Drug-drug interactions and their harmful effects in hospitalised patients: a systematic review and meta-analysis

Drug-drug interaction among elderly patients in Africa: a systematic review and meta-analysis

BACKGROUND

Elderly patients are at a heightened risk of drug-drug interactions due to their high prevalence of comorbidities, polypharmacy, and age-related physiological changes that alter drug metabolism and excretion. In Africa, these risks are compounded by unique healthcare challenges, including limited access to diagnostic tools, and high burdens of communicable diseases. The aim of this study is to estimate the prevalence of drug-drug interactions and its associated factors among elderly patients in Africa.

METHODS

Relevant research articles were identified from databases such as HINARI, Science Direct, Embase, PubMed/MEDLINE, Google Scholar, and Research Gate. Data were extracted via a Microsoft Excel spreadsheet and analyzed via STATA version 11.0. Egger regression tests and funnel plot analysis were used to check for publication bias, and the I2 statistic was used to evaluate statistical heterogeneity. Sensitivity and subgroup analyses were also conducted to identify potential causes of heterogeneity.

RESULTS

Fifteen articles were analyzed, and a total of 5651 potential drug-drug interactions (pDDIs) were identified in 1952 patients, resulting in an average of 2.89 pDDIs per patient. The overall prevalence of pDDIs among elderly patients was 52.53% (95% confidence interval (CI): 35.40, 69.66). However, the prevalence of pDDIs ranged widely from 2.8 to 90.1%. When the severity of the interactions was considered, the prevalence of pDDIs was 20.59%, 69.4%, 34.32% and 1.59% for major, moderate, minor, and contraindicated DDIs, respectively. Polypharmacy, long hospital stays, hypertension and diabetes mellitus were identified as factors associated with pDDIs among elderly patients in Africa.

CONCLUSION

DDIs are prevalent among elderly patients in Africa and are often associated with polypharmacy, prolonged hospitalizations, and the presence of chronic comorbidities, particularly hypertension and diabetes mellitus. Moderate-severity interactions were the most prevalent DDIs. The study suggests addressing this issue requires targeted interventions, including improved pharmacovigilance, enhanced prescribing practices, and integration of DDI risk assessment into routine clinical care. The study also suggests that the database itself could have modified the DDI prevalence rate. As a result, a single DDI identification database needs to be authorized; otherwise, clinical knowledge should be taken in to account when interpreting the information obtained.

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.

Concordance analysis of two databases to search for potential drug interactions in onco-hematologic patients

INTRODUCTION

Potential drug interactions exert a significant impact on patient safety, especially within intricate onco-hematological treatments, potentially resulting in toxicity or treatment failures. Despite the availability of databases for potential drug interaction investigation, persistent heterogeneity in concordance rates and classifications exists. The additional variability in database agreement poses further complexity, notably in critical contexts like onco-hematology.

AIM

To analyze the concordance of two databases for researching potential drug interaction in prescriptions for hematological patients at a University Hospital in the Midwest region of Brazil.

METHOD

Cross-sectional study developed in a Brazilian hospital. The search for potential drug interaction was conducted in Micromedex® and UpToDate®. The variables were: the presence of potential drug interaction, severity, mechanism, management, and documentation. Data was analyzed in terms of frequency (absolute and relative), Cohen's kappa, and Fleiss kappa.

RESULTS

The presence of potential drug interaction, showed a lack of concordance between the databases (k = -0.115 [95% CI: 0.361-0.532], p = 0.003). Regarding the mechanism, a strong agreement was observed (k = 0.805, p < 0.001 [95% CI: 0.550-0.941]). The management concordance showed a fair agreement, 46.8% (k = 0.22, p < 0.001 [95% CI: 0.099-0.341]). Stratifying the categories, significant concordance was observed in "Adjustment of dose + Monitoring" (k = 0.302, p = 0.018) and "Monitoring" (k = 0.417, p = 0.001), while other categories did not reach statistical significance.

CONCLUSION

Our study emphasizes the variability in potential drug interaction research, revealing disparities in severity classification, management recommendations, and documentation practices across databases.

Factors Associated with the Practice of Assessing Drug-Drug Interactions Among Pharmacists in Saudi Arabia

BACKGROUND

Drug-drug interactions (DDIs) occur when two or more drugs are administered concomitantly, changing the pharmacokinetics or pharmacodynamics of a drug's characteristics. Despite the advances in health technology, DDIs remain a concern to patient safety. This study aimed to (1) assess the knowledge, attitude, and practice of hospital and community pharmacists toward DDIs in Saudi Arabia and (2) examine factors associated with their practice.

METHODS

A cross-sectional study was conducted using an online self-administered questionnaire targeting hospital and community pharmacists working in Saudi Arabia. The study questionnaire consisted of five sections: demographics, knowledge, attitude, and practice toward DDIs, as well as pharmacy characteristics. Descriptive statistics were used to summarize the characteristics of participants as count and percentage. Chi-square tests were used to examine associations between practice variables and other independent variables.

RESULTS

A total of 131 pharmacists participated in the study. The majority were males (81.7%), aged 26-35 years (64.9%), and worked in community pharmacies (81.7%). Nearly half of the participants reported optimal practice regarding checking drug interactions before dispensing any drug. Factors associated with the practice of checking DDIs were found to be gender, perceived workload, perceived knowledge, and attitude variables. Regarding the practice of asking patients about their prescription and OTC drugs, there were statistically significant differences between hospital and community pharmacists.

CONCLUSIONS

Our findings on both community and hospital pharmacists in Saudi Arabia reveal that pharmacists' attitudes and perceived knowledge might influence the practice of pharmacists toward DDIs.

Prevalence of potential drug‒drug interactions and associated factors among elderly patients in Ethiopia: a systematic review and meta-analysis

BACKGROUND

The occurrence of potential drug‒drug interactions (pDDIs) is a serious global issue that affects all age groups, with the elderly population being the most vulnerable. This is due to their relatively high rates of comorbidity and polypharmacy, as well as physiological changes that can increase the potential for DDIs and the likelihood of adverse drug reactions. The aim of this study was to estimate the prevalence of pDDIs and associated factors among elderly patients in Ethiopia.

METHODS

A comprehensive literature search using the preferred reporting items for systematic review and meta-analysis statement was conducted on HINARI, Science Direct, Embase, PubMed/MEDLINE, Google Scholar, and Research Gate. Data were extracted via a Microsoft Excel spreadsheet and analyzed via STATA version 11.0. Egger regression tests and funnel plot analysis were used to check publication bias, and the I2 statistic was used to evaluate statistical heterogeneity. Sensitivity and subgroup analyses were also conducted to identify potential causes of heterogeneity.

RESULTS

Seven articles were analyzed, and a total of 1897 pDDIs were identified in 970 patients, resulting in an average of 1.97 DDIs per patient. The number of DDIs per patient ranged from 0.18 to 5.86. The overall prevalence of pDDIs among elderly patients was 50.69% (95% CI 18.77-82.63%). However, the prevalence of pDDIs ranged widely from 2.80 to 90.1%. When the severity of the interactions was considered, the prevalence of potential DDIs was found to be 28.74%, 70.68%, and 34.20% for major, moderate, and minor pDDIs, respectively. Polypharmacy and long hospital stays were identified as factors associated with pDDIs among elderly patients in Ethiopia.

CONCLUSIONS

The overall prevalence of pDDIs among elderly patients was high, with a wide range of prevalence rates. Moderate-severity interactions were the most prevalent. Polypharmacy and long hospital stays were identified as factors associated with pDDIs among elderly patients. The study suggests that DDIs identification database itself could have modified the DDIs prevalence rate. As a result, a single DDIs identification database needs to be authorized; otherwise, clinical knowledge should be taken into account when interpreting the information obtained.

Drug-drug-interactions in patients with atrial fibrillation admitted to the emergency department

Introduction

Polypharmacy is a growing concern in healthcare systems. While available data on potential drug-drug interactions (pDDI) from emergency department (ED) patients is derived from heterogenous populations, this study specifically focused on patients with atrial fibrillation (AF). We hypothesized that patients with AF have similar comorbidities, receive similar drugs, and have similar pDDIs. The overarching aim was to highlight frequent pDDIs, providing practical guidance for treating healthcare professionals and consequently reduce the risk of adverse drug reactions.

Methods

Two hundred patients ≥18 years with AF, who received rate- or rhythm-controlling medication at the ED of the University Hospital Vienna, and who were on long-term medication before admission, were eligible. Long-term medication alone, as well as in combination with medication administered at the ED were analyzed for pDDIs using the Lexicomp® Drug interactions database.

Results

Within the long-term medication of patients', we identified 664 pDDIs. Drugs administered at the ED increased pDDIs more than 3-fold to 2085. Approximately, every fifth patient received a contraindicated drug combination (on average 0.24 per patient), while 70% received drug combinations for which therapy modifications are recommended (on average 1.59 per patient). The most frequently involved drugs included amiodarone, propofol, bisoprolol, enoxaparin, and acetylsalicylic acid. Increased risk of bleeding, QTc prolongation, and myopathy were among the most relevant potential consequences of these interactions.

Discussion

In conclusion, an optimization of medication would be advisable in almost every AF patient. Treating healthcare professionals should be cautious of drugs that increase bleeding risk, prolong QTc, or bear a risk for myopathy.

