ArticleJournal of clinical medicine2022
Evaluating the Medication Regimen Complexity Score as a Predictor of Clinical Outcomes in the Critically Ill.
Article in Journal of clinical medicine, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
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Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
6 citing papers in PubMed, 8 citations in OpenAlex.
- A Data-Driven Medication Regimen Complexity Score for Critically Ill Patients: MRC-ICU 2.0.Pharmacotherapy · 2026Observational
- Optimizing critical care pharmacotherapy: dynamic prospective evaluation of the medication regimen complexity-intensive care unit (MRC-ICU) score in critically ill patients.Scientific reports · 2026Article
- Augmenting Mortality Prediction in Critically Ill Adults With Medication Data and Machine Learning Models.Critical care explorations · 2025Article
- A common data model for the standardization of intensive care unit medication features.JAMIA open · 2024Article
- Medication Regimen Complexity Index Score at Admission as a Predictor of Inpatient Outcomes: A Machine Learning Approach.International journal of environmental research and public health · 2023Article
- Pharmacotherapy for sleep during critical illness and beyond.Frontiers in neurologyReview
Corrections and comments
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Authors and funding
8 authors at 3 institutions in 1 country.
Funding
Abstract
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.
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Registered trials
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