Prevalence Of Drug-drug Interactions Research Articles

The prevalence of antiretroviral drug interactions with other drugs used in women living with HIV and its association with HIV drug change and patient compliance

BackgroundDrug-drug interactions (DDIs) between antiretroviral therapy (ART) and commonly used co-medications in HIV patients, especially women, impact treatment efficacy and patient safety.ObjectiveThis study aimed to study the prevalence and types of drug-drug interactions (DDIs) between antiretroviral therapy drugs (ARTs) and comedications among a female population with HIV. Additionally, the study investigates the association of these DDIs with ART medication changes and treatment adherence.MethodsThis cross-sectional study included 632 adult women living with HIV (WLHIV). Data was retrospectively extracted from patient files. Drug.com interaction checker website was used to assess DDIs between ART and non-ART medications. Changes to the ART regimen previously attributed to ART side effects or patient non-adherence were considered drug changes.ResultsA total of 429 WLHIV (mean age: 44.05 ± 9.50) were eligible. The prevalence of DDIs between ART and non-ART medications was 21.4%, with 4.7% minor, 18.4% moderate, and 8.9% major interactions. The highest prevalence of DDI was among cardiovascular medication users (71.7%), followed by central nervous system drugs (69.2%). Changing medications resulted in a decrease in DDIs, with significant reductions in total and minor interactions. Participants without DDIs had better adherence to ART. DDI between ART and non-ART medications was significantly associated with ART drug change, even after accounting for side effects attributed to ARTs, indicating an independent twofold association (OR = 1.99, CI 1.04–3.77). Moreover, further adjustments for HIV viral load and CD4 + cell count did not change the significance of the association (OR = 2.01, CI 1.03–3.92).ConclusionDDIs in WLHIV impact adherence to ART. Altering ART may not be directly related to ART side effects, but rather primarily due to interactions with non-ART medications. Modifying non-ART drug regimens can reduce the likelihood of DDIs.

Severity and Risk Rating of Drug-Drug Interaction Potency in Chronic Kidney Disease in Public Health Hospital

Background: Chronic kidney disease has emerged as a prominent cause of mortality worldwide in the last two decades. Drug interactions are a significant problem in individuals with chronic kidney disease, as they often receive numerous concurrent treatments. The aim is to examine the frequency of drug-drug interactions in outpatient treatment for chronic renal disease, classified according to their severity and risk level. Furthermore, the study aims to demonstrate the combined effect of the most common drug-drug interactions potency and associated risk factors. Methods: This study is a retrospective cross-sectional analysis of outpatients diagnosed with chronic kidney disease at Ansari Saleh Public Hospital in Banjarmasin, Indonesia. Medical records from 2022 were obtained retrospectively from computerised sources. The evaluation of potential interactions between drugs was conducted using Lexicomp®. The categorical data were displayed as percentages, and the continuous variables were depicted as means. Results: The study found that most drug interactions fell into the moderate severity (77.1%) and category C (75.5%) for the risk assessment. The prevalence of drug-drug interactions was 83.6% and the average number of potential drug interactions per patient was 3.34 ± 3.481. The concurrent use of candesartan and furosemide was the most prevalent drug-drug interaction (5.1%). The number of prescribed medications was a notable determinant for probable drug-drug interactions (p < 0.05). Conclusion: Identifying and averting potential drug-drug interactions is crucial to guarantee patient safety.

Clinical, pharmacological, and qualitative characterization of drug-drug interactions in pregnant women initiating HIV therapy in Sub-Saharan Africa.

We investigated the impact of Drug-Drug Interactions (DDIs) on virologic control among HIV-positive pregnant women initiating antiretroviral therapy while identifying drivers for Traditional Medicine (TM) use and exploring the nature and extent of TM-related DDIs. Employing a three-pronged approach, we examined DDIs arising from comedication, including TM, in ART. The DolPHIN-2 trial (NCT03249181) randomized 268 HIV-positive pregnant women in Uganda and South Africa to dolutegravir (DTG)-based (135) or efavirenz-based (133) regimens while systematically recording comedications and screening for DDIs. We used Cox regression models to compare time-to-virologic control between participants with and without DDIs. We conducted in-depth interviews and focus group discussions among 37 and 67 women with and without HIV, respectively, to explore reasons for TM use during pregnancy. Additionally, in-vitro and in-vivo studies evaluated the composition and impact of clay-based TM, mumbwa, on DTG plasma exposure. The baseline prevalence of DDIs was 67.2%, with TM use prevalent in 34% of participants, with mumbwa being the most frequent (76%, 69/91). There was no difference in virologic response between participants with and without DDIs. Fetal health and cultural norms were among the reasons cited for TM use. Analysis of mumbwa rods confirmed significant amounts of aluminium (8.4%-13.9%) and iron (4%-6%). In Balb-C mice, coadministration of mumbwa led to a reduction in DTG exposure observed in the AUC0-24 (-21%; P = 0.0271) and C24 (-53%; P = 0.0028). The widespread use of clay-based TM may compromise HIV treatment, necessitating medication screening and counselling to manage DDIs in pregnant women.

