Assessment of potential drug-drug interactions and its associated factors in the hospitalized cardiac patients

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

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

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.

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

BACKGROUND

Drug-drug interactions (DDIs) influence the effectiveness of medication and thus determine the treatment outcomes of diseases managed with pharmacotherapy. This study aimed to determine the prevalence, severity, and factors associated with potential drug-drug interactions in prescriptions presented at private pharmacies in Mbarara city.

METHODS

DDIs were identified and classified basing on risk and severity using Lexicomp drug interaction database. STATA version 13 was used to analyze the collected data. Descriptive statistics were used to summarize the severity of potential DDIs identified. Bivariate and multivariate logistic regression was employed to identify different factors associated with the presence of potential DDIs.

RESULTS

A total of 295 prescriptions from 18 private pharmacies were studied and the prevalence of clinically significant potential DDIs was 37.6%. About half (149, 50.5%) of the patients were females, the majority (199, 67.5%) were adults 18-59 years of age whereas most (208, 70.5%) had a comorbid condition. Over one half (162, 54.9%) of the prescriptions were received from hospitals and majority of the prescriptions had 4 drugs prescribed (n = 175, 59.32%). Having one or more comorbidities and prescribing of therapeutic drug categories including anti-fungal, antihypertensives, analgesics, or corticosteroids were significantly associated with potential DDIs.

CONCLUSIONS

The prevalence of potential drug-drug interactions in outpatient setting in Mbarara city was high and majority of the potential DDIs were of moderate severity. Having 1 or more comorbidities and prescribing of therapeutic drug categories including antifungals, antihypertensives, analgesics, or corticosteroids were significantly associated with potential DDIs.

Assessment of frequency and types of drug interactions in intensive care units: a cross-sectional study

Background

Drug interactions can cause adverse reactions, from treatment inefficiency to serious treatment complications in the patient. Due to the complexity of drug therapy and the simultaneous use of several drugs and different drug groups, patients hospitalized in intensive care units are exposed to more drug interactions. Therefore, this study was conducted to investigate the frequency of drug interactions in patients hospitalized in the ICU.

Methods

In this cross-sectional study, the files of 300 patients hospitalized in the ICU were examined. Drug interactions were determined using Lexicomp software and the book drug iteration facts. Data analysis was done using SPSS 21 software.

Findings

The findings showed that there were a total of 1121 cases of interference. Two hundred thirty-one (77%) patients had moderate interference, 94 (31.3%) patients had mild interference, and 67 patients (22.3%) had severe interference. One hundred eight patients had B-type interference, 223 C-type interference, 116 D-type interference, and 6 X-type interference, so most of the interactions are C-type interference. One hundred eighty-six patients had pharmacokinetic interference and 201 patients had pharmacodynamics interference. The highest interaction was between two drugs, heparin and aspirin with 58 cases.

Conclusion

This study highlights the alarming frequency and types of drug interactions observed in ICU. The high prevalence of drug interactions emphasizes the need for improved medication management and vigilance in these critical care settings. Polypharmacy and certain drug combinations were identified as major contributing factors to the occurrence of drug interactions, which calls for regular medication reviews and cautious prescribing practices.

Medication Related-Problems and Associated Factors Among Patients with Hypertension at a Tertiary Care Hospital in Ethiopia: A Prospective Interventional Study

Background

Hypertension affects more than 1.4 billion people worldwide currently, with that number anticipated to climb to 1.6 billion by 2025 with high mortality and morbidity effects. Medication related problems in cardiovascular disease patients, especially among hypertension patients were found to be high and a critical problem which is associated with high mortality, complication, prolonged hospital stay, compromised quality of life and increase health care cost.

Objective

To determine medication related problems and its predictors among hypertension patients on chronic follow-up at Jimma Medical Center.

Methods

A prospective interventional study was conducted among hypertension patients from November 28, 2021 to June 30, 2022 at Jimma Medical Center. Medication related problems were classified and identified based on Pharmaceutical care network Europe drug classification tool version 9.0. Interventions were done through discussion with individual prescriber and patients. Consecutive sampling technique was used. Binary Logistic regression was used to identify independent predictors of medication related problems. Variables having P-values < 0.05 were considered statistically significant.

Results

Among 384 hypertension patients included in the study, 219 (57.1%) were male. The mean (SD) age was 49.06+17.79. Two thirds of study participants had at least one medication related problem. A total of 483 MRPs were identified among 231 (60.15%) patients. Treatment effectiveness related problem (55.48%) was the most common observed medication related problems. Alcoholism (AOR; 3.15, 95% CI [1.46-7.23]), stage II hypertension (AOR=2.77, 95% CI= [3.53-4.66]); comorbidity (AOR=2.88, 95% CI= [1.47-5.66]) and polypharmacy (AOR=3.07, 95% CI= [1.57-5.99]) were the independent predictors of medication related problems.

Conclusion

The prevalence of medication related problems was high among hypertensive patients. Alcoholism, stage II hypertension, comorbidity and poly-pharmacy were the predictors of medication related problems. Therefore, to overcome the problems, clinical pharmacists, physicians and other health care professionals have to work in collaboration.

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.

Drug-Drug Interactions in Elderly Adults in Dentistry Care: a Cross-Sectional Study

Statement of the Problem

Given the increase in the population of the elderly patients and the risk of systemic diseases in these individuals, the prevalence of the intake of various drugs is higher in elderly patients, which exposes them to the side effects of drugs including potential drug-drug interactions (DDIs).

Purpose

Therefore, the present study is an attempt to evaluate the drug interactions between the drugs used by the elderly patients visiting Kerman School of Dentistry and the common dental drugs in 2020.

Materials and Method

This cross-sectional study was conducted on the elderly patients (≥60 years (who referred to Kerman School of Dentistry for dental problems. After obtaining the oral informed consent and collecting demographic information, the drugs used by the patients and their systemic diseases were questioned, listed, and compared with the drugs mentioned in their files. The drug interactions with the common dental drugs were studied in the elderly patients using the www.drugs.com website. Chi-square, T, ANOVA, Kruskal-Wallis, and Mann-Whitney tests were used to compare the variables. The significance level was 0.05.

Results

Of participants included in this study, 78 (52%) were female and 72(48%) were male. The average age of these patients was 71.27 6.32 years. The most common systemic diseases were hypertension (57.3%), heart diseases (42.0%), and diabetes mellitus (40.7%). Our analysis of the DDIs between 11 commonly prescribed dental drugs and 95 drugs used by the patients revealed 212 DDIs (21.7% minor, 68.3% moderate, and 9.9% major interactions). There was a significant relationship between the number of drugs and DDIs, whereas DDIs had no significant relationship with gender and educational level.

Conclusion

The results reflected the high percentage of DDIs among the patients. In addition, there was a significant relationship between polypharmacy, which is highly prevalent among the elderly patients, and drug interactions.

Drug-Drug-Gene Interactions in Cardiovascular Medicine

Cardiovascular disease remains a leading cause of both morbidity and mortality worldwide. It is widely accepted that both concomitant medications (drug-drug interactions, DDIs) and genomic factors (drug-gene interactions, DGIs) can influence cardiovascular drug-related efficacy and safety outcomes. Although thousands of DDI and DGI (aka pharmacogenomic) studies have been published to date, the literature on drug-drug-gene interactions (DDGIs, cumulative effects of DDIs and DGIs) remains scarce. Moreover, multimorbidity is common in cardiovascular disease patients and is often associated with polypharmacy, which increases the likelihood of clinically relevant drug-related interactions. These, in turn, can lead to reduced drug efficacy, medication-related harm (adverse drug reactions, longer hospitalizations, mortality) and increased healthcare costs. To examine the extent to which DDGIs and other interactions influence efficacy and safety outcomes in the field of cardiovascular medicine, we review current evidence in the field. We describe the different categories of DDIs and DGIs before illustrating how these two interact to produce DDGIs and other complex interactions. We provide examples of studies that have reported the prevalence of clinically relevant interactions and the most implicated cardiovascular medicines before outlining the challenges associated with dealing with these interactions in clinical practice. Finally, we provide recommendations on how to manage the challenges including but not limited to expanding the scope of drug information compendia, interaction databases and clinical implementation guidelines (to include clinically relevant DDGIs and other complex interactions) and work towards their harmonization; better use of electronic decision support tools; using big data and novel computational techniques; using clinically relevant endpoints, preemptive genotyping; ensuring ethnic diversity; and upskilling of clinicians in pharmacogenomics and personalized medicine.

