Life‐threatening drug interactions: what the physician needs to know

KGRLFF: Detecting Drug-Drug Interactions Based on Knowledge Graph Representation Learning and Feature Fusion

Accurate prediction of drug-drug interactions (DDIs) plays an important role in improving the efficiency of drug development and ensuring the safety of combination therapy. Most existing models rely on a single source of information to predict DDIs, and few models can perform tasks on biomedical knowledge graphs. This paper proposes a new hybrid method, namely Knowledge Graph Representation Learning and Feature Fusion (KGRLFF), to fully exploit the information from the biomedical knowledge graph and molecular structure of drugs to better predict DDIs. KGRLFF first uses a Bidirectional Random Walk sampling method based on the PageRank algorithm (BRWP) to obtain higher-order neighborhood information of drugs in the knowledge graph, including neighboring nodes, semantic relations, and higher-order information associated with triple facts. Then, an embedded representation learning model named Knowledge Graph-based Cyclic Recursive Aggregation (KGCRA) is used to learn the embedded representations of drugs by recursively propagating and aggregating messages with drugs as both the source and destination. In addition, the model learns the molecular structures of the drugs to obtain the structured features. Finally, a Feature Representation Fusion Strategy (FRFS) was developed to integrate embedded representations and structured feature representations. Experimental results showed that KGRLFF is feasible for predicting potential DDIs.

Prevalence of Potential Drug Interactions With Direct-Acting Antivirals for COVID-19 Among Hospitalized Patients

PURPOSE

Clinicians consider polypharmacy, comorbidities, and other factors including the potential for drug-drug interactions (DDIs) when evaluating therapeutic options for specific clinical diagnoses. Contemporary treatment for coronavirus disease 2019 (COVID-19) includes direct-acting antivirals (DAAs). We sought to characterize patients' characteristics, comorbidities, and medications received during their hospitalization for COVID-19 and quantify potential DDIs that clinicians consider in selecting appropriate DAAs.

METHODS

Patients hospitalized with a primary diagnosis of COVID-19 between May 2020 and December 2022 from the PINC AI Healthcare Database were identified. Medications administered during the hospitalization with the potential to cause DDIs with nirmatrelvir/ritonavir, remdesivir, or molnupiravir (per the Emergency Use Authorization factsheet or package insert) were assessed. For DDIs with nirmatrelvir/ritonavir, medications are categorized as "Contraindicated," "Avoid Concomitant Use," or "Other DDIs" (includes recommendation for dose modification or clinical and laboratory monitoring). For remdesivir, coadministration with chloroquine phosphate and hydroxychloroquine sulfate was not recommended. For molnupiravir, no drugs are listed as having potential DDIs. In a subset of patients, a multivariable logistic regression model was used to examine the association between documented patient/hospital characteristics and the likelihood of being "Contraindicated" to receive nirmatrelvir/ritonavir.

FINDINGS

Of the 788,238 patients hospitalized for COVID-19 in 920 hospitals, 53% were ≥ 65 years old, and 31% had Charlson Comorbidity Index (CCI) ≥ 3. During the study period, about half of the patients received medications categorized as "Contraindicated" (11%) and/or "Avoid Concomitant Use" (41%) with nirmatrelvir/ritonavir. The frequency of administered drugs was higher in those aged ≥ 65 years (68%), CCI ≥ 3 (78%), with high-risk underlying conditions (55%). About 1% of patients received medications that were not recommended to be coadmistered with remdesivir. Among a subset of patients hospitalized for COVID-19 in 2022, those who were older, had higher CCI, high-risk underlying conditions, severe hepatic impairment, Medicare insurance, and hospitalized in larger hospitals were significantly more likely to be categorized as "Contraindicated" when considering nirmatrelvir/ritonavir as a therapeutic option to manage COVID-19.

IMPLICATIONS

A significant proportion of patients hospitalized for COVID-19 receive medications for other conditions that have the potential to result in DDIs with DAAs; most predominantly with nirmatrelvir/ritonavir, a strong CYP3A enzyme inhibitor, fewer with remdesivir, and none with molnupiravir. Higher age and comorbidity burden were significantly associated with a higher likelihood of receiving medications that are "Contraindicated" with nirmatrelvir/ritonavir. In the evolving COVID-19 era, these findings provide insights into patients hospitalized for COVID-19, and the polypharmacy evaluations that clinicians may encounter when selecting among DAAs to manage COVID-19.