Drug-Drug Interactions and Their Association with Adverse Health Outcomes in the Older Community-Dwelling Population: A Prospective Cohort Study.

Evidence on associations between drug-drug interactions (DDIs) and health outcomes in the older community-dwelling population is limited. We estimate potentially clinically important DDI prevalence and examine the association between DDIs and (1) adverse drug events (ADEs), (2) emergency hospital attendance and (3) health-related quality of life (HRQoL) in an older community-dwelling population in Ireland. This is a prospective cohort study of community-dwelling older adults (N = 904) aged ≥ 70 years from 15 general practices in Ireland recruited in 2010 (wave-1) and followed-up over 2 years (wave-2; 2012-2013), with linked national pharmacy claims data. Individuals dispensed two or more drugs (wave-1: N = 842; wave-2: N = 763) were included. DDI prevalence at baseline, follow-up and 6 months prior to each health outcome was estimated. Multi-level regression was used to model the association between DDI-exposure and health outcomes at follow-up. DDI prevalence, adjusted incidence-rate ratios (aIRR), adjusted odds ratios (aOR), β coefficients and robust standard error (RSE) from multi-level regression analyses, and 95% confidence intervals (CIs) are reported. At wave-1, n = 196 (23.3% [95% CI 20.5-26.3]), individuals were potentially exposed to ≥ 1 DDI, increasing to n = 345 (45.2% [41.7-48.9]) at wave-2. At 2-year follow-up, the median number of ADEs was 3 (interquartile range [IQR 2-5]); 229 (30.1%) had ≥ 1 emergency hospital attendance, and the mean EQ-5D was 0.74 (± 0.23). Evidence for the association between DDI-exposure and emergency hospital attendance at follow-up was lacking (aOR = 1.38 [0.42-4.53]). DDI-exposure was associated with an increasing number of ADEs (aIRR = 1.26 [1.03-1.55]), and decreasing EQ-5D utility (β = - 0.07, [-0.11 to -0.04], RSE = 0.02). Aspirin-warfarin, clarithromycin-prednisolone, amiodarone-furosemide, clarithromycin-salbutamol, rosuvastatin-warfarin, amiodarone-bisoprolol, and aspirin-nicorandil were common DDIs 6 months preceding these health outcomes. We found a two-fold increase in DDI prevalence between wave 1 and 2. DDI exposure was associated with increasing ADEs and declining HRQoL at 2-year follow-up. Common DDIs involved anticoagulants, cardiovascular and antimicrobial drugs, which should be targeted for medicine optimisation.

Pharmacokinetics and pharmacodynamics of drug‒drug interactions in hospitalized older adults treated with direct oral anticoagulants.

Polypharmacy is a frequent situation in older adults that increases the risk of drug-drug interactions (DDIs), both pharmacokinetic (PK) and pharmacodynamic (PD). Direct oral anticoagulants (DOACs) are frequently prescribed in older adults, mainly because of the high prevalence of atrial fibrillation (AF). DOACs are subject to cytochrome P450 3A4 (CYP3A4)- and/or P-glycoprotein (P-gp)-mediated PK DDIs and PD DDIs when co-administered with drugs that interfere with platelet function. The aim of our study was to assess the prevalence of DDIs involving DOACs in older adults and the associated risk factors at admission and discharge. This was a cross-sectional study conducted in an acute geriatric unit between January 1, 2018 and December 31, 2022, including patients over 75 years of age treated with DOACs at admission and/or discharge, for whom a comprehensive collection of co-medications was performed. From 909 hospitalizations collected, the prevalence of PK DDIs involving DOACs was 16.9% at admission and 20.7% at discharge, and the prevalence of PD DDIs was 20.7% at admission and 20.2% at discharge. Factors associated with DDIs were bleeding history [adjusted odds ratio (ORa) 1.74, 95% confidence interval (CI) 1.13-2.68], number of drugs > 6 (ORa 2.54, 95% CI 1.88-3.46) and reduced dose of DOACs (ORa 0.39, 95% CI 0.28-0.54) at admission and age > 87 years (ORa 0.74, 95% CI 0.55-0.99), number of drugs > 6 (ORa 2.01, 95% CI 1.48-2.72) and reduced dose of DOACs (ORa 0.41, 95% CI 0.30-0.57) at discharge. This study provides an indication of the prevalence of DDIs as well as the profile of DDIs and patients treated with DOACs.

