on ICU. It also aims to assess the performance of mortality prediction models in frail patients.
All admissions to a single ICU over 1-year were prospectively allocated a Clinical Frailty Score (CFS). Logistic regression analysis was used to investigate the effect of frailty on death or poor outcome (death/discharge to a medical facility). Logistic regression analysis, area under the Receiver Operator Curve (AUROC) and Brier scores were used to investigate the ability of two mortality prediction models, ICNARC and APACHE II, to predict mortality in frail patients.
Of 849 patients, 700 (82%) patients were not frail, and 149 (18%) were frail. Frailty was associated with a stepwise increase in the odds of death or poor outcome (OR for each point rise of CFS = 1.23 ([1.03-1.47]; = .024) and 1.32 ([1.17-1.48]; = <.001) respectively). Renal support conferred the greatest odds of death and poor outcome, followed by respiratory support, then cardiovascular support (which increased the odds of death but not poor outcome). Frailty did not modify the odds already associated with organ support. The mortality prediction models were not modified by frailty (AUROC = .220 and .437 respectively). Inclusion of frailty into both models improved their accuracy.
Frailty was associated with increased odds of death and poor outcome, but did not modify the risk already associated with organ support. Inclusion of frailty improved mortality prediction models.
本研究旨在确定衰弱对已经与在重症监护病房接受器官支持相关的死亡风险或不良结局的影响。它还旨在评估衰弱患者中死亡率预测模型的性能。
对一家重症监护病房1年期间的所有入院患者前瞻性地分配临床衰弱评分(CFS)。使用逻辑回归分析来研究衰弱对死亡或不良结局(死亡/转至医疗机构)的影响。使用逻辑回归分析、受试者操作特征曲线下面积(AUROC)和Brier评分来研究两种死亡率预测模型(ICNARC和急性生理学及慢性健康状况评分系统II [APACHE II])预测衰弱患者死亡率的能力。
849例患者中,700例(82%)患者不衰弱,149例(18%)患者衰弱。衰弱与死亡或不良结局的几率逐步增加相关(CFS每增加1分的比值比分别为1.23 [1.03 - 1.47];P = 0.024)和1.32 [1.17 - 1.48];P = <0.001)。肾脏支持带来的死亡和不良结局几率最高,其次是呼吸支持,然后是心血管支持(心血管支持增加了死亡几率,但未增加不良结局几率)。衰弱并未改变与器官支持相关的几率。死亡率预测模型未因衰弱而改变(AUROC分别为0.220和0.437)。将衰弱纳入两个模型均提高了其准确性。
衰弱与死亡和不良结局几率增加相关,但并未改变与器官支持相关的风险。纳入衰弱改善了死亡率预测模型。