Clinically relevant potential drug-drug interactions in intensive care patients: A large retrospective observational multicenter study

The effect of computerised decision support alerts tailored to intensive care on the administration of high-risk drug combinations, and their monitoring: a cluster randomised stepped-wedge trial

BACKGROUND

Drug-drug interactions (DDIs) can harm patients admitted to the intensive care unit (ICU). Yet, clinical decision support systems (CDSSs) aimed at helping physicians prevent DDIs are plagued by low-yield alerts, causing alert fatigue and compromising patient safety. The aim of this multicentre study was to evaluate the effect of tailoring potential DDI alerts to the ICU setting on the frequency of administered high-risk drug combinations.

METHODS

We implemented a cluster randomised stepped-wedge trial in nine ICUs in the Netherlands. Five ICUs already used potential DDI alerts. Patients aged 18 years or older admitted to the ICU with at least two drugs administered were included. Our intervention was an adapted CDSS, only providing alerts for potential DDIs considered as high risk. The intervention was delivered at the ICU level and targeted physicians. We hypothesised that showing only relevant alerts would improve CDSS effectiveness and lead to a decreased number of administered high-risk drug combinations. The order in which the intervention was implemented in the ICUs was randomised by an independent researcher. The primary outcome was the number of administered high-risk drug combinations per 1000 drug administrations per patient and was assessed in all included patients. This trial was registered in the Netherlands Trial Register (identifier NL6762) on Nov 26, 2018, and is now closed.

FINDINGS

In total, 10 423 patients admitted to the ICU between Sept 1, 2018, and Sept 1, 2019, were assessed and 9887 patients were included. The mean number of administered high-risk drug combinations per 1000 drug administrations per patient was 26·2 (SD 53·4) in the intervention group (n=5534), compared with 35·6 (65·0) in the control group (n=4353). Tailoring potential DDI alerts to the ICU led to a 12% decrease (95% CI 5-18%; p=0·0008) in the number of administered high-risk drug combinations per 1000 drug administrations per patient, after adjusting for clustering and prognostic factors.

INTERPRETATION

This cluster randomised stepped-wedge trial showed that tailoring potential DDI alerts to the ICU setting significantly reduced the number of administered high-risk drug combinations. Our list of high-risk drug combinations can be used in other ICUs, and our strategy of tailoring alerts based on clinical relevance could be applied to other clinical settings.

FUNDING

ZonMw.

Are polypharmacy side effects predicted by public data still valid in real-world data?

Background and Objective

Although interest in predicting drug-drug interactions is growing, many predictions are not verified by real-world data. This study aimed to confirm whether predicted polypharmacy side effects using public data also occur in data from actual patients.

Methods

We utilized a deep learning-based polypharmacy side effects prediction model to identify cefpodoxime-chlorpheniramine-lung edema combination with a high prediction score and a significant patient population. The retrospective study analyzed patients over 18 years old who were admitted to the Asan medical center between January 2000 and December 2020 and took cefpodoxime or chlorpheniramine orally. The three groups, cefpodoxime-treated, chlorpheniramine-treated, and cefpodoxime & chlorpheniramine-treated were compared using inverse probability of treatment weighting (IPTW) to balance them. Differences between the three groups were analyzed using the Kaplan-Meier method and Cox proportional hazards model.

Results

The study population comprised 54,043 patients with a history of taking cefpodoxime, 203,897 patients with a history of taking chlorpheniramine, and 1,628 patients with a history of taking cefpodoxime and chlorpheniramine simultaneously. After adjustment, the 1-year cumulative incidence of lung edema in the patient group that took cefpodoxime and chlorpheniramine simultaneously was significantly higher than in the patient groups that took cefpodoxime or chlorpheniramine only (p=0.001). Patients taking cefpodoxime and chlorpheniramine together had an increased risk of lung edema compared to those taking cefpodoxime alone [hazard ratio (HR) 2.10, 95% CI 1.26-3.52, p<0.005] and those taking chlorpheniramine alone, which also increased the risk of lung edema (HR 1.64, 95% CI 0.99-2.69, p=0.05).