Prevalence and differences in the co-administration of drugs known to interact: an analysis of three distinct and large populations

BackgroundThe co-administration of drugs known to interact greatly impacts morbidity, mortality, and health economics. This study aims to examine the drug–drug interaction (DDI) phenomenon with a large-scale longitudinal analysis of age and gender differences found in drug administration data from three distinct healthcare systems.MethodsThis study analyzes drug administrations from population-wide electronic health records in Blumenau (Brazil; 133 K individuals), Catalonia (Spain; 5.5 M individuals), and Indianapolis (USA; 264 K individuals). The stratified prevalences of DDI for multiple severity levels per patient gender and age at the time of administration are computed, and null models are used to estimate the expected impact of polypharmacy on DDI prevalence. Finally, to study actionable strategies to reduce DDI prevalence, alternative polypharmacy regimens using drugs with fewer known interactions are simulated.ResultsA large prevalence of co-administration of drugs known to interact is found in all populations, affecting 12.51%, 12.12%, and 10.06% of individuals in Blumenau, Indianapolis, and Catalonia, respectively. Despite very different healthcare systems and drug availability, the increasing prevalence of DDI as patients age is very similar across all three populations and is not explained solely by higher co-administration rates in the elderly. In general, the prevalence of DDI is significantly higher in women — with the exception of men over 50 years old in Indianapolis. Finally, we show that using proton pump inhibitor alternatives to omeprazole (the drug involved in more co-administrations in Catalonia and Blumenau), the proportion of patients that are administered known DDI can be reduced by up to 21% in both Blumenau and Catalonia and 2% in Indianapolis.ConclusionsDDI administration has a high incidence in society, regardless of geographic, population, and healthcare management differences. Although DDI prevalence increases with age, our analysis points to a complex phenomenon that is much more prevalent than expected, suggesting comorbidities as key drivers of the increase. Furthermore, the gender differences observed in most age groups across populations are concerning in regard to gender equity in healthcare. Finally, our study exemplifies how electronic health records’ analysis can lead to actionable interventions that significantly reduce the administration of known DDI and its associated human and economic costs.

Override rate of drug-drug interaction alerts in clinical decision support systems: A brief systematic review and meta-analysis.

Primary studies have demonstrated that despite being useful, most of the drug-drug interaction (DDI) alerts generated by clinical decision support systems are overridden by prescribers. To provide more information about this issue, we conducted a systematic review and meta-analysis on the prevalence of DDI alerts generated by CDSS and alert overrides by physicians. The search strategy was implemented by applying the terms and MeSH headings and conducted in the MEDLINE/PubMed, EMBASE, Web of Science, Scopus, LILACS, and Google Scholar databases. Blinded reviewers screened 1873 records and 86 full studies, and 16 articles were included for analysis. The overall prevalence of alert generated by CDSS was 13% (CI95% 5-24%, p-value <0.0001, I^2 = 100%), and the overall prevalence of alert override by physicians was 90% (CI95% 85-95%, p-value <0.0001, I^2 = 100%). This systematic review and meta-analysis presents a high rate of alert overrides, even after CDSS adjustments that significantly reduced the number of alerts. After analyzing the articles included in this review, it was clear that the CDSS alerts physicians about potential DDI should be developed with a focus on the user experience, thus increasing their confidence and satisfaction, which may increase patient clinical safety.

Potential drug-drug interactions between discharge medication from the emergency department and home medication in tertiary hospital

Objective: This retrospective analysis aimed to comprehensively examine the age distribution, gender prevalence, comorbidity patterns, and potential drug-drug interactions among discharged emergency department (ED) patients. By elucidating these factors, the study would contribute valuable insights for improving patient care and medication safety. Methods: The study used retrospective data collection and analyzed cross-sectional data of patients discharged from the ED at King Abdullah Medical City from January to February 2023. Results: The results showed that the majority of discharged patients were between the ages of 36 and 50 years (56.4%) and had a balanced gender distribution. The most common department of discharge was cardiology (42.1%). The analysis also revealed that 68.5% of patients had 3 to 6 comorbidities. The study found significant associations between discharge status and potential drug-drug interactions (DDIs), with patients discharged against medical advice having a higher incidence of potential DDIs (p = 0.037). Conclusion: The study highlighted the importance of training emergency physicians to use hospital systems to identify and prevent potential DDIs. The prevalence of DDIs between prescribed ED medication and home medication was found to be high. The study suggested that discharge status and DDI severity are significant factors influencing the frequency of potential DDIs.

