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评估药物治疗方案的复杂性作为预测死亡率的指标。

Evaluation of medication regimen complexity as a predictor for mortality.

机构信息

Department of Clinical and Administrative Pharmacy, University of Georgia College of Pharmacy, 1120 15th Street, HM-118, Augusta, GA, 30912, USA.

Bouve College of Health Sciences, Northeastern University, Boston, MA, USA.

出版信息

Sci Rep. 2023 Jul 4;13(1):10784. doi: 10.1038/s41598-023-37908-1.

Abstract

While medication regimen complexity, as measured by a novel medication regimen complexity-intensive care unit (MRC-ICU) score, correlates with baseline severity of illness and mortality, whether the MRC-ICU improves hospital mortality prediction is not known. After characterizing the association between MRC-ICU, severity of illness and hospital mortality we sought to evaluate the incremental benefit of adding MRC-ICU to illness severity-based hospital mortality prediction models. This was a single-center, observational cohort study of adult intensive care units (ICUs). A random sample of 991 adults admitted ≥ 24 h to the ICU from 10/2015 to 10/2020 were included. The logistic regression models for the primary outcome of mortality were assessed via area under the receiver operating characteristic (AUROC). Medication regimen complexity was evaluated daily using the MRC-ICU. This previously validated index is a weighted summation of medications prescribed in the first 24 h of ICU stay [e.g., a patient prescribed insulin (1 point) and vancomycin (3 points) has a MRC-ICU = 4 points]. Baseline demographic features (e.g., age, sex, ICU type) were collected and severity of illness (based on worst values within the first 24 h of ICU admission) was characterized using both the Acute Physiology and Chronic Health Evaluation (APACHE II) and the Sequential Organ Failure Assessment (SOFA) score. Univariate analysis of 991 patients revealed every one-point increase in the average 24-h MRC-ICU score was associated with a 5% increase in hospital mortality [Odds Ratio (OR) 1.05, 95% confidence interval 1.02-1.08, p = 0.002]. The model including MRC-ICU, APACHE II and SOFA had a AUROC for mortality of 0.81 whereas the model including only APACHE-II and SOFA had a AUROC for mortality of 0.76. Medication regimen complexity is associated with increased hospital mortality. A prediction model including medication regimen complexity only modestly improves hospital mortality prediction.

摘要

虽然药物治疗方案的复杂性(通过新型药物治疗方案复杂性重症监护病房[MRC-ICU]评分衡量)与基线疾病严重程度和死亡率相关,但 MRC-ICU 是否能改善医院死亡率预测尚不清楚。在描述 MRC-ICU、疾病严重程度和医院死亡率之间的关联后,我们试图评估将 MRC-ICU 添加到基于疾病严重程度的医院死亡率预测模型中的增量收益。这是一项单中心、观察性重症监护病房(ICU)队列研究。纳入了 2015 年 10 月至 2020 年 10 月期间入住 ICU 时间≥24 小时的 991 名成年患者。通过接受者操作特征曲线(AUROC)下面积评估主要结局死亡率的逻辑回归模型。每天使用 MRC-ICU 评估药物治疗方案的复杂性。该指数是 ICU 入住的前 24 小时内开具的药物的加权总和[例如,同时开胰岛素(1 分)和万古霉素(3 分)的患者,MRC-ICU=4 分]。收集了基线人口统计学特征(如年龄、性别、ICU 类型)和疾病严重程度(基于 ICU 入院后前 24 小时内的最差值),使用急性生理学和慢性健康评估(APACHE II)和序贯器官衰竭评估(SOFA)评分进行描述。对 991 例患者的单因素分析显示,平均 24 小时 MRC-ICU 评分每增加 1 分,医院死亡率增加 5%[比值比(OR)1.05,95%置信区间 1.02-1.08,p=0.002]。包含 MRC-ICU、APACHE II 和 SOFA 的模型的死亡率 AUROC 为 0.81,而仅包含 APACHE-II 和 SOFA 的模型的死亡率 AUROC 为 0.76。药物治疗方案的复杂性与医院死亡率的增加相关。包含药物治疗方案复杂性的预测模型仅适度改善了医院死亡率预测。

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