Conclusions

Validation of polypharmacy side effect predictions with real-world data can aid patient and clinician decision-making before conducting randomized controlled trials. Simultaneous use of cefpodoxime and chlorpheniramine was associated with a higher long-term risk of lung edema compared to the use of cefpodoxime or chlorpheniramine alone.

Adverse drug events caused by three high-risk drug-drug interactions in patients admitted to intensive care units: A multicentre retrospective observational study

AIMS

Knowledge about adverse drug events caused by drug-drug interactions (DDI-ADEs) is limited. We aimed to provide detailed insights about DDI-ADEs related to three frequent, high-risk potential DDIs (pDDIs) in the critical care setting: pDDIs with international normalized ratio increase (INR+ ) potential, pDDIs with acute kidney injury (AKI) potential, and pDDIs with QTc prolongation potential.

METHODS

We extracted routinely collected retrospective data from electronic health records of intensive care units (ICUs) patients (≥18 years), admitted to ten hospitals in the Netherlands between January 2010 and September 2019. We used computerized triggers (e-triggers) to preselect patients with potential DDI-ADEs. Between September 2020 and October 2021, clinical experts conducted a retrospective manual patient chart review on a subset of preselected patients, and assessed causality, severity, preventability, and contribution to ICU length of stay of DDI-ADEs using internationally prevailing standards.

RESULTS

In total 85 422 patients with ≥1 pDDI were included. Of these patients, 32 820 (38.4%) have been exposed to one of the three pDDIs. In the exposed group, 1141 (3.5%) patients were preselected using e-triggers. Of 237 patients (21%) assessed, 155 (65.4%) experienced an actual DDI-ADE; 52.9% had severity level of serious or higher, 75.5% were preventable, and 19.3% contributed to a longer ICU length of stay. The positive predictive value was the highest for DDI-INR+ e-trigger (0.76), followed by DDI-AKI e-trigger (0.57).

CONCLUSION

The highly preventable nature and severity of DDI-ADEs, calls for action to optimize ICU patient safety. Use of e-triggers proved to be a promising preselection strategy.

Optimization of Therapy and the Risk of Probiotic Use during Antibiotherapy in Septic Critically Ill Patients: A Narrative Review

Optimizing the entire therapeutic regimen in septic critically ill patients should be based not only on improving antibiotic use but also on optimizing the entire therapeutic regimen by considering possible drug–drug or drug–nutrient interactions. The aim of this narrative review is to provide a comprehensive overview on recent advances to optimize the therapeutic regimen in septic critically ill patients based on a pharmacokinetics and pharmacodynamic approach. Studies on recent advances on TDM-guided drug therapy optimization based on PK and/or PD results were included. Studies on patients <18 years old or with classical TDM-guided therapy were excluded. New approaches in TDM-guided therapy in septic critically ill patients based on PK and/or PD parameters are presented for cefiderocol, carbapenems, combinations beta-lactams/beta-lactamase inhibitors (piperacillin/tazobactam, ceftolozane/tazobactam, ceftazidime/avibactam), plazomicin, oxazolidinones and polymyxins. Increased midazolam toxicity in combination with fluconazole, nephrotoxic synergism between furosemide and aminoglycosides, life-threatening hypoglycemia after fluoroquinolone and insulin, prolonged muscle weakness and/or paralysis after neuromuscular blocking agents and high-dose corticosteroids combinations are of interest in critically ill patients. In the real-world practice, the use of probiotics with antibiotics is common; even data about the risk and benefits of probiotics are currently spares and inconclusive. According to current legislation, probiotic use does not require safety monitoring, but there are reports of endocarditis, meningitis, peritonitis, or pneumonia associated with probiotics in critically ill patients. In addition, probiotics are associated with risk of the spread of antimicrobial resistance. The TDM-guided method ensures a true optimization of antibiotic therapy, and particular efforts should be applied globally. In addition, multidrug and drug–nutrient interactions in critically ill patients may increase the likelihood of adverse events and risk of death; therefore, the PK and PD particularities of the critically ill patient require a multidisciplinary approach in which knowledge of clinical pharmacology is essential.

