Prevalence Of Potential Drug-drug Interactions Research Articles

Prevalence and factors associated with potential drug-drug interactions in prescriptions presented at private pharmacies in Mbarara city, southwestern Uganda.

Drug-drug interactions (DDIs) influence the effectiveness of medication and thus determine the treatment outcomes of diseases managed with pharmacotherapy. This study aimed to determine the prevalence, severity, and factors associated with potential drug-drug interactions in prescriptions presented at private pharmacies in Mbarara city. DDIs were identified and classified basing on risk and severity using Lexicomp drug interaction database. STATA version 13 was used to analyze the collected data. Descriptive statistics were used to summarize the severity of potential DDIs identified. Bivariate and multivariate logistic regression was employed to identify different factors associated with the presence of potential DDIs. A total of 295 prescriptions from 18 private pharmacies were studied and the prevalence of clinically significant potential DDIs was 37.6%. About half (149, 50.5%) of the patients were females, the majority (199, 67.5%) were adults 18-59 years of age whereas most (208, 70.5%) had a comorbid condition. Over one half (162, 54.9%) of the prescriptions were received from hospitals and majority of the prescriptions had 4 drugs prescribed (n= 175, 59.32%). Having one or more comorbidities and prescribing of therapeutic drug categories including anti-fungal, antihypertensives, analgesics, or corticosteroids were significantly associated with potential DDIs. The prevalence of potential drug-drug interactions in outpatient setting in Mbarara city was high and majority of the potential DDIs were of moderate severity. Having 1 or more comorbidities and prescribing of therapeutic drug categories including antifungals, antihypertensives, analgesics, or corticosteroids were significantly associated with 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.

Drug-drug interactions in an intensive care unit and comparison of updates in two databases

ObjectiveCritically ill patients are at increased risk of drug-drug interactions but their prevalence and clinical relevance remains unclear. The prevalence of potential drug-drug interactions in an intensive care unit according to Micromedex Drug-Reax® and Lexi-Interact® databases was studied and the concordance between the two databases was assessed. In addition, drug-drug interactions detected in 2013 were compared with those identified in 2018 to determine updates between these years. MethodBetween January and June 2013, 152 critical care patients were prospectively included. Cardiac patients were excluded. Demographic and clinical data together with the drugs administered on the first calendar day of intensive care unit admission were recorded. Potential drug-drug interactions were searched in both Drug-Reax® and Lexi-Interact® and their prevalence, level of severity and evidence were compared considering the same sample in 2013 and 2018. ResultsIn 2013, 1,025 potential drug-drug interactions were identified, corresponding to 438 unique pairs. Lexi-Interact® identified more interactions (92.8%) than Drug-Reax® (34.0%). The percentage of agreement between databases was 274%. The number of interactions included in both databases increased after the five years but their level of evidence decreased. The most common potential drug-drug interactions involved sedatives and analgesics, intentionally prescribed concomitantly. Only two potential drug-drug interactions were classified as contraindicated by both databases. None of the potential drug-drug interactions identified had a noticeable clinical impact. Neither did they imply a prescription change. ConclusionsThis study shows that the prevalence of potential drug-drug interactions in the intensive care unit is high, although their clinical relevance is generally low. Our data also show a lack of concordance between Drug-Reax® and Lexi-Interact®, as well as their updates.

The comorbidity and co-medication profile of patients with progressive supranuclear palsy

BackgroundProgressive supranuclear palsy (PSP) is usually diagnosed in elderly. Currently, little is known about comorbidities and the co-medication in these patients.ObjectivesTo explore the pattern of comorbidities and co-medication in PSP patients according to the known different phenotypes and in comparison with patients without neurodegenerative disease.MethodsCross-sectional data of PSP and patients without neurodegenerative diseases (non-ND) were collected from three German multicenter observational studies (DescribePSP, ProPSP and DANCER). The prevalence of comorbidities according to WHO ICD-10 classification and the prevalence of drugs administered according to WHO ATC system were analyzed. Potential drug–drug interactions were evaluated using AiDKlinik®.ResultsIn total, 335 PSP and 275 non-ND patients were included in this analysis. The prevalence of diseases of the circulatory and the nervous system was higher in PSP at first level of ICD-10. Dorsopathies, diabetes mellitus, other nutritional deficiencies and polyneuropathies were more frequent in PSP at second level of ICD-10. In particular, the summed prevalence of cardiovascular and cerebrovascular diseases was higher in PSP patients. More drugs were administered in the PSP group leading to a greater percentage of patients with polypharmacy. Accordingly, the prevalence of potential drug–drug interactions was higher in PSP patients, especially severe and moderate interactions.ConclusionsPSP patients possess a characteristic profile of comorbidities, particularly diabetes and cardiovascular diseases. The eminent burden of comorbidities and resulting polypharmacy should be carefully considered when treating PSP patients.

