Evaluation of Potential Drug-Drug Interactions among Patients of the Nephrology and Kidney Transplant Wards of a Major Teaching Hospital in Iran

Aims: This study was aimed to find the prevalence of potential DDIs in patients and identify factors associated with these interactions. Study design: All patients' medication regimens were screened for potential DDIs through Lexi-Interact® Online application. Place and Duration of Study: This study was conducted for five months in 2017-2018 at the nephrology and kidney transplant ward of Razi hospital, Rasht, Iran. Methodology: Each potential DDI was characterized based on severity, onset, mechanism, risk rating and reliability rating. The patient's comorbidity was assessed with the Charlson comorbidity index. The quality of patients' life was assessed with the Kidney Disease Quality of Life Instrument-SF36TM questionnaire. Results: The study included 191 patients (109 [57.07%] males and 82 [42.93%] females) with a mean age of 58.09 ± 17.76 years. The analysis revealed that 29.4 % of potential DDIs had good and 13.5% had excellent evidence. There was a statistically significant association among the number of prescribed medications (polypharmacy), hospital ward, age, Body Mass Index, education, history of drug addiction, length of hospitalization, dyslipidemia, and hypothyroidism. Conclusion Potential DDIs are common in patients of the nephrology and kidney transplant wards, so proper patient monitoring is essential for minimizing and preventing potential adverse outcomes of DDIs.

Appraisal and discernment of prevalent drug-drug interactions in patients with psychiatric disorders

Background: Drug-drug interactions (DDIs) contribute majorly to hospital admissions, treatment failures, avoidable medical complications and subsequent healthcare costs. Thus, we employ a mechanistic approach to prospectively investigate the incidence of potential DDIs in the psychiatric patients in a clinical setting.Methods: In this prospective, observational, multi centred study conducted for a span of 6 months, psychiatric inpatients (≥18 years) prescribed with 2 or more medications daily for any medical illness were included. The secured prescriptions of the inpatients selected in accordance to the inclusion criteria were then assessed for DDIs using Micromedex(TM) as a standard.Results: Of the total 400 enrolled participants, 383 (95%) of them showed at least one pDDI regardless of the severity. An average of 7.33 interactions per patient was also deduced. A high prevalence of pDDIs totalling to 2900 was recorded in our study with an average of 7.33 interactions per patient. Most of the interactions were of major (56.52%) and moderate severity (39.07) followed by contraindicated (2.55) and minor (1.83). Cardiovascular system (41.77%) had the highest potential to be affected due to the pDDIs identified. Trihexyphenidyl, haloperidol, promethazine, amisulpride, risperidone, divalproex, trifluoperazine, olanzapine and clozapine where among the most commonly encountered drugs in these interactions.Conclusions: A high prevalence of pDDIs totalling to 2900 was recorded in our study with an average of 7.33 interactions per patient. A significant association of the pDDIs with variables such as age, gender, diagnosis and total number of drugs used was identified. More studies are required to explore the overall pattern of DDIs in psychiatric patients along with their levels and correlation with different risk factors. Careful monitoring and documentation are necessary to prevent further complications thereby improving the therapeutic outcome.

Drug–Drug Interactions in Italian Patients with Chronic Hepatitis C Treated with Pangenotypic Direct Acting Agents: Insights from a Real-World Study