Deciphering the Intricate Interplay in the Framework of Antibiotic-Drug Interactions: A Narrative Review

Drug interactions are a significant and integral part of the concept of medication-related adverse events, whether referring to potential interactions or those currently observed in real-world conditions. The high global consumption of antibiotics and their pharmacokinetic and pharmacodynamic mechanisms make antibiotic-drug interactions a key element that requires continuous study due to their clinical relevance. In the present work, the current state of knowledge on antibiotic-drug interactions, which are less studied than other drug-drug interactions despite their frequent use in acute settings, has been consolidated and updated. The focus was on the interactions of the commonly used antibiotics in clinical practice, on the characteristics of the geriatric population susceptible to interactions, and on the impact of online drug interaction checkers. Additionally, strategies for optimizing the management of these interactions, including spacing out administrations, monitoring, or avoiding certain combinations, are suggested. Sustained research and careful monitoring are critical for improving antibiotic safety and efficacy, especially in susceptible populations, to enhance precision in managing antibiotic-drug interactions.

Drug interactions in a coronary care unit: Adversity or therapeutic success?

OBJECTIVES

To analyze the prevalence and factors associated with potential clinically significant drug interactions (pDDIs) in a coronary care unit and to describe clinical management for reducing the occurrence of pDDIs.

METHODS

A cross-sectional and analytical study was conducted on 120 patients aged≥18 years and who had used two or more medications who were admitted to coronary care unit at a high-complexity hospital in Campinas, São Paulo, Brazil. Participants were recruited consecutively from May 2018 to April 2019. Data were obtained from medical records. The Micromedex tool was used for the analysis of pDDIs. Descriptive statistics and a generalized linear model with Poisson distribution were used to assess the relations between independent variables and exposure to pDDIs.

RESULTS

The prevalence of patients exposed to pDDIs of major severity was 81.6%. 73.8% had the increased risk of bleeding as the clinical impact and involved the co-administration of drugs related to antiplatelet therapy and anticoagulation. Having had a myocardial infarction (P=.007), using a greater number of medications (P=.009), and consuming a greater number of medications that act on the blood and hematopoietic organs (P=.006) increased the likelihood of greater potential drug interactions.

CONCLUSION

The prevalence of major severity pDDI was high. Having suffered a myocardial infarction, using polypharmacy and receiving medications that act on the blood/hematopoietic organs increased the likelihood of this clinical outcome. However, the most combinations showed synergistic effects that improved cardiocirculatory performance, highlighting the need for therapeutic success, with this contributing to the restoration of patients' health and improvement in their quality of life.

Characteristics of CYP3A4-related potential drug-drug interactions in outpatients receiving prescriptions from multiple clinical departments

BACKGROUND

Drug-drug interactions (DDIs) increase the incidence of adverse drug reactions (ADRs). In a previous report, we revealed that the incidence of potential DDIs due to the same CYP molecular species in one prescription exceeds 90% among patients taking six or more drugs and that CYP3A4 markedly influences the increase in the number of potential DDIs in clinical practice. However, the factors contributing to an increased number of potential DDIs in prescriptions from multiple clinical departments remain poorly clarified.

METHODS

This observational study was performed at five pharmacies in Okayama Prefecture, Japan. Patients who visited these pharmacies from 11 April 2022 to 24 April 2022 were included, except those who had prescriptions only from a single clinical department. A stratified analysis was performed to determine the incidence of CYP3A4-related potential DDIs according to the number of drugs taken. Additionally, factors associated with an increase in the number of drugs involved in CYP3A4-related potential DDIs were identified using multiple linear regression analysis. In this study, potential DDIs for the prescription data subdivided by clinical department, containing two or more drugs, were used as control data.

RESULTS

Overall, 372 outpatients who received prescriptions from multiple clinical departments were included in the current study. The number of drugs contributing to CYP3A4-related potential DDIs increased with an increase in the number of clinical departments. Notably, in cases taking fewer than six drugs, prescriptions from multiple clinical departments had a higher frequency of CYP3A4-related potential DDIs than those in prescriptions subdivided by clinical department. Multiple regression analysis identified "Cardiovascular agents", "Agents affecting central nervous system", and "Urogenital and anal organ agents" as the top three drug classes that increase CYP3A4-related potential DDIs.

CONCLUSION

Collectively, these results highlight the importance of a unified management strategy for prescribed drugs and continuous monitoring of ADRs in outpatients receiving prescriptions from multiple clinical departments even if the number of drugs taken is less than six.

Survey of Potential Drug Interactions, Use of Non-Medical Health Products, and Immunization Status among Patients Receiving Targeted Therapies

In recent years, several changes have occurred in the management of chronic immunological conditions with the emerging use of targeted therapies. This two-phase cross-sectional study was conducted through structured in-person interviews in 2018-2019 and 2022. Additional data sources included ambulatory medical records and the itemized reimbursement reporting interface of the National Health Insurance Fund. Drug interactions were analyzed using the UpToDate Lexicomp, Medscape drug interaction checker, and Drugs.com databases. The chi-square test was used, and odds ratios (ORs) were calculated. In total, 185 patients participated. In 53% of patients (n = 53), a serious drug-drug interaction (DDI) was identified (mean number: 1.07 ± 1.43, 0-7), whereas this value was 38% (n = 38) for potential drug-supplement interactions (mean number: 0.58 ± 0.85, 0-3) and 47% (n = 47) for potential targeted drug interactions (0.72 ± 0.97, 0-5) in 2018. In 2022, 78% of patients (n = 66) were identified as having a serious DDI (mean number: 2.27 ± 2.69, 0-19), 66% (n = 56) had a potential drug-supplement interaction (mean number: 2.33 ± 2.69, 0-13), and 79% (n = 67) had a potential targeted drug interactions (1.35 ± 1.04, 0-5). Older age (>60 years; OR: 2.062), female sex (OR: 3.387), and polypharmacy (OR: 5.276) were identified as the main risk factors. Screening methods and drug interaction databases do not keep pace with the emergence of new therapeutics.

Drug-Drug Interactions and Actual Harm to Hospitalized Patients: A Multicentre Study Examining the Prevalence Pre- and Post-Electronic Medication System Implementation

INTRODUCTION

Drug-drug interactions (DDIs) have potential to cause patient harm, including lowering therapeutic efficacy. This study aimed to (i) determine the prevalence of potential DDIs (pDDIs); clinically relevant DDIs (cDDIs), that is, DDIs that could lead to patient harm, taking into account a patient's individual clinical profile, drug effects and severity of potential harmful outcome; and subsequent actual harm among hospitalized patients and (ii) examine the impact of transitioning from paper-based medication charts to electronic medication management (eMM) on DDIs and patient harms.

METHODS

This was a secondary analysis of the control arm of a controlled pre-post study. Patients were randomly selected from three Australian hospitals. Retrospective chart review was conducted before and after the implementation of an eMM system, without accompanying clinical decision support alerts for DDIs. Harm was assessed by an expert panel.

RESULTS

Of 1186 patient admissions, 70.1% (n = 831) experienced a pDDI, 42.6% (n = 505) a cDDI and 0.9% (n = 11) an actual harm in hospital. Of 15,860 pDDIs identified, 27.0% (n = 4285) were classified as cDDIs. The median number of pDDIs and cDDIs per 10 drugs were 6 [interquartile range (IQR) 2-13] and 0 (IQR 0-2), respectively. In cases where a cDDI was identified, both drugs were 44% less likely to be co-administered following eMM (adjusted odds ratio 0.56, 95% confidence interval 0.46-0.73).

CONCLUSION

Although most patients experienced a pDDI during their hospital stay, less than one-third of pDDIs were clinically relevant. The low prevalence of harm identified raises questions about the value of incorporating DDI decision support into systems given the potential negative impacts of DDI alerts.

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.

Risk Factors for Potential Drug-Drug Interactions in Patients on Chronic Peritoneal Dialysis

INTRODUCTION

The prevalence of potential drug-drug interactions (pDDIs) is becoming a major safety concern, as it has been previously linked to a significant number of adverse drug events and could have serious consequences for patients, including death. This is especially relevant for patients with chronic renal failure, as they are particularly vulnerable to drug-drug interactions. The aim of this study was to evaluate the prevalence and associated factors of pDDIs in patients receiving chronic peritoneal dialysis.

METHODS

An observational, cross-sectional study was conducted on consecutive peritoneal dialysis patients attending four tertiary care hospitals for regular monthly examination. The primary outcome was the number of pDDIs identified using Lexicomp. Potential predictors were determined using multiple linear regression.

RESULTS

Total number of patients included in the study was 140. The results showed that pDDIs were highly prevalent, especially in patients who use antiarrhythmics (p = 0.001), have diabetes mellitus (p = 0.001), recently started peritoneal dialysis (p = 0.003), or have higher number of prescribed drugs (p < 0.001). Number of prescribed drugs (p < 0.001) remained a significant predictor of high-risk pDDIs in addition to the female gender (p = 0.043).

CONCLUSION

Clinicians should be particularly cautious when prescribing multiple medications to high-risk patients, such as peritoneal dialysis patients, to mitigate the risk of drug-drug interactions and associated adverse health outcomes.