Polypharmacy and potential drug–drug interactions among people living with HIV in the era of integrase strand transfer inhibitor-based antiretroviral therapy

We aimed to investigate the prevalence of polypharmacy and potential drug-drug interactions (DDIs) and the associated factors with DDIs among people living with HIV (PLWH) in the modern era of antiretroviral therapy (ART). This cross-sectional study included PLWH who had been on ART for at least 3 months at two designated hospitals for HIV care in Taiwan. All ART and non-ART prescriptions were collected from the NHI-MediCloud System and screened for DDIs using the University of Liverpool HIV drug interactions database. A case-control analysis was conducted to investigate the factors associated with DDIs. From June 2021 to August 2022, 1007 PLWH were included. Their median age was 40 years (interquartile range, 33-49) and 96.2% were taking INSTI-based ART. The proportions of PLWH with at least 1 non-communicable diseases and polypharmacy were 50.0% and 18.7%, respectively. Seven (0.7%) PLWH had red-flagged DDIs, and 159 (15.8%) had amber-flagged DDIs. In multivariable models, the prevalence of DDIs was higher in PLWH with an older age (aOR, per 1-year increase, 1.022), number of co-medications (aOR, 1.097), use of boosted INSTI-based ART (versus unboosted INSTI, aOR, 8.653), and concomitant medications in the category of alimentary tract and metabolism (aOR, 11.058) and anti-neoplastic and immunomodulating agents (aOR, 14.733). In the INSTI era, the prevalence of potential DDIs was lower than previously noted, but remained substantial. Clinicians should routinely monitor DDIs, especially in older PLWH, those with increased number of co-medications, and those who are taking booster-containing ART or medications from specific categories.

Polypharmacy, potentially inappropriate medications, and drug-drug interactions in older COVID-19 inpatients

ObjectivesThe purpose of this study was to assess the impact of polypharmacy, potentially inappropriate medications, and drug-drug interactions on in-hospital mortality in older COVID-19 inpatients.MethodsA cross-sectional study was conducted using electronic medical data from a tertiary hospital in Chengdu from December 2022 to January 2023. The 2019 AGS/Beers criteria was used to evaluate the potentially inappropriate mediation (PIM) status of older COVID-19 inpatients (age ≥ 65 years), the drug-drug interactions were evaluated on Medscape, and multivariate logistic regression was used to identify the risk factors associated with in-hospital mortality.ResultsA total of 206 older COVID-19 inpatients were included in the study. The mean number of drugs per day was 13.04. The prevalence of PIM use based on the 2019 AGS Beers Criteria was 66.99%. The prevalence of drug-drug interactions was 61.65%. Logistic regression demonstrated that age ≥ 80 (OR: 10.321, 95% CI: 1.649, 64.579, P = 0.013), renal insufficiency (OR: 4.740, 95% CI: 1.366, 16.447, P = 0.014), long-term hospitalization (OR: 6.637, 95% CI: 1.030, 42.779, P = 0.046), severe pneumonia (OR: 50.230, 95% CI: 5.180, 487.041, P = 0.001) were influencing factors associated with in-hospital mortality in older COVID-19 inpatients.ConclusionsThe polypharmacy, potentially inappropriate medications, and drug-drug interactions were seen in many older COVID-19 inpatients.

A retrospective cohort study of prescribing outcomes in outpatients treated with nirmatrelvir-Ritonavir for COVID-19 in an interdisciplinary community clinic.

