Prevalence and predictors of potential drug-drug interactions in patients of internal medicine wards of a tertiary care hospital in India

Study on risk factors and associated drug related problems in patients with stroke

BACKGROUND

The second most common cause of death and disability worldwide is stroke. Drug-related problems (DRPs) can arise during any step of the medication process, whether it involves prescribing, transcribing, dispensing, or administering drugs. The purpose of this study was to assess risk factors and associated DRPs in patients with stroke.

METHODS

A cross-sectional study was conducted involving patients who had been diagnosed with stroke for 3 months using a purposive sampling technique at Annapurna Hospital. Data on demographics, comorbidities, and medications were collected through patient medical records, medicine Cardex, and nursing notes. DRPs were identified and classified using the Hepler-Strand classification system. Medscape software was used to assess potential drug-drug interactions (pDDIs). Descriptive statistics, chi-square tests, and binary logistic regression were performed.

RESULTS

Among the 111 patients, the mean age was 58.72 ± 15.68 years. The majority of strokes were ischemic (68.5%), with the middle cerebral artery being the most commonly affected (24.3%). Males were more commonly affected (76.6%) than females (23.4%). Hypertension was the most prevalent comorbidity (61.3%), followed by diabetes mellitus (27.0%) and hyperlipidemia (21.6%). Hyperlipidemia was significantly associated with risk factors for ischemic stroke. The study found that 91.9% of stroke patients experienced DRPs, with pDDIs being the most common type (91.09%). The severity of pDDIs was predominantly categorized as "monitor closely" (73.2%). The use of more than 10 medications was a significant predictor for high-severity pDDIs.

CONCLUSION

The study concludes that polypharmacy is a significant predictor for high-severity pDDIs, highlighting the need for careful consideration when adding new medications to a patient's therapy. The high rate of pDDIs (91%) emphasizes the critical role of clinical pharmacists in identifying and mitigating these interactions to prevent further drug-related complications in stroke patients. Further research is needed to explore interventions to reduce DRPs.

CLINICAL TRIAL NUMBER

Not applicable.

A retrospective study on potential drug‒drug interactions in patients with severe asthma receiving biological therapy: a single-center experience

BACKGROUND

Prevalence of potential drug-drug interactions (pDDIs) in adult patients with severe asthma on biological therapy and their clinical significance have not been fully addressed, thus the aim of this study was to investigate them.

METHODS

In this retrospective observational study, patients who were diagnosed with severe asthma and to whom biological therapy was prescribed between September 2015 and December 2020, were enrolled. The study was conducted at the Department of Allergic and Obstructive Pulmonary Diseases, Clinic for Lung Diseases Jordanovac, Clinical Hospital Center Zagreb. Data on demographic characteristics as well as concomitant medication were collected. The analysis of pDDIs was conducted via Lexicomp® online software. Interactions of significance levels A and B were only recorded, while those of levels C, D and X were further analysed. The collected data was processed via Microsoft Excel 365 software.

RESULTS

60 adult patients, 60% female and 40% male, with median age of 56.2 years, were enrolled. The incidence of pDDIs was 86.67%. Total number of pDDIs detected was 518, out of which 43.24%, 45%, 4.44% and 7.3% of clinical significance B, C, D and X. Interactions of level C, D and X were recorded in, as follows: 83.33%, 25% and 33.33% patients with an average of 4.66, 1.53 and 1.9 interactions per patient. Only 13.33% of the patients had none of the potential clinically significant DDI. Most drug pairs contained at least one antiasthmatic drug. Muscarinic receptor antagonists, oral corticosteroids, β2 agonists and methylxanthines showed potential of entering into clinically significant DDIs, while leukotriene antagonists and biologicals showed no potential for the above.

CONCLUSION

Prevalence of potential drug-drug interactions in patients with severe asthma on biological therapy is high. The majority of identified interactions have moderate to high level of clinical significance. Their identification, prevention and resolution could contribute to optimizing therapy, maximizing its therapeutic effect and avoiding undesirable adverse events.