Effect of P. corylifolia on the pharmacokinetic profile of tofacitinib and the underlying mechanism

This work aimed to explore the mechanisms underlying the interaction of the active furanocoumarins in P. corylifolia on tofacitinib both in vivo and in vitro. The concentration of tofacitinib and its metabolite M8 was determined using UPLC-MS/MS. The peak area ratio of M8 to tofacitinib was calculated to compare the inhibitory ability of furanocoumarin contained in the traditional Chinese medicine P. corylifolia in rat liver microsomes (RLMs), human liver microsomes (HLMs) and recombinant human CYP3A4 (rCYP3A4). We found that bergapten and isopsoralen exhibited more significant inhibitory activity in RLMs than other furanocoumarins. Bergapten and isopsoralen were selected to investigate tofacitinib drug interactions in vitro and in vivo. Thirty rats were randomly allocated into 5 groups (n = 6): control (0.5% CMC-Na), low-dose bergapten (20 mg/kg), high-dose bergapten (50 mg/kg), low-dose isopsoralen (20 mg/kg) and ketoconazole. 10 mg/kg of tofacitinib was orally intervented to each rat and the concentration level of tofacitinib in the rats were determined by UPLC-MS/MS. More imporrantly, the results showed that bergapten and isopsoralen significantly inhibited the metabolism of tofacitinib metabolism. The AUC(0-t), AUC(0-∞), MRT(0-t), MRT(0-∞) and Cmax of tofacitinib increased in varying degrees compared with the control group (all p < 0.05), but CLz/F decreased in varying degrees (p < 0.05) in the different dose bergapten group and isopsoralen group. Bergapten, isopsoralen and tofacitinib exhibit similar binding capacities with CYP3A4 by AutoDock 4.2 software, confirming that they compete for tofacitinib metabolism. P. corylifolia may considerably impact the metabolism of tofacitinib, which can provide essential information for the accurate therapeutic application of tofacitinib.

Drug-drug interaction prediction: databases, web servers and computational models

In clinical treatment, two or more drugs (i.e. drug combination) are simultaneously or successively used for therapy with the purpose of primarily enhancing the therapeutic efficacy or reducing drug side effects. However, inappropriate drug combination may not only fail to improve efficacy, but even lead to adverse reactions. Therefore, according to the basic principle of improving the efficacy and/or reducing adverse reactions, we should study drug-drug interactions (DDIs) comprehensively and thoroughly so as to reasonably use drug combination. In this review, we first introduced the basic conception and classification of DDIs. Further, some important publicly available databases and web servers about experimentally verified or predicted DDIs were briefly described. As an effective auxiliary tool, computational models for predicting DDIs can not only save the cost of biological experiments, but also provide relevant guidance for combination therapy to some extent. Therefore, we summarized three types of prediction models (including traditional machine learning-based models, deep learning-based models and score function-based models) proposed during recent years and discussed the advantages as well as limitations of them. Besides, we pointed out the problems that need to be solved in the future research of DDIs prediction and provided corresponding suggestions.

Potential drug-drug interactions in outpatients with depression of a psychiatry department

Objective

This study aims to explore the prevalence and associated risk factors for potential drug-drug interactions (pDDIs) in prescriptions among outpatients with depression, and report the widespread relevant drug interactions.

Methods

The cross-sectional retrospective study was conducted on outpatients in a psychiatric hospital. We included prescriptions of outpatients with a principal diagnosis of depression from April 1st to June 30th in 2021. The patients were ≥ 18 years old and treated with two or more drugs including at least one psychotropic drug. pDDIs were detected and identified mainly using Medscape's drug interactions checker. Gender, the number of concomitant drugs, age and diagnosis were analysed as potential risk factors for the occurrence of pDDIs by logistic regression.