Prevalence of QT-Prolonging Drug-Drug Interactions in Psychiatry: A Systematic Review and Meta Analysis

Background: Drug-drug interactions (DDIs) are considered an emerging threat to the patients if undetected. DDIs can prolong QT interval, leading to fatal ventricular arrhythmia. Antipsychotics and antidepressants prescribed commonly to psychiatric patients have the propensity to prolong QT interval and can precipitate Torsades de pointes (TdP). This review aimed to summarize the prevalence of QT interval prolonging DDIs in psychiatric patients. Methods: This meta-analysis was carried out following the MOOSE (Meta-analysis of Observational Studies in Epidemiology) statement. Databases like Pubmed/MEDLINE, Google Scholar and Research gate were scanned for English language papers. Indexed terms from Medical Subject (MeSH) and other search terms for "QT prolongation", "Drug interactions", and "Psychiatry" were used to identify the articles. All published articles available until the day of the collection were considered. Outcome measures were analyzed with meta package in R language. Results: A total of 5 studies were eligible for inclusion. From the included studies, QT-prolonging DDIs were found in 14806 patients out of 30122 patients. The prevalence of QT-prolonging DDIs in psychiatric patients was found to be 42% (95% confidence interval: 21%, 66%). The factors associated with potential drug-drug interactions were related to patient characteristics such as polypharmacy, age and comorbid disease. Conclusion: This review concluded that psychiatric patients were prescribed the drugs/drug combinations which can prolong QT interval and can cause adverse effects on the cardiovascular system. Hence, it is important to implement precautionary safety interventions, be vigilant and prevent QT prolongation and adverse cardiac effects in clinical practice.

Update and Application of a Deep Learning Model for the Prediction of Interactions between Drugs Used by Patients with Multiple Sclerosis

Patients with multiple sclerosis (MS) often take multiple drugs at the same time to modify the course of disease, alleviate neurological symptoms and manage co-existing conditions. A major consequence for a patient taking different medications is a higher risk of treatment failure and side effects. This is because a drug may alter the pharmacokinetic and/or pharmacodynamic properties of another drug, which is referred to as drug-drug interaction (DDI). We aimed to predict interactions of drugs that are used by patients with MS based on a deep neural network (DNN) using structural information as input. We further aimed to identify potential drug-food interactions (DFIs), which can affect drug efficacy and patient safety as well. We used DeepDDI, a multi-label classification model of specific DDI types, to predict changes in pharmacological effects and/or the risk of adverse drug events when two or more drugs are taken together. The original model with ~34 million trainable parameters was updated using >1 million DDIs recorded in the DrugBank database. Structure data of food components were obtained from the FooDB database. The medication plans of patients with MS (n = 627) were then searched for pairwise interactions between drug and food compounds. The updated DeepDDI model achieved accuracies of 92.2% and 92.1% on the validation and testing sets, respectively. The patients with MS used 312 different small molecule drugs as prescription or over-the-counter medications. In the medication plans, we identified 3748 DDIs in DrugBank and 13,365 DDIs using DeepDDI. At least one DDI was found for most patients (n = 509 or 81.2% based on the DNN model). The predictions revealed that many patients would be at increased risk of bleeding and bradycardic complications due to a potential DDI if they were to start a disease-modifying therapy with cladribine (n = 242 or 38.6%) and fingolimod (n = 279 or 44.5%), respectively. We also obtained numerous potential interactions for Bruton's tyrosine kinase inhibitors that are in clinical development for MS, such as evobrutinib (n = 434 DDIs). Food sources most often related to DFIs were corn (n = 5456 DFIs) and cow's milk (n = 4243 DFIs). We demonstrate that deep learning techniques can exploit chemical structure similarity to accurately predict DDIs and DFIs in patients with MS. Our study specifies drug pairs that potentially interact, suggests mechanisms causing adverse drug effects, informs about whether interacting drugs can be replaced with alternative drugs to avoid critical DDIs and provides dietary recommendations for MS patients who are taking certain drugs.

The Prevalence and Severity of Potential Drug-Drug Interactions in Internal Medicine Ward at Soba Teaching Hospital

Background

Multiple drug therapies are commonly used to achieve a desired therapeutic goal, especially in hospitalized patients. However, drug-drug interactions might occur and threaten the patients' safety.

Objective

This study aims to assess the prevalence and severity of potential drug-drug interactions (PDDIs) in the internal medicine ward at Soba Teaching Hospital.

Methods

A retrospective cross-sectional hospital-based study was carried out in the internal medicine ward at Soba Teaching Hospital from June 2021 to December 2021. The data was collected from patients' medical records. PDDIs were identified using Lexicomp® drug interaction software.

Results

A total of 377 patients were included in this study, and overall prevalence of PDDIs was 62.9%. We have identified 989 potential DDIs and 345 pairs of interacting drugs, the mean of the PDDIs per patient was 4.17 ± 4.079. Among 345 PDDIs most were of moderate interactions 70.1% (n=242) followed by Minor interactions 19.1% (n=66). The most common type of interaction was of category C representing 63.5% (n=219). A significant association was observed between the occurrence of PDDIs with patients' age, presence of chronic diseases, length of hospital stay, and number of medications received by the patients.

Conclusion

Drug-drug interactions were highly prevalent in the internal medicine ward. Therefore, certain attempts are required to increase the awareness of the physicians about these interactions and minimize their occurrence.

Potentially Harmful Drug-Drug Interactions and Their Associated Factors Among Hospitalized Cardiac Patients: A Cross-Sectional Study

BACKGROUND

Cardiovascular diseases are responsible for a significant proportion of mortalities worldwide. Elderly patients are the most affected by cardiovascular diseases, and because of factors such as polypharmacy, multimorbidity, and age-related changes in drug availability and metabolism, they are highly susceptible to the occurrence of drug-drug interactions. Drug-drug interactions are among the many drug-related problems leading to negative outcomes among inpatients and outpatients. Thus, it is important to investigate the prevalence, involved drugs, and factors related to potential drug-drug interactions (pDDIs) to properly optimize pharmacotherapy regimens for these patients.

OBJECTIVE

We aimed to determine the prevalence of pDDIs, drugs most frequently implicated, and significant predictors associated with these interactions among hospitalized patients in the Cardiology Unit at Sultan Qaboos University Hospital in Muscat, Oman.

METHODS

This retrospective cross-sectional study included 215 patients. Micromedex Drug-Reax® was used to identify pDDIs. Data extracted from patients' medical records were collected and analyzed. Univariable and multivariable linear regression was applied to determine the predictors associated with the observed pDDIs.

RESULTS

A total of 2057 pDDIs were identified, with a median of nine (5-12) pDDIs per patient. Patients with at least one pDDI accounted for 97.2% of all the included patients. The majority of pDDIs were of major severity (52.6%), fair level of documentation (45.5%), and pharmacodynamic basis (55.9%). Potential drug-drug interactions between atorvastatin and clopidogrel were the most frequently observed (9%). Of all the detected pDDIs, around 79.6% of them included at least one antiplatelet drug. Having diabetes mellitus as a comorbidity (B = 2.564, p < 0.001) and the number of drugs taken during the hospitalization period (B = 0.562, p < 0.001) were factors positively associated with the frequency of pDDIs.

CONCLUSIONS

Potential drug-drug interactions were highly prevalent among hospitalized cardiac patients at Sultan Qaboos University Hospital, Muscat, Oman. Patients having diabetes as a comorbidity and with a high number of administered drugs were at a higher risk of an increased number of pDDIs.

Adverse drug reactions in the ambulatory internal patients at the emergency department: Focus on causality assessment and drug-drug interactions

A non-interventional retrospective study in ambulatory patients was conducted at the emergency department of the Division of internal medicine. In 2 months, 266 suspected adverse drug reactions (ADRs) were identified in 224/3453 patients (6.5 %). In 158/3453 patients (4.6 %), an ADR was the reason for emergency department visit and in 49 patients (1.4 %), ADRs led to hospitalisation. A causality assessment algorithm was developed, which included Naranjo algorithm and levels of ADR recognition by the treating physician and the investigators. Using this algorithm, 63/266 ADRs (23.7 %) were classified as "certain", whereas using solely the Naranjo score calculation, only 19/266 ADRs (7.1 %) were assessed as "probable" or "certain", and the rest of ADRs (namely, 247/266 = 92.9 %) were assessed as "possible". There were 116/266 (43.6 %) ADRs related to potential drug-drug interactions (DDIs), stated in at least one of the literature sources used. Based on the causality relationship, the rate of the clinically expressed DDIs was 19.0 %, or 12/63 "certain" ADR cases. Of these, 10 cases presented serious DDI-related ADRs. In summary, ADR causality assessment based exclusively on Naranjo algorithm demonstrated low sensitivity at an ambulatory emergency setting. Additional clinical judgment, including the opinion of the treating physician, proved necessary to avoid under-rating of the causality relationship, and enabled the determination of clinically expressed DDIs.

[Contribution of the pharmaceutical record in the analysis of drug interactions during retrocession in a centre for cancer research]

OBJECTIVES

To implement the pharmaceutical record in retrocession, to evaluate its contribution to the analysis of drug interactions and to estimate the sustainability of this approach.