Prescription audit and drug interactions of anti-diabetic drugs at Outpatient Department at a tertiary care teaching hospital in Eastern Nepal

Type 2 diabetes mellitus (T2DM) is the third major non-communicable disease in Nepal. Drug utilization studies help in reducing the patient’s expenditure, adverse drug reactions and drug-drug interactions. It would help in understanding of consumption of drugs including newer ones. Objective was to analyze the prescribing pattern and drug interactions of anti-diabetic drugs. A prospective cross-sectional study was conducted among patients having T2DM at Birat Medical College and Teaching Hospital (BMCTH), Biratnagar, Nepal from May 2019- August 2019. WHO core drug use indicators were used to analyze the obtained data. Descriptive statistics like mean, standard deviation, frequency and percentage were calculated using Microsoft Excel 2013. Out of 200 patients, 104 (52.0%) were females and 49.5% were from the age group of 41-60 years. Average number of drugs per patient was 5.74. Biguanides (40.7%) were the most common prescribed oral antidiabetic drugs followed by Sulfonylureas (23.3%). The percentage of drugs prescribed by generic name and from WHO essential drug list was 0.6% and 15.4% respectively. A total of 95 (47.5%) patients has potential drug-drug interaction (DDI) and it was most common in the age group of 41-60 years (43.2%). Among 95 DDI, Metformin+Amlodipine ranked in 1st position (16 encounters). Polypharmacy was prevalent in the present study. Metformin was the most commonly prescribed anti-diabetic drug. The percentage of drugs from the WHO essential medicine list and prescribed by generic names was low. Prevalence of potential DDI was high.

Prevalence of potential drug-drug interactions among intensive care unit patients receiving linezolid: a cross-sectional study.

Linezolid is commonly used in intensive care units (ICU) but has the potential to interact with other drugs. This study aimed to evaluate the prevalence of potential drug-drug interactions in ICU patients receiving linezolid. Data of ICU patients receiving linezolid were extracted and included in the Hospital Prescription Analysis Program of China, and the risk of potential drug-drug interactions between concomitant drugs and linezolid was evaluated using the Lexicomp database. A total of 3,712 ICU patients from 59 hospitals were included in the analysis, and patients received an average of 17 concomitant drugs. A total of 67.9% of patients had potential drug-drug interactions. Patients receiving concomitant drugs with risk ratings of "X", "D", and "C" categories were 20.8%, 30.4%, and 35.1%, respectively. Opioids were the most frequently prescribed drug class with drug-drug interactions (DDIs) in the "X" category, whereas butorphanol, metoclopramide, and sufentanil were the most contraindicated concomitant drugs. ICU patients receiving linezolid have a high prevalence of potential drug-drug interactions, and efforts should be made to better recognize and manage this risk.

S967 Real-World Prevalence of Potential Drug-Drug Interactions Associated With Oral Advanced Therapies Indicated for Ulcerative Colitis

S967 Real-World Prevalence of Potential Drug-Drug Interactions Associated With Oral Advanced Therapies Indicated for Ulcerative Colitis

A meta-analysis assessing the prevalence of drug-drug interactions among hospitalized patients.