Results

A total of 13,617 prescriptions were included in the present analysis, and 4222 prescriptions (31.0%) were at risk of 8557 pDDIs. The risk of pDDIs in patients who were prescribed 4-6 drugs (OR: 3.49, 95% CI: 3.11-3.91, p < 0.001) or 7 or more drugs simultaneously (OR: 7.86, 95% CI: 1.58-39.04, p < 0.05) increased compared with patients prescribed 2-3 drugs. Patients with recurrent depressive disorders (OR: 1.18, 95% CI: 1.02-1.36, p < 0.05) had an increased risk of pDDIs compared with patients with depressive episodes. In terms of severity of pDDIs identified by Medscape's drug interactions checker, 0.7%, 16.4%, 77.5% and 5.4% of pDDIs were classified as contraindicated, serious, monitor closely and minor, respectively. The most common pDDI was escitalopram + quetiapine (374 prescriptions), which was classified as serious and monitor closely due to different mechanisms of interaction. Increased central nervous system (CNS)-depressant effect was the most frequent potential clinical adverse outcome of the identified pDDIs.

Conclusions

pDDIs in outpatients with depression were prevalent in this retrospective study. The number of concomitant drugs and severity of the disease were important risk factors for pDDIs. The pDDIs of the category monitor closely were the most common, and the CNS-depressant effect was the most frequent potential clinical adverse outcome.

Understanding and managing common drug interactions

Drug interactions are common in clinical practice and have a direct effect on patients' morbidity and mortality. However, with the appropriate knowledge they can be avoided. The administration of drugs is an essential nursing task and an increasing number of specialist nurses are also independent prescribers. This article details some of the common patterns of drug-drug interactions and aims to support nurses in optimising patients' medicines use.

The Challenge and Importance of Integrating Drug-Nutrient-Genome Interactions in Personalized Cardiovascular Healthcare

Despite the rich armamentarium of available drugs against different forms of cardiovascular disease (CVD), major challenges persist in their safe and effective use. These include high rates of adverse drug reactions, increased heterogeneity in patient responses, suboptimal drug efficacy, and in some cases limited compliance. Dietary elements (including food, beverages, and supplements) can modulate drug absorption, distribution, metabolism, excretion, and action, with significant implications for drug efficacy and safety. Genetic variation can further modulate the response to diet, to a drug, and to the interaction of the two. These interactions represent a largely unexplored territory that holds considerable promise in the field of personalized medicine in CVD. Herein, we highlight examples of clinically relevant drug–nutrient–genome interactions, map the challenges faced to date, and discuss their future perspectives in personalized cardiovascular healthcare in light of the rapid technological advances.

Lessons of the month 2: A case of inappropriate drug-drug interaction in kidney transplant

Carbamazepine remains a first-line antiepileptic medication for the treatment of partial seizures. Despite its widespread use, carbamazepine has significant neurotoxicity and hypersensitivity reactions. We report a case of a patient post-kidney transplant who was on regular carbamazepine for childhood epilepsy and developed nystagmus, diplopia and a broad-base gait after receiving diltiazem. Understanding of the interaction between diltiazem and carbamazepine is necessary to prevent the neurotoxic effects.

Predictors of drug-drug interactions of medications prescribed to patients admitted due to suicidal behavior

INTRODUCTION

Drug-drug interactions among people with suicidal behavior is a challenging topic, considering the harm it poses for patients already vulnerable and the lack of literature on the thematic. This aspect must not be neglected in research and clinical practice, and thus requires thorough investigation.

OBJECTIVE

to investigate predictors of drug-drug interaction of prescribed drugs and the prescription of two or more drugs for people admitted due to suicidal behavior in a psychiatric emergency department (short-stay hospital ward).

METHOD

A cross-sectional study with retrospective approach, carried out in a Brazilian psychiatric emergency unit in 2015. Data about first and last medical prescriptions were collected from 127 patients' files. Descriptive statistics and the Zero Adjusted Logarithmic Distribution (ZALG) model were adopted, with the significance level α = 0.05.

RESULTS

Potential drug-drug interactions were found in most of the first and last prescriptions. The sample majority were female, with previous suicide attempts, being discharged from the hospital with three drugs (or more) prescribed, and without referral to any health service. Age and comorbidities were predictors of more drug prescriptions and the amount of prescribed drugs was the most important predictor of drug-drug interactions (quantity and severity).

