The prevalence of major potential drug-drug interactions at a University health centre pharmacy in Jamaica

Evaluation of Potential Drug Interactions with AiDKlinik® in a Random Population Sample

Purpose

Undesirable drug interactions are frequent, they endanger the success of therapy, and they lead to adverse drug reactions. The present study aimed to evaluate statistically potentially drug interactions in a locally circumscribed, random sample population.

Patients and Methods

In a random sample population of 264 patients taking medications, we performed analyses with the drug information system AiDKlinik^®. Statistical analysis was performed using SAS version 9.4.

Results

Statistically potentially drug interactions were recorded in 82/264 (31.1%) subjects, including 39/82 (47.56%) men, and 43/82 (52.43%) women (χ²= 0.081; p = 0.776). The average number of potential possible interactions detected per person was 1.60 ± 1.21. The regression model with the variables age, body-mass-index and number of long-term-medications shows a significant association between the number of long-term medications taken and the number of moderately severe and severe reactions to drug interactions (F(3.239) = 28.67, p < 0.0001; (t(239) 8.28; p < 0.0001)). After backward elimination, the regression model showed a significant interaction with the number of long-term medications (t (240) = 8.73, p < 0.0001) and body-mass-index (t (240) = 2.02, p = 0.0442). In descriptive analysis, the highest percentages of potential drug interactions occurred in 42/82 (51.22%) subjects with body mass indices (BMIs) >25 kg/m² and in 28/82 (34.15%) subjects aged 61–70 years.

Conclusion

Number of long-term medications use, age, and obesity may lead to increased drug–drug interactions in a random population sample.

Assessment of Drug Interactions with Online Electronic Checkers in Multi-Pathological Patients

INTRODUCTION

Multi-pathological patients are at high risk of drug interactions and side effects. We aimed to assess the usefulness of 3 online drug interaction checkers.

METHODS

In a cross-sectional study, carried out in the Medicine Department of Hospital General of Castellon, Spain, in February 2020, we assessed drug interaction detection with 3 online electronic checkers, Drugs.com, Lexicomp®, and Medscape, and compared results obtained with the 3 tools. From every hospitalized patient, we obtained the list of drugs he or she had been taking until admission. Bivariable tests were used for analysis. p values <0.05 were considered significant.

RESULTS

We included data from 134 patients; 68 (51%) were male; median (and interquartile range) of their age was 82 (76-88) years. A total of 1,082 substance drugs were entered in the checkers. The number of highest grade interactions found with every program was Drugs.com 85, Lexicomp® 33, and Medscape 67. Positive correlations were found between age and number of drug substances prescribed (p = 0.009) and between number of drug substances prescribed and interactions found with any of the 3 checkers (p < 0.001 in all 3 cases). Regarding highest grade interactions, agreement among all 3 checkers was poor.

CONCLUSIONS

The 3 online checkers we assessed found a large number of interactions. The 3 programs gave very discrepant results. Impact on Practice Statements: The analyzed programs, Drugs.com, Lexicomp®, and Medscape Interactions, found a large number of drug interactions in the studied patients. The 3 programs gave very discrepant results among them.

The Prevalence of Selected Potential Drug-Drug Interactions of Analgesic Drugs and Possible Methods of Preventing Them: Lessons Learned From the Analysis of the Real-World National Database of 38 Million Citizens of Poland

Introduction: Drug-drug interactions may lead to poor health outcomes, as well as increased costs and utilization of healthcare services. Unfortunately, real-world data continuously prove high prevalence of potential drug-drug interactions (pDDIs) worldwide. Among identified drivers, ageing, multimorbidity and polypharmacy play a very important role. With these factors being widespread, the need for implementation of strategies minimizing the burden of pDDIs becomes an urgency. This, however, requires a better understanding of the prevalence of pDDIs and the underlying causative factors.

Aim of study: To assess the real-world prevalence of pDDIs and its characteristics in the general population of Poland, using analgesic drugs as a model, and to find out whether pDDIs are caused by prescribing coming from the very same prescribers (co-prescribing).

Methods: A retrospective analysis of the 2018 dispensation data of the National Health Fund (NHF) - the only Polish public healthcare payer organization with nationwide coverage. We searched for selected pDDIs of non-steroidal anti-inflammatory drugs (NSAIDs) with antihypertensives, other NSAIDs (double use), oral glucocorticoids, oral anticoagulants, selective serotonin reuptake inhibitors (SSRIs), serotonin–norepinephrine reuptake inhibitors (SNRIs), and antiplatelet drugs; as well as opioides with SSRIs, SNRIs, gabapentinoids, and benzodiazepines. A pDDI was deemed present if two drugs standing in a possible conflict were dispensed within the same calendar month.