Drug-drug interactions (DDIs), particularly in hospitalized patients can result in adverse drug events and unfavorable health consequences. The aim of this meta-analysis is to provide up-to-date evidence on the prevalence of clinically evident adverse drug events due to DDIs in hospitalized patients. Data from Scopus, PubMed, Cochrane and Web of Science were extracted using these keywords (Drug interaction/drug-drug interactions, Hospital/ hospitals, Adverse drug event, Hospitalized patients, inpatient, Department, Hospital stay, Harm, Mortality, death). The studies that include Observational studies on hospitalized patients, reporting potential DDIs using an electronic database, and reporting the clinically observed adverse drug interactions (ADI) through symptoms, signs or Laboratory tests are included. Using Open meta-Software (version 12.11.14), the incidence of clinically evident DDIs among hospitalized patients was determined and shown in a forest plot. Only 15 of the 8261 articles found through a literature search met the inclusion criteria and reported the desired outcome. The pooled prevalence of potential drug-drug interactions is 64.9% (CI 95% 0.618-0.736). While clinically evident DDIs have a pooled frequency of 17.17% (CI 95% 0.133-0.256). The issue of DDIs remains a significant concern in hospitalized patients, with a notable rise in their prevalence. This meta-analysis encompassed a greater quantity of studies and demonstrated a heightened proportion of drug-drug interaction prevalence in comparison to the percentages reported in the previously published meta-analysis.

Prevalence of potential drug-drug interactions with ritonavir-containing COVID-19 therapy.

BACKGROUND: Patients with COVID-19 receiving ritonavir-containing therapies are at risk of potential drug-drug interactions (pDDIs) because of ritonavir's effects on cytochrome P450 3A4. OBJECTIVE: To assess the prevalence of pDDIs with ritonavir-containing COVID-19 therapy in adults with COVID-19 using the Optum Clinformatics Data Mart database. METHODS: In this retrospective, observational cohort study, patients with COVID-19 aged 18 years or older prescribed cytochrome P450 3A4-mediated medications with supply days overlapping the date of COVID-19 diagnosis between January 1, 2020, and June 30, 2021, were classified as having pDDIs. pDDI was classified as contraindicated, major, moderate, or mild using established drug interaction resources. Prevalence of pDDIs with ritonavir-containing COVID-19 therapy was estimated for the entire cohort and in patient groups with high risk of severe COVID-19 progression or pDDIs. Actual COVID-19 treatments received by the patients, if any, were not considered. Outcomes were presented descriptively without adjusted comparisons. RESULTS: A total of 718,387 patients with COVID-19 were identified. The age-sex standardized national prevalence of pDDIs of any severity was estimated at 52.2%. Approximately 34.5% were at risk of contraindicated or major pDDIs. Compared with patients without pDDI, patients exposed to pDDIs were older and more likely to be female, reside in long-term care facilities, and have risk factors for progression to severe COVID-19. Higher prevalence of major/contraindicated pDDIs was observed in older patients (76.1%), female patients (65.0%), and patients with multiple morbidities (84.6%). CONCLUSIONS: Study findings demonstrate that more than one-third of patients with COVID-19 were at risk of significant pDDIs if treated with ritonavir-containing COVID-19 therapy and highlight the need to assess all patients with COVID-19 for pDDIs. Ritonavir-based therapies may not be appropriate for certain patient groups, and alternative therapies should be considered. DISCLOSURES: Drs Igho-Osagie, Puenpatom, and Grifasi Williams are employees of Merck Sharp & Dohme LLC, a subsidiary of Merck & Co., Inc. Dr Song and Ms He are employees of Analysis Group, Inc., and served as paid consultants for Merck Sharp & Dohme LLC, a subsidiary of Merck & Co., Inc. Drs Yi and Wang, and Mr Berman, and Ms Gu were employees of Analysis Group, Inc., at the time of study conduct. Financial support for this study was provided by Merck Sharp & Dohme LLC, a subsidiary of Merck & Co., Inc. The study sponsor was involved in the design and conduct of the study; collection, management, analysis, interpretation of data; preparation, review, or approval of the manuscript; and decision to submit the manuscript for publication.

Prevalence of Potential Drug-drug Interactions With Ritonavir-containing COVID-19 Therapy in the United States: An Analysis of the National Health and Nutrition Examination Survey