This Italian observational real-world study aims to assess in chronic hepatitis C virus (HCV) patients treated with pangenotypic direct acting agents (pDAAs) glecaprevir/pibrentasvir (GLE/PIB) or sofosbuvir/velpatasvir (SOF/VEL) the potential drug–drug interactions (DDIs) with concomitant medications prescribed, with a focus on cardiovascular and system nervous (CNS) co-medications. Data were collected from administrative databases covering 6.9 million health-assisted individuals. All patients prescribed SOF/VEL or GLE/PIB between 11/2017 and 12/2018 were included. Patients were analyzed while on DAA. DDIs were identified according to the Liverpool University tool. Overall, 3,181 HCV patients were included: 1619 in the GLE/PIB cohort and 1,562 in the SOF/VEL cohort. SOF/VEL patients were generally older than GLE/PIB ones (mean age 58.4 vs. 53.1, p < 0.001) and had more cardiovascular and CNS comorbidities (58% vs. 42%, p < 0.001 and 33% vs. 28%, p = 0.002, respectively). Contraindications due to DDIs in the GLE/PIB cohort affected 9.3% and 3.2% of patients before and on DAA, respectively, while the percentages in the SOF/VEL cohort were 3.2% before and 0.4% after pDAAs initiation. Among GLE/PIB patients, 2.7% had cardiovascular drugs (all statins) contraindicated while on DAA. The potential DDIs between cardiovascular drugs and SOF/VEL were mainly with statins (5%). SOF/VEL was prescribed in patients with older age and with more cardiovascular and CNS comorbidities. Despite this, a proportion of contraindicated drugs lower than that of GLE/PIB was registered.

Evaluation of drug-drug interactions in hospitalized patients on medications for OUD

Introduction Medications used to treat OUD have common metabolic pathways and pharmacodynamic properties that can lead to drug-drug interactions (DDIs) that may go unnoticed in the inpatient setting. The purpose of this study was to identify the frequency of DDIs between medications prescribed for OUD and commonly used inpatient medications. Methods This was a retrospective review of orders for buprenorphine, buprenorphine-naloxone, and methadone to identify potential DDIs. Adult inpatients with an order for one of these medications for OUD were included. Medication regimens were evaluated throughout the inpatient stay and on day of discharge for DDIs. DDIs were classified by severity and type of interaction (increased risk of QT prolongation, additive CNS effects/respiratory depression, and opioid withdrawal). The primary endpoint was the number of potential DDIs. Other endpoints included number of each classification/severity of DDI, duration of therapy of interacting medications, and modifications made to OUD medications because of DDIs. Results A total of 102 patients were included, with 215 inpatient interactions and 83 interactions at discharge identified. While inpatient, 85% of patients were on an interacting medication, and 46% of patients were on an interacting medication at discharge. The most common classification of DDI was additive CNS effects/respiratory depression (68.8% inpatient, 50.6% discharge), followed by QT prolongation (24.2% inpatient, 45.8% discharge). The majority of DDIs were classified as requiring close monitoring rather than contraindicated. Discussion There are opportunities to optimize the prescribing practices surrounding OUD medications in both the inpatient setting and at discharge to ensure patient safety.

Pharmacotherapy Profiles in People with Opioid Use Disorders: Considerations for Relevant Drug–Drug Interactions with Antiviral Treatments for Hepatitis C

People who inject drugs (PWID) are often affected by physical and psychological diseases and prone to co-medication. In Germany, about 50% of PWID are on opioid substitution therapy (OST). Comprehensive data on pharmacotherapy in these patients may help to select antiviral therapy against hepatitis C virus (HCV) infections and avoid drug–drug interactions (DDIs). We compared co-medication profiles based on statutory health insurance prescriptions (IQVIA database) of PWID (n = 16,693), OST (n = 95,023) and treated HCV patients (n = 7886). Potential DDIs with the most widely used HCV direct-acting agents (Sofosbuvir/Velpatasvir, Glecaprevir/Pibrentasvir and Elbasvir/Grazoprevir) were evaluated based on the Liverpool DDI database. Co-medication was present in 57% of PWID, 57% of OST, 44% of patients on HCV therapy and 46% in a subgroup receiving OST+HCV therapy (n = 747 of 1613). For all groups, co-medication belonging to ATC-class N (nervous system) was most commonly prescribed (in 75%, 68%, 41% and 62% of patients, respectively). Contraindications (i.e., DDIs precluding HCV therapy) were infrequent (0.4–2.5% of co-medications); potential DDIs with HCV therapies were shown for 13–19% of co-medications, namely for specific substances including some analgesics, antipsychotics, anticoagulants, lipid lowering drugs and steroids. In conclusion, concomitant pharmacotherapy is common and clinically relevant when treating HCV infection in PWID.