Drug-related problems and its predictors among hospitalized heart failure patients at Jimma Medical Center, South West Ethiopia: prospective interventional study

Background

Drug-related problems are associated with high mortality, complications, prolonged hospital stay, compromised quality of life, and increased healthcare costs. This problem is high in patients hospitalized with chronic conditions such as heart failure. However, there are limited studies conducted on this area, particularly in Ethiopia.

Objective

To evaluate drug-related problems, their predictors, and clinical pharmacist intervention among hospitalized heart failure patients at Jimma Medical Center, Ethiopia.

Methods and participants

A prospective interventional study was conducted among hospitalized heart failure patients from September 30, 2020, to May 28, 2021, at Jimma Medical Center. Drug-related problems were sorted based on the Pharmaceutical Care Network Europe drug classification tool version 9.0. Patient's specific data were collected using a structured questionnaire. Data was analyzed using statistical software package version 23.0. Multivariate logistic regression analysis was used to identify independent predictors of drug-related problems occurrence and statistical significance was considered at a p value < 0.05.

Results

A total of 237 heart failure patients were included in this study. The mean (SD) age was 49.06 + 17.79. About two-thirds (66.2%) of study patients had at least one drug-related problem during their hospital stay. A total of 283 drug-related problems were identified among 157 patients. Treatment effectiveness-related problem (55.48%) was the most common observed drug-related problem. The independent predictors of drug-related problems were khat chewing [AOR = 3.25, 95% CI = (1.46–7.23)], hospital stay > 18 days [AOR = 3.77, 95% CI = (1.93–7.37)]; presence of comorbid condition [AOR = 2.59, 95% CI = (1.35–4.96)] and polypharmacy [AOR = 2.94, 95% CI = (1.54–5.61)].

Conclusion

The prevalence of drug-related problems was high among hospitalized heart failure patients in the study area. Chewing khat, prolonged hospital stay, comorbidity, and polypharmacy were the predictors of drug-related problems. Hence, to overcome these problems, clinical pharmacists, physicians, and other health professionals have to work in collaboration.

A Prospective Study of Medication Surveillance of a Pediatric Tertiary Care Hospital in Lahore, Pakistan

PURPOSE

Several studies have shown that polypharmacy is the main cause of drug interactions, and the prevalence and the level of the severity varied with the duration of stay in the hospital, sex and race of the patients. The aims of this investigation were to identify the drug-drug interactions in hospitalized pediatric patients associated with polypharmacy, and to categorize the drug interactions in pharmacokinetic or pharmacodynamic interactions according to their level of severity.

METHODS

A cross-sectional, prospective analytical study was performed at a pediatric tertiary care hospital in Lahore, Pakistan for the duration of 4 months, which included prescription orders for 300 patients. Data were collected from patient medical files about previous and current medication history. Drug interactions were analyzed using interaction checker on Medscape and categorized according to the severity levels.

RESULTS

Out of 300 patients, the occurrence of drug interactions was found in 157 (52.3%) patients, while in 143 (47.7%), no interaction was found. Among these interactions, 50.7% were pharmacodynamic interactions, and 49.30% were pharmacokinetic interactions. Eighty-one percent of prescription orders with drug interactions contained more than three drugs, and 11.9% of interactions were severe. The majority of interactions were of amikacin-vancomycin, piroxicam-captopril and captopril-ciprofloxacin.

CONCLUSION

Most of the interactions were moderate among patients with multiple drug prescriptions. The drug interactions can be minimized by providing special patient monitoring and adequate management with prior knowledge of these drug interaction.

Prevalence of potential drug - drug interactions in the cardiothoracic intensive care unit patients in a Chinese tertiary care teaching hospital

Background

With an increasing number of reviews describing clinically significant drug–drug interactions (DDIs), the scope and severity of interactions involving commonly used drugs in cardiothoracic intensive care units (CCUs) remain unclear. This study aims to identify risk factors and determine the incidence of potential DDIs in intensive care units.

Methods

DDIs were identified based on the profile of the prescribed drug and classified according to the Micromedex drug interaction database. Potential risk factors associated with DDIs have been identified.

Results

A total of 3193 medication episodes were evaluated, and 680 DDIs (21.3%) were found. A total of 203 patients were recruited into the study, with an average of 3.4 DDIs per patient [95% confidence interval (3.2 − 3.6)]. A total of 84.2% of the patients experienced at least one DDI. Anticoagulant and antiplatelet agents were involved in 33.5% (228/680) of the potential drug − drug interactions in the CCU. Univariate analysis and multiple logistic regression analysis showed that the age of the patient and the number of medications prescribed were significantly correlated with the occurrence of DDIs. In multiple linear regression analysis, the number of DDIs had a significant correlation only with the number of prescription drugs.

Conclusions

A high prevalence of DDIs was observed, especially in intensive care units without pharmacist intervention and computerized drug monitoring systems, highlighting the need for active surveillance to prevent potential adverse events.

Identification of Potential of Drug-Drug Interaction and Its Affecting Factors: A cross-sectional study among hospitalized coronary heart disease patients

Background:

Coronary Heart Disease (CHD) patients are at risk of suffering from drug interactions, leading to a higher risk of mortality and morbidity among these patients. This study aims to identify the potential drug-drug interactions (PDDIs) and CHD patients' related factors.

Methods:

A cross-sectional study was performed among the CHD patients to identify the PDDIs from 2014 to 2017 at Secondary Hospital. The PDDIs were categorized according to the interaction mechanism, onset, severity, and documentation.

Results:

Among 91 CHD patients, 151 PDDIs were identified consisting of pharmacodynamics mechanism and delayed onset, 50.33% and 83.44%, respectively. Furthermore, there was a correlation between the number of PDDIs and the number of drugs (r = 0.496; p < 0,001).

Conclusion:

: This study revealed that the more the drugs were prescribed to CHD patients, the more the PDDIs risk would occur. The regular monitoring of the CHD patient’s prescriptions is noteworthy to avoid the PDDIs.

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

Purpose

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

Patients and Methods

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

Results

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

Conclusion

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

Prevalence of polypharmacy and risk of potential drug-drug interactions among hospitalized patients with emphasis on the pharmacokinetics

BACKGROUND

Both polypharmacy and potential drug-drug interactions (pDDIs), especially those at the pharmacokinetic level, are common in hospitalized patients and are associated with adverse effects and failure of therapy.

OBJECTIVE

The aim of the present study is to investigate retrospectively the prevalence of polypharmacy and the risk of potential pharmacokinetic drug-drug interaction among hospitalized patients.

METHODS

The medical documentation of hospitalized patients in the unit of internal diseases at the hospital "St Marina" in Varna, Bulgaria for a period of six months (January-July 2016) was retrospectively reviewed. Lexicomp® Drug Interaction software was used for the detection of pDDI. Descriptive statistic and logistic regression were used for data analysis.

