E-PRE-DELIRIC risk stratification model in management of delirium in intensive care unit: Outcomes and risk prediction performance
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摘要:
背景 谵妄是重症监护病房常见并发症，可增加死亡风险，影响预后，其防控重要性大于治疗。国内外尚未见通过风险分层模型联合优化的评估措施筛查中高风险及亚综合型谵妄并进行早期干预的报道。 目的 探讨基于E-PRE-DELIRIC早期风险分层模型的谵妄管理模式对重症监护病房(intensive care unit，ICU)患者谵妄发生率的影响，并对该风险预测模型进行效能验证研究。 方法 以常州市第四人民医院ICU病区2019年6月 - 2021年12月收治的患者为研究对象，干预组采用E-PRE-DELIRIC风险分层模型对入组患者进行风险分层，并建立基于logistic回归的多指标风险预测模型，通过ROC分析评估其预测效能。临床药师加入ICU谵妄管理团队，对中高风险患者实施重点药学监护，实施早期干预。对照组按常规谵妄管理模式执行。比较两组患者谵妄发生率、谵妄持续时间、疼痛评分、ICU住院时间和药物不良反应发生率。 结果 共纳入212例患者，干预组107例，对照组105例。两组年龄、性别、认知障碍史、酗酒史、既往病史、紧急入院、入院APACHEⅡ评分、尿素氮(blood urea nitrogen，BUN)、平均动脉压(mean arterial pressure，MAP)、糖皮质激素使用率和主要合并疾病等方面的差异均无统计学意义(P＞0.05)。与对照组比较，干预组谵妄发生率显著降低[8.41% (9/98) vs 26.67% (28/77)，P＜0.01]，疼痛评分较低[Md(IQR)：0(0，0) vs 0.5(0，0.5)]，ICU住院时间较短[(10.21 ± 8.21) d vs (13.32 ± 9.74) d]，药物不良反应发生率显著降低[3.74% (4/103) vs 11.43% (12/93)]，差异均有统计学意义(P ＜0.05)。以本研究样本所建风险预测模型：Log(P/1 - P)(联合虚拟指标/概率) = -1.317 + 0.018 × 年龄 + 0.712 × 认知功能障碍史 + 0.215 × 酗酒史 + 0.592 × 治疗经历 + 0.008 × 入ICU时的MAP值 + 0.416 × 呼吸衰竭 + 0.011 × 入ICU时的BUN值。ROC分析显示，7指标联合应用对ICU患者发生谵妄的风险预测效能较高，ROC-AUC (95% CI)、敏感度、特异度、准确度分别为0.882 (0.834 ~ 0.931)、0.892、0.869、0.873。 结论 基于E-PRE-DELIRIC早期风险预估分层模型的谵妄管理模式(药学监护及早期干预等措施)可降低ICU患者谵妄发生率，降低药物不良反应发生率，并能缩短患者的ICU住院时间。 -
关键词:
- E-PRE-DELIRIC模型 /
- 谵妄管理模式 /
- 重症监护病房 /
- 临床药师 /
- 谵妄发生率
Abstract:Background Delirium is a common complication in intensive care unit, which can increase the mortality and affect the prognosis. Prevention and control are more important than treatment. However, there is no assessment or early intervention to screen medium high risk and sub comprehensive delirium by joint optimization of risk stratification model at home and abroad. Objective To explore the effect of delirium management mode based on E-PRE-DELIRIC early risk stratification model on the incidence of delirium in intensive care unit (ICU), and verify the effectiveness of the risk prediction model. Methods Taking the patients admitted to the ICU ward of Changzhou Fourth People's Hospital from June 2019 to December 2021 as the research objects, the intervention group adopted the delirium management and control mode based on the early risk stratification model, the multi-index risk prediction model based on logistic regression was established and its prediction performance was evaluated by ROC analysis. The control group performed the conventional delirium management mode. The incidence of delirium, duration of delirium, pain score, length of stay in ICU and incidence of adverse drug reactions were compared between the two groups. Results A total of 212 patients were included, 107 cases were in the intervention group and 105 cases in the control group. There was no significant difference between the two groups in terms of age, gender, history of cognitive impairment, history of alcoholism, past medical history, emergency admission, admission APACHE II score, BUN and MAP, glucocorticoid use rate and major combined diseases (P>0.05). Compared with the control group, the incidence of delirium in the clinical pharmacist intervention group was significantly lower (8.41% [9/98] vs 26.67% [28/77], P<0.01), the pain score was lower ([0, 0] vs [0, 0.5], P<0.01), the length of stay in ICU was shorter ([10.21 ± 8.21] d vs [13.32 ± 9.74] d, P<0.05), and the incidence of adverse drug reactions was significantly lower (3.74% [4/103] vs 11.43% [12/93], P<0.05). The risk prediction model based on the sample of this study was Log(P/1-P)(Joint virtual indicator / probability)=-1.317 + 0.018 × Age + 0.712 × History of cognitive impairment + 0.215 × History of alcoholism + 0.592 × Treatment experience + 0.008 × MAP value when entering ICU + 0.416 × Respiratory failure + 0.011 × BUN value when entering ICU. According to ROC analysis, the combined application of these seven indicators had high prediction efficiency for the risk of delirium in ICU patients, with ROC-AUC (95%CI), sensitivity, specificity and accuracy of 0.882 (0.834-0.931), 0.892, 0.869 and 0.873, respectively. Conclusion Delirium management model based on early risk prediction hierarchical model can reduce the incidence of delirium in ICU patients and adverse drug reactions, and shorten the length of stay in ICU. -