METHODS

This prospective, descriptive, monocentric study was conducted over five months. All patients presenting at the retrocession were eligible. After having offered them the pharmaceutical record and having completed it, drug interactions were sought. If the impact was considered significant, a pharmaceutical intervention was transmitted to the referring physician of the institution and recorded in the computerized patient record.

RESULTS

The pharmaceutical record was offered to 497 patients, i.e., 87 % of eligible patients. At the first meeting, 7 % of patients (n=34) were aware of it and 72 % had one open. In total, 395 pharmaceutical records were filled in at least once, 41 of which we created. Only 25 patients (5 %) refused the process and 90 % of the existing records were filled by the pharmacy. In total, 419 prescriptions were analysed for 330 patients: the pharmaceutical record was therefore a useful tool for 66 % of patients. For 17 % (n=57) of them, or 11 % of included patients, 99 drug interactions with a high risk of clinical impact were detected with the retroceded drug. On average, the presentation, creation and feeding of the drug record took one minute each and the analysis of interactions 14minutes.

CONCLUSIONS

Easy to implement, the pharmaceutical record is a useful tool to search for drug interactions with retroceded drugs. It helps to optimize patient follow-up, despite the limited information available.

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

BACKGROUND

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.

METHODS

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).

RESULTS

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.

CONCLUSIONS

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.

Frequency, severity, and factors associated with clinically significant drug-drug interactions among patients with cancer attending Mbarara Regional Referral Hospital Cancer Unit, Uganda

BACKGROUND

Cancer is a major public health problem with pharmacotherapy being the cornerstone of its management. Cancer patients receive multiple drugs concurrently risking Drug-Drug Interactions (DDIs). DDIs, though avoidable, can significantly contribute to morbidity, mortality, and increased healthcare costs in this population of patients. Currently, there is no published study from Uganda on clinically significant DDIs (cs-DDIs) among cancer patients. This study identifies frequency, severity, and factors associated with cs-DDIs at Mbarara Regional Referral Hospital Cancer Unit (MRRHCU).

METHOD

A cross-sectional study was conducted among 300 cancer patients receiving chemotherapy from a tertiary care hospital in western Uganda from January-February 2022. A questionnaire and data collection form were used to collect patient data. Lexicomp® Drug interaction software was used to screen the patient drug information for DDIs and assess their severity. Predictors of DDIs were identified using logistic regression using SPSS (Statistical Package for Social Sciences).

RESULT

Three hundred participants were enrolled with a mean age of 48 ± 23.3 years. One hundred eighty-one patients experienced 495 cs-DDIs; with a mean of 1.7 ± 2.2. The prevalence of cs-DDI was 60.3% (55.0-66.0% at 95% CI). Digestive organ neoplasms were the most commonly (80, 26.7%) diagnosed category, and 'plant alkaloids and other natural products were the most frequently (143, 47.7%) used chemotherapeutic drug classes. About three-quarters of cs-DDIs were rated as category C risk (367, 74.1%) whereas over two-thirds (355, 71.7%) were moderate in severity.. Being female (aOR = 2.43 [1.23-4.48 at 95% CI]; P-value = 0.011) and use of ≥ 6 drugs concurrently (aOR = 18.82 [9.58-36.95 at 95% CI]; P-value < 0.001)) were significantly associated with cs-DDIs.

CONCLUSION

More than half of the participants experienced at-least one cs-DDI which is generally higher than what was reported in high-income settings. About three-quarters were category C and moderate in severity, and require enhanced monitoring for safety and treatment outcome. Being female and using ≥ 6 drugs were significantly associated with cs-DDIs.

Potential Drug-Drug Interactions Among Hospitalised Elderly Patients in Northern Sri Lanka, A Lower Middle-Income Country: A Retrospective Analysis

BACKGROUND AND OBJECTIVES

Elderly individuals are more vulnerable to potential drug-drug interactions (pDDIs) as age-related physiological changes, polypharmacy and hospitalisations are known to increase the risk of pDDIs. The aims of this study were to assess the impact of hospitalisation and other associated factors on pDDIs in elderly patients, in a resource-limited setting.

METHODS

This is a retrospective analysis of data of elderly patients (aged ≥ 65 years) admitted to the medical units of Jaffna Teaching Hospital. Preadmission and post-admission data were collected from clinic and hospital records, respectively. The British National Formulary was used to identify and categorise pDDIs. Point prevalence of pDDIs in elderly patients and the total number of pDDIs before and after hospitalisation were estimated. Factors contributing to pDDIs were determined by univariate and multivariable logistic regression.

RESULTS

Two hundred and eighty-eight hospitalised elderly patients with a median age of 71 years (interquartile range 67-76 years) showed a significant increase in the prevalence of pDDIs post-admission compared with the preadmission values (77.1% vs 61.5%; p < 0.001) associated with an increase in total pDDIs (377 vs 488; p < 0.001) where the majority (> 75%) were potential pharmacodynamic interactions. An unadjusted analysis showed a significant association between pDDI and polypharmacy [taking five or more medications] (odds ratio [OR] = 14.17; 95% confidence interval [CI] 7.41-27.10), the presence of more than three underlying medical conditions (OR 4.14; 95% CI 1.70-10.06), ischaemic heart disease (OR 3.25; 95% CI 1.78-5.94) and asthma (OR 8.14; 95% CI 2.46-26.88). However, when adjusted for confounders only polypharmacy (OR 14.10; 95% CI 6.50-30.60) and the presence of underlying asthma (OR 11.61; 95% CI 2.82-47.85) were associated with pDDIs.

CONCLUSIONS

The prevalence of pDDIs among elderly patients was high and increased with hospital admissions. Polypharmacy and relevant comorbidities were contributory factors. Increased awareness of the potential for pDDIs through appropriate training and simple measures including a proper drug history, creating a bespoke pDDI list and frequent medication reviews by healthcare professionals would help to mitigate pDDIs in resource-limited and technology-limited settings.

Prevalence of Potential Pharmacological Interactions in Patients Undergoing Systemic Chemotherapy in a Tertiary Hospital

Introduction: Pharmacological interactions are frequently observed in patients with chronic diseases, and their occurrence is proportional to the amount of medication used daily. Patients undergoing chemotherapy treatment commonly have comorbidities, which favor a greater prevalence of polypharmacy, increasing the risk of drug interactions. Therefore, the aim of this study was to estimate the prevalence of drug interactions in patients undergoing intravenous chemotherapy treated at a hospital oncology service in southern Brazil. Methods: This was an observational study with a cross-sectional design that was carried out with the analysis of secondary data obtained through the review of medical records. The population assessed consisted of all cancer patients who received intravenous chemotherapy from October to December 2020. Results: Out of the 297 patients included in the study, 231 (77.8%) had at least 1 potential pharmacological interaction. In total, 1044 drug interactions were found that were classified according to severity, resulting in 18 (1.7%) contraindicated drug-drug interactions (DDI), 699 (67%) severe, 281 (26.9%) moderate, and 46 (4.4%) minor interactions. There was an association between polypharmacy and the prevalence of drug interactions. Conclusion: The results demonstrate that a large percentage of patients undergoing chemotherapy are susceptible to drug interactions. Thus, it is necessary that prescribers consider all drugs used by patients and, when possible, prescribe alternative drugs that have less potential for interaction in order to prevent drug interactions adverse effects and provide a better prognosis for patients.

Colchicine and macrolides: a cohort study of the risk of adverse outcomes associated with concomitant exposure

Colchicine is increasingly used as the number of potential indications expands. However, it also has a narrow therapeutic index that is associated with bothersome to severe side effects. When concomitantly use with medications inhibiting its metabolism, higher plasma levels will result and increase likelihood of colchicine toxicity. We conducted a cohort study using electronic health records comparing encounters with colchicine plus a macrolide and colchicine with an antibiotic non-macrolide. We assessed the relationship between the two groups using adjusted multivariate logistic regression models and the risk of rhabdomyolysis, pancytopenia, muscular weakness, heart failure, acute hepatic failure and death. 12670 patients on colchicine plus an antibiotic non-macrolide were compared to 2199 patients exposed to colchicine plus a macrolide. Patients exposed to colchicine and a macrolide were majority men (n = 1329, 60.4%) and white (n = 1485, 67.5%) in their late sixties (mean age in years 68.4, SD 15.6). Heart failure was more frequent in the colchicine plus a macrolide cohort (n = 402, 18.3%) vs the colchicine non-macrolide one (n = 1153, 9.1%) (p < 0.0001) and also had a higher mortality rate [(85 (3.87%) vs 289 (2.28%), p < 0.0001 macrolides vs non-macrolides cohorts, respectively]. When the sample was limited to individuals exposed to either clarithromycin or erythromycin and colchicine, the adjusted OR for acute hepatic failure was 2.47 (95% CI 1.04–5.91) and 2.06 for death (95% CI 1.07–3.97). There is a significant increase in the risk of hepatic failure and mortality when colchicine is concomitantly administered with a macrolide. Colchicine should not be used concomitantly with these antibiotics or should be temporarily discontinued to avoid toxic levels of colchicine.