Large observational studies have demonstrated the real-world effectiveness of nirmatrelvir-ritonavir in preventing severe COVID-19 in higher risk individuals, but have provided limited information on other aspects of nirmatrelvir-ritonavir use. Our objective was to evaluate prescribing outcomes such as the prevalence of drug-drug interactions (DDI), adverse drug events (ADE) and treatment adherence in an outpatient community clinic setting. We conducted a single-centre retrospective cohort study of adult outpatients prescribed nirmatrelvir-ritonavir in our community COVID-19 assessment clinic in Toronto, Ontario between March 3 and September 20, 2022. We performed a descriptive analysis of the patient population, DDIs, DDI interventions, treatment adherence, ADEs and clinical outcomes of patients prescribed nirmatrelvir-ritonavir. There were 637 individuals prescribed nirmatrelvir-ritonavir during the study period. The median age was 70, the median number of risk factors for severe disease were 2, 45% were immunocompromised and 82% had received 3 or more COVID-19 vaccine doses. 95% (542/572) completed the 5-day course of therapy with 68% (388/572) having complete symptom resolution by 28-day. Eleven percent (60/572) experienced recurrent symptoms following the completion of nirmatrelvir-ritonavir. Over 70% had one or more clinically significant DDIs requiring mitigation and 62% of patients experienced at least one ADE, which was most commonly dysgeusia or gastrointestinal-related. Ninety-five percent (542/572) of patients completed therapy as prescribed. Overall, hospitalization within 28 days was 3.3% with 1.2% attributed to COVID-19 and there were no deaths. Nirmatrelvir-ritonavir was associated with a high prevalence of clinically significant DDIs, which required mitigation strategies and a high frequency of mild ADEs. Collaborative assessment to address medication alterations resulted in high treatment adherence.

The prevalence of relevant drug-drug interactions and associated clinical outcomes in patients with cancer-associated thrombosis on concurrent anticoagulation and anticancer or supportive care therapies

BackgroundA main concern in the management of patients with cancer-associated thrombosis (CAT) is drug-drug interactions (DDIs) between anticoagulants and anticancer therapies. Their clinical implications remain unclear. MethodsTo quantify the prevalence of DDIs and risks of recurrent venous thromboembolism (VTE) and bleeding events in patients with CAT on anticoagulation, we conducted a retrospective cohort study in patients with CAT on concurrent anticoagulants and anticancer and/or supportive care therapies. All patients were followed for 6 months from CAT diagnosis or until death (whichever occurred first). The primary outcome was the percentage of patients with anticoagulant DDIs classified as risk C, D, or X in Lexicomp® at any time during the 6 months. Secondary outcomes included recurrent VTE and clinically relevant bleeding events. We calculated the 6-month cumulative incidence of outcomes with 95 % confidence interval (CI) and compared those with and without DDIs, considering death as a competing risk. ResultsAmong 267 patients included, 111 (41.6 %) had DDIs with anticoagulants at any time during the study. Those on DOACs at any time had more DDIs compared to LMWH (50.9 % vs 19.3 %, p < 0.0001). The 6-month incidence was 8.2 % (95 % CI 5.3–11.9) for recurrent VTE and 6.7 % (95 % CI 4.2–10.2) for clinically relevant bleeding, with no significant differences between groups with or without DDIs. ConclusionsThere are high incidences of DDIs in patients with CAT on anticoagulants, more with DOACs. DDIs classified as risk C, D, or X by Lexicomp® were not associated with recurrent VTE or bleeding events in our cohort.

Prevalence of Drug-Drug Interactions in Primary Care Prescriptions in Egypt: A Cross-Sectional Retrospective Study.

In clinical practice, drug-drug interactions (DDIs) pose significant risks to a large number of patients. Consequently, healthcare providers are required to diligently identify, monitor, and effectively handle these interactions in order to enhance patient outcomes. In Egypt, DDIs are poorly addressed, with no reports for DDIs in primary care. In our cross-sectional, retrospective, observational study, we collected a total of five thousand, eight hundred and twenty prescriptions across eight major governorates in Egypt. Prescriptions were collected over a span of 15 months between 1 June 2021 and 30 September 2022. These prescriptions were analyzed for potential DDIs using the Lexicomp® drug interactions tool. The prevalence of DDIs was found to be 18%, with 22% of the prescriptions having two or more potential DDIs. Moreover, we found 1447 DDIs of categories C (monitoring therapy recommended), D (therapy modification suggested), and X (avoid combination). The most commonly interacting drugs in our study were diclofenac, aspirin, and clopidogrel, while non-steroidal anti-inflammatory drugs (NSAIDs) were the most reported therapeutic class implicated in pharmacologic DDIs. Pharmacodynamic agonistic activity was the most common mechanism of interaction. Therefore, it is crucial to conduct screenings, detect early signs, and closely monitor drug-drug interactions (DDIs) to enhance patients' overall health outcomes, medication responses, and safety. In this regard, the clinical pharmacist assumes a vital role in implementing these preventive measures.

