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

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.

Effect of educational intervention on medication reconciliation practice of hospital pharmacists in a developing country - A non-randomised controlled trial

BACKGROUND

Medication reconciliation is an evidence-based practice that reduces medication-related harm to patients. This study evaluated the effect of educational intervention on medication reconciliation practice of pharmacists among ambulatory diabetes and hypertensive patients.

METHODS

A non-randomized clinical trial on medication reconciliation practice was carried out among 85 and 61 pharmacists at the intervention site and control site, respectively. Medication reconciliation was carried out among 334 (intervention-183; control-151) diabetes and/or hypertensive patients by the principal investigator to indirectly evaluate pharmacists' baseline medication reconciliation practice at both sites. A general educational intervention was carried out among intervention pharmacists. Medication reconciliation was carried out by the principal investigator among another cohort of 96 (intervention-46; control-50) and 90 (intervention-44; control-46) patients at three and six months postintervention, respectively, to indirectly assess pharmacists' postintervention medication reconciliation practice. Thereafter, a focused educational intervention was carried out among 15 of the intervention pharmacists. Three experts in clinical pharmacy analysed the medication reconciliation form filled by the 15 pharmacists after carrying out medication reconciliation on another cohort of 140 patients, after the focused intervention. Data was summarized with descriptive (frequency, percentage, mean ± standard deviation) and inferential (Pearson product-moment correlations analysis, independent-samples t-test and one-way ANOVA) statistics with level of significance set at p<0.05.

KEY FINDINGS

Baseline medication reconciliation practice was poor at both sites. Post-general educational intervention, medication discrepancy was significantly reduced by 42.8% at the intervention site (p<0.001). At the intervention site, a significant increase of 54.3% was observed in patients bringing their medication packs for clinic appointments making medication reconciliation easier (p=0.003), at 6-months postintervention. Thirty-five, 66 and 48 drug therapy problems were detected by 31 (43.1%), 33 (66.0%) and 32 (71.1%) intervention pharmacists at 1-, 3- and 6-month post-general educational intervention, respectively. Post-focused educational intervention, out of a total of 695 medications prescribed, 75 (10.8%) medication discrepancies were detected and resolved among 42 (30%) patients by the 15 pharmacists.

CONCLUSIONS

The educational interventions improved pharmacists' medication reconciliation practice at the intervention site. It is expected that this research would help create awareness on medication reconciliation among pharmacists in developing countries, with a view to reducing medication-related patient harm.

Frequency, Predictors, and Outcomes of the Potential Drug-Drug Interactions in the ICUs of Teaching Hospitals in Ardabil, Northwest of Iran During 2019-2020

Introduction: Drug-drug interactions (DDIs) can reduce therapeutic efficacy and increase the duration and cost of hospitalization so that patients are sometimes exposed to significant complications and even death. Patients in the intensive care unit (ICU) are at higher risk of DDIs for a variety of reasons, including impaired absorption, decreased metabolism, and renal failure. The main objective of this study was to evaluate frequency, clinical ranking and risk factors of potential DDIs in the ICUs of 3 teaching hospitals in Ardabil. Methods: In this descriptive-analytical cross-sectional study, drug prescriptions 355 patients admitted to the ICUs were studied. Patient information including age, sex, diagnosis, number of prescribers, number of drugs, length of stay, and status of patients' discharge (recovery or death) were recorded and checked using the online software up to date and the book Drug Interaction Facts. Finally, the data were statistically analyzed using the SPSS software. Results: The number of patients studied was 355. The mean age of the patients were 51.88 ± 23.22 years, and on average, 8.45 drugs had been prescribed for each patient. The total number of DDIs was 1597 among which class X was 1.4%, class D was 26.2%, and class C was 67.7%. Four hundred ninety-seven unique pairs of DDIs were identified. Age, number of prescribed drugs and length of stay in ICU were associated with prevalence of DDIs. Age and number of drugs were also identified as the risk factors of patients' discharge caused by death. Conclusion: DDIs can complicate health state of patients in ICUs and may increase the length of hospital stay. Setting up computerized systems to alert drug interactions in hospital wards and pharmacotherapeutic intervention by clinical pharmacist can minimize DDIs.