Adverse drug reactions and correlations with drug–drug interactions: A retrospective study of reports from 2011 to 2020

Introduction: Adverse drug reactions (ADRs) represent a public health problem worldwide that deserves attention due to the impact on mortality, morbidity, and healthcare costs. Drug–drug interactions (DDIs) are an important contributor to ADRs. Most of the studies focused only on potential DDIs (pDDIs), while the detailed data are limited regarding the ADRs associated with actual DDIs.

Methods: This retrospective study evaluated ADRs reported between 2011 and 2020 in a tertiary hospital. The causality and severity of ADRs were evaluated through the Naranjo Algorithm and Hartwig’s scale, respectively. Preventability classification was based on the modified Schoumock and Thornton scale. For ADRs with at least two suspected drugs, pDDIs were identified according to the Lexi-Interact. We further checked whether the ADR description in the reports corresponded to the clinical consequences of the pDDIs.

Results: A total of 1,803 ADRs were reported, of which 36.77% ADRs were classified as mild, 43.26% as moderate, and 19.97% as severe. The assessment of causality showed that the distributions of definite, probable, and possible categories were 0.33%, 58.68%, and 40.99%, respectively. A total of 53.97% of ADRs were identified as preventable ADRs, while 46.03% were recognized as unpreventable. The severity of ADRs was significantly correlated with age, the number of suspected drugs and preventability. Antimicrobial agents were the most common implicated pharmacological group, and the most frequently affected system was the gastrointestinal system. Considering individual drugs, aspirin was the most frequently reported drug. Among 573 ADRs with at least two suspected drugs, 105 ADRs were caused by actual DDIs, of which only 59 and 6 ADRs were caused by actual DDIs in category D and X, respectively. The most frequent drugs involved in actual DDIs of category D were aspirin and heparin, with the majority of ADRs being gastrointestinal bleeding.

Conclusion: This study analyzed the pattern of ADRs in detail and obtained clinical evidence about ADRs associated with actual DDIs. These findings may be useful to compare patterns between different centers and to design preventive strategies for ADRs. Continuous education and training should be provided for physicians regarding the knowledge and recognition of ADRs associated with DDIs.

Facing the challenge of polypharmacy when prescribing for older people with cardiovascular disease. A review by the European Society of Cardiology Working Group on Cardiovascular Pharmacotherapy

Population ageing has resulted in an increasing number of older people living with chronic diseases (multimorbidity) requiring five or more medications daily (polypharmacy). Ageing produces important changes in the cardiovascular system and represents the most potent single cardiovascular risk factor. Cardiovascular diseases (CVDs) constitute the greatest burden for older people, their caregivers, and healthcare systems. Cardiovascular pharmacotherapy in older people is complex because age-related changes in body composition, organ function, homeostatic mechanisms, and comorbidities modify the pharmacokinetic and pharmacodynamic properties of many commonly used cardiovascular and non-cardiovascular drugs. Additionally, polypharmacy increases the risk of adverse drug reactions and drug interactions, which in turn can lead to increased morbi-mortality and healthcare costs. Unfortunately, evidence of drug efficacy and safety in older people with multimorbidity and polypharmacy is limited because these individuals are frequently underrepresented/excluded from clinical trials. Moreover, clinical guidelines are largely written with a single-disease focus and only occasionally address the issue of coordination of care, when and how to discontinue treatments, if required, or how to prioritize recommendations for patients with multimorbidity and polypharmacy. This review analyses the main challenges confronting healthcare professionals when prescribing in older people with CVD, multimorbidity, and polypharmacy. Our goal is to provide information that can contribute to improving drug prescribing, efficacy, and safety, as well as drug adherence and clinical outcomes.

Potential Drug Interactions Between Psychotropics and Intravenous Chemotherapeutics Used by Patients With Cancer

Introduction: Patients undergoing cancer treatment usually have comorbidities, and psychiatric disorders are commonly seen in these patients. For the treatment of these psychiatric disorders, the use of psychotropic drugs is common, turning these patients susceptible to untoward drug interactions. Therefore, the aim of this study was to estimate the prevalence of clinically relevant drug-drug interactions (DDI) between chemotherapeutic and psychotropic agents in patients with cancer treated at an oncology service in southern Brazil. Methods: An observational epidemiological study with a cross-sectional census-type design was carried out between October and December 2020. The drug-drug interactions were identified through consultation and analysis of the Medscape Drug Interaction Check and Micromedex databases. The interactions were classified as major, when the interaction can be fatal and/or require medical intervention to avoid or minimize serious adverse effects and moderate, when the interaction can exacerbate the patient's condition and/or requires changes in therapy. Results: A total of 74 patients was included in the study among the 194 patients seen in the oncology service during the period studied. A total of 24 (32.4%) DDIs were found, 21 (87.5%) of which were classified as being of major risk and 3 (12.5%) as moderate risk. According to the mechanism of action, 19 (79.1%) were classified as pharmacodynamic interactions and 5 (20.9%) as pharmacokinetic interactions. Conclusion: It was shown that a considerable percentage of patients undergoing intravenous chemotherapy are at risk of pharmacological interaction with psychotropic drugs. Thus, it is essential that the oncologist considers all psychotropic drugs and other drugs used by patients in order to avoid drug-drug interactions.

Comparison of different decision support software programs in perspective of potential drug-drug interactions in the oncology clinic

INTRODUCTION

One of the most intriguing situations for healthcare providers is cancer therapy. Drug-drug interactions (DDIs) account for 20-30% of all adverse effects. Cancer patients are more likely to have potential-DDIs since they are taking other drugs with anticancer treatments to prevent the side effects of chemotherapeutic agents. The purpose of this research is to compare various decision support software (CDSS) programs in terms of potential DDIs.

METHODS

A cross-sectional study was carried out. A clinical pharmacist assessed the treatment regimens of 231 cancer patients. pDDIs were evaluated using three sources: Lexicomp®, Medscape®, and Micromedex®. The ethical approval was given in November 2017 with decision number 21/286.

RESULTS

A total of 231 participants who were receiving therapy and had a median age of 61.5 ± 9.18 years were assessed. Almost half of the patients (49%) were female, and 155 had at least one comorbidity in addition to cancer. Medscape had a substantial pDDI ratio of 7.09%, Micromedex had a ratio of 11.15%, and Lexicomp had a ratio of 19.50%. The total number of pDDIs for major/X/contraindicated were 363-2716 (1.56-11.7 pDDI/patient) for Medscape®, 60-1723 (0.26-7.4 pDDI/patient) for Micromedex, and 145-984 (0.62-2.24 pDDI/patient) for Lexicomp®. One of the most common pDDI found was diclofenac and dexamethasone. Interactions between escitalopram and granisetron were also common, and different CDSSs made different recommendations.

CONCLUSIONS

In this study, significant disparities in the quantity and severity of CDSS across distinct CDSS were discovered. One of the major finding of our study was suboptimal prescribing. To address this issue, regulatory organizations should establish and verify validation and reporting mechanisms.

Factors associated with the workload of health professionals in hospital at home: a systematic review

BACKGROUND

Understanding the factors related to workload, could help hospital at home (HaH) managers to make decisions on the most appropriate and efficient use of the HaH services. Published studies on this topic are scarce, so we have conducted a systematic review to identify such factors according to published evidence.

METHODS

Due to the heterogeneity of HaH models, HaH was defined as a care that provides a set of medical and nursing care and attention of hospital rank to patients at home, when they no longer require hospital infrastructure but still need active monitoring and complex care. The electronic data base literature search was conducted in MEDLINE (Ovid), EMBASE (Ovid), and Cinahl (EBSCOhost) from inception to December 2021, including grey literature. Search terms related to `hospital at home´, `workload´ and `care time´ were used. There was no restriction on language, type of study or year of publication. Quality of included studies was assessed using the Critical Appraisal Skills Programme (CASP) checklist and certainty in the body of evidence was assessed using the GRADE Pro Tool. Results were summarised in a tabulated format.

RESULTS

Eighteen studies with 56,706 patients were included. Workload was measured as time, number of visits or both. The predictive factors of the workload included variables related to patient characteristics and other valid and reliable patient classification systems, as well as characteristics of the institutions where the studies were conducted. The factors associated with higher workloads were: being older, male, living in a rural environment, presenting a higher number of diagnoses, having worse functional status and being unable to assume self-care.

CONCLUSIONS

The identified predictors of workload are mostly associated with home nursing care. The results could be useful and applicable to different organisational models of HaH health systems. More studies that include physicians and proxy measures of workload are needed.

Drug interaction alerts in older primary care patients, and related medically justified actions

PURPOSE

To describe presented interaction alerts in older patients, and the extent to which these require further medical action for the specific patient or are already being addressed.

METHODS

Interaction alerts presented at a physician consultation, for 274 consecutive primary care patients treated with two or more drugs (median age: 75 years; 59% female), were extracted. These alerts are based on Janusmed, a decision support integrated in the medical records that provides recommendations for managing the interactions. One general practitioner (GP) and one GP/clinical pharmacologist determined in retrospect, first independently and then in consensus, whether the alerts justified further medical action, considering each patient's health condition.

RESULTS

In all, 405 drug interaction alerts in 151 (55%) patients were triggered. Medical action in response was deemed medically justified for 35 (9%) alerts in 26 (17%) patients. These actions most often involved a switch to a less interacting drug from the same drug class (n = 10), a separate intake (n = 9), or the ordering of a laboratory test (n = 8). Out of 531 actions suggested by the alert system, only 38 (7%) were applicable to the specific patient, as, for instance, laboratory parameters were already being satisfactorily monitored or a separate intake implemented.