RESULTS

In this study, 294 patients out of 510 (57%) were selected with polypharmacy. The number of detected potential pharmacokinetic DDIs (pPKDDIs) was only 216 (or 12,4%), but almost 40% of patients with polypharmacy were exposed to at least one pPKDDIs. The most common pPKDDIs occur at the biotransformation level - 78 (36,1%), and the most common enzyme form that is involved in these interactions is cytochrome 3A4 (44 or 20,4%). The number of prescribed medications (>7) was found to increase the possibility of having pDDIs (OR 25.535, 95% CI 12.529 to 52.042; p = <0.001) and pPKDDIs (OR 5.165, 95% CI 3.430 to 7.779; p = <0.001) as well.

CONCLUSION AND RELEVANCE

Caution should be taken in patients taking more than seven drugs and careful assessment of the pPKDDIs should be made. When such interactions are detected, they need to be properly evaluated and managed.

Risk Factors for the Occurrence of Potential Drug-Drug Interactions in Surgical Patients

Background: Drug-drug interactions are defined as modifications of the drug action that result from the simultaneous administration of another individual drug or several drugs. Nowadays, potential drug-drug interactions (DDIs) are most frequently detected and analyzed using personal digital assistant software programs (online interaction checker tools).

Objective: To determine the risk factors for the emergence of all drug-drug interactions in surgical patients with particular emphasis on clinically significant interactions.

Patients and methods: This was a retrospective cohort analysis of patients treated at the Surgical Clinic of the Clinical Center Kragujevac. Three interaction checkers were used to reveal drug-drug interactions: Medscape, Epocrates and Micromedex.

Results: The study included total of 200 patients, aged 58.54±17.08 years. Average number of drug-drug interactions per patient was between 10.50±9.10 (Micromedex) and 18.75±17.14 (Epocrates). Number of prescribed drugs, antidepressive therapy, antiarrhythmic therapy, number of pharmacological/therapeutic subgroups (2nd level of ATC classification) prescribed, delirium or dementia, diabetes, heart failure, and number of physicians who prescribed drugs to single patient were identified as risk factors for drug-drug interactions while length of hospitalization in days and age of patient in years emerged as protective factors.

Conclusion: Drug-drug interactions are relatively common in surgical patients and predisposed by factors such as number of prescribed drugs or drug group per patient, number of physicians who prescribed drugs, antidepressive therapy, antiarrhythmic therapy, presence of delirium or dementia, diabetes and heart failure. On the other hand, prolonged hospitalization and higher age are factors that reduce the risk of interactions in surgical patients.

Influence of drug-related problems on length of hospital stay of women with a history of preeclampsia: A multicenter study

BACKGROUND

Approximately 5-7 % of pregnant women have hypertension during pregnancy, requiring antihypertensive drug treatment. There have been a lack of studies evaluating how drug-related problems (DRPs) affect morbidity or mortality in the postpartum period among women with a history of preeclampsia.

OBJECTIVE

To determine the influence of drug-related problems on length of hospital stay of postpartum women with a history of preeclampsia.

METHODS

This cross-sectional study included postpartum women diagnosed with preeclampsia, from June to November 2016, in two teaching maternity hospitals in Brazil. The outcomes assessed were, length of hospital stay of postpartum women. The DRPs were classified through the Pharmaceutical Care Network Europe Foundation (PCNE) v 8.01.

RESULTS

600 women were included, and 354 (59%) were exposed to at least one DRP. The most frequent DRPs were no administration of the prescribed medication, lack of prescription of a medication, although the indication was clear, and ineffectiveness (unknown reason). In patients exposed to DRP, the average length of hospital stay after labour was 5.4 (S.D. 3.6) days versus 4.4 (S.D. 3.3) days in patients non-exposed to DRP (p = 0.0001). The period (in days) to achieve blood pressure control after labour was 4.5 (S.D. 3.5) 3.5 (S.D. 3.2), respectively (p = 0.0001). There were no deaths during the study.

CONCLUSION AND RELEVANCE

Drug-related problems significantly increased the length of hospital stay in postpartum women with a history of preeclampsia.

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.

Frequency of polypharmacy and drug interactions in inpatients in the emergency department, Southwest of Iran

This study aimed to evaluate the polypharmacy extent and the frequency and severity of drug interactions by evaluating inpatients in the emergency department. In this epidemiologicaldescriptive study, data were collected retrospectively by reviewing medical records of 92 hospitalized patients in the emergency department with a stay over 48 hours. Out of the study population, 54.3% and 45.7% were respectively male and female, with a mean age of 59.09. In terms of hospitalization, 27.2% and 16.3% were hospitalized due to heart problems and trauma, respectively and the mean length of hospitalization was 3.91 with a standard deviation of 2.57 days. The mean drug received was 8.48, with a standard deviation of 4.48. Of the patients, 81.5% received more than 5 drugs; in addition, the observed amounts of drug interactions of A, B, C, D, and X were 2.5%, 17%, 59.3%, 19.5%, and 1.9%, respectively. The drug interaction prevalence in inpatients in the emergency department was high. The presence of a pharmacist is necessary to identify drug interactions and reduce drug-therapy problems to provide quality services.

Drug-drug interactions in neonatal intensive care: A prospective cohort study

BACKGROUND

To characterize the prevalence and profile of drug-drug interactions (DDIs), the drugs most related to major DDIs and risk factors of their prescription in a neonatal intensive care unit (NICU).

METHODS

Neonates admitted to a NICU who had at least one medication prescribed and a hospital stay >24 h were included in a prospective cohort study (August 2017 to July 2018). All medications prescribed during the hospitalization were collected from all neonates (n = 220), with the screening for DDIs. Prevalence and type of DDIs was identified. Network analysis was used to identify the drugs more implicated with DDIs. Logistic regression was used for the analysis of risk factors (p < 0.05).

RESULTS

Over 70% of neonates were exposed to DDIs and 29% were exposed to major DDIs. The network analysis identified furosemide, fentanyl, aminophylline and fluconazole as most implicated with DDI, fentanyl was especially associated with major DDIs. The number of drugs (OR 1.60, p < 0.01), caesarean delivery (OR 2.68, p < 0.05), gestational age (OR 1.03, p < 0.01) and APGAR score (OR 0.78, p < 0.01) were identified as risk factors for exposure to DDI.

CONCLUSION

Neonates in intensive care have a high exposure to DDIs and the occurrence of major DDIs is related specifically to the prescription of fentanyl. The number of prescribed drugs, gestational age, cesarean delivery and low APGAR score in the first minute were identified as risk factors for DDIs in NICU.

Prevalence and Clinical Significance of Drug-Drug and Drug-Dietary Supplement Interactions among Patients Admitted for Cardiothoracic Surgery in Greece

Background: Drug interactions represent a major issue in clinical settings, especially for critically ill patients such as those with cardiovascular disease (CVD) who require cardiothoracic surgery (CTS) and receive a high number of different medications. Methods: A cross-sectional study aimed at evaluating the exposure and clinical significance of drug–drug (DDIs) and drug–dietary supplement interactions (DDSIs) in patients admitted for CTS in the University Hospital of Crete Greece. DDIs were evaluated regarding underlying pharmacological mechanisms upon admission, preoperation, postoperation, and discharge from CTS clinic. Additionally, upon admission, the use of dietary supplements (DSs) and if patients had informed their treating physician that they were using these were recorded with subsequent analysis of potential DDSIs with prescribed medications. Results: The study employed 76 patients who were admitted for CTS and accepted to participate. Overall, 166 unique DDIs were identified, with 32% of them being related to pharmacokinetic (PK) processes and the rest (68%) were related to possible alterations of pharmacodynamic (PD) action. CVD medications and drugs for central nervous system disorders were the most frequently interacting medications. In total, 12% of the identified DDIs were of serious clinical significance. The frequency of PK-DDIs was higher during admission and discharge, whereas PD-DDIs were mainly recorded during pre- and postoperation periods. Regarding DS usage, 60% of patients were using DSs and perceived them as safe, and the majority had not informed their treating physician of this or sought out medical advice. Analysis of medical records showed 30 potential combinations with prescribed medications that could lead in DDSIs due to modulation of PK or PD processes, and grapefruit juice consumption was involved in 38% of them. Conclusions: An increased burden of DDIs and DDSIs was identified mostly upon admission for patients in CTS clinics in Greece. Healthcare providers, especially prescribing physicians in Greece, should always take into consideration the possibility of DDIs and the likely use of DS products by patients to promote their well-being; this should only be undertaken after receiving medical advice and an evidenced-based evaluation.