Pharmacokinetic Alterations Associated with Critical Illness

Haemodynamic, metabolic, and biochemical derangements in critically ill patients affect drug pharmacokinetics and pharmacodynamics making dose optimisation particularly challenging. Appropriate therapeutic dosing depends on the knowledge of the physiologic changes caused by the patient's comorbidities, underlying disease, resuscitation strategies, and polypharmacy. Critical illness will result in altered drug protein binding, ionisation, and volume of distribution; it will also decrease oral drug absorption, intestinal and hepatic metabolism, and renal clearance. In contrast, the resuscitation strategies and the use of vasoactive drugs may oppose these effects by leading to a hyperdynamic state that will increase blood flow towards the major organs including the brain, heart, kidneys, and liver, with the subsequent increase of drug hepatic metabolism and renal excretion. Metabolism is the main mechanism for drug clearance and is one of the main pharmacokinetic processes affected; it is influenced by patient-specific factors, such as comorbidities and genetics; therapeutic-specific factors, including drug characteristics and interactions; and disease-specific factors, like organ dysfunction. Moreover, organ support such as mechanical ventilation, renal replacement therapy, and extracorporeal membrane oxygenation may contribute to both inter- and intra-patient variability of drug pharmacokinetics. The combination of these competing factors makes it difficult to predict drug response in critically ill patients. Pharmacotherapy targeted to therapeutic goals and therapeutic drug monitoring is currently the best option for the safe care of the critically ill. The aim of this paper is to review the alterations in drug pharmacokinetics associated with critical illness and to summarise the available evidence.

Drug Utilization and Potential Drug-Drug Interactions within an Intensive Care Unit at a University Tertiary Care Hospital in Egypt

There are few reports on drug utilization and drug-drug interactions in Intensive Care Units (ICUs) in Egypt. A total of 94 patients participated in this retrospective observational study. Patient's medical records were used to collect demographics, medical history, admission and discharge dates and medications used. The mean ± SD of the Glasgow Coma Scale (GCS) scores was 9.9 ± 4.4 and the median length of stay was 7 days (range 1-47 days). The total number of prescribed medications ranged from 4-29 with a mean ± SD of 14.1 ± 5.5 medications per patient. The top three most prescribed categories belonged to (1) anti-infective agents (23.9%); (2) electrolyte, caloric and water balance agents (14.6%); and (3) blood formation, coagulation and thrombosis (11.3%). The proton pump inhibitor, esomeprazole, was the most frequently prescribed medication accounting for 6.5% of total prescriptions, followed by clindamycin and magnesium sulfate each accounting for 3.5% of total prescriptions. The potential Drug-Drug Interactions (pDDIs) showed a total of 968 pDDIs with a mean ± SD (range) of 10.2 ± 9.4 (0-43) pDDIs per patient: severe (contraindicated) (3), major (178), moderate (618) and minor (169). Overall, the drug utilization patterns in this study were consistent with ICU drug utilization from other countries in the region. The implementation of clinical decision support systems and the involvement of clinical pharmacists may help improve medication safety.