CONCLUSIONS

More than every other older patient receives drug treatment that triggers drug interaction alerts. Nine in ten alerts were already being addressed or were not relevant in the clinical setting, whereas, for the remaining tenth, some medical action, that for unknown reasons had not been taken, was reasonable. These findings show that interaction alerts are questionable as indicators of problematic prescribing.

Emergency room admissions induced by drug-drug interactions in the elderly: a cross-sectional study

The elderly people are increasingly exposed to polymedication and therefore to the risks of drug–drug interactions (DDIs). However, there are few data available on the clinical consequences of these drug combinations. We investigated the impact of the various DDIs classified as severe in terms of emergency admissions in the elderly. A cross‐sectional study was conducted using information from the emergency department admissions of Bordeaux University Hospital between September 2016 and August 2017. Events of interest were frequency of concomitant uses of interacting drugs that are contraindicated or warned against and frequency of emergency admissions due to contraindicated or warned against concomitant uses of interacting drugs. Five thousand, eight hundred sixty (5860) admissions to the emergency department were analyzed. A total of 375 (6.4%) contraindicated or warned against concomitant uses were identified, including 163 contraindicated (43.5%) and 212 warned against (56.5%). Reason for admission appeared likely related to the underlying DDI in 58 cases. Within these, 36 admissions were assessed as probably due to a DDI (0.6% of hospitalizations) and 22 as certainly (0.4% of hospitalizations). Of these, there were 24 (45%) admissions related to a long QT syndrome (LQTS), nine (16%) related to a drug overdose, and eight (14%) related to a hemorrhage. An antidepressant was involved in 22 of the 24 cases of LQTS. Seven of the eight cases of hemorrhage involved the antithrombotic agents / non‐steroidal anti‐inflammatory drugs combination. Elderly patients admitted to emergency departments are particularly exposed to high‐risk potential DDIs. These drug combinations lead mainly to LQTS and involve certain antidepressants.

Evaluation of potential drug-drug interactions in cancer patients at a tertiary care hospital in Pakistan

BACKGROUND

Despite harboring a high burden of cancer patients who are at high risk of potential drug-drug interactions (pDDIs), there is scarcity of published information about pDDIs in cancer patients from Pakistan.

OBJECTIVE

To evaluate frequency, pattern, mechanism and factors associated with pDDIs in cancer patients treated at a tertiary care hospital in Pakistan.

METHODS

In this cross-sectional analytical study, a total of 253 eligible ambulatory cancer patients treated at Center for Nuclear Medicine and Radiotherapy Hospital Quetta were evaluated for pDDIs using IBM Micromedex® Drug Interactions. SPSS (version 26) was used for conducting multivariate analysis to find factors associated with the presence pDDIs. A p-value <0.05 was considered statistically significant.

RESULTS

A total of 141/253 (55.7%) patients were exposed to at-least one pDDI. A total of 251 pDDIs were noted with a median of one pDDI/per patient (interquartile range:1-2) Majority interactions were of major severity (72.9%), pharmacodynamic (49.8%) and had fair documentation level (64.1%). Anti-cancer drugs were involved in 73.0% pDDIs with doxorubicin as the most commonly involved (40.0%) anti-cancer followed by cyclophosphamide (27.6%) and cisplatin (13.5%). Potential cardiac adverse events made the bulk (33.8%) of predicted events. Receiving >2 anti-cancer (OR = 5.19, p-value = 0.001) and >6 ancillary drugs (OR = 4.16, p-value = 0.033) emerged as the risk factors of pDDIs.

CONCLUSIONS

The prevalence of pDDIs was within the range reported in published literature. Solid medication review, availability of DDI detecting tools and clinical pharmacist, and paying special attention to the high-risk patients may reduce the frequency of pDDIs at the study site.

Heterogeneity in the identification of potential drug-drug interactions in the intensive care unit: A systematic review, critical appraisal, and reporting recommendations

Patients admitted to the intensive care unit (ICU) are frequently exposed to potential drug‐drug interactions (pDDIs). However, reported frequencies of pDDIs in the ICU vary widely between studies. This can be partly explained by significant variation in their methodological approach. Insight into methodological choices affecting pDDI frequency would allow for improved comparison and synthesis of reported pDDI frequencies. This study aimed to evaluate the association between methodological choices and pDDI frequency and formulate reporting recommendations for pDDI frequency studies in the ICU. The MEDLINE database was searched to identify papers reporting pDDI frequency in ICU patients. For each paper, the pDDI frequency and methodological choices such as pDDI definition and pDDI knowledge base were extracted, and the risk of bias was assessed. Each paper was categorized as reporting a low, medium, or high pDDI frequency. We sought associations between methodological choices and pDDI frequency group. Based on this comparison, reporting recommendations were formulated. Analysis of methodological choices showed significant heterogeneity between studies, and 65% of the studies had a medium to high risk of bias. High risk of bias, small sample size, and use of drug prescriptions instead of administrations were related to a higher pDDI frequency. The findings of this review may support researchers in designing a reliable methodology assessing pDDI frequency in ICU patients. The reporting recommendations may contribute to standardization, comparison, and synthesis of pDDI frequency studies, ultimately improving knowledge about pDDIs in and outside the ICU setting.

The impact of treatment choices on potential drug-drug interactions in hypertensive patients

AIMS

The aim of this study was to analyse potential drug-drug interactions (pDDIs) and their potential adverse drug reactions (ADRs) among hypertensive patients. Moreover, we investigated the possibility of reducing pDDIs with different treatment choices.

METHODS

This was a cross-sectional study including all outpatients with hypertension and two or more medications, treated in a university hospital in Serbia. Lexicomp Interact (Lexi-Comp, Inc., Hudson, OH) was used for identification of pDDIs and potential ADRs. Treatment choices were explored according to patient characteristics, treatment guidelines and the interacting potential of drugs. Data were analysed using descriptive analysis and multiple logistic regression.

RESULTS

A total of 350 patients were included in this study, with average age (77 [36-98] years and 6.1 [2.5]) medications. The majority of patients (86.0%) had at least one clinically significant pDDI, and the average was 3.78 (3.90) (range 1-25). Suggestions for treatment change aimed mainly at eliminating drug duplications, reducing the use of thiazide diuretics, sulfonylureas, alpha-lipoic acid and pentoxifylline and increasing the use of calcium-channel blockers, when appropriate. pDDIs would have decreased to 2.10 (2.52), P <.001, yet male gender, ≥6 medications, cardiovascular diseases, diabetes, benign prostatic hyperplasia, would be predictive of two or more pDDIs. The main potential adverse outcomes of pDDIs were hypotension, renal failure, hypoglycaemia, bradycardia and lactic acidosis.

CONCLUSION

Careful choice of drugs can reduce but not eliminate pDDIs and their potential ADRs in hypertensive patients. Close monitoring for hypotension, renal failure, hypoglycaemia, bradycardia and lactic acidosis is necessary.

Real clinical impact of drug-drug interactions of immunosuppressants in transplant patients

The main objective was to determine the prevalence of real drug-drug interactions (DDIs) of immunosuppressants in transplant patients. We conducted a prospective, observational 1-year study at a tertiary hospital, including all transplanted patients. We evaluated data from monitoring blood concentrations of immunosuppressive drugs and adverse drug events (ADEs) caused by DDIs. The DDIs were classified as C, D, or X according to their Lexi-Interact rating (C = monitor therapy, D = consider therapy modification, X = avoid combination). The clinical importance of real DDIs was expressed in terms of patient outcomes. The causality of DDIs was determined using Drug Interaction Probability Scale. The data were analyzed using Statistical Package for Social Sciences v. 25.0. A total of 309 transplant patients were included. Their mean age was 52.0 ± 14.7 years (18-79) and 69.9% were male. The prevalence of real DDIs was 21.7%. Immunosuppressive drugs administered with antifungal azoles and tacrolimus (TAC) with nifedipine have a great clinical impact. Real DDIs caused ADEs in 22 patients. The most common clinical outcome was nephrotoxicity (1.6%; n = 5), followed by hypertension (1.3%; n = 4). Suggestions for avoiding category D and X DDIs included: changing the immunosuppressant dosage, using paracetamol instead of non-steroidal anti-inflammatory drugs, and interrupting atorvastatin. The number of drugs prescribed and having been prescribed TAC was associated with an increased risk of real DDIs. There are many potential DDIs described in the literature but only a small percentage proved to be real DDIs, based on the patients´ outcomes.

Basic principles of combination therapy: focus on drug-drug interaction

The article is devoted to the issue of drug interactions in the combination regimens. Today, when drug therapy is the first-line approach for patients with noncommunicable diseases, and the world population ageing leads to an increase in the number of patients with severe comorbidity and polypharmacy, the problem of drug-drug interaction is especially relevant. The article discusses the main types of drug interactions  — pharmacokinetic (related to absorption, distribution, metabolism and excretion of drugs) and pharmacodynamic ones, leading to synergy or antagonism of the pharmacological effects. The consequences of drug interactions can be desirable and undesirable, while the latter are much more common. Attention should be directed precisely to preventing such interactions. Also, using data from special scales and lists (Beers criteria, STOPP/START criteria), the options for various adverse drugdrug interactions are briefly described. In addition, the article provides a number of Internet resources that allow assessing the drug interaction risk when prescribing combination therapy.