Assessment of Potential Drug–Drug Interactions and Their Predictors in Chronic Outpatient Department of Dessie Referral Hospital, Dessie, Northeast Ethiopia

Objective

To assess the prevalence and predictors of Potential drug–drug interactions (DDIs) at the chronic outpatient department of Dessie Referral Hospital, Dessie, Northeast Ethiopia.

Patients and Methods

A cross-sectional study was carried out on the medical records of patients treated in the chronic ambulatory department of Dessie Referral Hospital (DRH), from March 1/2019 to May 30/2019. Ethical clearance was granted from the department of pharmacy, college of medicine, and health sciences, Wollo University. Lexi-comp computer program database was used to detect pDDIs. SPSS version 22 was used to produce a descriptive analysis of the background data and logistic regression to identify predictors of pDDIs.

Results

In this study, the medical record of 300 patients has been reviewed and 489 pDDIs have been identified. The prevalence of pDDIs per patient was 1.63. Of all the identified pDDIs, the moderate severity interactions were the majority, 88.55% (n=433) followed by 8.38% (n=41) of minor, 2.66% (n=13) of major, and 0.41% (n=2) of contraindicated drug interactions. Taking three or more drugs at a time has been found as a statistically significant predictor of the occurrence of pDDIs.

Conclusion

A high rate of moderate severity pDDIs have been recorded. A system of checks and balances should be developed and executed for all those who are involved in prescribing, dispensing, and administration of medications for effective identification and prevention of pDDIs.

Adverse drug reactions related to potential serious drug interactions in patients with cardiovascular diseases

OBJECTIVE

To assess the occurrence of adverse drug reactions associated with potential serious drug interactions identified in prescriptions of hospitalized patients with cardiovascular disease.

METHOD

A documentary, quantitative, and cross-sectional research study. Between August and September 2016, ninety-nine prescriptions of patients hospitalized for more than 48 hours in the cardiology ward of a hospital in Rio de Janeiro were analyzed. Drug interactions were evaluated by Micromedex®, and adverse events were identified through trackers and analyzed by specialists using the Naranjo Algorithm, by means of descriptive statistics.

RESULTS

Eighteen potential serious interactions were detected in 22 drug pairs, mainly simvastatin x anlodipine (18%) and enoxaparin x clopidogrel (18%). Of the 18 medical records investigated, four trackers were found and three probable adverse events (16.6%) were defined due to hemorrhagic changes in patients.

CONCLUSION

Drug interactions are likely to cause harm to the patient, which requires implementing barriers for the safety of the medication system.

Assessing Drug-Drug Interaction Potential among Patients Admitted to Surgery Departments in Three Palestinian Hospitals

Background

Drug-drug interactions (DDIs) are a common issue that leads to adverse drug reactions in hospitals. Patients in the surgical department are expected to have potential DDIs that may lead to morbidity and mortality.

Objectives

To study potential DDI prevalence in the surgery departments in 3 hospitals in Palestine. Moreover, to identify pertinent factors that are associated with drug-drug interactions.

Method

A cross-sectional study in 3 governmental Palestinian hospitals: Palestine Medical Complex, Rafidia Hospital, and Beit Jala Hospital. Patients who are 20 years old or above and admitted to the surgical wards between September 2017 and February 2018 were included in the study. Patient demographics, all medications given in the hospital, and hospitalization period were obtained from medical files. The digital clinical decision support system Micromedex® was used for analysis and classification of possible drug interactions. Bivariate analysis and logistic regression were used to study the risk factors for developing DDIs.

Results

502 patients were included in this report. The prevalence of potential DDIs among patients admitted to surgery wards in three Palestinian hospitals was 56%. The number of detected potential DDIs per patient was 2.22 ± 3.76. The number of prescribed medications (P < 0.001) was found to increase the possibility of having drug interactions.

Conclusions

DDIs in Palestinian hospitals are a prevalent problem, and caution should be taken when ordering medications to hospitalized patients in surgery departments.

Potential drug-drug interactions associated with adverse clinical outcomes and abnormal laboratory findings in patients with malaria

BACKGROUND

Hospitalized patients with malaria often present with comorbidities or associated complications for which a variety of drugs are prescribed. Multiple drug therapy often leads to drug-drug interactions (DDIs). Therefore, the current study investigated the prevalence, levels, risk factors, clinical relevance, and monitoring parameters/management guidelines of potential DDIs (pDDIs) among inpatients with malaria.

METHODS

A retrospective cohort study was carried out at two tertiary care hospitals. A total of 398 patients' profiles were evaluated for pDDIs using the Micromedex Drug-Reax^®. Odds ratios were calculated to identify the strength of association between presence of DDIs and potential risk factors via logistic regression analysis. Further, the clinical relevance of frequent pDDIs was investigated.

RESULTS

Of 398 patients, pDDIs were observed in 37.2% patients, while major-pDDIs in 19.3% patients. A total of 325 interactions were found, of which 45.5% were of major- and 34.5% moderate-severity. Patients with the most common pDDIs were found with signs/symptoms and abnormalities in laboratory findings representing nephrotoxicity, hepatotoxicity, QT interval prolongation, and reduced therapeutic efficacy. The following drug pairs reported the highest frequency of adverse events associated with the interactions; calcium containing products-ceftriaxone, isoniazid-rifampin, pyrazinamide-rifampin, isoniazid-acetaminophen, and ciprofloxacin-metronidazole. The adverse events were more common in patients prescribed with the higher doses of interacting drugs. Multivariate regression analysis showed statistically significant association of pDDIs with 5-6 prescribed medicines (p = 0.01), > 6 prescribed medicines (p < 0.001), > 5 days of hospital stay (p = 0.03), and diabetes mellitus (p = 0.04).

CONCLUSIONS

PDDIs are commonly observed in patients with malaria. Healthcare professional's knowledge about the most common pDDIs could help in preventing pDDIs and their associated negative effects. Pertinent clinical parameters, such as laboratory findings and signs/symptoms need to be checked, particularly in patients with polypharmacy, longer hospital stay, and diabetes mellitus.

Drug scheduling by nurses and drug interactions in patients with cardiovascular diseases

OBJECTIVES

to identify and characterize the potential serious drug interactions in patients hospitalized with cardiovascular diseases, relating them to the schedules established for drug administration by nurses.

METHODS

a documentary, quantitative and sectional research. Ninety-nine prescriptions from patients admitted to the cardiology ward of a hospital in Rio de Janeiro for more than 48 hours were analyzed. Drug interaction was assessed using the Micromedex® software. The data were analyzed using descriptive and inferential statistics.

RESULTS

serious interactions were evidenced in 22 drug pairs, most frequently at 6 p.m. and 6 a.m., times with higher dose scheduling performed by nurses. The most recurrent drug pairs involved in serious interactions were simvastatin + amlodipine and enoxaparin + clopidogrel.

CONCLUSIONS

drug scheduling by nurses requires a review of the criteria for proposing schedules for drugs in order to ensure patient safety.