PurposeThe evolving epidemiology and treatment landscape of COVID-19 necessitates research into potential drug-drug interactions (pDDIs) from the use of new treatments for COVID-19, particularly those that contain ritonavir, a potent inhibitor of the cytochrome P350 3A4 (CYP3A4) metabolic pathway. In this study, we assessed the prevalence of pDDIs between medications for chronic conditions metabolized through the CYP3A4 metabolic pathway and ritonavir-containing COVID-19 medications in the US general population. MethodsThis study combined National Health and Nutrition Examination Survey (NHANES) waves 2015 to 2016 and 2017 to March 2020 to observe pDDI prevalence between ritonavir-containing therapy and coadministered medications among US adults 18 years or older. CYP3A4-mediated medications were identified from affirmative medication questionnaire response and associated prescription examination by surveyors. CYP3A4-mediated medications with associated pDDIs with ritonavir and assessed pDDI severity (minor, major, moderate, and severe) were obtained from the University of Liverpool's COVID-19 online drug interaction checker, Lexicomp, and US Food and Drug Administration fact sheets. pDDI prevalence and severity were evaluated by demographic characteristics and COVID-19 risk factors. FindingsA total of 15,685 adult participants were identified during the 2015 to 2020 NHANES waves. Survey participants used a mean (SD) of 2.7 (1.8) drugs with likelihood of a pDDI. The weighted prevalence of major to contraindicated pDDIs among the US population was 29.3%. Prevalence rates among those 60 years and older, with serious heart conditions, with moderate chronic kidney disease (CKD), with severe CKD, with diabetes, and with HIV were 60.2%, 80.7%, 73.9%, 69.5%, 63.4%, and 68.5%, respectively. Results remained largely unchanged after removal of statins from the list of drugs associated with ritonavir-based pDDIs. ImplicationsApproximately one-third of the US population would be at risk for a major or contraindicated pDDI should they receive a ritonavir-containing regimen, and this risk increases significantly among individuals 60 years or older and with comorbidities such as serious heart conditions, CKD, diabetes, and HIV. The state of polypharmacy in the US population and the quickly changing COVID-19 landscape indicate significant risk of pDDIs among those requiring treatment with ritonavir-containing COVID-19 medications. Practitioners should take polypharmacy, age, and comorbidity profile into account when prescribing COVID-19 therapies. Alternative treatment regimens should be considered, especially for those of older age and those with risk factors for progression to severe COVID-19.

Prevalence of Potential Drug-Drug Interactions Among Hypertensive Pregnant Women Admitted to a Tertiary Care Hospital.

The aim is to determine the frequency of potential drug-drug interactions (pDDIs) and to analyze the clinically relevant drug interactions among hypertensive pregnant women. This was an observational, cross-sectional study conducted at a tertiary care hospital. The prescriptions of the hypertensive pregnant women admitted to the hospital from June 2021 to December 2021 were analyzed for potential drug-drug interactions using the database from Lexicomp ® Solutions android mobile application version 7.5.4(Wolters Kluwer, The Netherlands). A total of 127 patients were evaluated during the study period of 6 months, of which 70 (55.12%) had pDDIs. The total number of pDDIs was 85, of which 70 (82.35 %) were clinically relevant interactions with the majority of them having moderate severity (81.17%) followed by minor severity (17.65%) and major severity (1.18%). The most frequently interacting pDDIs were between Labetalol and Lornoxicam (42.35%), followed by Labetalol and Diclofenac (22.35%). This study highlights the high prevalence of potential drug interactions among hypertensive pregnant women and the need for rational drug use and strict vigilance in their monitoring.

High prevalence of potential psychotropic drugs interactions among Brazilian dental patients.

To determine the prevalence of potential drug-drug interactions involving psychotropics prescribed by dentists, and dispensed by the public healthcare system, as well as to describe the severity and level of evidence of those interactions in the state of Minas Gerais, Brazil. We conducted data analysis from pharmaceutical claims in which dental patients received systemic psychotropics in 2017. Data from the Pharmaceutical Management System provided the drug dispensing history of the patients, allowing the identification of those on concomitant medication use. The outcome was the occurrence of potential drug-drug interactions, which were detected according to IBM Micromedex®. Independent variables were the patient's sex, age, and the number of drugs used. Descriptive statistics was performed using SPSS v. 26. Overall, 1480 individuals were prescribed psychotropic drugs. The prevalence of potential drug-drug interactions was 24.8% (n=366). The total of 648 interactions was observed and, most of which were of major severity (n=438, 67.6%). Most interactions occurred in female individuals (n=235; 64.2%), with 46.0 (±17.3) years-old, concurrently taking 3.7 (±1.9) drugs. A substantial proportion of dental patients presented potential drug-drug interactions, mostly of major severity, which might be life-threatening.