Potential drug-drug interactions in outpatients with depression of a psychiatry department

Objective

This study aims to explore the prevalence and associated risk factors for potential drug-drug interactions (pDDIs) in prescriptions among outpatients with depression, and report the widespread relevant drug interactions.

Methods

The cross-sectional retrospective study was conducted on outpatients in a psychiatric hospital. We included prescriptions of outpatients with a principal diagnosis of depression from April 1st to June 30th in 2021. The patients were ≥ 18 years old and treated with two or more drugs including at least one psychotropic drug. pDDIs were detected and identified mainly using Medscape's drug interactions checker. Gender, the number of concomitant drugs, age and diagnosis were analysed as potential risk factors for the occurrence of pDDIs by logistic regression.

Results

A total of 13,617 prescriptions were included in the present analysis, and 4222 prescriptions (31.0%) were at risk of 8557 pDDIs. The risk of pDDIs in patients who were prescribed 4-6 drugs (OR: 3.49, 95% CI: 3.11-3.91, p < 0.001) or 7 or more drugs simultaneously (OR: 7.86, 95% CI: 1.58-39.04, p < 0.05) increased compared with patients prescribed 2-3 drugs. Patients with recurrent depressive disorders (OR: 1.18, 95% CI: 1.02-1.36, p < 0.05) had an increased risk of pDDIs compared with patients with depressive episodes. In terms of severity of pDDIs identified by Medscape's drug interactions checker, 0.7%, 16.4%, 77.5% and 5.4% of pDDIs were classified as contraindicated, serious, monitor closely and minor, respectively. The most common pDDI was escitalopram + quetiapine (374 prescriptions), which was classified as serious and monitor closely due to different mechanisms of interaction. Increased central nervous system (CNS)-depressant effect was the most frequent potential clinical adverse outcome of the identified pDDIs.

Conclusions

pDDIs in outpatients with depression were prevalent in this retrospective study. The number of concomitant drugs and severity of the disease were important risk factors for pDDIs. The pDDIs of the category monitor closely were the most common, and the CNS-depressant effect was the most frequent potential clinical adverse outcome.

Assessment of risk factors associated with potential drug-drug interactions among patients suffering from chronic disorders

Patients suffering from chronic diseases are more likely to experience pDDIs due to older age, prolonged treatment, severe illness and greater number of prescribed drugs. The objective of the current study was to assess the prevalence of pDDIs and risk factors associated with occurrence of pDDIs in chronic disease patients attending outpatient clinics for regular check-ups. Patients suffering from diabetes, chronic obstructive pulmonary disease (COPD), stroke and osteoporosis were included in the study. This study was a cross sectional, observational, prospective study that included 337 patients from outpatient clinics of respiratory ward, cardiac ward and orthopedic ward of Nishter Hospital Multan, Pakistan. The mean number of interactions per patient was 1.68. A greater risk for occurrence of pDDI was associated with older age ≥ 60 years (OR = 1.95, 95% CI = 1.44-2.37, p<0.001); polypharmacy (≥ 5 drugs) (OR = 3.74, 95% CI 2.32-4.54, p<0.001); overburden (OR = 2.23, 95% CI = 1.64-3.16, p<0.01); CCI score (OR = 1.28, 95% CI = 1.04-1.84, p<0.001); multiple prescribers to one patient (OR = 1.18, 95% CI = 1.06-1.41, p<0.01); and trainee practitioner (OR = 1.09, 95% CI = 1.01-1.28, p<0.01). Old age, polypharmacy, overburden healthcare system, higher comorbidity index, multiple prescribers to one patient and trainee practitioner were associated with increased risk of occurrence of pDDIs in chronic disease patients.

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.

Evaluation of medication risk at the transition of care: a cross-sectional study of patients from the ICU to the non-ICU setting

OBJECTIVES

To describe the incidence and types of medication errors occurring during the transfer of patients from the intensive care unit (ICU) to the non-ICU setting and explore the key factors affecting medication safety in transfer care.