Validation of an HPLC Method for the Simultaneous Quantification of Metabolic Reaction Products Catalysed by CYP2E1 Enzyme Activity: Inhibitory Effect of Cytochrome P450 Enzyme CYP2E1 by Salicylic Acid in Rat Liver Microsomes

Inhibition of cytochrome P450 (CYP) alters the pharmacokinetic parameters of the drug and causes drug–drug interactions. Salicylic acid been used for the treatment of colorectal cancer (CRC) and chemoprevention in recent decades. Thus, the aim of this study was to examine the in vitro inhibitory effect of salicylic acid on CYP2E1 activity in rat liver microsomes (RLMs) using high-performance liquid chromatography (HPLC). High-performance liquid chromatography analysis of a CYP2E1 assay was developed on a reversed phase C₁₈ column (SUPELCO 25 cm × 4.6 mm × 5 µm) at 282 nm using 60% H₂O, 25% acetonitrile, and 15% methanol as mobile phase. The CYP2E1 assay showed a good linearity (R² > 0.999), good reproducibility, intra- and inter-day precision (<15%), acceptable recovery and accuracy (80–120%), and low detection (4.972 µM and 1.997 µM) and quantitation limit values (15.068 µM and 6.052 µM), for chlorzoxazone and 6-hydroxychlorzoxazone, respectively. Salicylic acid acts as a mixed inhibitor (competitive and non-competitive inhibition), with K_i (inhibition constant) = 83.56 ± 2.730 µM and concentration of inhibitor causing 50% inhibition of original enzyme activity (IC₅₀) exceeding 100 µM (IC₅₀ = 167.12 ± 5.460 µM) for CYP2E1 enzyme activity. Salicylic acid in rats would have both low and high potential to cause toxicity and drug interactions with other drugs that are substrates for CYP2E1.

Survey on Polypharmacy and Drug-Drug Interactions Among Elderly People with Cardiovascular Diseases at Yekatit 12 Hospital, Addis Ababa, Ethiopia

Background

Elderly people are most commonly associated with cardiac disease. Cardiovascular diseases are interlinked with co-morbidities which require multiple drug therapy in addition to cardiovascular drugs. This results to polypharmacy which carries a high risk of potential drug-drug interactions. Elderly patients are at a particular risk of drug related problems because of increased level of polypharmacy and the physiological changes which accompany aging. This study was aimed to assess polypharmacy and potential drug-drug interactions (DDIs) among elderly people with cardiovascular diseases at Yekatit 12 hospital.

Methodology

A retrospective cross-sectional study using patients chart review was conducted on all elderly people with cardiovascular diseases at Yekatit 12 hospital in the period between March 2018 and March 2019. The types, seriousness and level of potential DDIs were checked using Medscape online drug interaction checker.

Results

The mean number of drugs per prescription was 4.25 ± 1.754 and the prevalence of polypharmacy (concurrent use of 5 and more drugs) was 42.7%. Polypharmacy and potential DDIs were significantly associated with polymorbidity (P = 0.000), being hospitalized (P = 0.047) and congestive heart failure (P = 0.016). A total of 850-potential DDIs were identified, the mean number of potential DDIs was 3.37 per prescription. The potential DDIs were mainly significant (73.29%) in nature and pharmacodynamics (73.06%) in mechanism. The prevalence of total and serious potential DDIs were 84.3% and 17.3%, respectively. Most commonly interacting drug combination was aspirin + enalapril (30.2%).

Conclusion

A higher incidence of polypharmacy and increased risk of potential DDIs in elderly people with cardiovascular disease are major therapeutic issues at Yekatit 12 hospital.

Potential drug-drug interactions in the psychiatric hospital: Frequency analysis

Introduction: Drug-drug interactions are an important clinical problem in pharmacotherapy. This study is focused on different types of drugs used in a psychiatric hospital.

Materials and methods: The pharmacoepidemiological study included the analysis of medical records of 500 psychiatric inpatients. The patients were divided into 2 groups: under 65 and over 65 years of age. All the drug prescriptions were analyzed to identify the combinations of drugs that can induce drug-drug interactions and determine their clinical significance.

Results and discussion: Over 77% of hospitalized patients were administered drug combinations that could induce drug-drug interactions, most of which were of moderate clinical significance. A reliable association was found between the patient’s age, the clinical significance of drug-drug interactions, and the pharmacotherapy structure. The most common irrational drug combinations were identified.

Conclusion: Timely analysis of drug prescriptions for potential drug-drug interactions can enhance the safety of pharmacotherapy and decrease the risk of adverse drug reactions in the psychiatric inpatient setting.

Potential Drug-drug Interactions in Acute Ischemic Stroke Patients at the Neurological Intensive Care Unit

Background

Clinically relevant potential drug-drug interactions are considered preventable adverse drug reactions.

Objective

The aim of this study was to ascertain the frequency of potential drug-drug interactions in acute ischemic stroke patients and to explore factors associated with occurrence of potentially contraindicated drug-drug interactions.

Methods

This observational retrospective cohort and nested case-control study was carried out among patients treated for acute ischemic stroke at the Neurological Intensive Care Unit in the Clinical Centre Kragujevac, Serbia. The potentially drug-drug interactions for each day of hospitalization were identifi ed using Micromedex® soft ware. Based on the existence or absence of potentially contraindicated drug-drug interactions, the participants were divided into a group of cases (n=111) and the control group (n=444).

Results

A total of 696 patients were analysed. All patients had a minimum of one potential drug-drug interaction during hospitalization. The most common drugs involved in potential drug-drug interactions were aspirin (8.02%), diclofenac (7.49%) and warfarin (7.14%). The number of medications prescribed for simultaneous use during hospitalisation and the use of antipsychotics in therapy signifi cantly increased the likelihood of potentially contraindicated drug-drug interactions aft er adjustment by means of logistic regression for 1.2 and 3 times, respectively.

Conclusions

This study suggests that patients with acute ischemic stroke are frequently exposed to potential drug-drug interactions. It is essential to identify potentially drug-drug interactions in these patients as early as possible in order to prevent adverse drug reactions and ensure safe recovery. Besides, full attention should be paid when adding each new medication in therapy, particularly when a neurologist decides to prescribe antipsychotics, such as risperidone.

Identification and ranking of important bio-elements in drug-drug interaction by Market Basket Analysis

Introduction: Drug-drug interactions (DDIs) are the main causes of the adverse drug reactions and the nature of the functional and molecular complexity of drugs behavior in the human body make DDIs hard to prevent and threat. With the aid of new technologies derived from mathematical and computational science, the DDI problems can be addressed with a minimum cost and effort. The Market Basket Analysis (MBA) is known as a powerful method for the identification of co-occurrence of matters for the discovery of patterns and the frequency of the elements involved. Methods: In this research, we used the MBA method to identify important bio-elements in the occurrence of DDIs. For this, we collected all known DDIs from DrugBank. Then, the obtained data were analyzed by MBA method. All drug-enzyme, drug-carrier, drug-transporter and drug-target associations were investigated. The extracted rules were evaluated in terms of the confidence and support to determine the importance of the extracted bio-elements. Results: The analyses of over 45000 known DDIs revealed over 300 important rules from 22 085 drug interactions that can be used in the identification of DDIs. Further, the cytochrome P450 (CYP) enzyme family was the most frequent shared bio-element. The extracted rules from MBA were applied over 2000000 unknown drug pairs (obtained from FDA approved drugs list), which resulted in the identification of over 200000 potential DDIs. Conclusion: The discovery of the underlying mechanisms behind the DDI phenomena can help predict and prevent the inadvertent occurrence of DDIs. Ranking of the extracted rules based on their association can be a supportive tool to predict the outcome of unknown DDIs.

