Observational studyScientific reports2023
Evaluation of medication regimen complexity as a predictor for mortality.
Observational study in Scientific reports, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
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.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
10 citing papers in PubMed, 16 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
- Prediction of pharmacist medication interventions using medication regimen complexity.JAMIA open · 2025Article
- PharmacyGPT: exploration of artificial intelligence for medication management in the intensive care unit.BMC medical informatics and decision making · 2025Article
- Augmenting Mortality Prediction in Critically Ill Adults With Medication Data and Machine Learning Models.Critical care explorations · 2025Article
- Consensus recommendations for the integration of critical care pharmacists on intensive care unit teams: Endorsed by the American Association of Critical-Care Nurses, American College of Clinical Pharmacy, American Society of Health-System Pharmacists, Institute for Safe Medication Practices, and Society of Critical Care Medicine.Journal of the American College of Clinical Pharmacy : JACCP · 2025Article
- Unsupervised machine learning analysis to identify patterns of ICU medication use for fluid overload prediction.Pharmacotherapy · 2025Article
- A common data model for the standardization of intensive care unit medication features.JAMIA open · 2024Article
- Cluster analysis driven by unsupervised latent feature learning of medications to identify novel pharmacophenotypes of critically ill patients.Scientific reports · 2023Article
- Pharmacotherapy for sleep during critical illness and beyond.Frontiers in neurologyReview
Corrections and comments
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Authors and funding
10 authors at 8 institutions in 1 country.
Funding
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.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.