Causation of potential drug to drug interactions alerts, alert overrides, and adverse drug events

Background: Drug-drug interactions (DDIs) leading to adverse drug event (ADEs) are of special interest because they represent preventable medication errors. Preventable ADE can result in errors involving the manifestation of adverse patient outcomes. Given the high complexity of critically ill cardiac patients, it is important to learn how CDDSS affects outcomes in this population and the number of alerts that likely be safely suppressed. Purpose: Identify adverse DDIs that is clinically detected and review the appropriateness of the doctor’s actions to the potential DDIs (PDDIs) alert. Study Design: This is a prospective observational study conducted at critical cardiac care unit (CCU) in a selected tertiary cardiac center for a duration of six months. Methods: Physicians treating critically ill cardiac patients were presented with PDDIs data which were acquired from two commercially available CDDSS. The relationship between the decision to prescribe and factors hypothesized to affect physicians' decisions were examined. Results: Evaluation of 709 patient medication profiles were conducted, resulting in 521 assessed patient profiles having had one or more PDDIs with 87% of them were influenced by polypharmacy. Ninety-one patients (17.5%) were associated with one or more adverse DDIs. Of the total 3284 potential DDIs alerts, 95.5% of the alerts were overridden. Preventable ADE as an outcome of inappropriate override have resulted 83.1 %. (236/284) of adverse DDIs. Whereas, appropriate overrides as an outcome of clinically irrelevant ADE were 16.9 % (48/284). Conclusion: Poor preventive actions taken by the doctors caused drug related harm to the patients despite having CDDSS in place. This suggests that CDDSS is an important application to minimize the harm associated with adverse DDIs by alerting physicians of potentially unsafe situations.

Comparing Potential Drug–Drug Interactions in Companion Animal Medications Using Two Electronic Databases

Multiple-drug prescriptions can cause drug–drug interactions (DDIs), which increase risks associated with healthcare in veterinary medicine. Moreover, many human medicines are used in canine patients under the responsibility of veterinarians and may cause severe problems due to off-label use. Currently, many electronic databases are being used as tools for potential DDI prediction, for example, Micromedex and Drugs.com, which may benefit the prediction of potential DDIs for drugs used in canine. The purpose of this study was to examine different abilities for the identification of potential DDIs in companion animal medicine, especially in canine patients, by Micromedex and Drugs.com. Micromedex showed 429 pairs of potential DDIs, while Drugs.com showed 842 pairs of potential DDIs. The analysis comparing results between the two databases showed 139 pairs (12.28%) with the same severity and 993 pairs (87.72%) with different severities. The major mechanisms of contraindicated and major potential DDIs were cytochrome P450 induction–inhibition and QT interval prolongation. Veterinarians should interpret potential DDIs from several databases with caution and keep in mind that the results might not be reliable due to differences in sensitivity to drugs, drug-metabolizing enzymes, and elimination pathway between animals and humans.

Polypharmacy and severe potential drug-drug interactions among older adults with cardiovascular disease in the United States

Background Polypharmacy continues to be a topic of concern among older adults and puts patients at increased risk of potential drug-drug interactions (DDIs) and negative health outcomes. The objective of this study was to assess the prevalence of polypharmacy among older adults with cardiovascular disease (CVD) and to identify severe potential DDIs. Methods A retrospective chart review was conducted in a tertiary care center over a three-month period where we reviewed home medications of older adults upon hospital admission. Inclusion criteria were age ≥ 65 years, history of CVD, and admission to the cardiology service. Polypharmacy was defined as 5 or more medications taken concomitantly, hyper-polypharmacy was defined as 10 or more medications taken concomitantly, and severe potential DDIs were considered to be those belonging to category D or X using Lexicomp® Drug Information Handbook. Category D interaction states that modification of therapy should be considered while category X states that the combination should be absolutely avoided. Results A total of 404 patients with a mean age of 76.6 ± 7.4 years were included. Patients were taking an average of 11.6 ± 4.5 medications at home and 385 (95%) received polypharmacy, 278 (69%) received hyper-polypharmacy, and 313 (77.5%) had at least one severe potential DDI. Under category D, the most common potential DDIs were drugs with additive central nervous system (CNS) depressant effect and drugs that increase the risk of QT prolongation. Under category X, the most common potential DDIs were non-selective β-blockers that may diminish the bronchodilator effect of β2 agonists and drugs with anticholinergic properties that enhance the ulcerogenic effect of oral solid potassium. Conclusions Polypharmacy, hyper-polypharmacy, and severe potential DDIs are very common in older adults with CVD. Clinicians should vigilantly review patients’ drug records and adjust therapy accordingly to prevent adverse drug reactions and negative health outcomes.