DESIGN

Multicentre, retrospective, epidemiological study.

PARTICIPANTS

Patients transferred from the ICU to a non-ICU setting between 1 July 2019 and 30 June 2020.

MAIN OUTCOME MEASURES

Incidence and types of medication errors.

RESULTS

Of the 1546 patients transferred during the study period, 899 (58.15%) had at least one medication error. Most errors (83.00%) were National Coordinating Council (NCC) for Medication Error Reporting and Prevention (MERP) category C. A small number of errors (17.00%) were category D. Among patients with medication errors, there was an average of 1.68 (SD, 0.90; range, 1-5) errors per patient. The most common types of errors were route of administration 570 (37.85%), dosage 271 (17.99%) and frequency 139 (9.23%). Eighty-three per cent of medication errors reached patients but did not cause harm. Daytime ICU transfer (07:00-14:59) and an admission diagnosis of severe kidney disease were found to be factors associated with the occurrence of medication errors as compared with the reference category (OR, 1.40; 95% CI 1.01 to 1.95; OR, 6.78; 95% CI 1.46 to 31.60, respectively).Orders for bronchorespiratory (OR, 5.92; 95% CI 4.2 to 8.32), cardiovascular (OR, 1.91; 95% CI 1.34 to 2.73), hepatic (OR, 1.95; 95% CI 1.30 to 2.91), endocrine (OR, 1.99; 95% CI 1.37 to 2.91), haematologic (OR, 2.58; 95% CI 1.84 to 3.64), anti-inflammatory/pain (OR, 2.80; 95% CI 1.90 to 4.12) and vitamin (OR, 1.73; 95% CI 1.26 to 2.37) medications at transition of care were associated with an increased odds of medication error.

CONCLUSIONS

More than half of ICU patients experienced medication errors during the transition of care. The vast majority of medication errors reached the patient but did not cause harm.

Predictors of drug-drug interactions of medications prescribed to patients admitted due to suicidal behavior

INTRODUCTION

Drug-drug interactions among people with suicidal behavior is a challenging topic, considering the harm it poses for patients already vulnerable and the lack of literature on the thematic. This aspect must not be neglected in research and clinical practice, and thus requires thorough investigation.

OBJECTIVE

to investigate predictors of drug-drug interaction of prescribed drugs and the prescription of two or more drugs for people admitted due to suicidal behavior in a psychiatric emergency department (short-stay hospital ward).

METHOD

A cross-sectional study with retrospective approach, carried out in a Brazilian psychiatric emergency unit in 2015. Data about first and last medical prescriptions were collected from 127 patients' files. Descriptive statistics and the Zero Adjusted Logarithmic Distribution (ZALG) model were adopted, with the significance level α = 0.05.

RESULTS

Potential drug-drug interactions were found in most of the first and last prescriptions. The sample majority were female, with previous suicide attempts, being discharged from the hospital with three drugs (or more) prescribed, and without referral to any health service. Age and comorbidities were predictors of more drug prescriptions and the amount of prescribed drugs was the most important predictor of drug-drug interactions (quantity and severity).

CONCLUSIONS

the variables associated with drug-drug interactions and prescription of two or more drugs among people with suicidal behavior needs to be investigated in different contexts and addressed in interventions with the aim to promote patient safety.

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.

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.

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

Introduction

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

Methods

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

Results

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

Conclusion

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

False Laboratory Test Result Through Colistin Interference in an Intensive Care Patient: Case Report

BACKGROUND

In blood samples taken for testing purposes during drug infusion in the intensive care unit, there is a risk of interference due to drug-reactive interaction during the analysis.