CONCLUSIONS

the variables associated with drug-drug interactions and prescription of two or more drugs among people with suicidal behavior needs to be investigated in different contexts and addressed in interventions with the aim to promote patient safety.

The Future of Analytical and Interpretative Toxicology: Where are We Going and How Do We Get There?

(Forensic) toxicology has faced many challenges, both analytically and interpretatively, especially in relation to an increase in potential drugs of interest. Analytical toxicology and its application to medicine and forensic science have progressed rapidly within the past centuries. Technological innovations have enabled detection of more substances with increasing sensitivity in a variety of matrices. Our understanding of the effects (both intended and unintended) have also increased along with determination and degree of toxicity. However, it is clear there is even more to understand and consider. The analytical focus has been on typical matrices such as blood and urine but other matrices could further increase our understanding, especially in postmortem (PM) situations. Within this context, the role of PM changes and potential redistribution of drugs requires further research and identification of markers of its occurrence and extent. Whilst instrumentation has improved, in the future, nanotechnology may play a role in selective and sensitive analysis as well as bioassays. Toxicologists often only have an advisory impact on pre-analytical and pre-interpretative considerations. The collection of appropriate samples at the right time in an appropriate way as well as obtaining sufficient circumstance background is paramount in ensuring an effective analytical strategy to provide useful results that can be interpreted within context. Nevertheless, key interpretative considerations such as pharmacogenomics and drug-drug interactions as well as determination of tolerance remain and in the future, analytical confirmation of an individual's metabolic profile may support a personalized medicine and judicial approach. This should be supported by the compilation and appropriate application of drug data pursuant to the situation. Specifically, in PM circumstances, data pertaining to where a drug was not/may have been/was contributory will be beneficial with associated pathological considerations. This article describes the challenges faced within toxicology and discusses progress to a future where they are being addressed.

Investigating Potential Drug-Drug Interactions from Greek e-Prescription Data

BACKGROUND

The prevalence of potential drug-drug interactions (pDDIs) is indicative of the prevalence of actual drug-drug interactions and prescription quality. However, they are significantly understudied in Greece.

OBJECTIVE

To determine the prevalence of pDDIs among outpatients and identify factors associated with their occurrence.

METHODS

Anonymous e-prescription data between 2012 and 2017 were obtained from community pharmacies in Thessaloniki, Greece. Patients taking more than one medication for at least three months were included. pDDIs were identified and categorized depending on their clinical significance using Drug Interactions Checker. Crude and adjusted odds ratios (ORs) with accompanying 95% confidence intervals (CIs) of risk factors of pDDIs occurrence were identified using multivariable logistic regression.

RESULTS

During the study period, 6,000 anonymous e-prescriptions (1,000 per year) satisfying the inclusion criteria, were collected. The overall prevalence of major pDDIs was 17.4% (63.0% for moderate pDDIs). The most common major pDDIs were between amlodipine and simvastatin (22.8% of major interactions) followed by clopidogrel and omeprazole (6.4% of major interactions). Polypharmacy (≥5 concomitantly received medications) was associated with an increased risk of major pDDIs (adjusted OR, 5.72; 95% CI, 4.87-6.72); no associations were observed regarding age, sex and number of prescribing physicians.

CONCLUSION

The prevalence of pDDIs in this study was higher than previously reported in other European countries, with polypharmacy being a potential risk factor. Those results argue for a need for improvement in the area of prescribing in Greece.

Advancement in predicting interactions between drugs used to treat psoriasis and its comorbidities by integrating molecular and clinical resources

OBJECTIVE

Drug-drug interactions (DDIs) can result in adverse and potentially life-threatening health consequences; however, it is challenging to predict potential DDIs in advance. We introduce a new computational approach to comprehensively assess the drug pairs which may be involved in specific DDI types by combining information from large-scale gene expression (984 transcriptomic datasets), molecular structure (2159 drugs), and medical claims (150 million patients).

MATERIALS AND METHODS

Features were integrated using ensemble machine learning techniques, and we evaluated the DDIs predicted with a large hospital-based medical records dataset. Our pipeline integrates information from >30 different resources, including >10 000 drugs and >1.7 million drug-gene pairs. We applied our technique to predict interactions between 37 611 drug pairs used to treat psoriasis and its comorbidities.

