Clinical drug interactions in outpatients of a university hospital in Thailand

Knowledge and information sources of potential drug-drug interactions of healthcare professionals among Buraydah Hospitals

BACKGROUND AND OBJECTIVE

Drug-drug interactions (DDI) are known to increase the risk of morbidity and mortality, and adversely affect the patient's quality of life. The study was to assess healthcare professional's (HCP) knowledge of DDIs in general hospitals of Buraydah.

METHODS

A cross-sectional survey using convenience sampling methods was conducted among 135 healthcare professionals in general hospitals of Buraydah between November and December 2016. The study was carried out after approval and permission from the Regional Research Ethics Committee (November 2016). Respondents were asked to classify 15 drug pairs as 'contraindicated', 'could be used with monitoring', or 'no interaction'. A response option of 'not sure' was also provided. Data were collected using a self-administered questionnaire. The descriptive analysis was done using frequency distribution and percentage for demographic data and other responses to questions. Data were collected, tabulated, and analyzed using Statistical Package for Social Sciences (SPSS) software (version 23). Logistic regression analysis was used to assess the independent variables that affect the HCP knowledge, the significant levels were set at p-value < 0.05.

RESULTS

A total of 135 healthcare professionals were included in the study. The percentage of HCPs who correctly classified the drug pairs ranged from 15 (11.1%) for "Allopurinol + Pyrazinamide" to 90 (66.7%) for "acetaminophen with codeine + amoxicillin". The average number of correctly categorized drug pairs was 5. About one-half of the respondents 73 (54.1%) answered correctly. The level of education was found to be an independent predictor of DDI knowledge. The results from the multivariate analysis indicated that a higher potential DDI knowledge level was associated with pharmacists. Pharmacists had 8.27 times higher DDI knowledge tests than nurses, P value = 0.001. Pharmacists 43(31.9%) were the most cited information source.

CONCLUSIONS

The present study revealed that health care professional's DDI knowledge was inadequate. Level of education was significantly associated with healthcare professionals' DDI knowledge. Pharmacists were the most cited DDI information source. Healthcare professionals should update their DDI knowledge through continuing education and should improve their familiarity with DDI information sources. These updated educations help to provide the appropriate therapeutic outcomes.

Assessment of potential drug–drug interactions among outpatients in a tertiary care hospital: focusing on the role of P-glycoprotein and CYP3a4 (retrospective observational study)

Background

Selecting a medicine has a significant impact on the quality of therapy including efficacy and safety. P-glycoprotein and CYP3A4 share several common substrates known as bi-substrates. Both play major role in the pharmacokinetics and pharmacodynamics when over or under expressed.

Objective

The study aimed to assess the Drug–Drug Interaction (DDI) related to P-glycoprotein (P-gp) and Cytochrome P450-3A4 (CYP3A4), to predict their clinical outcomes and also to discover prospective predictors of pDDIs.

Methods

The subjects in this retrospective study ranged in age from 18 to 95 years with polypharmacy prescriptions. Information was gathered through patient medical records. Based on Micromedex and previous literature studies, medications prescribed to the patients were observed for pDDIs according to risk rating scale for drug interactions.

Results

A total of 504 patients (160 males and 344 females) were included in the study. The mean of pDDI seen in the patients was 1.66 ± 1.48 and total 825 pDDIs were discovered. The factors significantly associated with having ≥1 pDDIs included: taking ≥5 medicines (OR 1.747), increased age (OR 1.026) increased comorbidities (OR 1.73).

Conclusion

In prescriptions, a considerable number of probable DDI were discovered. Therefore, careful selection of drugs and identification of mechanisms for DDI is needed to lower the frequency of pDDI.

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.

Introducing the Big Knowledge to Use (BK2U) challenge

The purpose of the Big Data to Knowledge initiative is to develop methods for discovering new knowledge from large amounts of data. However, if the resulting knowledge is so large that it resists comprehension, referred to here as Big Knowledge (BK), how can it be used properly and creatively? We call this secondary challenge, Big Knowledge to Use. Without a high-level mental representation of the kinds of knowledge in a BK knowledgebase, effective or innovative use of the knowledge may be limited. We describe summarization and visualization techniques that capture the big picture of a BK knowledgebase, possibly created from Big Data. In this research, we distinguish between assertion BK and rule-based BK (rule BK) and demonstrate the usefulness of summarization and visualization techniques of assertion BK for clinical phenotyping. As an example, we illustrate how a summary of many intracranial bleeding concepts can improve phenotyping, compared to the traditional approach. We also demonstrate the usefulness of summarization and visualization techniques of rule BK for drug-drug interaction discovery.

Potentially severe drug-drug interactions among older people and associations in assisted living facilities in Finland: a cross-sectional study

OBJECTIVE

This study aims to assess potentially severe class D drug-drug interactions (DDDIs) in residents 65 years or older in assisted living facilities with the use of a Swedish and Finnish drug-drug interaction database (SFINX).

