Evaluating the Medication Regimen Complexity Score as a Predictor of Clinical Outcomes in the Critically Ill.

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.

Survival and recovery modeling of acute kidney injury in critically ill adults.

Objectives: Acute kidney injury is common among the critically ill. However, the incidence, medication use, and outcomes of acute kidney injury have been variably described. We conducted a single-center, retrospective cohort study to examine the risk factors and correlates associated with acute kidney injury in critically ill adults with a particular focus on medication class usage. Methods: We reviewed the electronic medical records of all adult patients admitted to an intensive care unit between 1 February and 30 August 2020. Acute kidney injury was defined by the 2012 Kidney Disease: Improving Global Outcomes guidelines. Data included were demographics, comorbidities, symptoms, laboratory parameters, interventions, and outcomes. The primary outcome was acute kidney injury incidence. A Least Absolute Shrinkage and Selection Operator regression model was used to determine risk factors associated with acute kidney injury. Secondary outcomes including acute kidney injury recovery and intensive care unit mortality were analyzed using a Cox regression model. Results: Among 226 admitted patients, 108 (47.8%) experienced acute kidney injury. 37 (34.3%), 39 (36.1%), and 32 patients (29.6%) were classified as acute kidney injury stages I-III, respectively. Among the recovery and mortality cohorts, analgesics/sedatives, anti-infectives, and intravenous fluids were significant (p-value < 0.05). The medication classes IV-fluid electrolytes nutrition (96.7%), gastrointestinal (90.2%), and anti-infectives (81.5%) were associated with an increased odds of developing acute kidney injury, odd ratios: 1.27, 1.71, and 1.70, respectively. Cox regression analyses revealed a significantly increased time-varying mortality risk for acute kidney injury-stage III, hazard ratio: 4.72 (95% confidence interval: 1-22.33). In the recovery cohort, time to acute kidney injury recovery was significantly faster in stage I, hazard ratio: 9.14 (95% confidence interval: 2.14-39.06) cohort when compared to the stage III cohort. Conclusion: Evaluation of vital signs, laboratory, and medication use data may be useful to determine acute kidney injury risk stratification. The influence of particular medication classes further impacts the risk of developing acute kidney injury, necessitating the importance of examining pharmacotherapeutic regimens for early recognition of renal impairment and prevention.

Drug-Induced QTc Prolongation: What We Know and Where We Are Going.

Drug-induced QTc prolongation is a concerning electrocardiogram (ECG) abnormality. This cardiac disturbance carries a 10% risk of sudden cardiac death due to the malignant arrhythmia, Torsades de Pointes. The Arizona Center for Education and Research on Therapeutics (AzCERT) has classified QTc prolonging therapeutic classes, such as antiarrhythmics, antipsychotics, anti-infectives, and others. AzCERT criteria categorize medications into three risk categories: "known," "possible," and "conditional risk" of QTc prolongation and Torsades de Pointes. The list of QTc prolonging medications continues to expand as new drug classes are approved and studied. Risk factors for QTc prolongation can be delineated into modifiable or non-modifiable. A validated risk scoring tool may be utilized to predict the likelihood of prolongation in patients receiving AzCERT classified medication. The resultant risk score may be applied to a clinical decision support system, which offers mitigation strategies. Mitigation strategies including discontinuation of possible offending agents with a selection of an alternative agent, assessment of potential drug interactions or dose adjustments through pharmacokinetic and pharmacodynamic monitoring, and initiation of both ECG and electrolyte monitoring are essential to prevent a drug-induced arrhythmia. The challenges presented by the COVID-19 pandemic have led to the development of innovative continuous monitoring technology, increasing protection for both patients and healthcare workers. Early intervention strategies may reduce adverse events and improve clinical outcomes in patients identified to be at risk of QTc prolongation.