Clinically Relevant Interactions with Anti-Infectives on Intensive Care Units-A Multicenter Delphi Study

Patients in intensive care units (ICUs) are at high risk of drug–drug interactions (DDIs) due to polypharmacy. Little is known about type and frequency of DDIs within German ICUs. Clinical pharmacists’ interventions (PI) recorded in a national database (ADKA-DokuPIK) were filtered for ICU patients. Binary DDIs involving ≥1 anti-infective agent with >1 database entry were selected. A modified two-step Delphi process with a group of senior hospital pharmacists was employed to evaluate selected DDIs for clinical relevance by using a five-point scale and to develop guidance for clinical practice. In total, 16,173 PI were recorded, including 1836 (11%) DDIs in the ICU setting. Of the latter, 41% (756/1836) included ≥1 anti-infective agent, 32% (590/1836) were binary DDIs, and 25% (455/1836) were listed at least twice. This translates into 88 different DDIs, 74% (65/88) of which were rated as being clinically relevant by our expert panel. The majority of DDIs (76% [67/88]) included macrolides, antifungals, or fluoroquinolones. This percentage was even higher in DDIs being rated as clinically relevant by the experts (85% [55/65]). It is noted that an inter-professional discussion and approach is needed in the individual patient management of DDIs. The guidance developed might be a tool for decision support.

Anti-hypertensive drugs deprescribing: an updated systematic review of clinical trials

Background

Polypharmacy is defined as the prescription of at least 5 different medicines for therapeutic or prophylactic effect and is a serious issue among elderly patients, who are frequently affected by multi-morbidity. Deprescribing is one of the proposed approaches to reduce the number of administered drugs, by eliminating those that are inappropriately prescribed. The aim of this systematic review is to provide an updated and systematic assessment of the benefit-risk profile of deprescribing of anti-hypertensive drugs, which are among the most commonly used drugs.

Methods

MEDLINE, EMBASE and The Cochrane Library were searched for studies assessing the efficacy and safety of anti-hypertensive drugs deprescribing in the period between January, 12,016 and December, 312,019. The quality of randomized clinical trials (RCTs) was assessed using the GRADE approach for the evaluation of the main outcomes. The risk of bias assessment was carried out using the Cochrane risk-of-bias tool.

Results

Overall, two RCTs were identified. Despite summarized evidence was in favor of anti-hypertensive deprescribing, the overall risk of bias was rated as high for each RCT included. According to the GRADE approach, the overall quality of the RCTs included was moderate regarding the following outcomes: systolic blood pressure < 150 mmHg after 12 weeks of follow-up, quality of life, frailty and cardiovascular risk.

Conclusions

This updated systematic review of the efficacy and safety of anti-hypertensive treatment deprescribing found two recently published RCTs, in addition to the previous guideline of the National Institute for Health and Care Excellence (NICE). Evidence points towards non-inferiority of anti-hypertensive deprescribing as compared to treatment continuation, despite the quality of published studies is not high. High quality experimental studies are urgently needed to further assess the effect of deprescribing for this drug class in specific categories of patients.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12875-021-01557-y.

Pharmacological Interactions of Nintedanib and Pirfenidone in Patients with Idiopathic Pulmonary Fibrosis in Times of COVID-19 Pandemic

The discovery of antifibrotic agents have resulted in advances in the therapeutic management of idiopathic pulmonary fibrosis (IPF). Currently, nintedanib and pirfenidone have become the basis of IPF therapy based on the results of large randomized clinical trials showing their safety and efficacy in reducing disease advancement. However, the goal of completely halting disease progress has not been reached yet. Administering nintedanib with add-on pirfenidone is supposed to enhance the therapeutic benefit by simultaneously acting on two different pathogenic pathways. All this becomes more important in the context of the ongoing global pandemic of coronavirus disease 2019 (COVID-19) because of the fibrotic consequences following SARS-CoV-2 infection in some patients. However, little information is available about their drug–drug interaction, which is important mainly in polymedicated patients. The aim of this review is to describe the current management of progressive fibrosing interstitial lung diseases (PF-ILDs) in general and of IPF in particular, focusing on the pharmacokinetic drug-drug interactions between these two drugs and their relationship with other medications in patients with IPF.

Potential drug-drug interactions in patients with cardiovascular diseases: findings from a prospective observational study

Background

Patients with cardiovascular diseases (CVD) are at high risk of experiencing drug–drug interactions (DDIs). The objective of this study was to evaluate the frequency, level and risk factors associated with potential-DDIs (pDDIs) in hospitalized CVD patients at cardiology departments of two tertiary care hospitals in Quetta, Pakistan.

Methods

In the current prospective observational study, a total of 300 eligible CVD inpatients were evaluated for pDDIs using Lexicomp Interact®. The pDDIs were classified into class A (no known interaction); B (no action needed); C (monitor therapy: it is documented that the benefits of an interaction outweigh the risk, appropriately monitor therapy in order to avoid potential adverse outcomes); D (consider therapy modification: it is documented that proper actions must be taken to reduce the toxicity resulting from an interaction); X (avoid combination: the risk of an interaction outweighs the benefits and are usually contraindicated). Multivariate binary logistic regression analysis was used to find factors associated with the presence of Class-D and/or X pDDIs. A p-value < 0.05 was considered statistically significant.

Results

With a median of 8.50 pDDIs per patient, all patients (100%) had ≥ 1 pDDIs. Out of total 2787 pDDIs observed, 74.06% (n = 2064) were of moderate and (n = 483) 17.33% of major severity. Class C pDDIs were most common (n = 1971, 70.72%) followed by D (n = 582, 20.88%), B (n = 204, 7.32%) and X (n = 30, 1.08%). Suffering from cardiovascular diseases other than myocardial infarction (OR 0.053, p-value < 0.001) and receiving > 12 drugs (OR 4.187, p-value = 0.009) had statistical significant association with the presence of class D and/or X pDDIs.

Conclusion

In the current study, pDDIs were highly prevalent. The inclusion of DDI screening tools, availability of clinical pharmacists and paying special attention to the high-risk patients may reduce the frequency of pDDIs at the study sites.

Pharmacokinetics of Commonly Used Antimicrobials in Critically Ill Adults During Extracorporeal Membrane Oxygenation: A Systematic Review

PURPOSE

Adequate dosing of antimicrobials is critical to properly treat infections and limit development of resistance and adverse effects. Limited guidance exists for antimicrobial dosing adjustments in patients requiring extracorporporeal membrane oxygenation (ECMO) therapy. A systematic review was conducted to delineate the pharmacokinetics (PK) and pharmacodynamics (PD) of antimicrobials in critically ill adult patients requiring ECMO.

METHODS

Medline, EMBASE, Global Health, and All EBM Reviews databases were searched. Grey literature was examined. All studies reporting PK/PD parameters of antimicrobials in critically ill adults treated with ECMO were included, except for case reports and congress abstracts. Ex vivo studies were included. Two independent reviewers applied the inclusion and exclusion criteria. Reviewers were then paired to independently abstract data and evaluate methodological quality of studies using the ROBINS-I tool and the compliance with ClinPK guidelines. Patients' and studies' characteristics, key PK/PD findings, details of ECMO circuits and co-treatments were summarized qualitatively. Dosing recommendations were formulated based on data from controlled studies.

RESULTS

Thirty-two clinical studies were included; most were observational and uncontrolled. Fourteen ex vivo studies were analysed. Information on patient characteristics and co-treatments was often missing. The effect of ECMO on PK/PD parameters of antimicrobials varied depending on the studied drugs. Few dosing recommendations could be formulated given the lack of good quality data.

CONCLUSION

Limited data exist on the PK/PD of antimicrobials during ECMO therapy. Rigorously designed and well powered populational PK studies are required to establish empiric dosing guidelines for antimicrobials in patients requiring ECMO support.

PROSPERO REGISTRATION NUMBER

CRD42018099992 (Registered: July 24th 2018).

Comparison of Clinical Importance of Drug Interactions Identified by Hospital Pharmacists and a Local Clinical Decision Support System

Background

Drug-drug interactions (DDIs) may cause adverse drug events, potentially leading to hospital admission. Clinical decision support systems (CDSSs) can improve decision-making by clinicians as well as drug safety. However, previous research has suggested that pharmacists are concerned about discrepancies between CDSSs and common clinical practice in terms of severity ratings and recommended actions for DDIs.

Objectives

The primary objective was to characterize the level of agreement in terms of DDI severity ranking and actions recommended between the local CDSS and pharmacists. The secondary objectives were to determine the level of agreement among pharmacists concerning DDI severity, to determine the influence of the CDSS on clinicians' decision-making, and to review the literature supporting the severity rankings of DDIs identified in the study institution's database.

Methods

This 2-part survey study involved pharmacists and pharmacy residents working at 1 of 4 health organizations within the Lower Mainland Pharmacy Services, British Columbia, who were invited to participate by email. Participants were first asked to rank the severity of 15 drug pairs (representing potential DDIs) on a 5-point Likert scale and to select an action to manage each interaction. Participants were then given the CDSS severity classification for the same 15 pairs and again asked to select an appropriate management action.