Adverse drug reactions caused by drug-drug interactions in cardiovascular disease patients: introduction of a simple prediction tool using electronic screening database items

Objective: Cardiovascular disease (CVD) drugs have been frequently implicated in adverse drug reaction (ADR)-related hospitalizations. Drug-drug interactions (DDIs) are common preventable cause of ADRs, but the impact of DDIs in the CVD population has not been investigated. Hence, the primary aim of the study was to identify DDIs associated with ADRs in CVD patients at hospital admission. The second aim was to develop a simple tool to identify high-risk patients for DDI-related adverse events. Methods: An observational study was conducted on the Cardiology Ward of University Clinical Hospital Center. Data were obtained from medical charts. A clinical panel identified DDIs implicated in ADRs, using LexiInteract database and Drug Interaction Probability Scale. Statistics were performed using PASW 22 (SPSS Inc.). Results: DDIs contributed to hospital admission with a total prevalence of 9.69%. DDI-related ADRs affected mainly cardiac function (heart rate or rhythm, 41.07%); bleeding and effect on blood pressure were equally distributed (17.86%). Non-cardiovascular ADRs were found in 23.21% of DDIs. After admission, 73% of the identified DDIs led to changes in prescription. Prediction ability of calculated DDI adverse event probability scores was rated as good (AUC = 0.80, p < .001). Conclusions: CVD patients are highly exposed to adverse DDIs; about one in ten patients hospitalized with CVD might have a DDI contributing to the hospitalization. Given the high prevalence of CVD, DDI-related harm might be a significant burden worldwide. Identification of patients with high DDI adverse event risk might ease the recognition of DDI-related harm and improve the use of electronic databases in clinical practice.

Impact of Clinical Pharmacist's Interventions on Potential Drug-Drug Interactions in the Cardiac Care Units of Two University Hospitals in Shiraz, South of Iran

Objective:

The main objective of this study aimed to assess drug–drug interactions (DDIs) in the cardiac care unit (CCU) and cardiac surgery units and the role of a clinical pharmacist in detecting and preventing the expected DDIs.

Methods:

This cross-sectional study was conducted in the CCU Units of Nemazee and Shahid Faghihi Hospitals, two referral hospitals in Shiraz, South of Iran, from August to February 2016. Patients older than 18 years, who were admitted and had received >24 h of inpatient services in these wards with two or more medication orders, were included in this study. All medication orders were evaluated by a pharmacist and DDIs were examined based on the Lexi-Interact™ software. In cases with serious DDIs (D or X), the physicians and nurses were informed, and intervention was conducted by a clinical pharmacist.

Findings:

A total of 3706 medical orders were evaluated. 6478 DDIs were detected, of which, 446 (6.88%) belonged to Classes D and X, and a total of 43.43% of all hospitalizations had at least one DDI. Factors with the most considerable influence on DDIs included an increased number of prescribed medications and patients underlying disease. The physicians accepted 62% of the interventions. The most frequent drugs responsible for interactions of Classes C, D, and X were aspirin, warfarin, and clopidogrel, respectively.

Conclusion:

This study shows that a significant number of clinical DDIs exist in hospitalized patients, especially among consumers of warfarin and aspirin. The role of a clinical pharmacist in preventing such interactions and safer pharmacotherapy management for hospitalized patients is essential.

The role of the clinical pharmacist in the prevention of potential drug interactions in geriatric heart failure patients

Background The treatment of heart failure patients is very complex and includes lifestyle modification as well as different pharmacological therapies. Polypharmacy is very common in such patients and they are at increased risk of potential drug-drug interactions and associated effects such as poor adherence, compliance and adverse events. Objective The aim of the present study is to investigate retrospectively the prescribed pharmacotherapy of the hospital discharged heart failure patients for possible drug interactions. Settings Clinic for Cardiology of the "Saint Marina" University Hospital in Varna, Bulgaria. Method Lexicomp^® Drug interaction software was used for screening potential drug-drug interactions. Logistic regression was applied to determine the odds ratio for the association between the age and number of drugs taken and the number of potential drug-drug interactions. Main outcome measure Incidence and type of pDDIs in geriatric heart failure patients. Results A retrospective study was conducted by reviewing the medical records of 248 selected heart failure patients for the prescribed medicines for a 1-year period (January 2015-December 2015). The total number of potential drug-drug interactions was 1532, or approximately 6.28 (± 4.72 SD) per one person. The range of prescribed drugs was between three and fourteen, 92% of them have been taking more than five medicines, an average of 7.12 (± 2.07 SD) per patient. The average age was 72.35 (± 10.16 SD). The results have shown stronger association between the number of drugs taken (more than 7) and the occurrence of potential drug-drug interactions (more than 10)-37.84 (95% CI 9.012-158.896, P ≤ 0.001). No statistically significant differences were found between age and occurrence of potential drug-drug interactions (more than 10)-1.008 (95% CI 0.441-2.308, P = 0.848). Conclusion The incidence of drug-drug interactions in heart failure patients is high. The clinical pharmacist, as a part of the multidisciplinary team, could reduce medication-related problems, such as drug interactions, and to optimize drug therapy by checking the treatment prescribed at the discharge of these patients.

Potential Drug-Drug Interactions in Patients With Urinary Tract Infections: A Contributing Factor in Patient and Medication Safety

Introduction: Hospitalized patients with urinary tract infections (UTIs) often present with comorbid illnesses and are subsequently prescribed multiple medications, which increases the likelihood of drug-drug interactions. Therefore, this study aimed to explore the prevalence, levels, risk factors, and clinical relevance of potential drug-drug interactions (pDDIs) in hospitalized patients with UTIs. Secondly, we aimed to develop management guidelines and identify monitoring parameters for the most frequent interactions.

Methods: A retrospective cross-sectional study was conducted in internal medicine wards of two tertiary care hospitals in Peshawar, Khyber Pakhtunkhwa, Pakistan. The clinical profiles of 422 patients with UTIs were reviewed for pDDIs using the Micromedex Drug-Reax^®. Logistic regression was applied to assess the association of pDDIs with various risk factors. The clinical relevance of frequent pDDIs was identified by assessing the potential adverse outcomes of pDDIs including patients’ signs, symptoms, and abnormal laboratory findings.

Results: Of 422 patients, at least one pDDI was identified in 62.3% patients, while 40% patients had at least one major pDDI. A total of 1,086 pDDIs were identified, of which 53.4% and 39.3% were of moderate and major severity, respectively. Patients with most frequent pDDIs were presented with hypoglycemia, hepatotoxicity, nephrotoxicity, hypertension, and decreased therapeutic response. These adverse events were more prevalent in patients taking higher doses of interacting drugs. Multivariate regression analysis revealed significant association of pDDIs with six or more medicines (p < 0.001), diabetes mellitus (p < 0.001), ischemic heart disease (p = 0.02), and congestive cardiac failure (p = 0.04).

Conclusions: Patients with UTIs present with a considerable number of clinically important pDDIs. Polypharmacy, diabetes mellitus, ischemic heart disease, and congestive cardiac failure increase the risk of pDDIs. Knowledge about the most frequent pDDIs will enable healthcare professionals to implement optimized monitoring and management strategies regarding associated adverse consequences in order to ensure patient safety. Most of the interactions can be managed by considering alternative therapy and dose reduction.

Drug-related problems in prescribing for coronary artery diseases in Vietnam: cross-sectional study

OBJECTIVES

To determine the prevalence, patterns and determinants of drug-related problems (DRPs) in prescribing for coronary artery diseases (CADs) in Vietnam.

METHODS

Retrospective cross-sectional study on outpatients with CADs at a general hospital in Can Tho, Vietnam. DRPs were classified according to Pharmaceutical Care Network Europe definitions. We determined the prevalence and patterns of DRPs. Logistic regression was used to identify the determinants of DRPs.