Potential drug-drug interactions of antiretrovirals and antimicrobials detected by three databases

Standard treatment for HIV infection involves a combination of antiretrovirals. Additionally, opportunistic infections in HIV infected patients require further antimicrobial medications that might cause drug-drug interactions (DDIs). The objective of this study was to to compare the recognition of DDIs between antiretrovirals and antimicrobials by three proprietary databases and evaluate their concordance. 114 items of antiretrovirals and antimicrobials from the National List of Essential Medicines of Thailand 2018 were used in the study. However, 21 items were not recognised by Micromedex, Drugs.com, and Liverpool HIV interactions. Only 93 items were available for the detection of potential DDIs by the three databases. Potential DDIs detected from the three databases included 292 pairs. Liverpool showed the highest number of DDIs with 285 pairs compared with 259 pairs by drugs.com and 133 pairs by Micromedex. Regarding the severity classifications, Liverpool reported 10% Contraindicated; Micromedex reported 14% contraindicated and 59% major; Drugs.com reported 21% major. The Fleiss’ kappa agreements were fair to poor among the three databases, higher agreement was observed for DDIs classified as severe. This study highlights the need to harmonize the evaluation and interpretation of DDI risk in order to produce standardized information to support prescribers.

Non-vitamin K Oral Anticoagulants and Anti-seizure Medications: A Retrospective Cohort Study

Purpose: Concerns of drug–drug interactions (DDIs) between anti-seizure medications (ASMs) and non-vitamin K oral anticoagulants (NOACs) have emerged in recent case reports and guidelines. Theoretically, the induction of hepatic cytochrome P450 3A4 (CYP3A4) enzyme and permeability glycoprotein (P-GP) efflux transporter protein systems may reduce the effect of NOACs. We aimed to investigate whether such DDIs are clinically relevant in a real-world situation.Methods: We retrospectively reviewed 320 ischemic stroke patients with atrial fibrillation (Af) and grouped them according to different potential interactions with CYP3A4 and P-GP. Ischemic stroke events, transient ischemic attack (TIA) events, follow-up duration, baseline characteristics, concomitant ASMs, and stroke risk factors were collected. Statistical analysis included Kaplan–Meier survival curves and the log-rank test.Results: Overall, 320 ischemic stroke with Af patients received NOACs. Among the NOAC users, 75 also took ASMs, including 56 that have potential DDIs: 43 (13.4%) were categorized as potential CYP and P-GP DDIs and 13 (4.1%) as P-GP-only DDIs. The remaining 264 (82.5%) patients were used as controls including 19 exposed to nonsignificant DDI ASMs and 245 patients without ASM exposure. The incidence rates of recurrent stroke/TIA events in both CYP3A4 and P-GP DDIs, P-GP DDIs only, and no DDIs were 7.5, 2.1, and 8.4/100 person-years, respectively. Kaplan–Meier survival curves and the log-rank test did not show significant differences among the groups.Conclusions: The recurrent stroke rate of NOAC users with potential DDIs was not higher than in those without potential DDIs in this single-institute study. Our results suggest that theoretical interactions between ASMs and NOACs may not be as severe as previously thought in a real-world situation.