CASE REPORT

A 19-year-old female patient had undergone surgery for intracranial astrocytoma, 12 years ago. Acinetobacter baumannii was found in the blood culture and deep tracheal aspiration fluid of the patient who had a fever (39.2 °C) with a body temperature during the follow-up. The patient was started on colistin 2 * 4.5 million IU. After the colistin infusion, biochemical tests were requested to control the patient's clinical situation. CK-MB mass and ProBNP values were measured in high concentrations. Cardiology consultation was requested to evaluate the increase in the CK-MB mass and ProBNP values. The patient's ECG and echocardiography showed no abnormality. The increase in cardiac markers was neither clinically acceptable nor insignificant. There was no hemolysis in the sample or analytical error in the device. Variability in the tests was thought to be due to the interference. As the bloodletting time was questioned, it was determined that it was taken during colistin treatment. In order to determine the effect of colistin-related interference on the other tests, the laboratory was contacted and additional tests (TSH, FT4, Anti- TPO, B-HCG, Estradiol, Prolactin, CA 125, CA 15-3, CA 19-9, Vitamin B12, C-Peptide, DDimer, PTH, 25 hydroxy vitamin D, PT, INR, APTT) were conducted. During colistin treatment, in many tests, bias was detected between -75 and + 268.80%.

CONCLUSION

Clinicians should consider suspicious test results that are incompatible with the diagnosis for the possibility of erroneous measurements due to colistin interference and review the sampling processes.

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.

Clinical significance of potential drug-drug interactions in a pediatric intensive care unit: A single-center retrospective study

Despite the high prevalence of potential drug-drug interactions in pediatric intensive care units, their clinical relevance and significance are unclear. We assessed the characteristics and risk factors of clinically relevant potential drug-drug interactions to facilitate their efficient monitoring in pediatric intensive care units. This retrospective cohort study reviewed the medical records of 159 patients aged <19 years who were hospitalized in the pediatric intensive care unit at Seoul National University Hospital (Seoul, Korea) for ≥3 days between August 2019 and February 2020. Potential drug-drug interactions were screened using the Micromedex Drug-Reax® system. Clinical relevance of each potential drug-drug interaction was reported with official terminology, magnitude of severity, and causality, and the association with the patient's clinical characteristics was assessed. In total, 115 patients (72.3%) were exposed to 592 potential interactions of 258 drug pairs. In 16 patients (10.1%), 22 clinically relevant potential drug-drug interactions were identified for 19 drug pairs. Approximately 70% of the clinically relevant potential drug-drug interactions had a severity grade of ≥3. Exposure to potential drug-drug interactions was significantly associated with an increase in the number of administrated medications (6-7 medications, p = 0.006; ≥8, p<0.001) and prolonged hospital stays (1-2 weeks, p = 0.035; ≥2, p = 0.049). Moreover, clinically relevant potential drug-drug interactions were significantly associated with ≥8 prescribed drugs (p = 0.019), hospitalization for ≥2 weeks (p = 0.048), and ≥4 complex chronic conditions (p = 0.015). Most potential drug-drug interactions do not cause clinically relevant adverse outcomes in pediatric intensive care units. However, because the reactions that patients experience from clinically relevant potential drug-drug interactions are often very severe, there is a medical need to implement an appropriate monitoring system for potential drug-drug interactions according to the pediatric intensive care unit characteristics.

Towards The Automated, Empirical Filtering of Drug-Drug Interaction Alerts in Clinical Decision Support Systems: Historical Cohort Study of Vitamin K Antagonists

Background

Drug-drug interactions (DDIs) involving vitamin K antagonists (VKAs) constitute an important cause of in-hospital morbidity and mortality. However, the list of potential DDIs is long; the implementation of all these interactions in a clinical decision support system (CDSS) results in over-alerting and alert fatigue, limiting the benefits provided by the CDSS.

Objective

To estimate the probability of occurrence of international normalized ratio (INR) changes for each DDI rule, via the reuse of electronic health records.

Methods

An 8-year, exhaustive, population-based, historical cohort study including a French community hospital, a group of Danish community hospitals, and a Bulgarian hospital. The study database included 156,893 stays. After filtering against two criteria (at least one VKA administration and at least one INR laboratory result), the final analysis covered 4047 stays. Exposure to any of the 145 drugs known to interact with VKA was tracked and analyzed if at least 3 patients were concerned. The main outcomes are VKA potentiation (defined as an INR≥5) and VKA inhibition (defined as an INR≤1.5). Groups were compared using the Fisher exact test and logistic regression, and the results were expressed as an odds ratio (95% confidence limits).