RESULTS

Among 683 patients (mean age 63.4; 64.3% female), the prevalence of DRPs was 61.1%. DRPs comprised inappropriate indication (3.5%), inappropriate dosage (22.2%), wrong frequency of use (24.2%), wrong time of taking medications (4.1%), taking medications at the wrong time around meals (19.2%) and drug interactions (19.3%). Patients who took ≥ 5 drugs were more likely to have DRPs (adjusted odds ratio = 1.96; 95% confidence interval = 1.31-2.93). Patients without health insurance were more likely to have inappropriate indication (ORa = 2.93; 95%CI = 1.28-6.70). Taking medications at inappropriate times around meals was common among men (ORa = 1.82; 95%CI = 1.23-2.69) and among those with health insurance (ORa = 1.66; 95%CI = 1.05-2.63). Patients < 65 years old were more likely to be prescribed inappropriate doses (ORa = 1.67; 95%CI = 1.15-2.45). Prescriptions with ≥ 5 drugs were more likely to be taken at inappropriate frequency (ORa = 1.87; 95%CI = 1.09-3.21) and to cause drug interactions (ORa = 6.48; 95%CI = 2.59-16.24).

CONCLUSIONS

DRPs are common among patients with CADs in Vietnam. The number of DRPs increases with the number of drugs in prescriptions. Further studies should identify other potential determinants of DRPs and effective interventions to improve prescribing practice in Vietnam.

Potential drug-drug interactions among pneumonia patients: do these matter in clinical perspectives?

BACKGROUND

Pneumonia patients are usually hospitalized due to severe nature of the disease or for the management of comorbid illnesses or associated symptoms. Such patients are prescribed with multiple medications which increase the likelihood of potential drug-drug interactions (pDDIs). Therefore, in this study the prevalence, levels (severity and documentation), predictors (risk factors), and clinical relevance of pDDIs among inpatients diagnosed with pneumonia have been investigated.

METHODS

Clinical records of 431 hospitalized patients with pneumonia were checked for pDDIs using drug interactions screening software (Micromedex-DrugReax). Odds-ratios for predictors were calculated using logistic regression analysis. Clinical relevance of pDDIs was assessed by evaluation of patients' clinical profiles for potential adverse outcomes of the most frequent pDDIs. Abnormal patients' signs/symptoms and laboratory investigations indicating adverse outcomes of interactions were reported.

RESULTS

Of total 431 profiles, pDDIs were reported in 73.1%. Almost half of the profiles were having major-pDDIs (53.8%). Total number of pDDIs were 1318, of which 606 were moderate- and 572 were major-pDDIs. Patient's profiles identified with the most frequent interactions were presented with signs, symptoms, and abnormalities in labs indicating decrease therapeutic response, electrolyte abnormalities, hypoglycemia, bleeding, hepatotoxicity, and hypertension. These adverse events were more prevalent in patients taking higher doses of the interacting drugs as compared to lower doses. Logistic regression analysis revealed significant association for major-pDDIs with 6-10 prescribed medicines (OR = 26.1; p = 0.002), > 10 prescribed medicines (OR = 144; p <  0.001), and tuberculosis (OR = 8.2; p = 0.004).

CONCLUSIONS

PDDIs are highly prevalent in patients with pneumonia. Most frequent and clinically important pDDIs need particular attention. Polypharmacy and tuberculosis increase the risk of pDDIs. Identifying patients more at risk to pDDIs and careful monitoring of pertinent signs/symptoms and laboratory investigations are important measures to reduce pDDIs and their related adverse consequences.

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

Background

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

Methods

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

Results

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

Conclusion

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

Potential drug-drug interactions and associated factors among hospitalized cardiac patients at Jimma University Medical Center, Southwest Ethiopia

Background

Concomitant use of several drugs for a patient is often imposing increased risk of drug-drug interactions. Drug-drug interactions are a major cause for concern in patients with cardiovascular disorders due to multiple co-existing conditions and the wide class of drugs they receive. This study is aimed to assess the prevalence of potential drug-drug interactions and associated factors among hospitalized cardiac patients at medical wards of Jimma University Medical Center, Southwest Ethiopia.

Methods

A hospital-based prospective observational study was conducted among hospitalized cardiac adult patients based on the inclusion criteria. Patient-specific data were collected using structured data collection tool. Potential drug-drug interaction was analyzed using Micromedex 3.0 DRUG-REAX^® System. Data were analyzed using statistical software package, version 20.0. To identify the independent predictors of potential drug-drug interaction, multiple stepwise backward logistic regression analysis was done. Statistical significance was considered at a p-value < 0.05. Written informed consent from patients was obtained and the patients were informed about confidentiality of the information obtained.

Results

Of the total 200 patients, majority were male (52.50%) and with a mean(±standard deviation) age of 42.54(±7.89) years. Out of 673 patients' prescriptions analyzed, 521 prescriptions comprised potential drug interactions and it was found that 967 drug interactions were present. The prevalence rate of potential drug-drug interactions among the study unit was 4.83 per patient and 1.44 per prescription regardless of the severity during their hospital stay. Overall the prevalence rate of potential drug interactions was 74.41%. Older age (adjusted odds ratio (95% confidence interval): 1.067 (2.33-27.12), p = 0.049), long hospital stay (⩾7 days) (adjusted odds ratio (95% confidence interval): 2.80 (1.71-4.61), p = 0.024), and polypharmacy (adjusted odds ratio (95% confidence interval): 1.64 (0.66-4.11), p = 0.041) were independent predictors for the occurrence of potential drug-drug interactions.

Conclusion

This study demonstrated a high prevalence of potential DIs among hospitalized cardiac patients in medical wards due to the complexity of pharmacotherapy. The prevalence rate is directly related to age, number of prescribed drugs, and length of hospital stay. Pharmacodynamic drug-drug interaction was the common mechanism of drug-drug interactions. Therefore, close monitoring of hospitalized patients is highly recommended.

Drug-drug interactions in patients with acute coronary syndrome across phases of treatment

The objective of this study is to evaluate potential drug-drug interactions (pDDIs) and risk factors for pDDIs in three phases of an acute coronary syndrome (ACS) treatment: from the point of first medical contact to the coronary angiography (first phase), after coronary angiography to the last day of hospitalization (second phase), and at discharge from hospital (third phase). This retrospective observational cohort clinical study was conducted at the Clinic for Cardiology of the Clinical Centre Kragujevac, a public tertiary care hospital in Kragujevac, Serbia. Micromedex^® interaction checker was used to detect pDDIs. This study included 245 ACS patients. All patients were exposed to at least one pDDI in all the phases of treatment. Mean total number of pDDIs was 9.47 ± 6.07, 10.11 ± 6.92, and 6.29 ± 3.66 in first, second, and third phases, respectively. Age, > 6 h from the beginning of the symptoms to admission, primary PCI, STE-ACS, COPD, delirium, hyperlipidemia, hypertension, obesity, systolic blood pressure at admission, TIMI risk score at admission, ALT, LDL, number of physicians who prescribed drugs to a single patient, number of prescribed drugs, and various pharmacological classes increased risk of pDDIs. Mechanical ventilation, dementia, and drug allergy noted in the medical documentation protected against them. Effects of heart failure, diabetes, and aPTT depended on phase of treatment and severity of pDDI. In conclusion, physicians should be vigilant to the possibility of pDDIs in patients harbouring factors that may increase their rate.

Assessment of Potential Drug-Drug Interactions in Hospitalized Cardiac Patients of a Secondary Care Hospital in the United Arab Emirates

OBJECTIVE

To identify the types, severity, and documentation grades of potential drug-drug interactions (pDDIs) and to identify the predictors of pDDIs among hospitalized cardiac patients.

METHODS

This was a cross-sectional study. All the patients who were admitted for >24 h in a cardiology ward of a general hospital of the United Arab Emirates and prescribed with cardiac medications were included. The occurrence of any pDDI between cardiac medications and other coprescribed medications was identified using Micromedex database 2.0^® and graded and documented based on the severity and documentation.