Results: Out of 38.4 million citizens of Poland, 23.3 million were dispensed prescribed drugs reimbursed by NHF in 2018. In this cohort, we have identified 2,485,787 cases of analgesic drug pDDIs, corresponding with 6.47% of the Polish population. Out of these, the most prevalent pDDI was caused by “NSAIDs + antihypertensives” (1,583,575 cases, i.e., 4.12% of the Polish population), followed by “NSAIDs + NSAIDs” (538,640, 1.40%) and “NSAIDs + glucocorticoids” (213,504, 0.56%). The most persistent pDDIs among those studied were caused by “Opioids + Gabapentinoids” (2.19, 95%CI: 2.16–2.22 months). On average, 76.63% of all cases of pDDIs were caused by drugs prescribed by the very same prescribers.

Conclusion: Based on high-quality, nationwide data, we have found a high prevalence of analgesic drugs-related pDDIs in Poland. Over ¾ of the identified pDDIs were caused by co-prescribing, i.e., prescriptions issued by the same prescribers. The significance of the problem, illustrated with our findings on analgesic drugs-related pDDIs in Poland, deserves much more scientific and policymaker attention.

Prevalence of Drug Interaction in Severely Obese Individuals and Associated Factors: Baseline Results from a Clinical Trial

The prevalence of obesity is increasing worldwide and is commonly associated with comorbidities. The use of several drugs is often necessary, which leads to Potential Drug Interactions (PDI) that may increase the morbidity and mortality. This study aimed to analyze the prevalence of drug interaction and its association with socio-demographics, health status, and drug use in severely obese individuals. Baseline data from a randomized clinical trial registered at Clinicaltrial.gov (NCT02463435) were used. A total of 150 individuals aged 18–65 years with a body mass index of 35 kg/m2 were included. The outcome variable was the presence of PDI, and the explanatory variables were divided into the following four levels: socio-demographic, lifestyle, health, and medication use. The prevalence of PDI was 50% (n = 75) (95% CI 41–58). The variables associated with drug–drug interactions in the multiple analyses were arterial hypertension (PR 1.83, 95%, CI 1.10–3.04), polypharmacy (PR 3.12, 95%, CI 2.17–4.50), and diabetes mellitus (PR 0.60, 95%, CI 0.45–0.81). The risk factors for the occurrence of drug interaction were the presence of diabetes mellitus, hypertension, and polypharmacy.

[Potential drug interactions in adults and the elderly in primary health care]

The objective of the present study was to characterize the potential drug interactions (PDI), estimating the factors associated to their occurrence in adults and the elderly assisted by the Programa Médico de Família de Niterói, Rio de Janeiro. This is a sub-study of STUDY DIGITALIS, which included individuals enrolled in the Niteroi Family Medical Program (45-99 years). In this study, 341 individuals with a prescription of two or more drugs were analyzed. The classification of PDI followed MICROMEDEX. There were 113 different interactions. Of the total number of individuals, 63.6% had at least one PDI. The variables with higher probability of PDI were: lower level of schooling; income less than R$800.00; absence of health plan; previous diagnosis of hypertension and diabetes; use of 5 or more medications prescribed. After adjustment, the variables previous diagnosis of hypertension and diabetes and use of 5 or more prescription drugs remained statistically significant. Careful management of primary care treatment with monitoring is important in patients with PDI, especially in patients who are more susceptible.

Effect of an educational intervention on the number potential drug-drug interactions

Background

The objective of this study was to evaluate effect of an Educational intervention on the number Potential Drug-Drug Interactions in the Emergency Hospital.

Methods

The prevalence and structure of Major Drug-Drug Interactions at Emergency care Hospitals of Aktobe, Uralsk, Atyrau cities (Kazakhstan) were studied (pharmacoepidemiological, cross-sectional study). Educational interventions were developed and implemented to improve pharmacotherapy in the Cardiology Department of the Aktobe Emergency Hospital, followed by an assessment of their effect.

Results

The effect of educational interventions was revealed, which led to a significant decrease in the indicators of drug interactions of the Major Drug-Drug Interactions by 18.2% (OR: 0.45; 95% CI, 0.25-to-0.82) in the cardiological patients of the Emergency Care Hospital of Aktobe city compared to the Regional Cardiology Center of Uralsk.

Conclusion

The implementation of educational pharmacotherapy programs decreased the number of clinically significant drug interactions in the Cardiology Department of Emergency Hospitals.