Results

The drugs known to interact with VKAs either did not have a statistically significant association regarding the outcome (47 drug administrations and 14 discontinuations) or were associated with significant reduction in risk of its occurrence (odds ratio<1 for 18 administrations and 21 discontinuations).

Conclusions

The probabilities of outcomes obtained were not those expected on the basis of our current body of pharmacological knowledge. The results do not cast doubt on our current pharmacological knowledge per se but do challenge the commonly accepted idea whereby this knowledge alone should be used to define when a DDI alert should be displayed. Real-life probabilities should also be considered during the filtration of DDI alerts by CDSSs, as proposed in SPC-CDSS (statistically prioritized and contextualized CDSS). However, these probabilities may differ from one hospital to another and so should probably be calculated locally.

The effect of different intensivist staffing patterns on the rate of potential drug-drug interactions in adult trauma intensive care units

BACKGROUND

Drug-drug interactions (DDIs) have created alarming challenges for public health, especially in those admitted to intensive care units (ICUs). Many studies have shown that involvement of intensivists in the ICUs improves the outcome and decreases the treatment costs. The effect of academic versus non-academic (therapeutic) intensivist as well as hours of coverage and attendance of intensivist on potential DDIs (pDDIs) was evaluated in six adult trauma ICUs of a level one trauma center.

METHODS

In this 6-month cross-sectional study, 200 patients were included. The DDIs were classified into five groups, including type A, B, C, D, and X. pDDIs were defined as interactions belonged to C, D and X categories. Patients in six adult ICUs with three different patterns of intensivist staffing models including type A (once-daily therapeutic intensivist visit followed by 24 h on-call), B (twice-daily academic intensivist visit, 8 h of attendance in ICU and 16 h on-call) and C (all criteria just like ICU type B, except for the presence of therapeutic instead of academic intensivist) were screened for pDDIs.

RESULTS

In total, 3735 drug orders and 3869 drugs (193 different types) were screened and 1826 pDDIs were identified. Type C, D and X interactions accounted for 60.6%, 35.5%, and 3.9% of all pDDIs, respectively. The mean of pDDI per patient was significantly higher (p-value < 0.001) in the ICU type A than ICU types C and B. The frequency of pDDIs was the highest in the type A ICUs. A statistically significant relationship was observed between the number of prescribed drugs and ICU length of stay (p-value < 0.001 and p = 0.009, respectively).

CONCLUSION

Different patterns of intensivist staffing affect pDDIs to varying degrees. In the studied ICUs academic versus therapeutic intensivist, twice versus once-daily visit, and 8 h attendance with16 h on-call versus 24 h on-call were associated with more reductions in pDDIs.

PLAIN LANGUAGE SUMMARY

The impact of different intensivist staffing patterns in ICUs on the rate of potential drug-drug interactionsDrug-drug interactions (DDIs) have created alarming challenges for public health, especially in patients admitted to intensive care units (ICUs). Many studies have shown that involvement of intensivists in the ICUs improves the outcome and limits the costs. Considering the high incidence of potential DDIs (pDDIs) occurring for critically ill patients and the importance of ADRs caused by pDDIs in ICUs, the effect of the presence of an academic versus therapeutic intensivist, as well as the hour of coverage of intensivist on prevalence of pDDIs was evaluated in six adult trauma ICUs of a level one trauma center in Shiraz, Iran. We also determined the prevalence of pDDIs and their associated risk factors. To the best of our knowledge, this is the first study that has assessed the effect of various ICU physician staffing models on the incidence and pattern of pDDIs.

Prevalence, severity, and nature of risk factors associated with drug-drug interactions in geriatric patients receiving cancer chemotherapy: A prospective study in a tertiary care teaching hospital

INTRODUCTION

Polypharmacy increases hazard of drug-drug interactions(DDIs), hospitalization, treatment toxicity, and mortality in elderly individuals with cancer. The present study explores and analyzes prevalence and severity of DDIs in geriatric cancer patients subjected to anticancer chemotherapy, their mechanisms, stratification of severity, and correlation between DDI risk and number of medications taken.