Clinical Pertinence and Determinants of Potential Drug-Drug Interactions in Chronic Kidney Disease Patients: A Cross-sectional Study

Background: Chronic kidney disease (CKD) is one of the major health issues effecting around 15% of world population, and its further complications has raised the need of polypharmacy for management. But this polypharmacy also upsurges the risk of potential drug-drug interactions (pDDIs) in CKD patients, which may further be responsible for increased morbidity and mortality. Objective: The main objective is therefore to evaluate the distribution, severity, causes, associated drug interactions, and clinical relevance of determination of pDDIs in CKD patients. Methods: Medical files of CKD patients examined at nephrology department, Maharishi Markandeshwar Institute of Medical Sciences and Research (MMIMSR), Mullana, between December 2022 and May 2023 were cross-sectionally assessed for this study. Medscape drug interaction checker was used to study patient profiles for pDDIs, and suggestive measures to minimize those pDDIs were studied using DDInter to ensure better clinical decision-making and patient safety. IBM SPSS (version 24) was utilized for statistical analysis. Results: The data reveal that 74.5% of the 200 medical files being evaluated had 839 pDDIs in total, out of which nearly 78.3% of patients had moderate, 15.6% had minor, and 6.07% had serious interactions. The potential adverse outcomes of pDDIs included an irregular heartbeat, hypokalemia, central nervous system (CNS) adverse effects, hypoglycemia, and a decline in therapeutic efficacy. The prevalence of pDDIs was discovered to be substantially correlated with age ≥60 years, (odds ratio [OR] = 0.65; 95% CI = 0.4-0.9; P = 0.040), length of stay ≥10 days (OR = 4.0; 95% CI = 1.29-6.1; P = 0.016), and number of prescribed drugs ≥10 (OR = 5.5; 95% CI = 2.45-10.69; P = 0.004). Conclusion: Patients with CKD have a high incidence of pDDIs (mainly mild to moderate). Older age, duration of hospital stays, and polypharmacy all raise the risk of pDDIs. Healthcare professionals (physicians and clinical pharmacist) should use drug interaction checker software programs like Medscape and DDInter to acquire knowledge about different pDDIS and their alternative measures so that the associated adverse drug reactions (ADRs) can be controlled and rational drug combination can be prescribed for management of CKD ensuring better patient care.

Predictors of potential clinically harmful drug-drug interactions at the medical wards in the University of Benin Teaching Hospital, Benin City

Drug-drug interactions are preventable causes of adverse events. Different factors have been recognized as important predictors of drug-drug interactions but few studies have addressed these predictors in patients admitted into medical wards of a tertiary hospital in Nigeria hence this study. This was a retrospective study conducted using case records of patients admitted into the medical wards between January 1 and December 31, 2020. Patients were selected using a systematic random sampling method. Socio-demographic details including age, gender, number of comorbidities, and number of medications prescribed and diagnosis were collected on days 1, 3, and at discharge. Potential drug-drug interactions were checked using Lexi-interact® software. Analysis was set at p < 0.05. A total of 430 case records were included in this study based on the inclusion criteria. Lexi-interact recorded a prevalence of (217) 50.5% on day 1, (146) 34.0% on day 3, and (290) 67.4% at discharge. A significant association (p < 0.05) was found between the potential drug-drug interactions (DDI) and an increased number of medicines prescribed on all the days of admission. Also, patients without certain infectious or parasitic diseases have reduced odds of developing DDI. There is a need for continuous monitoring of medications from admission to discharge especially in the elderly, those on multiple medications, certain infectious or parasitic diseases, and comorbidities as these impact on DDIs.

Assessment of Potential Drug-drug Interactions (pDDIs) and Their Risk Factors Among Hospitalized Cardiac Patients in a Tertiary-care Center of Central India: A Retrospective Record-based Study