RESULTS

Our approach achieves >0.9 area under the receiver operator curve (AUROC) for differentiating 11 861 known DDIs from 25 750 non-DDI drug pairs. Significantly, we demonstrate that the novel DDIs we predict can be confirmed through independent data sources and supported using clinical medical records.

CONCLUSIONS

By applying machine learning and taking advantage of molecular, genomic, and health record data, we are able to accurately predict potential new DDIs that can have an impact on public health.

A Review of the Metabolism and Potential Drug-drug Interactions With Addictive Drugs

People who use drugs (PWUD) are at increased risk for drug-related harms such as overdose. Additionally, they are also at increased risk of secondary harms from bacterial and other infections such as hepatitis B, hepatitis C, and Human Immunodeficiency Virus. These secondary harms, along with other medical conditions, typically require treatment with prescription medications. When considering treatment options, drug-drug interactions (DDIs) must be considered, unfortunately these interactions are often overlooked with addictive drugs. Although DDIs in PWUD have been reviewed for certain drug classes and specific drugs of abuse, no comprehensive list could be found. The objective of this article is to compile a list of potential DDIs between prescription drugs and addictive drugs to create a list allowing prescribers to make more informed decisions when prescribing a medication to PWUD.

Menstrual Dysfunction and Treatment Among Adolescents With Congenital Heart Disease

STUDY OBJECTIVE

This study describes menstrual dysfunction and treatment among adolescent and young adult (AYA) females with congenital heart disease (CHD).

DESIGN

Data collected from a 1-time survey completed by AYA females (and mothers if AYA unable).

SETTING

Participants were recruited from pediatric cardiology clinics.

PARTICIPANTS

Female AYA with CHD, aged 14-21 years (N = 114).

INTERVENTIONS

None.

MAIN OUTCOME MEASURES

The questionnaire assessed sexual and reproductive health (SRH) concerns, behaviors, and management. Outcome measures were self-reported menstrual complaints, use of over-the-counter (OTC) pain relief medications for dysmenorrhea, reported visits with a clinician for a menstrual problem, and reported use of hormones for menstrual problems or birth control.

RESULTS

Mean age was 17.0 years (SD = 2.2). The majority of participants (83%) reported 1 or more menstrual complaints (67.5% cramping, 42.1% irregular menses, 46.5% heavy periods), and 88% reported any history of taking OTC medications for pain relief. Increased menstrual complaints were not associated with level of cardiac complexity, reported transplantation, or reported use of hormonal contraception. However, 32% of participants reported use of hormonal contraception for menstrual dysfunction. Combined oral contraceptive pills (COCs) were the most common; 2 of these women carried contraindications to estrogen.

CONCLUSIONS

A large majority of AYA females with CHD reported menstrual dysfunction. Use of OTC medication for menstrual pain and inappropriate use of estrogen creates concerns that menstrual disorders may be unaddressed or addressed inappropriately. Thus, gynecological needs of adolescents with CHD may need to be specifically targeted by providers who feel comfortable with this population and their complex needs.

A Prospective Analysis of Potential and Observed Drug-Drug Interactions, Adverse Events and its Associated Risk Factors in Hospitalized Cardiology Patients in Benin

BACKGROUND & AIMS

The objective is to ascertain the pattern of potential drug-drug interactions (pDDIs) and record any observed DDIs and adverse events (AEs) in hospitalized Beninese cardiology patients from Sub-Saharan Africa and analyze all risk factors associated with DDIs and AEs.

METHODS

It was a prospective study in which data including AEs were assessed from medical files and interview of patients and their relatives. Patients who were treated with more than two drugs and who remained in the hospital for at least 48 hours were included. A computerized database system Pharma IAM- VIDAL version 2011 was used to identify the pattern for potential DDIs.