Frequency, Predictors, and Outcomes of the Potential Drug-Drug Interactions in the ICUs of Teaching Hospitals in Ardabil, Northwest of Iran During 2019-2020.

Introduction: Drug-drug interactions (DDIs) can reduce therapeutic efficacy and increase the duration and cost of hospitalization so that patients are sometimes exposed to significant complications and even death. Patients in the intensive care unit (ICU) are at higher risk of DDIs for a variety of reasons, including impaired absorption, decreased metabolism, and renal failure. The main objective of this study was to evaluate frequency, clinical ranking and risk factors of potential DDIs in the ICUs of 3 teaching hospitals in Ardabil. Methods: In this descriptive-analytical cross-sectional study, drug prescriptions 355 patients admitted to the ICUs were studied. Patient information including age, sex, diagnosis, number of prescribers, number of drugs, length of stay, and status of patients' discharge (recovery or death) were recorded and checked using the online software up to date and the book Drug Interaction Facts. Finally, the data were statistically analyzed using the SPSS software. Results: The number of patients studied was 355. The mean age of the patients were 51.88 ± 23.22 years, and on average, 8.45 drugs had been prescribed for each patient. The total number of DDIs was 1597 among which class X was 1.4%, class D was 26.2%, and class C was 67.7%. Four hundred ninety-seven unique pairs of DDIs were identified. Age, number of prescribed drugs and length of stay in ICU were associated with prevalence of DDIs. Age and number of drugs were also identified as the risk factors of patients' discharge caused by death. Conclusion: DDIs can complicate health state of patients in ICUs and may increase the length of hospital stay. Setting up computerized systems to alert drug interactions in hospital wards and pharmacotherapeutic intervention by clinical pharmacist can minimize DDIs.

The Prevalence of Drug-Drug Interactions and Reported Therapy Related Side Effects in Oncology Out-Patients

Objective: The use of multiple medications in cancer patients is unavoidable; thus, adverse drug-drug interactions are frequent. This study aims to assess the prevalence of potential drug interactions in oncology patients visiting the outpatient chemotherapy unit.&#x0D; Method: Demographic and health-related information of patients visiting an outpatient chemotherapy unit was recorded using a pre-prepared form. A comprehensive list of all concurrently used medications was compiled and checked for interactions with the Micromedex online drug interaction tool.&#x0D; Results: A total of 179 adult patients were included. We recorded an average of 9.3 drugs per patient with 79 patients using more than 10 drugs. A total of 1671 drugs including 303 chemotherapeutic agents were assessed for drug-drug interactions. A total of 374 interactions, of which 203 were significant, were recorded in 118 (65.9%) patients with an average of 3.2 interactions per patient. Only 46 major interactions were recorded for anticancer agents. Cyclophosphamide (n=13) and cisplatin (n=12) were involved in most interactions. The number of interactions correlated with the number of drugs used (p=.001) and the presence of comorbidities (p=.002). The presence of comorbidities increased the risk of interaction by 1.21 (p=.04). Recorded side effects were not correlated to drug interactions.&#x0D; Conclusion: Medication review in cancer patients is essential in establishing all medications used by patients. Routine assessment in terms of potential drug interactions and evaluation of these interactions by a qualified pharmacist may help in optimizing patient outcomes.

Evaluation of Drug Interactions in Hospitalized Patients with Respiratory Disorders in Greece

Background: Patients with respiratory disorders often have additional diseases and are usually treated with more than one medication to manage their respiratory conditions as well as additional comorbidities. Thus, they are frequently exposed to polypharmacy (≥5 drugs), which raises the risk for drug-drug interactions (DDIs) and adverse drug reactions (ADRs). In this work, we present the results regarding the prevalence of DDIs in hospitalized patients with respiratory disorders in Greece. Methods: A 6-month descriptive single-center retrospective observational study enrolled 102 patients with acute or chronic respiratory disorders. Clinical characteristics and medication regimens were recorded upon admission, hospitalization, and discharge. The prevalence of DDIs and their clinical significance was recorded and analyzed. Results: Unspecified acute lower respiratory tract infection (25%), exacerbations of chronic obstructive pulmonary disease (12%) and pneumonia (8%) were the most frequent reasons for admission. Cardiovascular disorders (46%), co-existing respiratory disorders (32%), and diabetes (25%) were the most prevalent comorbidities. Polypharmacy was noted in 61% of patients upon admission, 98% during hospitalization, and 63% upon discharge. Associated DDIs were estimated to be 55% upon admission, 96% throughout hospitalization, and 63% on discharge. Pharmacodynamic (PD) DDIs were the most prevalent cases (81%) and referred mostly to potential risk for QT-prolongation (31.4% of PD-DDIs) or modulation of coagulation process as expressed through the international normalized ratio (INR) (29.0% of DDIs). Pharmacokinetic (PK) DDIs (19% of DDIs) were due to inhibition of Cytochrome P450 mediated metabolism that could lead to elevated systemic drug concentrations. Clinically significant DDIs characterized as "serious-use alternative" related to 7% of cases while 59% of DDIs referred to combinations that could be characterized as "use with caution-monitor". Clinically significant DDIs mostly referred to medication regimens upon admission and discharge and were associated with outpatient prescriptions. Conclusions: Hospitalized patients with respiratory disorders often experience multimorbidity and polypharmacy that raise the risk of DDIs. Clinicians should be conscious especially if any occurring arrhythmias, INR modulations, and prolonged or increased drug action is associated with DDIs.