Results

Of the estimated 500 eligible pharmacists, a total of 73 pharmacists participated, for a response rate of about 15%. For DDIs of moderate severity, most participants chose to monitor. For severe and contraindicated interactions, the severity ranking and action proposed by participants varied, despite the same severity classification by the CDSS. There was poor agreement among respondents about the severity of the various DDIs. Moreover, knowledge of the CDSS severity ranking did not seem to change the actions proposed by most respondents.

Conclusion

This study identified a gap between the local CDSS and clinical practice. There were discrepancies in terms of severity rankings and actions proposed to manage DDIs, particularly for severe and contraindicated DDIs. The current CDSS did not appear to have a large impact on clinical decision-making, which suggests that it may not be functioning to its full potential.

Advancement in predicting interactions between drugs used to treat psoriasis and its comorbidities by integrating molecular and clinical resources

OBJECTIVE

Drug-drug interactions (DDIs) can result in adverse and potentially life-threatening health consequences; however, it is challenging to predict potential DDIs in advance. We introduce a new computational approach to comprehensively assess the drug pairs which may be involved in specific DDI types by combining information from large-scale gene expression (984 transcriptomic datasets), molecular structure (2159 drugs), and medical claims (150 million patients).

MATERIALS AND METHODS

Features were integrated using ensemble machine learning techniques, and we evaluated the DDIs predicted with a large hospital-based medical records dataset. Our pipeline integrates information from >30 different resources, including >10 000 drugs and >1.7 million drug-gene pairs. We applied our technique to predict interactions between 37 611 drug pairs used to treat psoriasis and its comorbidities.

RESULTS

Our approach achieves >0.9 area under the receiver operator curve (AUROC) for differentiating 11 861 known DDIs from 25 750 non-DDI drug pairs. Significantly, we demonstrate that the novel DDIs we predict can be confirmed through independent data sources and supported using clinical medical records.

CONCLUSIONS

By applying machine learning and taking advantage of molecular, genomic, and health record data, we are able to accurately predict potential new DDIs that can have an impact on public health.

How effective are electronic medication systems in reducing medication error rates and associated harm among hospital inpatients? A systematic review and meta-analysis

OBJECTIVE

To conduct a systematic review and meta-analysis to assess: 1) changes in medication error rates and associated patient harm following electronic medication system (EMS) implementation; and 2) evidence of system-related medication errors facilitated by the use of an EMS.

MATERIALS AND METHODS

We searched Medline, Scopus, Embase, and CINAHL for studies published between January 2005 and March 2019, comparing medication errors rates with or without assessments of related harm (actual or potential) before and after EMS implementation. EMS was defined as a computer-based system enabling the prescribing, supply, and/or administration of medicines. Study quality was assessed.

RESULTS

There was substantial heterogeneity in outcomes of the 18 included studies. Only 2 were strong quality. Meta-analysis of 5 studies reporting change in actual harm post-EMS showed no reduced risk (RR: 1.22, 95% CI: 0.18-8.38, P = .8) and meta-analysis of 3 studies reporting change in administration errors found a significant reduction in error rates (RR: 0.77, 95% CI: 0.72-0.83, P = .004). Of 10 studies of prescribing error rates, 9 reported a reduction but variable denominators precluded meta-analysis. Twelve studies provided specific examples of system-related medication errors; 5 quantified their occurrence.

DISCUSSION AND CONCLUSION

Despite the wide-scale adoption of EMS in hospitals around the world, the quality of evidence about their effectiveness in medication error and associated harm reduction is variable. Some confidence can be placed in the ability of systems to reduce prescribing error rates. However, much is still unknown about mechanisms which may be most effective in improving medication safety and design features which facilitate new error risks.

Potentially inappropriate medications and medication combinations before, during and after hospitalizations: an analysis of pathways and determinants in the Swiss healthcare setting

Background

A hospitalization phase represents a challenge to medication safety especially for multimorbid patients as acute medical needs might interact with pre-existing medications or evoke adverse drug effects. This project aimed to examine the prevalence and risk factors of potentially inappropriate medications (PIMs) and medication combinations (PIMCs) in the context of hospitalizations.

Methods

Analyses are based on claims data of patients (≥65 years) with basic mandatory health insurance at the Helsana Group, and on data from the Hirslanden Swiss Hospital Group. We assessed PIMs and PIMCs of patients who were hospitalized in 2013 at three different time points (quarter prior, during, after hospitalization). PIMs were identified using the PRISCUS list, whereas PIMCs were derived from compendium.ch. Zero-inflated Poisson regression models were applied to determine risk factors of PIMs and PIMCs.

Results

Throughout the observation period, more than 80% of patients had at least one PIM, ranging from 49.7% in the pre-hospitalization, 53.6% in the hospitalization to 48.2% in the post-hospitalization period. PIMCs were found in 46.6% of patients prior to hospitalization, in 21.3% during hospitalization, and in 25.0% of patients after discharge. Additional medication prescriptions compared to the preceding period and increasing age were the main risk factors, whereas managed care was associated with a decrease in PIMs and PIMCs.

Conclusion

We conclude that a patient’s hospitalization offers the possibility to increase medication safety. Nevertheless, the prevalence of PIMs and PIMCs is relatively high in the study population. Therefore, our results indicate a need for interventions to increase medication safety in the Swiss healthcare setting.

Drug interactions detected by a computer-assisted prescription system in primary care patients in Spain: MULTIPAP study

Background

Drug interactions increase the risk of treatment failure, intoxication, hospital admissions, consultations and mortality. Computer-assisted prescription systems can help to detect interactions.

Objectives

To describe the drug–drug interaction (DDI) and drug–disease interaction (DdI) prevalence identified by a computer-assisted prescription system in patients with multimorbidity and polypharmacy. Factors associated with clinically relevant interactions were analysed.

Methods

Observational, descriptive, cross-sectional study in primary health care centres was undertaken in Spain. The sample included 593 patients aged 65–74 years with multimorbidity and polypharmacy participating in the MULTIPAP Study, recruited from November 2016 to January 2017. Drug interactions were identified by a computer-assisted prescription system. Descriptive, bivariate, and multivariate analyses with logistic regression models and robust estimators were performed.

Results

Half (50.1% (95% CI 46.1–54.1)) of the patients had at least one relevant DDI and 23.9% (95% CI 18.9–25.6) presented with a DdI. Non-opioid–central nervous system depressant drug combinations and benzodiazepine–opioid drug combinations were the two most common clinically relevant interactions (10.8% and 5.9%, respectively). Factors associated with DDI were the use of more than 10 drugs (OR 11.86; 95% CI 6.92–20.33) and having anxiety/depressive disorder (OR 1.98; 95% CI 1.31–2.98). Protective factors against DDI were hypertension (OR 0.62; 95% CI 0.41–0.94), diabetes (OR 0.57; 95% CI 0.40–0.82), and ischaemic heart disease (OR 0.43; 95% CI 0.25–0.74).

Conclusion

Drug interactions are prevalent in patients aged 65–74 years with multimorbidity and polypharmacy. The clinically relevant DDI frequency is low. The number of prescriptions taken is the most relevant factor associated with presenting a clinically relevant DDI.

Drug-drug Interactions with Warfarin: A Systematic Review and Meta-analysis

AIM

The objective of this paper is to systematically review the literature on drug-drug interactions with warfarin, with a focus on patient-important clinical outcomes.

METHODS

MEDLINE, EMBASE, and the International Pharmaceutical Abstract (IPA) databases were searched from January 2004 to August 2019. We included studies describing drug-drug interactions between warfarin and other drugs. Screening and data extraction were conducted independently and in duplicate. We synthesized pooled odds ratios (OR) with 95% confidence intervals (CIs), comparing warfarin plus another medication to warfarin alone. We assessed the risk of bias at the study level and evaluated the overall certainty of evidence using GRADE.

RESULTS

Of 42,013 citations identified, a total of 72 studies reporting on 3,735,775 patients were considered eligible, including 11 randomized clinical trials and 61 observational studies. Increased risk of clinically relevant bleeding when added to warfarin therapy was observed for antiplatelet (AP) regimens (OR=1.74; 95% CI 1.56, 1.94), many antimicrobials (OR=1.63; 95% CI 1.45, 1.83), NSAIDs including COX-2 NSAIDs (OR=1.83; 95% CI 1.29, 2.59), SSRIs (OR=1.62; 95% CI 1.42, 1.85), mirtazapine (OR=1.75; 95% CI 1.30, 2.36), loop diuretics (OR=1.92; 95% CI 1.29, 2.86), and others. We found a protective effect of proton pump inhibitors (PPIs) against warfarin-related gastrointestinal (GI) bleedings (OR=0.69; 95% CI 0.64, 0.73). No significant effect on thromboembolic events or mortality of any drug group used with warfarin was found, including single or dual AP regimens.

CONCLUSIONS

This review found low to moderate certainty evidence supporting the interaction between warfarin and a small group of medications, which result in increased bleeding risk. PPIs are associated with reduced hospitalization for upper GI bleeding for patients taking warfarin. Further studies are required to better understand drug-drug interactions leading to thromboembolic outcomes or death.