Prevalence of Polypharmacy and Potential Drug-Drug Interactions Associated with Risk Factors in the Era of HIV Integrase Inhibitors: A Prospective Clinical Study.

People living with human immunodeficiency virus (PLWH), with the availability of modern antiretroviral drugs, have multiple comorbidities, which increase the risk of polypharmacy and potential drug-drug interactions (PDDIs). This is a particularly important issue for the aging population of PLWH. This study aims to review the prevalence and risk factors for PDDIs and polypharmacy in the era of HIV integrase inhibitors. A cross-sectional, two-center, prospective observational study was conducted on Turkish outpatients between October 2021 and April 2022. Polypharmacy was defined as the use of ≥5 non-HIV medications, excluding over-the-counter (OTC) drugs, and PDDIs were classified using the University of Liverpool HIV Drug Interaction Database (harmful/red flagged and potentially clinically relevant/amber flagged). The median age of the 502 PLWH included in the study was 42 ± 12.4 years and 86.1% were males. Most individuals (96.4%) were given integrase-based regimens (unboosted 68.7% and boosted 27.7%). In total, 30.7% of individuals were taking at least one OTC drug. The prevalence of polypharmacy was 6.8% (9.2% when OTC drugs were included). During the study period, the prevalence of PDDIs was 1.2% for red flag PDDIs and 16% for amber flag PDDIs. CD4+ T cell count >500 cells/mm3, number of comorbidities ≥3, comedication with drugs affecting blood and blood-forming organs, cardiovascular drugs, and vitamin/mineral supplements were associated with red flag or amber flag PDDIs. Drug interaction prevention is still important in HIV care. Individuals with multiple comorbidities should be closely monitored for non-HIV medications to prevent PDDIs.

High Prevalence of Potential Drug-Drug Interactions Among Patients Treated with Off-label Therapies for COVID-19

Background: During the first wave of the COVID-19 pandemic, severe patients were treated with the off-label drugs hydroxychloroquine and lopinavir/ritonavir. The aim of the study was to determine the prevalence of potential drug-drug interactions (DDIs) between hydroxychloroquine, lopinavir/ritonavir and concomitant medications used by hospitalized patients treated for COVID-19 in Costa Rica.
 Methods: We included all patients that received lopinavir/ritonavir or hydroxychloroquine as treatment for COVID-19. Clinical pharmacists reviewed the prescription profile of each patient and determined the probability and severity of any DDI through two databases (The Lexi-Interact program) and the Micromedex online interaction checker. A logistic regression model was used to identify variables associated with the occurrence of potential DDIs.
 Results: We identified a total of 108 potential DDIs in 34 inpatients (n=34). At least one of these DDIs occurred in 27 patients (79.4%; 95% CI: 65.8-92.9%). A total of 70 DDIs (64.8%) were classified as clinically relevant (grade D or X) by the clinical pharmacists. Only the number of concomitant drugs was associated with the occurrence of a probable DDI. The most common drugs associated with any DDI were fentanyl (n=12, 11.1%), midazolam (n=11, 10.2%), and insulin (n=10, 10.2%).
 Conclusion: A large proportion of patients treated with hydroxychloroquine and lopinavir/ritonavir for severe COVID-19 were at risk for clinical meaningful DDIs.

Prevalence of Potential Drug-Drug Interactions in Neonatal Intensive Care Unit of a Tertiary Care Hospital: A Prospective Observational Study

Hospitalized neonates in neonatal intensive care unit (NICU) are usually exposed to great number of drugs and they are susceptible to adverse outcomes due to their immature functioning organs and reasons like inappropriate dosing or choice of medicines. We aimed to assess the prevalence and characteristics of potential drug- drug interactions (pDDIs) in the NICU. In this prospective observational study, case sheets of neonates who were in the NICU for more than 24 hours and were administered with at least two drugs were analysed for pDDIs by using Lexicomp database. All pDDIs were classified according to their severity, reliability, risk level and their underlying mechanisms. Potential predictors and potential outcomes of pDDIs were also evaluated. We found that 66.2% of neonates were exposed to at least one pDDI. Total of 902 pDDIs comprising of 70 distinct pDDIs were identified of which 88% were moderate in severity. 11.8% and 0.2% of them were major and minor respectively. Most of pDDIs belonged to category C (61.4%) and category D (30%) of risk level. Majority of interactions had pharmacodynamic mechanism (65.7%) and fair scientific evidences (68.6%). The most common potential adverse drug events included increased sympathomimetic effects, nephrotoxicity and alteration of serum concentration of drugs. Systemic anti-infective were involved in majority of interactions. pDDIs were more prevalent in neonates with gestational age of <32 weeks, >11 days of hospital stay and those who received >11 concomitant drugs. Identification of pDDIs and monitoring the neonates for potential adverse outcomes is mandatory especially in high risk conditions to avoid or minimize the actual harm.