FINDINGS

A total of 842 pDDIs were identified in 155 patients. The overall relevant frequency for the occurrence of pDDIs was found to be 87.74%. A total of 79 pairs of pDDIs were identified. Among identified pDDIs, 41.33% and 56.65% were major and moderate severity type, respectively, whereas 12.32% were excellent and 36.81% were good documentation grade. The majority of pDDIs were between aspirin-bisoprolol (11.64%). Patients taking more than seven drugs (odds ratio [OR] = 9.90; 95% confidence interval [CI]: 2.28-42.99), polypharmacy (OR = 3.86; 95% CI: 0.93-16.08), and number of medical conditions (OR 0.25; 95% CI: 0.09-0.68) were significant predictors of pDDIs.

CONCLUSION

The study fosters the importance of regular and close monitoring for pDDIs among cardiac patients. Thus, multicenter interventional studies are required to determine the exact nature and types of pDDIs in the local population.

Risk of potential drug-drug interactions in the cardiac intensive care units. A comparative analysis between 2 tertiary care hospitals

OBJECTIVES

To identify and compare the prevalence of drug-drug interactions (DDIs) in the intensive cardiac care units (CCUs) of 2 tertiary care hospitals and analyze their association with various predictors. Methods: This one-year prospective cross-sectional study was conducted in 2 tertiary care hospitals of Peshawar, Khyber Teaching Hospital (KTH) and Hayatabad Medical Complex (HMC), Peshawar, Pakistan, between January 2014 to Janury 2015. The patient medication profiles from the respective CCUs were evaluated for potential DDIs (PDDIs) using Micromedex DrugReax and Drug interaction facts. Results: The prevalence of PDDIs was 96.5% and  95.7% in the 2 hospitals, with over 1200 PDDIs in total. A significant association was found between the number of prescribed drugs and PDDIs in both  hospitals.  Conclusion: The knowledge of PDDIs is either lacking among the clinicians or is not taken into consideration. Monitoring PDDIs and timely interventions are required to minimize the adverse outcomes.

Challenges in designing and executing clinical trials in a dish studies

The ever-increasing cost of drug discovery and development represents a significant challenge for the pharmaceutical industry and new strategies to bridge studies between preclinical testing and clinical trials are needed to reduce the knowledge gap prior to first human exposures, and to allow earlier decisions to be made on the further development of drugs. A number of studies have demonstrated that various cell types differentiated from human induced pluripotent stem cells (iPSCs) do not just respond similarly to human tissues in general, but rather recapitulate the drug response of their specific donor's, when exposed to the same drug in vivo. This recapitulation opens the doors to Clinical Trials in a Dish (CTiD), a platform which involves testing, in vitro, medical therapies for safety on cells collected from a sample of human patients, before moving into clinical trials. However, the science behind CTiD is complex, and every element of the process from tissue acquisition to data generation must be assessed and designed to meet quality metrics and standards. Without such rigorous assessment and design, the basic scientific integrity of CTiD constructs is likely compromised, and the results questionable. Given the lack of standard process and/or quality metrics in place for the use of stem cell-based products for in vitro testing per se, we discuss here the key elements that one needs to consider when designing, implementing and executing CTiD studies, in order to ensure an approach that will reliably mimic clinical trials, and allow obtaining reproducible and reliable experimental data.

In Vivo Assessment of the Effect of CYP1A2 Inhibition and Induction on Pomalidomide Pharmacokinetics in Healthy Subjects

Pomalidomide is an immunomodulatory drug, and the dosage of 4 mg per day taken orally on days 1‐21 of repeated 28‐day cycles has been approved in the European Union and the United States to treat patients with relapsed/refractory multiple myeloma. In vitro data showed that pomalidomide is a substrate of multiple cytochrome P450 (CYP) isozymes and that its oxidative metabolism is mediated primarily by CYP1A2 and CYP3A4, with minor contributions from CYP2C19 and CYP2D6. The effect of CYP1A2 inhibition by fluvoxamine (a strong CYP1A2 inhibitor) and CYP1A2 induction by smoking on pomalidomide pharmacokinetics in healthy subjects has been assessed in 2 separate phase 1 open‐label, single‐dose studies. Following administration of a single oral dose of 4 mg pomalidomide, the plasma exposure when coadministered with fluvoxamine was 225.1% and 123.7% of that when administered alone for the total plasma exposure (AUC_0‐inf) and the plasma peak exposure (C_max), respectively. In smokers with elevated CYP1A2 activity demonstrated by high caffeine clearance (a marker of CYP1A2 induction), the AUC_0‐inf was 32.3% lower, whereas the C_max was 14.4% higher than that in nonsmokers. In addition, pomalidomide was safe and well tolerated as a single oral dose of 4 mg in healthy male smokers and nonsmokers ≥ 40 to ≤ 80 years old, and a single oral dose of 4 mg pomalidomide coadministered with multiple oral 50‐mg doses of the CYP1A2 inhibitor fluvoxamine compared with pomalidomide alone was safe and well tolerated by the healthy male subjects.

A multicentered pharmacoepidemiological approach to evaluate clinically significant potential drug–drug interactions in medical intensive care settings in Pakistan

Background:

Iatrogenic injuries due to drug–drug interactions are particularly significant in critical care units because of the severely compromised state of the patient. The risk further increases with the use of multiple drugs, increasing age, and stay of the patient.

Objective:

The aim was to assess potential drug–drug interactions, evaluate clinically significant potential drug–drug interactions and their predictors in medical intensive care units of tertiary hospitals in Pakistan.

Methods:

Analysis of patient data collected from medical intensive care units of tertiary hospitals in Pakistan were carried out using Micromedex DrugReax. Various statistical tools were applied to identify the significance of associated predictors.

Results:

In a total of 830 patients, prevalence of potential drug–drug interactions was found to be 39%. These attributed to 190 drug combinations, of which 15.4% were clinically significant. A significant association of potential drug–drug interactions was present with number of prescribed drugs, age, and gender. In terms of clinically significant potential drug–drug interactions, the association was significant with increasing age. Moreover, one-way analysis of variance revealed a significant difference in the means of potential drug–drug interactions among the four hospitals.

Conclusion:

A prevalence of 39% potential drug–drug interactions was observed in patients of medical intensive care unit, with 22.8% being clinically significant. These attributed to nine drug pairs and could easily be avoided to reduce the risk of adverse effects from potential drug–drug interactions.

Risk factors for potential drug-drug interactions in intensive care unit patients

PURPOSE

To determine risk factors for each severity-based category of potential drug-drug interactions (DDIs) encountered at intensive care unit (ICU) patients.

METHODS

This was a retrospective cohort analysis of patients treated at the ICU of the Clinical Center Kragujevac, a public tertiary care hospital in Kragujevac, Serbia. Three interaction checkers were used to reveal drug-drug interactions: Medscape, Epocrates and Micromedex.

RESULTS

The study included 201 patients, 66.19±16.11 years of age. Average number of DDIs per patient ranged from 10.49±8.80 (Micromedex) to 29.43±21.51 (Medscape). Antiarrhythmic or anticonvulsant drug prescription, Charlson Comorbidity Index, male sex, length of hospitalization, number of drugs or therapeutic groups prescribed and surgery increased the risk of DDIs in ICU patients, while presence of delirium or dementia and transfer from emergency department to ICU protected against.

CONCLUSIONS

The rate of the DDIs in ICU patients at a tertiary care hospital is high, and adversely influenced by number of drugs or drug groups prescribed per patient, antiarrhythmic or anticonvulsant drug prescription, comorbidities, length of hospitalization and surgery. On the other hand, presence of cognitive deficit and transfer from emergency department to ICU protect ICU patients from the DDIs.