Prevalence of Drug-Drug Interactions in Older Community-Dwelling Individuals: A Systematic Review and Meta-analysis.

Drug-drug interactions (DDIs) can lead to medication-related harm, and the older population is at greatest risk. We conducted a systematic review and meta-analysis to estimate DDI prevalence and identify common DDIs in older community-dwelling adults. PubMed and EMBASE were searched for observational studies published between 01/01/2010 and 10/05/2021 reporting DDI prevalence in community-dwelling individuals aged ≥65 years. Nursing home and inpatient hospital studies were excluded. Study quality was assessed using the Joanna Briggs Institute critical appraisal tool. Meta-analysis was performed using a random-effects model with logit transformation. Heterogeneity was evaluated using Cochran's Q and I2. DDI prevalence and 95% confidence intervals (CIs) are presented. All analyses were performed in R (version 4.1.2). There were 5144 unique articles identified. Thirty-three studies involving 17,011,291 community-dwelling individuals aged ≥65 years met inclusion criteria. Thirty-one studies reported DDI prevalence at the study-participant level, estimates ranged from 0.8% to 90.6%. The pooled DDI prevalence was 28.8% (95% CI 19.3-40.7), with significant heterogeneity (p < 0.10; I2 = 100%; tau2 = 2.13) largely explained by the different DDI identification methods. Therefore, 26 studies were qualitatively synthesised and seven studies were eligible for separate meta-analyses. In a meta-analysis of three studies (N = 1122) using Micromedex®, pooled DDI prevalence was 57.8% (95% CI 52.2-63.2; I2 = 69.6%, p < 0.01). In a meta-analysis of two studies (N = 809,113) using Lexi-Interact®, pooled DDI prevalence was 30.3% (95% CI 30.2-30.4; I2 = 6.8%). In a meta-analysis of two studies (N = 947) using the 2015 American Geriatrics Society Beers criteria®, pooled DDI prevalence was 16.6% (95% CI 5.6-40.2; I2 = 97.5%, p < 0.01). Common DDIs frequently involved cardiovascular drugs, including ACE inhibitor-potassium-sparing diuretic; amiodarone-digoxin; and amiodarone-warfarin. DDIs are prevalent among older community-dwelling individuals; however, the methodology used to estimate these events varies considerably. A standardised methodology is needed to allow meaningful measurement and comparison of DDI prevalence.