A Cross Sectional Study About the Prevalance of Potential Drug-drug Interactions in Various Inpatient Departments of a South Indian Government Headquarters Hospital using Prescription Analysis

Abstract: Objectives: This study is focused on to identify the prevalence of potential drug-drug interactions among various inpatients’ departments of a government headquarters hospital in Tamil Nadu, India. Segregation of potential DDIs which were found in patients’ prescriptions according to their severity and examining the distribution of those DDIs in relevance to demographic features like gender and age are other objectives of this study. Materials and Methods: A prospective observational cross-sectional study was conducted with the periodicity of six months (between September 2021 and February 2022) in a government headquarters hospital of the state Tamil Nadu. This research includes six hundred and fifty- four (654) inpatients, including both male and female patients from various departments like general medicine, surgery, pediatric, psychiatric, post operative wards. Patients with serious illness and those who are not willing to participate were excluded from this study. Results: The average number of drug interaction per patient prescription was said to be 1.09. Number of prescriptions with 1 drug-drug interaction are 219. Fourteen prescriptions were found with more than six drug-drug interactions. Out of 718 potential DDIs, only 2 were contraindicated. The number of major DDIs was 335. Moderate drug interactions outnumbered minor drug interactions in our study. This study identified 2 contraindicated DDIs which were attributed to the same drug pair (ceftriaxone and ringer’s lactate solution) in two different pediatric prescriptions. Conclusion: Polypharmacy and drug-drug interactions are the widely recognized drug related problems. By mitigating polypharmacy issue, drug-drug interactions in prescriptions can be attenuated. Key words: Drug-drug interactions, Severity, Inpatients, Polypharmacy, Micromedex, Prescriptions.

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

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. The objective of the study was to determine the prevalence of pDDIs among outpatients and identify factors associated with their occurrence. 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. 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. 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.

Potential Drug-drug Interaction among the Patients Admitted in Intensive Care Units of a Tertiary Care Centre: A Descriptive Cross-sectional Study.

Drug interactions are one of the major contributors to increase hospital stay, inflate health care expenses, and cause serious adverse events and end-organ damage. Patients admitted to the intensive care unit are already critically sick and are at greater risk of these adverse outcomes. The study aimed to find out the prevalence of potential drug-drug interactions in the Intensive Care Units of a tertiary care centre. A descriptive cross-sectional study was conducted among the patients admitted in the Intensive Care Unit of a tertiary care hospital from April-June 2019. Ethical approval was taken from the Institutional Review Board at the institute (Reference number: 399). Convenience sampling method was used. Data was collected using proforma and potential drug-drug interactions were identified using Lexicomp® drug-interactions version 1.1 (Wolters Kluwer). All the drug interactions identified were classified and the severity scale of interactions was also defined. Statistical Package for the Social Sciences version 17.0 was used for data analysis. Point estimate at 95% Confidence Interval was calculated along with frequency, percentage, mean, standard deviation, and mode. Out of 101 patients, the prevalence of the drug-drug interaction was found to be 90 (89.11%) (83.04-95.18 at 95% Confidence Interval). A total of 490 drug-drug interactions were identified. In severity scale, it was seen that 311 (63.46%) were of moderate severity and 303 (61.83%) of drug interactions were categorised as category C in risk rating. Prevalence of potential drug-drug interactions was higher compared to similar published literature. The most common drug with potential interaction was fentanyl and among pairs was fentanyl plus paracetamol. drug interactions; intensive care units; Nepal; software.

Drug interactions in hospital prescriptions in Denmark: Prevalence and associations with adverse outcomes.