METHODS

This was a cross-sectional study conducted between January-July 2019 at the Medical Oncology/Hematology and Radiation-Oncology Departments, All India Institute of Medical Sciences(AIIMS) Rishikesh. The study included a convenience sampling of 126 geriatric cancer patients.

RESULTS

126 patients were enrolled in present study. DDIs were identified in 97.6% of elderly cancer patients, and 88.9% had at least one DDI with antineoplastic medications. Highest number of DDIs involving antineoplastic medications in any given patient was 12. DDIs involving medications used for treatment of non-cancerous diseases were observed in 83.3% of patients; highest number of interactions identified in any given patient was 15. Out of 473 interactions, 237(50.1%) DDIs were attributable to pharmacodynamic mechanisms of action. 126(27%) of DDIs involved pharmacokinetic mechanisms and 110(23.6%) involved unknown mechanisms. In this present study, total number of DDIs could be positively correlated with total number of medications and number of health problems.

CONCLUSIONS

Geriatric cancer patients are at high risk of DDIs ascribable to polypharmacy. Physicians may utilize online DDI checking softwares to alert themselves, characterize potential DDIs, and modify medications judiciously. An integrative and algorithmic approach with inclusion of geriatricians, oncologists, cardiologists, general practitioners, and clinical pharmacologists/ pharmacists is imperative to optimize drug therapy.

Risk Factors Associated With Medication Errors Among Patients Suffering From Chronic Disorders

Introduction: Medication error is unintentional and can be reduced by reducing the risk factors. Patients suffering from chronic diseases are at an increased risk of medication errors.

Objective: This work aims to assess the risk factors associated with medication errors among patients suffering from chronic disorders in hospitals of South Punjab, Pakistan.

Methodology: Multiple logistic regression analysis was used to assess the impact of different risk factors on the prevalence of medication errors in patients suffering from chronic diseases.

Results: A greater risk for the occurrence of medication errors was associated with age ≥60 years (odds ratio, OR = 1.9; 95% CI = 1.3–3.1; p = 0.001), overburdened healthcare system (OR = 2.2; 95% CI = 1.64–3.56; p < 0.000), number of prescribed drugs ≥5 (OR = 1.74; 95% CI = 1.02–2.64; p < 0.000), comorbidities (OR = 2.6; 95% CI = 1.72–3.6; p = 0.003), Charlson comorbidity index (OR = 1.31; 95% CI = 0.49–1.84; p = 0.004), and multiple prescribers to one patient (OR = 1.12; 95% CI = 0.64–1.76; p = 0.001).

Conclusion: Older age, overburdened healthcare system, number of prescribed drugs, comorbidities, Charlson comorbidity index, and multiple prescribers to one patient are significant risk factors for the occurrence of medication errors.

Prevalence of potential drug-drug interactions and associated factors among outpatients and inpatients in Ethiopian hospitals: a systematic review and meta-analysis of observational studies

BACKGROUND

Drug-drug interaction is an emerging threat to public health. Currently, there is an increase in comorbid disease, polypharmacy, and hospitalization in Ethiopia. Thus, the possibility of drug-drug interaction occurrence is high in hospitals. This study aims to summarize the prevalence of potential drug-drug interactions and associated factors in Ethiopian hospitals.

METHODS

A literature search was performed by accessing legitimate databases in PubMed/MEDLINE, Google Scholar, and Research Gate for English-language publications. To fetch further related topics advanced search was also applied in Science Direct and HINARI databases. The search was conducted on August 3 to 25, 2019. All published articles available online until the day of data collection were considered. Outcome measures were analyzed with Open Meta Analyst and CMA version statistical software. Der Simonian and Laird's random effect model, I² statistics, and Logit event rate were also performed.

RESULTS

A total of 14 studies remained eligible for inclusion in systematic review and meta-analysis. From the included studies, around 8717 potential drug-drug interactions were found in 3259 peoples out of 5761 patients. The prevalence of patients with potential drug-drug interactions in Ethiopian hospitals was found to be 72.2% (95% confidence interval: 59.1, 85.3%). Based on severity, the prevalence of major, moderate, and minor potential drug-drug interaction was 25.1, 52.8, 16.9%, respectively, also 1.27% for contraindications. The factors associated with potential drug-drug interactions were related to patient characteristics such as polypharmacy, age, comorbid disease, and hospital stay.

