Al-Mamun Mohammad A, Strock Jacob, Sharker Yushuf, Shawwa Khaled, Schmidt Rebecca, Slain Douglas, Sakhuja Ankit, Brothers Todd N
School of Pharmacy, University of West Virginia, 706 Health Sciences Ctr S, Morgantown, WV 26506, USA.
Graduate School of Oceanography, University of Rhode Island, 215 S Ferry Rd, Narragansett, RI 02882, USA.
J Clin Med. 2022 Aug 11;11(16):4705. doi: 10.3390/jcm11164705.
Background: Medication Regimen Complexity (MRC) refers to the combination of medication classes, dosages, and frequencies. The objective of this study was to examine the relationship between the scores of different MRC tools and the clinical outcomes. Methods: We conducted a retrospective cohort study at Roger William Medical Center, Providence, Rhode Island, which included 317 adult patients admitted to the intensive care unit (ICU) between 1 February 2020 and 30 August 2020. MRC was assessed using the MRC Index (MRCI) and MRC for the Intensive Care Unit (MRC-ICU). A multivariable logistic regression model was used to identify associations among MRC scores, clinical outcomes, and a logistic classifier to predict clinical outcomes. Results: Higher MRC scores were associated with increased mortality, a longer ICU length of stay (LOS), and the need for mechanical ventilation (MV). MRC-ICU scores at 24 h were significantly (p < 0.001) associated with increased ICU mortality, LOS, and MV, with ORs of 1.12 (95% CI: 1.06−1.19), 1.17 (1.1−1.24), and 1.21 (1.14−1.29), respectively. Mortality prediction was similar using both scoring tools (AUC: 0.88 [0.75−0.97] vs. 0.88 [0.76−0.97]. The model with 15 medication classes outperformed others in predicting the ICU LOS and the need for MV with AUCs of 0.82 (0.71−0.93) and 0.87 (0.77−0.96), respectively. Conclusion: Our results demonstrated that both MRC scores were associated with poorer clinical outcomes. The incorporation of MRC scores in real-time therapeutic decision making can aid clinicians to prescribe safer alternatives.
药物治疗方案复杂性（MRC）指的是药物类别、剂量和用药频率的组合。本研究的目的是探讨不同MRC工具的评分与临床结局之间的关系。方法：我们在罗德岛州普罗维登斯的罗杰·威廉姆斯医疗中心进行了一项回顾性队列研究，纳入了2020年2月1日至2020年8月30日期间入住重症监护病房（ICU）的317例成年患者。使用MRC指数（MRCI）和重症监护病房MRC（MRC-ICU）评估MRC。采用多变量逻辑回归模型确定MRC评分、临床结局之间的关联，并使用逻辑分类器预测临床结局。结果：较高的MRC评分与死亡率增加、ICU住院时间（LOS）延长以及机械通气（MV）需求增加相关。24小时时的MRC-ICU评分与ICU死亡率增加、LOS延长和MV需求显著相关（p<0.001），OR分别为1.12（95%CI：1.06−1.19）、1.17（1.1−1.24）和1.21（1.14−1.29）。使用两种评分工具进行的死亡率预测相似（AUC：0.88[0.75−0.97]对0.88[0.76−0.97]）。包含15种药物类别的模型在预测ICU LOS和MV需求方面表现优于其他模型，AUC分别为0.82（0.71−0.93）和0.87（0.77−0.96）。结论：我们的结果表明，两种MRC评分均与较差的临床结局相关。将MRC评分纳入实时治疗决策可帮助临床医生开出更安全的替代方案。