PurposeWhile the beneficial effects of medications are numerous, drug–drug interactions may lead to adverse drug reactions that are preventable causes of morbidity and mortality. Our goal was to quantify the prevalence of potential drug–drug interactions in drug prescriptions at Danish hospitals, estimate the risk of adverse outcomes associated with discouraged drug combinations, and highlight the patient types (defined by the primary diagnosis of the admission) that appear to be more affected.MethodsThis cross‐sectional (descriptive part) and cohort study (adverse outcomes part) used hospital electronic health records from two Danish regions (~2.5 million people) from January 2008 through June 2016. We included all inpatients receiving two or more medications during their admission and considered concomitant prescriptions of potentially interacting drugs as per the Danish Drug Interaction Database. We measured the prevalence of potential drug–drug interactions in general and discouraged drug pairs in particular during admissions and associations with adverse outcomes: post‐discharge all‐cause mortality rate, readmission rate and length‐of‐stay.ResultsAmong 2 886 227 hospital admissions (945 475 patients; median age 62 years [IQR: 41–74]; 54% female; median number of drugs 7 [IQR: 4–11]), patients in 1 836 170 admissions were exposed to at least one potential drug–drug interaction (659 525 patients; median age 65 years [IQR: 49–77]; 54% female; median number of drugs 9 [IQR: 6–13]) and in 27 605 admissions to a discouraged drug pair (18 192 patients; median age 68 years [IQR: 58–77]; female 46%; median number of drugs 16 [IQR: 11–22]). Meropenem‐valproic acid (HR: 1.5, 95% CI: 1.1–1.9), domperidone‐fluconazole (HR: 2.5, 95% CI: 2.1–3.1), imipramine‐terbinafine (HR: 3.8, 95% CI: 1.2–12), agomelatine‐ciprofloxacin (HR: 2.6, 95% CI: 1.3–5.5), clarithromycin‐quetiapine (HR: 1.7, 95% CI: 1.1–2.7) and piroxicam‐warfarin (HR: 3.4, 95% CI: 1–11.4) were associated with elevated mortality. Confidence interval bounds of pairs associated with readmission were close to 1; length‐of‐stay results were inconclusive.ConclusionsWell‐described potential drug–drug interactions are still missed and alerts at point of prescription may reduce the risk of harming patients; prescribing clinicians should be alert when using strong inhibitor/inducer drugs (i.e. clarithromycin, valproic acid, terbinafine) and prevalent anticoagulants (i.e. warfarin and non‐steroidal anti‐inflammatory drugs ‐ NSAIDs) due to their great potential for dangerous interactions. The most prominent CYP isoenzyme involved in mortality and readmission rates was 3A4.

Potential Drug-drug Interactions among Hospital Discharge Prescriptions in a Tertiary Care Centre of Nepal: A Descriptive Cross-sectional Study.

In our setup, potential drug-drug interactions are overlooked in routine clinical practice. In general, most of the discharges are handwritten in the developing world, and the discharge prescriptions are not checked with the database for potential drug-drug interactions checker. This study aimed to determine the prevalence of potential drug-drug interactions in the prescribed drugs in clinical practice in a tertiary care centre of Nepal. A descriptive cross-sectional study was conducted in a tertiary care center from October 2019 to December 2019. Ethical approval was taken from the Institutional Review Committee (Reference number: 394(6-11)E2/075/76). Through simple random sampling, the data about drug prescription was collected from the patient discharge records of the Department of Internal Medicine. The potential drug interactions were checked by using Lexicomp® drug interactions. Data was analysed using Statistical Package for the Social Sciences version 20.0. Point estimate at 95% Confidence Interval was calculated along with frequency, percentage, mean, standard deviation and mode. Among 382 discharge prescriptions, the prevalence of potential drug-drug interactions was 299 (78.3%) (74.1-82.4 at 95% Confidence Interval). A total of 1519 drug interactions with a mean of 5.08±3.89 drug interactions per prescription was identified. The major, moderate and minor drug-drug interactions according to the severity were found to be 163 (10.7%), 1162 (76.5%), and 178 (11.7%) respectively. The prevalence of potential drug-drug interactions is high among the patients on discharge compared to similar studies. Use of drug-drug interactions checker databases before discharge with computer-based discharge prescriptions is recommended.