DESIGN

A cross-sectional study of residents in assisted living facilities in Helsinki, Finland.

SETTING

A total of 1327 residents were assessed in this study. Drugs were classified according to the Anatomical Therapeutic Chemical (ATC) classification system and DDDIs were coded according to the SFINX.

MAIN OUTCOME MEASURES

Prevalence of DDDIs, associated factors and 3-year mortality among residents.

RESULTS

Of the participants (mean age was 82.7 years, 78.3% were females), 5.9% (N = 78) are at risk for DDDIs, with a total of 86 interactions. Participants with DDDIs had been prescribed a higher number of drugs (10.8 (SD 3.8) vs. 7.9 (SD 3.7), p < 0.001). A larger proportion of residents with DDDIs suffered from rheumatoid arthritis or osteoarthritis than those not exposed to DDDIs (24.7% vs. 15.4%, p = 0.030). The most frequent DDDIs were related to the concomitant use of potassium with amiloride (N = 12) or spironolactone (N = 12). Carbamazepine (N = 13) and methotrexate (N = 9) treatments were also frequently linked to DDDIs. During the follow-up, no differences in mortality emerged between the participants exposed to DDDIs and the participants not exposed to DDDIs.

CONCLUSIONS

Of the residents in assisted living, 5.9% were exposed to DDDIs associated with the use of a higher number of drugs. Physicians should be trained to find safer alternatives to drugs associated with DDDIs. KEY POINTS   Potentially severe, class D drug-drug interactions (DDDIs) have been defined in the SFINX database as clinically relevant drug interactions that should be avoided.  • Of the residents in assisted living, 5.9% were exposed to DDDIs that were associated with the use of a higher number of drugs.  • The most frequent DDDIs were related to the concomitant use of potassium with amiloride or spironolactone. Carbamazepine and methotrexate were also linked to DDDIs.  • No difference in mortality was observed between residents exposed to DDDIs and residents not exposed to DDDIs.

Prevalence of potential drug interactions in an Iranian general hospital

The hazards of prescribing many drugs, including side-effects, drug-drug interactions and difficulties of compliance have long been recognized as particular problems when prescribing. This study estimates the rate and factors associated with potential drug-drug interactions in prescriptions from wards of An Iranian General Hospital. Data were retrieved from the pharmacy of a general hospital (200 beds) during one year period 2010. Potential drug-drug interaction were identified using a computerized drug-drug interaction database system (Prescription Analyzer 2000, Sara Rayane Co., Iran). Patients of both genders and 15 years-old or more were included in this study. Prescriptions with two or more drugs prescribed were selected during one year period 2010. Gender number of drugs and therapeutic drug classes on prescriptions were explored as associated factors to drug-drug interaction. The overall prevalence of potential drug-drug interaction was 20.3%. The risks of severe potential drug interactions were relatively high and the rate of potential drug-drug interaction was significantly higher in women (60.6%) and the patients aged over 60 years old (57.1%). The frequency of the potentially severe drug-drug interaction was 10.8% with digoxin-furosemide as the most common interacting pair (5.91%). A positive correlation was found between drug-drug interaction, patient's age, number of drugs and drugs acting on cardiovascular system. So cardiology women inpatients, age more then 60 years old, and patients prescribed digoxin and angiotensin-converting enzyme inhibitors should be closely monitored for adverse outcomes from drug-drug interaction.

Out-patients Prescriptions are Safe from Drug Interactions or Not: A Pilot Study Report

The objective of the research work was to analysis the out patients drug interactions and alerts the healthcare professionals to prevent the future complications. The study was done in three pharmacies within a 200 meters distance of each other. The doctors involved were made aware of the study but data were collected without their knowledge. All prescriptions presented to the three pharmacies were analyzed during the five-month study period. A total of 500 prescriptions were analyzed and 64 drug-drug interactions were detected giving a drug-drug interaction rate of 12.8 percent but 436 (87.2%) prescriptions are free from drug interactions. Moderate drug interactions were found in 10.2%, Severe were 2.6% and contraindicated were 0% and also disease wise drug interaction analysis were carried out during the study results, more number of drug interactions reported in central nerves system followed by diabetes mellitus. Outpatient visits resulted in minimal numbers of clinically important drug-drug interactions, these interactions can have significant implications due to medication-related morbidity and mortality. Pharmacists can play a critical role in managing the medication therapy of patients at risk for clinically important drug-drug interactions.

Association of suboptimal prescribing and change in lower extremity physical function over time

BACKGROUND

Previous studies have found inconsistent links between suboptimal prescribing and negative patient outcomes. While suboptimal prescribing consists of multiple components, e.g. drugs to avoid in the elderly (DAE), potential drug interactions (PDI) and polypharmacy, most research has focused on the impact of drugs to avoid. This study explores the relationship between suboptimal prescribing, comorbid disease, and change in lower extremity functional limitation (LEFL).