RESULTS

156 patients were included in this study. The prevalence of potential DDIs was estimated at 93 % (145/156). Forty (5.1%) among 804 potential DDIs identified were observed clinically. The observed DDIs were attributable to low blood pressure (27.5%), hyponatremia (22.5%), hemorrhage (20.0%), hyperkalemia (17.5%) and nephrotoxicity (7.5%). The combination of spironolactone and furosemide resulted in hyponatremia while the combination of enoxaparin and potassium resulted in hyperkalemia. ACE inhibitor (or ARAII) in combination with furosemide resulted in the nephrotoxicity cases observed. Enoxaparin, Acetyl salicylic acid, Acenocoumarol and Clopidogrel were decreasingly involved in the pairs of drugs responsible for observed hemorrhages. 29 patients out of 156 (18.6%) had at least one AE. AEs were mainly (34.2%) of metabolic type. Severe AEs, which represented 18.4% was mostly from nephrotoxicity and metabolic disorders. More than 14 active substances multiplied the risk factor for AEs occurrence by 42, while more than 14 days hospitalization increased this risk by 42.

CONCLUSION

This study highlights the need to optimize treatments by strictly regulating blood pressure, serum sodium and potassium levels, coagulation parameters and looking for clinical signs of hemorrhage. Physician should be aware of certain drug associations that may carry a risk of severe adverse events.

Stimulatory effect on the transport mediated by organic anion transporting polypeptide 2B1

Drug-drug interaction (DDI) is one of causes of adverse drug events and can result in life-threatening consequences. Organic anion-transporting polypeptide (OATP) 2B1 is a major uptake transporter in the intestine and contributes to transport various clinically used therapeutic agents. The intestine has a high risk of DDI, because it has a special propensity to be exposed to a high concentration of drugs. Thus, understanding drug interaction mediated by OATP2B1 in the absorption process is important for the prevention of adverse drug events, including decrease in the therapeutic effect of co-administered drugs. Acute drug interaction occurs through the direct inhibitory effect on transporters, including OATP2B1. Moreover, some compounds such as clinically used drugs and food components have an acute stimulatory effect on transport of co-administered drugs by OATP2B1. This review summarizes the acute stimulatory effect on the transport mediated by OATP2B1 and discusses the mechanisms of the acute stimulatory effects of compounds. There are two types of acute stimulatory effects, substrate-independent and -dependent interactions on OATP2B1 function. The facilitating translocation of OATP2B1 to the plasma membrane is one of causes for the substrate-independent acute stimulatory effect. On the contrary, the substrate-dependent effect is based on the direct binding to the substrate-binding site or allosteric progesterone-binding site of OATP2B1.

Drug interaction resources: mind the gaps

Drug interactions can lead to significant toxicity or loss of clinical effect. The risks increase with the number of drugs the patient takes General and specialised drug interaction resources are available. Access to up-to-date electronic resources is encouraged There are gaps in the information on interactions for new drugs, those with complicated metabolism and drugs with limited use. It may be necessary to use multiple resources to find the information When assessing information about interactions, clinicians should evaluate the relevance for each patient. In high-risk situations, expert advice can be valuable Clinicians should report new or unusual drug interactions to the Therapeutic Goods Administration

Hyperkinetic reaction to dihydrocodeine

A young man was using dihydrocodeine analgesia for ear pain having had suppurative otitis media. He attended the emergency department with restlessness and twitching movements in his arms and legs. He had fever with otherwise normal vital signs. He had no signs of cerebellar pathology. Investigations were normal. The working diagnosis was of hyperkinetic reaction to dihydrocodeine. Symptoms resolved within 48 hours of withdrawing the drug. Serotonin toxicity is a rare side effect of dihydrocodeine. There is a theoretical basis for increased side effects when taken with cannabidiol-based substances.

Antifungal drugs: What brings the future?

The high burden and growing prevalence of invasive fungal infections (IFIs), the toxicity and interactions associated with current antifungal drugs, as well as the increasing resistance, ask for the development of new antifungal drugs, preferably with a novel mode of action. Also, the availability of oral or once-weekly alternatives would enable ambulatory treatment resulting in an improved patient's comfort and therapy adherence. However, only one new azole and two new posaconazole-formulations were marketed over the last decade. This review focuses on the antifungal drugs in the pipeline undergoing clinical evaluation. First, the newest azole, isavuconazole, with its improved safety profile and reduction in DDIs, will be discussed. Moreover, there are two glucan synthase inhibitors (GSIs) in the antifungal pipeline: rezafungin (CD101), a long-acting echinocandin with an improved stability that enables once weekly administration, and SCY-078, an orally available GSI with efficacy against azole- and echinocandin resistant isolates. A new oral formulation of amphotericin B will also be presented. Moreover, the first representative of a new antifungal class, the orotomides, with a broad spectrum and no cross-resistance with current antifungal classes, will be discussed. Finally, an overview of other antifungals that are still in earlier clinical development phases, is provided.