Background: Patients with cardiovascular disorders (CVD) possess multiple comorbidities and are prone to be prescribed multiple drugs, thus predisposing them to various drug-drug interactions (DDIs). Objective: This study was carried out to assess the potential-DDIs (pDDIs) among the drugs prescribed to hospitalized patients with CVD and associated factors. Method: It was a retrospective study conducted with the help of the medical records department. Medical records of all the patients admitted to the cardiology department of our tertiary care center from January 1st, 2019, to December 31st, 2019, were included for analysis using Lexicomp, an up-to-date drug interaction screening tool. The pDDIs were divided into classes A, B, C, D, and X, and those belonging to classes D or X were considered clinically significant. Multiple logistic regression was used to analyze the association between the factors associated with and the occurrence of clinically significant pDDIs, with a P-value < .05 considered statistically significant. Results: Almost all the records reflected (335/338) at least 1 pDDI. A total of 4966 pDDIs were detected, of which the majority belonged to category C (75.3%), and 5.1% of pDDIs were clinically significant. The patients who were prescribed more than 10 drugs per day (OR = 2.46; 95% CI: 1.27-4.82; P = .008), prescribed parenteral formulation (OR = 1.84; 95% CI: 1.57-2.21; P < .0001), or had a diagnosis of acute coronary syndrome (OR = 2.33; 95% CI:1.1-5.12; P = .03) were associated with clinically significant pDDIs. Other factors, that is, female sex, use of fixed-dose combinations, and the triad of diabetes mellitus, hypertension, and dyslipidemia, were positively associated with clinically significant pDDIs. Conclusion: Even though every patient had at least 1 pDDI, the prevalence of clinically significant pDDIs was relatively less. Use of >10 drugs/day, parenteral formulation, patients with acute coronary syndrome were significantly associated with clinically significant pDDIs.

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

BACKGROUND

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.

METHODS

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.

RESULTS

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.

CONCLUSIONS

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.

Potential Drug-Drug Interactions in Hospitalized Medical Patients: Data From Low Resource Settings

Introduction

Adverse events related to Drug-Drug Interactions (DDIs) are among the few common reasons for hospitalization worldwide; however, they can be prevented with an efficient patient-centered system. Different mechanisms have successfully limited the prevalence of DDIs in developed countries. There are limited data regarding DDIs from limited-resource settings. Furthermore, there is no cost-effective system that has shown promising results in preventing them in this setting. This study aims to assess the frequency of potential DDIs in a low-resource setting and to check its association with different factors such as poly-pharmacy and demographics.

Methods

Through this cross-sectional study, drug charts of patients admitted to a medical unit in November 2019 were analyzed using a structured questionnaire. A list of drugs co-prescribed to each patient was entered into the Medscape Drug Interaction checker to calculate the frequency and severity of potential DDIs.

Results

The mean age of patients was 49 years, and on average, seven drugs were prescribed to each patient. Among 100 analyzed prescriptions, 400 potential DDIs were identified with a mean of 4±5.42 per patient. According to Medscape interaction checker classification, 2 DDIs were contraindicated, 28 were serious, 246 required close monitoring, and 124 were minor. The most frequently encountered drug interaction was "spironolactone with furosemide." There was a significant correlation of the occurrence of potential DDIs with increased numbers of prescribed drugs.

Conclusion

Our patient population was prescribed more drugs per patient than calculated in other settings. Poly-pharmacy is an independent risk factor for DDIs. Lastly, advancing age exposes patients to poly-pharmacy, and therefore, they are at a higher risk of developing DDIs.

Risk factors for potential drug-drug interactions in patients with myasthenia gravis

OBJECTIVES

Our aim was to determine risk factors for and frequency of potential drug-drug interactions (pDDIs) among hospitalized patients with myasthenia gravis (MG).

METHODS

This was a retrospective cross-sectional study of the-first time hospitalized MG patients or patients hospitalized because of the exacerbation of MG at the Neurology Clinic of the Clinical Center of Serbia, Belgrade. Medical records and discharge summaries of hospitalized MG patients over a 10-year period were reviewed. The pDDIs were identified by means of Micromedex, and multivariate regression methods were used to reveal potential predictors of number of pDDIs per patient.

RESULTS

The study included 687 patients with MG. In total, 2041 pDDIs were detected in 608 (88.5%) patients. Among the discovered pDDIs, 329 different pDDIs were observed. The most frequent pDDIs were pyridostigmine-prednisone (487patients/70.9%) and aspirin-prednisone (90 patients/13.1%) classified as moderate, and enalapril-potassium chloride (71patients/10.3%) classified as major pDDI. Five drugs (aspirin, insulin, prednisone, cyclosporine, metformin) were responsible for 22.6% of different pDDIs. Dyspnea, generalized form of MG, diabetes mellitus, hypertension, total number of drugs-used, use of antiplatelets were identified as the relevant risk factors for total number of pDDIs (R2 = 0.626,F = 73.797, p < 0.001), while age of patients and history of cancer were inversely correlated with such an outcome.