图 1 基于E-PRE-DELIRIC谵妄早期风险预估分层的谵妄管理模式
Figure 1. Construction of delirium management protocol based on the layered model of early delirium risk prediction
图 2 7指标风险模型对ICU患者发生谵妄风险预测效能的ROC分析曲线
Figure 2. ROC curve of 7 index risk model for predicting the risk of delirium in ICU
表 1 两组患者临床基线特征比较
Table 1. Baseline characteristics of the trial participants
临床特征 干预组(n=107) 对照组(n=105) χ2/t/Z值 P值 性别(男/女)/例 65/42 63/42 0.012 0.911 年龄/岁 70.37 ± 14.68 70.09 ± 14.68 0.139 0.890 认知障碍史/(例，%) 10(9.35) 17(16.19) 2.234 0.135 酗酒史/(例，%) 21(19.63) 16(15.24) 0.708 0.400 入院紧急/(例，%) 48(44.86) 49(46.67) 0.070 0.792 存在呼吸衰竭/(例，%) 46(42.99) 34(32.38) 2.539 0.111 机械通气/(例，%) 78(72.90) 87(82.86) 3.047 0.081 APACHEⅡ评分 21.74 ± 7.80 19.90 ± 6.53 1.861 0.064 入ICU时的BUN值[mmol·L-1，Md(IQR)] 10.83(5.48，26.60) 9.55(4.90，25.66) 0.133 0.894 入ICU时的MAP值 94.99 ± 27.71 98.19 ± 22.90 0.916 0.361 应用糖皮质激/(例，%) 25(23.36) 19(18.10) 0.895 0.344 既往病史a/(例，%) 19(17.76)/50(46.73)/8(7.48)/30(28.04) 13(12.38)/41(39.05)/4(3.81)/47(44.76) 7.083 0.069 a手术史、医疗史、创伤史、神经内科或神经外科病史。 
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表 2 干预组患者谵妄早期风险预估分层
Table 2. Stratified statistical table of early delirium risk prediction of patients in the intervention group
谵妄早期风险预估分层 非常低(0 ~ 10%) 低风险
(10% ~ 20%)中风险
(20% ~ 35%)高风险
(＞35%)中高风险占比/% 例数 17 25 37 28 60.75
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表 3 干预组患者镇痛、镇静方案的药学监护
Table 3. Pharmaceutical care of analgesia and sedation schemes of patients in the intervention group
药学监护结果 变量 病例数/例 镇痛 布托啡诺泵注时间过长，浓度过高 13 地佐辛泵注时间过长，浓度过高 10 镇静 提醒咪达唑仑用药时长 5 提醒丙泊酚用药时长 1
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表 4 单一CAM-ICU谵妄评估方法与CAM-ICU和ICDSC联合评估筛查结果对比(%)
Table 4. Comparison of results between single CAM-ICU delirium assessment method and combined CAM-ICU and ICDSC assessment screening (%)
评估方法 干预组评估谵妄占比 对照组评估谵妄占比 干预组亚综合型谵妄 对照组亚综合型谵妄 谵妄总占比 亚综合型谵妄总占比 CAM-ICU 3.74 15.24 - - 9.43 - CAM-ICU + ICDSC 8.41 26.67 4.67 21.91 17.45 13.21
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表 5 两组患者管理效果相关指标分析
Table 5. Comparison of related indice of management effect between the two groups
效果指标 干预组
(n=107)对照组
(n=105)χ2/Z值 P值 谵妄(有/无)/例 9/98 28/77 12.259 ＜0.001 谵妄持续时间/[d，Md(IQR)] 1(0.5 ~ 3) 3(1 ~ 5) 3.931 ＜0.001 疼痛评分/Md(IQR) 0(0 ~ 0) 0.5(0 ~ 0.5) 3.232 ＜0.001 ICU住院时间/[d，Md(IQR)] 8(4 ~ 26) 14(5 ~ 35) 2.455 0.014 药物不良反应/(n/N，%) 4/103(3.74) 12/93(11.43) 4.492 0.034
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表 6 ICU患者发生谵妄的多因素logistic回归分析
Table 6. Multivariate logistic regression analysis of risk factors for delirium in ICU patients
风险因素 变量赋值 回归系数 标准差 Wald χ2 OR 95% CI 常数项 - -1.317 0.638 4.257 0.268 0.077 ~ 0.936 年龄 连续变量 0.018 0.003 36.000 1.018 1.012 ~ 1.024 认知功能障碍 1=有，0=无 0.712 0.273 6.802 2.038 1.194 ~ 3.480 饮酒史 1=有，0=无 0.215 0.088 5.969 1.240 1.043 ~ 1.473 既往病史a 1=有，0=无 0.592 0.214 7.653 1.808 1.188 ~ 2.750 入ICU时MAP值 连续变量 0.008 0.002 16.000 1.008 1.004 ~ 1.012 呼吸衰竭 1=有，0=无 0.416 0.132 9.932 1.516 1.170 ~ 1.963 入ICU时BUN值 连续变量 0.011 0.004 7.563 1.011 1.003 ~ 1.019 a既往病史包括手术史、医疗史、外伤史、神经外科病史，有其中之一的记为1，否则记为0。
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表 7 7指标风险模型对ICU患者发生谵妄风险预测效能的ROC分析结果
Table 7. ROC analysis of seven index risk model for predicting the risk of delirium in ICU patients
指标 ACU (95% CI) 敏感度(n/N) 特异度(n/N) 约登指数 准确率(n/N) 风险回归模型 0.882
(0.834 ~ 0.931)0.892(33/37) 0.869(152/175) 0.761 0.873(185/212)
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