CONCLUSIONS

There is a high prevalence of potential drug-drug interactions in Ethiopian hospitals. Polypharmacy, age, comorbid disease, and hospital stay were the risk factors associated with potential drug-drug interactions.

Prevalence of potential drug-drug interactions in outpatients of a general hospital in China: a retrospective investigation

Background Potential drug–drug interactions are important factors resulting in adverse drug reactions or therapeutic failure. Therefore, potential drug–drug interactions need to be identified to prevent the related risk and improve drug safety. Objective This study was designed to determine the prevalence of potential drug–drug interactions and investigate the association of potential drug–drug interactions with characteristics in outpatient prescriptions. Setting A large-scale general university hospital in Jinshan District of Shanghai, China. Method The retrospective study was conducted on data obtained from prescriptions containing two or more drugs, written for outpatients older than 18 years. They were screened for potential drug–drug interactions using Lexi-Interact in UpToDate, Stockley’s Drug Interactions and Medicine Specification in the order of priority. Main outcome measure Drug–drug interactions with C, D, X risk rating and clinical parameters recorded at the prescriptions. Results 16,120 prescriptions were screened for the presence of potential drug–drug interactions and 4882 (30.29%) prescriptions containing 6667 potential drug–drug interactions were identified. Among 6667 potential drug–drug interactions, 90.81% (6054/6667), 8.49% (566/6667), 0.70% (47/6667) potential drug–drug interactions belonged to the risk category of C, D and X, respectively. Male, old age and polypharmacy increased the likelihood of potential drug–drug interactions. The most frequently prescribed drugs responsible for potential drug–drug interactions included pioglitazone, dihydrocodeine, thalidomide, sotalol, amiodarone and amlodipine. The predominant potential adverse outcome of potential drug–drug interactions was the increased central nervous system suppression function with the mechanism of reinforced pharmacological effects. Conclusion This study showed that potentially significant drug–drug interactions in outpatients were prevalent in real-world practice. Considering the risk of potential clinical consequences related to potential drug–drug interactions, it is necessary to implement the computerized surveillance and warning systems with drug–drug interactions databases as well as develop the clinical guidelines regarding the widespread potential drug–drug interactions.

Prevalence of drug interactions in hospitalised elderly patients: a systematic review

BACKGROUND

The prevalence of drug-drug interactions (DDIs) in hospital settings is variable, and elderly patients are considered a high risk population for DDIs. There are no systematic reviews describing the prevalence of DDIs in hospitalised elderly patients.

OBJECTIVES

To assess and summarise the available data on the prevalence of DDIs in hospitalised elderly patients and to describe which drugs, drug classes and drug combinations are most commonly involved in DDIs.

DATA SOURCE

A systematic electronic literature search was conducted on Medline/PubMed, Embase, Lilacs, SciElo, Web of Science, Cinahl, Scopus, Cochrane, OpenGrey, Capes Thesis Bank, OasisBR, OpenAire and abstracts from scientific events, without limitation on language or period of publication. Study selection was completed on 21 September 2018.

STUDY ELIGIBILITY CRITERIA, PARTICIPANTS AND INTERVENTIONS

Original observational studies that reported the prevalence of actual or potential DDIs during hospitalisation in patients aged 60 years or older were included. The main outcome measure was prevalence of DDIs and number of DDIs per patient. Subgroup analysis was performed in studies that reported the prevalence of DDIs in geriatric units.

STUDY APPRAISAL AND SYNTHESIS METHODS

Study quality was assessed using the Agency for Healthcare Research and Quality methodological checklist for cross sectional and prevalence studies.