CONCLUSION

The frequency of the pDDIs in hospitalized MG patients is high, and adversely influenced by dyspnea, generalized MG, diabetes mellitus, hypertension, total number of drugs-used and use of antiplatelets.

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.

Medication-related problems and adverse drug reactions in Ethiopia: A systematic review

Medication-related problems (MRPs) are an important healthcare problem. This study aimed at reviewing the published literature in Ethiopia to estimate the prevalence of MRPs and to summarize associated factors. A comprehensive systematic search was conducted in PubMed, EMBASE, CINAHL, Scopus, Google Scholar, and Google databases from inception to April 2020. Articles that addressed MRPs were eligible for inclusion. Article screening, data extraction, and study quality analysis were performed independently by two reviewers. Studies targeting specific disease condition were considered as specific, while the remaining were nonspecific. The prevalence of MRPs was then computed in medians and interquartile ranges (IQR), while associated factors were summarized in a table. Of the thirty-two studies included in this review, the majority of them (n = 24) targeted MRPs, while the remaining studies (n = 8) investigated adverse drug reactions (ADRs). Studies varied in the study design, study population, and definition of MRPs and ADRs used. The overall median prevalence was 70.8% (IQR = 61.0-80.2) with a range of 16.0% to 88.7%. The median prevalence of MRPs in specific and nonspecific patients was 71.2% (IQR = 60.7-71.2) and 69.3% (IQR = 60.7-82.0), respectively. In addition, a median of 36.6% (IQR = 10.0-85.7) of patients experienced ADRs. Indication-related and effectiveness-related MRPs were commonly reported in both specific and nonspecific patients, while noncompliance MRPs were more prevalent among specific patients than nonspecific patients. Increasing age, presence of co-morbidity, and an increasing number of drugs were the commonly identified contributing factors of MRPs. The review showed that more than two-thirds of the study participants developed MRPs. Hence, an integrated approach should be designed to improve the optimal use of pharmacotherapy to reduce the burden of MRPs. Further, future research should be undertaken to prepare cost-effective and efficient prevention mechanisms to reduce or halt the development of MRPs.

Are patients with a nasally placed feeding tube at risk of potential drug-drug interactions? A multicentre cross-sectional study

Aims

The primary aims were to determine the rate of potential drug-drug interactions (pDDIs) in patients with nasally placed feeding tubes (NPFT) and the factors significantly associated with pDDIs. The secondary aim was to assess the change in pDDIs for patients between admission and discharge.

Material and methods

This multicentre study applied a cross-sectional design and was conducted in six Brazilian hospitals, from October 2016 to July 2018. Data from patients with NPFT were collected through electronic forms. All regular medications prescribed were recorded. Medications were classified according to the World Health Organization (WHO) Anatomical Therapeutic Chemical code. Drug-drug interaction screening software was used to screen patients’ medications for pDDIs. Negative binomial regression was used to account for the over dispersed nature of the pDDI count. Since the number of pDDIs was closely related to the number of prescribed medications, we modelled the rate of pDDIs with the count of pDDIs as the numerator and the number of prescribed medications as the denominator; six variables were considered for inclusion: time (admission or discharge), patient age, patient gender, age-adjusted Charlson Comorbidity Index (CCI) score, type of prescription (electronic or handwritten) and patient care complexity. To account for correlation within the two time points (admission and discharge) for each patient a generalised estimating equations approach was used to adjust the standard error estimates. To test the change in pDDI rate between admission and discharge a full model of six variables was fitted to generate an adjusted estimate.

Results

In this study, 327 patients were included. At least one pDDI was found in more than 91% of patients on admission and discharge and most of these pDDIs were classified as major severity. Three factors were significantly associated with the rate of pDDIs per medication: patient age, patient care complexity and prescription type (handwritten vs electronic). There was no evidence of a difference in pDDI rate between admission and discharge.

Conclusion

Patients with a NPFT are at high risk of pDDIs. Drug interaction screening tools and computerized clinical decision support systems could be effective risk mitigation strategies for this patient group.