Alteration of drug-metabolizing enzyme activity in palliative care patients: Microdosed assessment of cytochrome P450 3A

BACKGROUND

Cytochrome P450 3A is the most relevant drug-metabolizing enzyme in humans as it is involved in the elimination of 50% of marketed drugs. Nothing is known about the activity of cytochrome P450 3A in palliative care patients who have complicated symptoms often associated with a terminal illness.

AIM

In order to improve drug dosing in end-of-life care and to avoid drug interactions, cytochrome P450 3A activity was determined in patients of a palliative care unit under real-life clinical conditions.

DESIGN

As midazolam is an established marker substance for cytochrome P450 3A activity, this single-arm prospective trial was designed to obtain a 4-h pharmacokinetic profile of midazolam after oral administration of a 10-µg dose from each enrolled patient. Plasma concentrations of midazolam and its primary metabolite 1'-hydroxy-midazolam were quantified by mass spectrometry techniques. Cytochrome P450 3A activity was calculated as partial metabolic clearance from a limited sampling area under the curve. All other drugs taken by the participating patients were considered, as well as recent blood test results and patients' diagnoses. The trial was registered at German Clinical Trials Register ( www.drks.de ): DRKS00011753.

SETTING/PARTICIPANTS

The trial was carried out at a university palliative care unit under real-life clinical conditions. Every patient admitted to the ward was screened for possible participation, independent of the individual performance status.

RESULTS

Partial metabolic clearance of midazolam in palliative care patients was 31.7 ± 32.1 L/h. This was a highly significant 40% reduction (p < 0.0001) in comparison with the cytochrome P450 3A activity of healthy subjects.

CONCLUSION

Dosing of cytochrome P450 3A substrate drugs (e.g. macrolide antibiotics, benzodiazepines, calcium channel blockers) needs to be adjusted in palliative care patients; otherwise, escalation of debilitating symptoms due to drug interactions might occur.

Potential drug interactions in drug therapy prescribed for older adults at hospital discharge: cross-sectional study

BACKGROUND

Older adults with a range of comorbidities are often prescribed multiple medications, which favors drug interactions.

OBJECTIVES

To establish the frequency of potential drug interactions in prescriptions at hospital discharge among older adults and to identify the associated factors.

DESIGN AND SETTING

Cross-sectional study conducted in a public hospital.

METHODS

An initial face-to-face interview, data collection from the electronic medical records (covering sociodemographic, clinical, functional and drug therapy-related variables) and telephone follow-up after discharge were conducted to confirm the medication prescribed at discharge. Drug interactions were identified through the Micromedex DrugReax software, along with interactions that should be avoided among the elderly, as per the 2015 American Geriatric Society/Beers criteria. Multivariable logistic regression was performed.

RESULTS

Potential for drug interactions was identified in the discharge drug therapy of 67.8% of the 255 older adults evaluated (n = 172), and 54.5% (n = 145) of the drug interactions were major. Among the drug interactions that should be avoided among older adults, those that increase the risk of falls were the most frequent. The drug interactions thus identified were independently associated with polypharmacy (odds ratio, OR = 12.62; 95% confidence interval, CI 6.25-25.50; P = 0.00), diabetes mellitus (OR = 2.16; 95% CI 1.05-4.44; P = 0.04), hypothyroidism (OR = 7.29; 95% CI 2.03-26.10; P = 0.00), chronic kidney disease (OR = 3.41; 95% CI 1.09-10.64; P = 0.03) and hospitalization in geriatric units (OR = 0.45; 95% CI 0.22-0.89; P = 0.02).