RESULTS

34 studies were included, involving 9577 patients. The prevalence of DDIs ranged from 8.34% to 100%. In studies conducted in geriatric units, the prevalence ranged from 80.5% to 90.5%. The number of DDIs per patient ranged from 1.2 to 30.6. Single drugs most commonly involved in DDIs were furosemide, captopril, warfarin and dipyrone. Drug classes mostly involved were potassium sparing diuretics and angiotensin converting enzyme inhibitors.

LIMITATIONS

The main limitation is the heterogeneity between the included studies that precluded a meta-analysis. Several different methods were used to identify DDIs, majorly, and potential DDIs. Few studies have reported measures to control the quality of the collected data.

CONCLUSIONS AND IMPLICATIONS OF KEY FINDINGS

The prevalence of DDIs ranged widely, and the variation may reflect differences in the conditions of the elderly patients and level of attention (or complexity of care), as well as methodological differences, especially the methods and/or software used to identify DDIs.

SYSTEMATIC REVIEW REGISTRATION NUMBER

CRD42018096720.

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

Aims

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

Material and methods

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

Results

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

Conclusion

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

Severe complications of tramadol overdose in Iran

OBJECTIVES

Severe complications of tramadol overdose have been reported; however, few large-scale studies have investigated this issue. Therefore, this study aimed to explore the presentation and complications of tramadol overdose in patients admitted to an intoxication referral center in northwestern Iran.

METHODS

Patients with tramadol overdose admitted to Sina Teaching Hospital in Tabriz, Iran during 2013-2017 were included. For each patient, the following data were collected: demographics, previous drug or medication overdose, whether the patient was in the process of quitting drug use, ingested dose of tramadol and co-ingestants, Glasgow Coma Scale (GCS) score, clinical symptoms at the time of admission, and admission characteristics. Serotonin toxicity was diagnosed in patients who fit the Hunter criteria. Multiple logistic regression was performed to identify variables associated with the incidence of severe complications of tramadol overdose.

RESULTS

In total, 512 cases of tramadol overdose were evaluated, of which 359 patients were included, with a median age of 41 years (range, 16-69) and a median tramadol dose of 1,500 mg (range, 500-4,000). The most frequent complications associated with tramadol overdose were hypertension (38.4%), tachycardia (24.8%), and seizure (14.5%). No serotonin toxicity was detected in patients. Having a GCS score <15, having taken a tramadol dose of >1,000 mg, being in the process of quitting drug use, being 30-49 years old, and male sex were significantly related to the incidence of severe complications of tramadol overdose.

CONCLUSIONS

Although seizure was prevalent among Iranian patients with tramadol poisoning, serotonin toxicity and cardiogenic shock were rare findings.

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.

The prevalence of potentially beneficial and harmful drug-drug interactions in intensive care units

Background The present study was conducted with the aim of investigating the prevalence of potentially beneficial and harmful drug-drug interactions (DDIs) in intensive care units (ICUs). Methods The present cross-sectional prospective study was conducted in two ICUs in Shahr-e Kord city, Iran. The study sample was consisted of 300 patients. The Drug Interaction Facts reference text book [Tatro DS. Drug interaction facts. St Louis, MO: Walters Kluwer Health, 2010.] was used to determine the type and the frequency of the DDIs. Results The participants consisted of 189 patients men and 111 women. The mean age of patients was 44.2 ± 24.6 years. Totally, 60.5% of patients had at least one drug-drug interaction in their profile. The total number of DDIs found was 663 (the mean of the total number of drug-drug interactions was 2.4 interactions per patient). Of all the 663 interactions, 574 were harmful and others were beneficial. In terms of starting time, 98 of the potential interactions were rapid and 565 of them were delayed. In terms of severity, 511 of the potential interactions were moderate. Some of the drugs in the patients' medical records including phenytoin, dopamine, ranitidine, corticosteroid, dopamine, heparin, midazolam, aspirin, magnesium, calcium gluconate, and antibiotics, the type of ventilation, the type of nutrition and the duration of hospital stay were among the factors that were associated with high risk of potential DDIs (p < 0.05). Conclusions The prevalence of potentially beneficial and harmful DDIs, especially harmful drug-drug interactions, is high in ICUs and it is necessary to reduce these interactions by implementing appropriate programs and interventions.