Contextualized Drug-Drug Interaction Management Improves Clinical Utility Compared With Basic Drug-Drug Interaction Management in Hospitalized Patients

Drug–drug interactions (DDIs) frequently trigger adverse drug events or reduced efficacy. Most DDI alerts, however, are overridden because of irrelevance for the specific patient. Basic DDI clinical decision support (CDS) systems offer limited possibilities for decreasing the number of irrelevant DDI alerts without missing relevant ones. Computerized decision tree rules were designed to context‐dependently suppress irrelevant DDI alerts. A crossover study was performed to compare the clinical utility of contextualized and basic DDI management in hospitalized patients. First, a basic DDI‐CDS system was used in clinical practice while contextualized DDI alerts were collected in the background. Next, this process was reversed. All medication orders (MOs) from hospitalized patients with at least one DDI alert were included. The following outcome measures were used to assess clinical utility: positive predictive value (PPV), negative predictive value (NPV), number of pharmacy interventions (PIs)/1,000 MOs, and the median time spent on DDI management/1,000 MOs. During the basic DDI management phase 1,919 MOs/day were included, triggering 220 DDI alerts/1,000 MOs; showing 57 basic DDI alerts/1,000 MOs to pharmacy staff; PPV was 2.8% with 1.6 PIs/1,000 MOs costing 37.2 minutes/1,000 MOs. No DDIs were missed by the contextualized CDS system (NPV 100%). During the contextualized DDI management phase 1,853 MOs/day were included, triggering 244 basic DDI alerts/1,000 MOs, showing 9.6 contextualized DDIs/1,000 MOs to pharmacy staff; PPV was 41.4% (P < 0.01), with 4.0 PIs/1,000 MOs (P < 0.01) and 13.7 minutes/1,000 MOs. The clinical utility of contextualized DDI management exceeds that of basic DDI management.

Drug-related problems identified during pharmaceutical care interventions in an intensive care unit at a tertiary university hospital

Introduction:

Drug-related problems could potentially worsen the clinical outcomes in critically ill patients. Critically ill patients are generally considered more vulnerable to harm from drug-related problems due to frequent medication-related events and complicated clinical courses. However, drug-related problems identified by on-ward clinical pharmacists in medical intensive care units in Thailand are not well reported. This study reports clinically relevant data with the description of identified problems, common causes of drug-related problems, and pharmacists’ interventions performed in real world, so that it may serve as an educational material for pharmacists who implement a pharmaceutical care and participate in medical intensive care units.

Methods:

A retrospective descriptive study was conducted at a tertiary university hospital in Bangkok, Thailand, from January 2015 to December 2020. The drug-related problems were categorized according to Cipolle et al.’s classification. The severity of drug-related problems in this study was rated by modifying the definition of The National Coordinating Council for Medication Error Reporting and Prevention Taxonomy of Medication Error to report harm from drug-related problem-related patient outcomes.

Results:

A total of 698 drug-related problems were detected in 374 critically ill patients. The prevalence of drug-related problems occurring in critically ill patients admitted to the medical intensive care unit was 73.9%. The most frequent drug-related problems were dosage too high (27.7%), ineffective drug (17.2%), need for additional drug therapy (15.3%), unnecessary drug therapy (14.6%), dosage too low (14.3%), adverse drug reaction (9.7%), and non-adherence (1.2%). The severity of drug-related problems in the medical intensive care unit was assessed as a drug-related problem with no harm (78.2%). Pharmacists’ interventions were advised according to drug-related problem identification to provide personalized pharmacotherapy optimization in critically ill patients.

Conclusion:

The most frequent drug-related problem identified during pharmaceutical care interventions in the medical intensive care unit at tertiary university hospital is dosage too high. The severity of drug-related problems is mostly determined as drug-related problems with no harm.

Heterogeneity in the identification of potential drug-drug interactions in the intensive care unit: A systematic review, critical appraisal, and reporting recommendations

