Chen Yu, Du Hang, Wei Bao-Hua, Chang Xue-Ni, Dong Chen-Ming
Intensive Care Unit 1, Lanzhou University Second Hospital, Lanzhou, Gansu, China.
Medicine (Baltimore). 2017 Jul;96(29):e7543. doi: 10.1097/MD.0000000000007543.
The objective is to develop a model based on risk stratification to predict delirium among adult critically ill patients and whether early intervention could be provided for high-risk patients, which could reduce the incidence of delirium.We designed a prospective, observational, single-center study. We examined 11 factors, including age, APACHE-II score, coma, emergency operation, mechanical ventilation (MV), multiple trauma, metabolic acidosis, history of hypertension, delirium and dementia, and application of Dexmedetomidine Hydrochloride. Confusion assessment method for the intensive care unit (CAM-ICU) was performed to screen patients during their ICU stay. Multivariate logistic regression analysis was used to develop the model, and we assessed the predictive ability of the model by using the area under the receiver operating characteristics curve (AUROC).From May 17, 2016 to September 25, 2016, 681 consecutive patients were screened, 61 of whom were excluded. The most frequent reason for exclusion was sustained coma 30 (4.4%), followed by a length of stay in the ICU < 24 hours 18 (2.6%) and delirium before ICU admission 13 (1.9%). Among the remaining 620 patients (including 162 nervous system disease patients), 160 patients (25.8%) developed delirium, and 64 (39.5%) had nervous system disease. The mean age was 55 ± 18 years old, the mean APACHE-II score was 16 ± 4, and 49.2% of them were male. Spearman analysis of nervous system disease and incidence of delirium showed that the correlation coefficient was 0.186 (P < .01). We constructed a prediction model that included 11 risk factors. The AUROC was 0.78 (95% CI 0.72-0.83).We developed the model using 11 related factors to predict delirium in critically ill patients and further determined that prophylaxis with Dexmedetomidine Hydrochloride in delirious ICU patients was beneficial. Patients who suffer from nervous system disease are at a higher incidence of delirium, and corresponding measures should be used for prevention.
ChiCTR-OOC-16008535.
目的是开发一种基于风险分层的模型,以预测成年重症患者的谵妄情况,并确定是否可为高危患者提供早期干预,从而降低谵妄的发生率。我们设计了一项前瞻性、观察性、单中心研究。我们考察了11个因素,包括年龄、急性生理与慢性健康状况评分系统II(APACHE-II)评分、昏迷、急诊手术、机械通气(MV)、多发伤、代谢性酸中毒、高血压病史、谵妄和痴呆,以及盐酸右美托咪定的应用。在重症监护病房(ICU)住院期间,采用重症监护病房意识模糊评估法(CAM-ICU)对患者进行筛查。采用多因素逻辑回归分析建立模型,并通过受试者操作特征曲线下面积(AUROC)评估模型的预测能力。2016年5月17日至2016年9月25日,连续筛查681例患者,排除61例。最常见的排除原因是持续性昏迷30例(4.4%),其次是在ICU住院时间<24小时18例(2.6%)和ICU入院前谵妄13例(1.9%)。在其余620例患者(包括162例神经系统疾病患者)中,160例(25.8%)发生谵妄,64例(39.5%)患有神经系统疾病。平均年龄为55±18岁,平均APACHE-II评分为16±4,其中49.2%为男性。对神经系统疾病与谵妄发生率进行Spearman分析,相关系数为0.186(P<0.01)。我们构建了一个包含11个危险因素的预测模型。AUROC为0.78(95%可信区间0.72-0.83)。我们利用11个相关因素建立模型来预测重症患者的谵妄,并进一步确定在谵妄的ICU患者中预防性使用盐酸右美托咪定是有益的。患有神经系统疾病的患者谵妄发生率较高,应采取相应措施进行预防。
中国临床试验注册中心注册号:ChiCTR-OOC-16008535。