METHODS

This prospective cohort study used data from the Hispanic Established Population for the Epidemiologic Study of the Elderly. Baseline data collection occurred between 1993 and 1994 with three additional waves of data collected approximately every 2 years. Based on the disablement process model, the dependent variable was change in LEFL over the 7-year study period. Independent variables included suboptimal prescribing: DAE, PDI and polypharmacy. Measures of pathology included comorbid diseases (stroke, cancer, hypertension, cardiovascular disease, arthritis, and diabetes). Age, gender, education, smoking, cognitive status, depression, body mass index, marital status, and self-reported health were controlled in analyses.

RESULTS

Diabetes, stroke, and arthritis were associated with a decline in LEFL. Polypharmacy mediated the relationship between diabetes and LEFL, and polypharmacy was also significantly associated with decrements in LEFL.

CONCLUSION

The effect of suboptimal prescribing on change in LEFL was limited to both direct and mediational effects of polypharmacy. Additional research exploring the association between suboptimal prescribing and a variety of quality measures using a diverse set of outcomes would improve our understanding of the impact of suboptimal prescribing more broadly defined.

Identification of severe potential drug-drug interactions using an Italian general-practitioner database

OBJECTIVE

To analyze prescriptions in a general-practitioner database over 1 year to determine the frequency, the characteristics, and the monitoring of the severe potential drug-drug interactions (DDIs).

METHODS

We retrospectively analyzed the clinical records from 16 general practitioners in the Veneto region, an area in northern Italy. The study covered the period from January 1 to December 31, 2004. We selected all severe and well-documented interactions according to the book Drug Interaction Facts by David S. Tatro (Facts and Comparisons, St. Louis, MO, 2006). We grouped severe potential DDIs according to their specific potential risk, and for the most frequently interacting drug pairs, we investigated whether some specific tests had been prescribed by physicians for safety monitoring.

RESULTS

During the study period, 16,037 patients (55% female) with at least one drug prescription were recorded, and a total of 185,704 prescriptions relating to 1,020 different drugs were analyzed. Ramipril was the most frequently prescribed drug followed by acetylsalicylic acid and atorvastatin. The final number of different types of severe potential DDIs was 119, which occurred 1,037 times in 758 patients (4.7% of the total number of patients). More than 80% of drugs involved in severe potential DDIs were cardiovascular drugs. Digoxin was the most frequently involved drug. Electrolyte disturbances, increase in serum digoxin levels, risk of hemorrhage, severe myopathy or rhabdomyolysis, and cardiac arrhythmias were the most commonly implicated potential risks. When considering patients using digoxin with loop or thiazide diuretics for more than 5 months, 72% had at least one test to monitor potential digoxin toxicity, whereas 28% had no tests. Sixty-four percent of patients using digoxin with amiodarone, verapamil, or propafenone had an ECG and/or digoxin monitoring, and 36% of them did not have any tests.

CONCLUSIONS

The present study revealed that, in a group of Italian general practitioners, the risks of severe potential drug interactions are relatively low and the drugs concerned are few. Analyses of specific tests showed that physicians are generally aware of the potential risks caused by digoxin drug associations. However not all patients were closely monitored and this should be improved.

Pharmacokinetics and interactions of headache medications, part II: prophylactic treatments

The present part II review highlights pharmacokinetic drug-drug interactions (excluding those of minor severity) of medications used in prophylactic treatment of the main primary headaches (migraine, tension-type and cluster headache). The principles of pharmacokinetics and metabolism, and the interactions of medications for acute treatment are examined in part I. The overall goal of this series of two reviews is to increase the awareness of physicians, primary care providers and specialists regarding pharmacokinetic drug-drug interactions (DDIs) of headache medications. The aim of prophylactic treatment is to reduce the frequency of headache attacks using beta-blockers, calcium-channel blockers, antidepressants, antiepileptics, lithium, serotonin antagonists, corticosteroids and muscle relaxants, which must be taken daily for long periods. During treatment the patient often continues to take symptomatic drugs for the attack, and may need other medications for associated or new-onset illnesses. DDIs can, therefore, occur. As a whole, DDIs of clinical relevance concerning prophylactic drugs are a limited number. Their effects can be prevented by starting the treatment with low dosages, which should be gradually increased depending on response and side effects, while frequently monitoring the patient and plasma levels of other possible coadministered drugs with a narrow therapeutic range. Most headache medications are substrates of CYP2D6 (e.g., beta-blockers, antidepressants) or CYP3A4 (e.g., calcium-channel blockers, selective serotonin re-uptake inhibitors, corticosteroids). The inducers and, especially, the inhibitors of these isoenzymes should be carefully coadministered.