Patients admitted to the intensive care unit (ICU) are frequently exposed to potential drug‐drug interactions (pDDIs). However, reported frequencies of pDDIs in the ICU vary widely between studies. This can be partly explained by significant variation in their methodological approach. Insight into methodological choices affecting pDDI frequency would allow for improved comparison and synthesis of reported pDDI frequencies. This study aimed to evaluate the association between methodological choices and pDDI frequency and formulate reporting recommendations for pDDI frequency studies in the ICU. The MEDLINE database was searched to identify papers reporting pDDI frequency in ICU patients. For each paper, the pDDI frequency and methodological choices such as pDDI definition and pDDI knowledge base were extracted, and the risk of bias was assessed. Each paper was categorized as reporting a low, medium, or high pDDI frequency. We sought associations between methodological choices and pDDI frequency group. Based on this comparison, reporting recommendations were formulated. Analysis of methodological choices showed significant heterogeneity between studies, and 65% of the studies had a medium to high risk of bias. High risk of bias, small sample size, and use of drug prescriptions instead of administrations were related to a higher pDDI frequency. The findings of this review may support researchers in designing a reliable methodology assessing pDDI frequency in ICU patients. The reporting recommendations may contribute to standardization, comparison, and synthesis of pDDI frequency studies, ultimately improving knowledge about pDDIs in and outside the ICU setting.

Clinically Relevant Interactions with Anti-Infectives on Intensive Care Units-A Multicenter Delphi Study

Patients in intensive care units (ICUs) are at high risk of drug–drug interactions (DDIs) due to polypharmacy. Little is known about type and frequency of DDIs within German ICUs. Clinical pharmacists’ interventions (PI) recorded in a national database (ADKA-DokuPIK) were filtered for ICU patients. Binary DDIs involving ≥1 anti-infective agent with >1 database entry were selected. A modified two-step Delphi process with a group of senior hospital pharmacists was employed to evaluate selected DDIs for clinical relevance by using a five-point scale and to develop guidance for clinical practice. In total, 16,173 PI were recorded, including 1836 (11%) DDIs in the ICU setting. Of the latter, 41% (756/1836) included ≥1 anti-infective agent, 32% (590/1836) were binary DDIs, and 25% (455/1836) were listed at least twice. This translates into 88 different DDIs, 74% (65/88) of which were rated as being clinically relevant by our expert panel. The majority of DDIs (76% [67/88]) included macrolides, antifungals, or fluoroquinolones. This percentage was even higher in DDIs being rated as clinically relevant by the experts (85% [55/65]). It is noted that an inter-professional discussion and approach is needed in the individual patient management of DDIs. The guidance developed might be a tool for decision support.

The Prevalence of Drug-Drug Interactions with Antiretroviral Therapy in Human Immunodeficiency Virus-Infected Patients in the Intensive Care Unit

Background: Persons living with human immunodeficiency virus (HIV) (PWH) on antiretroviral therapy (ART) are frequently admitted to the intensive care unit (ICU). Persons living with HIV on ART may be at higher risk for potential drug-drug interactions (pDDIs) due to polypharmacy in the ICU. We determined the prevalence of pDDI with ART in critically ill PWH. Objectives: The primary outcome was prevalence of pDDI between ART and ICU medications. Secondary outcomes included pDDI per ICU admission, pDDI severity, ICU, and hospital length of stay (LOS). Methods: A single-center, retrospective cohort evaluating PWH ≥ 18 years old admitted to the ICU for > 24 hours who received ART during ICU admission, between January 2013 and 2015 at a tertiary care hospital in the United States. Each ICU admission was counted as a separate encounter. Medication databases and chart review were used to identify pDDI. Results: We included 77 PWH encounters; mean age was 55 ± 9 years and 65% were male. We identified 208 pDDIs among 53/77 (68.8%), with a mean 4 ± 2 pDDI per ICU admission. Antipsychotics (20%), analgesics (20%), and anti-lipemics (11%) were the most common ICU medications with ART-related pDDI. Of the pDDI, 64% were major, 24% moderate, and 12% contraindicated. Median ICU and hospital LOS were 4 days (IQR: 3-5) and 11 days (IQR: 7-31), respectively. Conclusion: Most PWH had at least one pDDI during ICU admission. Collaborations among pharmacists, intensivists, and infectious disease/HIV specialists to develop effective, actionable strategies, such as electronic health record alerts, could reduce pDDIs for PWH on ART in the ICU.