CONCLUSION

The frequency of potential drug interactions in drug therapy prescribed at discharge for these older adults was high. Polypharmacy, diabetes mellitus, hypothyroidism and chronic kidney disease were positively associated with occurrences of drug interactions, while hospitalization in geriatric units showed an inverse association.

Restarting antidepressant and antipsychotic medication after intentional overdoses: need for evidence-based guidance

Intentional drug overdoses with antidepressant and antipsychotic medications are an increasingly common problem. Currently, there is little guidance with regard to reintroduction of these medications after intentional overdoses. We have used published toxicological and pharmacokinetic data to obtain factors which control the recovery from overdoses. From such data, we have proposed guidance regarding their reintroduction, provided there are no adverse effects or contraindications. Tentatively, we suggest that when adverse effects from the overdose are lost, treatment could recommence after a further mean half-life of elimination. Most antidepressant and antipsychotic drugs are metabolized by cytochrome P450 enzymes and, where cytochrome P450 inhibitors are co-ingested, serial plasma concentrations should optimally be obtained in order to assess a suitable time for reintroduction of the psychoactive drugs. We hope the proposals presented will stimulate research and discussion that lead to better guidance for clinicians concerning reintroduction of psychoactive medication after intentional overdose.

Evaluation of Clinical Relevance of Drug-Drug Interaction Alerts Prior to Implementation

INTRODUCTION

Drug-drug interaction (DDI) alerts are often implemented in the hospital computerized provider order entry (CPOE) systems with limited evaluation. This increases the risk of prescribers experiencing too many irrelevant alerts, resulting in alert fatigue. In this study, we aimed to evaluate clinical relevance of alerts prior to implementation in CPOE using two common approaches: compendia and expert panel review.

METHODS

After generating a list of hypothetical DDI alerts, that is, alerts that would have been triggered if DDI alerts were operational in the CPOE, we calculated the agreement between multiple drug interaction compendia with regards to the severity of these alerts. A subset of DDI alerts (n = 13), with associated patient information, were presented to an expert panel to reach a consensus on whether each alert should be included in the CPOE.

RESULTS

There was poor agreement between compendia in their classifications of DDI severity (Krippendorff's α: 0.03; 95% confidence interval: -0.07 to 0.14). Only 10% of DDI alerts were classed as severe by all compendia. On the other hand, the panel reached consensus on 12 of the 13 alerts that were presented to them regarding whether they should be included in the CPOE.

CONCLUSION

Using an expert panel and allowing them to discuss their views openly likely resulted in high agreement on what alerts should be included in a CPOE system. Presenting alerts in the context of patient cases allowed panelists to identify the conditions under which alerts were clinically relevant. The poor agreement between compendia suggests that this methodology may not be ideal for the evaluation of DDI alerts. Performing preimplementation review of DDI alerts before they are enabled provides an opportunity to minimize the risk of alert fatigue before prescribers are exposed to false-positive alerts.

Characterization of drug-drug interactions in patients whose substance intake was objectively identified by detection in urine

BACKGROUND

Identification of drug-drug interactions (DDIs) typically relies on patient medication lists which are prone to inaccuracies. This study describes use of a mass spectrometry test to detect recently ingested substances in urine with subsequent identification of DDIs.

RESEARCH DESIGN AND METHODS

This was a retrospective analysis of the prevalence of DDIs identified in patients with chronic pain, addiction and/or behavioral health conditions in the U.S. Relationships between patient demographics, polypharmacy and the occurrence of DDIs were also described.

RESULTS

Of 15,004 patients, 2964 (20%) had a DDI identified. There was a positive association between the number of substances detected in urine and the number of interactions identified (r = 0.5033, p-value = 0.0001). Of patients with polypharmacy, 15.6% had contraindicated or severe interactions identified compared to only 3.2% of those without polypharmacy. For polypharmacy patients, the youngest population studied had a much higher likelihood of having one or more DDIs identified compared to the other age groups (p-value = 0.0002).

CONCLUSIONS

By utilizing a mass spectrometry test to objectively detect recently ingested substances followed by identification of DDIs, healthcare providers may be able to better characterize the true incidence of DDIs. Study findings may not be generalizable to healthcare populations outside of pain management, addiction treatment, and behavioral health.