40 PREVALENCE OF DRUG-DRUG INTERACTIONS IN OLDER COMMUNITY-DWELLERS: A SYSTEMATIC REVIEW AND META-ANALYSIS

Abstract Background Polypharmacy (regular use of ≥5 medicines) is common in the older population and is an independent risk factor for Drug-Drug Interactions (DDIs). We conducted a systematic review and meta-analysis to summarise the prevalence of DDIs in older (≥65years) community-dwellers. Methods An electronic database search was conducted in PubMed and EMBASE. Observational studies published in English between 01/01/2010-10/05/2021 reporting DDI prevalence in community-dwellers aged ≥65years were included. Nursing home and inpatient hospital studies were excluded. Articles were independently double screened for eligibility. Data were independently extracted, 20% extracted in duplicate. Quality assessment was performed using the Joanna Briggs Institute critical appraisal tool. Prevalence estimates and 95% confidence intervals (CI) are presented. All analyses were performed using the metafor package(v3.0.2) in R(v4.1.2). (PROSPERO:CRD42020216686). Results 5144 unique articles were identified. 33 studies involving 17,011,291 community-dwellers aged ≥65years (age range 65-103) met inclusion criteria. 22 studies measured DDIs broadly classified as (potentially) clinically important. DDI identification methods varied across studies: 5 used Micromedex®; 3 used the 2015 AGS Beers criteria®; 3 used Lexi-Interact®; 2 used drugs.com; 6 used multiple methods; and 14 used a unique method. 31 studies reported DDI prevalence at the study participant level; estimates ranged from 0.8% to 90.6%. 26 studies were qualitatively synthesised and 7 studies were eligible for meta-analyses. In a meta-analysis of 3 studies (n=1122) using Micromedex®, DDI prevalence in older (≥65years) community-dwellers was estimated to be 57.8% (95%CI: 52.2-63.2%; I2 69.6%, p&amp;lt;0.01). In a meta-analysis of 2 studies (n=809,113) using Lexi-Interact®, the estimated prevalence was 30.3% (95%CI: 30.2-30.4%; I2 6.8%). In a meta-analysis of 2 studies (n=947) using the 2015 AGS Beers criteria®, the estimated prevalence was 16.6% (95%CI: 5.6-40.2%; I2 97.5%, p&amp;lt;0.01). Conclusion DDIs are prevalent among older community-dwellers; however, the methodology used to estimate these events varies considerably. A standardised method is needed to allow meaningful measurement of DDI prevalence in this population.

The prevalence of drug–drug interactions in cancer therapy and the clinical outcomes

BackgroundWhen a patient concomitantly uses two or more drugs, a drug–drug interaction (DDI) may occur, and patients with cancer are at high risk of DDIs because they commonly receive multiple medications. However, data on the prevalence of DDIs are scarce, especially in Saudi Arabia. ObjectiveOur aim was to evaluate the occurrence of DDIs in patients with cancer and identify risk factors for these DDIs and the clinical outcomes. MethodA retrospective cross-sectional study was conducted in KFMC. Data were collected from the medical records and phone calls, and the patient's drugs were screened for interactions using Micromedex and Lexi-Comp. The data were statistically analysed using IBM SPSS version 24 statistical program. ResultsIn 72 patients (mean age of 47 years; 11 medications), the prevalence of DDIs was 60 %, and 2 potential DDIs were identified. According to Lexi-Comp, 137 (51.8 %) were categorized as pharmacodynamics interactions. In Micromedex, 94 potential DDIs were identified, 68.1 % were categorized as pharmacokinetic interactions, the comparison between the interaction of Lexi-Comp and Micromedex for 9 drugs. Eight drug pairs showed statistically significant difference in category of interaction (P < 0.05). Six pair of drugs showed statistically significant difference in mechanism of action (p < 0.05). Number of drugs was reported as significant risk factor (p = 0.007), type of treatment such as chemotherapy (p = 0.0000) and inpatient admission in terms of length of stay in hospital was also found significant risk factor (p = 0.031). ConclusionTo prevent DDIs, Physicians and pharmacists should be more aware of these potential interactions to prevent DDIs.

Drug-Drug Interactions with Oral Anticoagulants as Potentially Inappropriate Medications: Prevalence and Outcomes in Elderly Patients in Primary Care and Hospital Settings.

Direct oral anticoagulants and vitamin K antagonists are considered as potentially inappropriate medications (PIM) in several situations according to Beers Criteria. Drug–drug interactions (DDI) occurring specifically with these oral anticoagulants considered PIM (PIM–DDI) is an issue since it could enhance their inappropriate character and lead to adverse drug events, such as bleeding events. The aim of this study was (1) to describe the prevalence of oral anticoagulants as PIM, DDI and PIM–DDI in elderly patients in primary care and during hospitalization and (2) to evaluate their potential impact on the clinical outcomes by predicting hospitalization for bleeding events using machine learning methods. This retrospective study based on the linkage between a primary care database and a hospital data warehouse allowed us to display the oral anticoagulant treatment pathway. The prevalence of PIM was similar between primary care and hospital setting (22.9% and 20.9%), whereas the prevalence of DDI and PIM–DDI were slightly higher during hospitalization (47.2% vs. 58.9% and 19.5% vs. 23.5%). Concerning mechanisms, combined with CYP3A4–P-gp interactions as PIM–DDI, were among the most prevalent in patients with bleeding events. Although PIM, DDI and PIM–DDI did not appeared as major predictors of bleeding events, they should be considered since they are the only factors that can be optimized by pharmacist and clinicians.