Interacting Drug Combinations Research Articles

Prevalence of potential drug-drug interactions with disease-specific treatments in patients with pulmonary arterial hypertension or chronic thromboembolic pulmonary hypertension: A registry study.

Polypharmacy increases the risk of drug–drug interactions that may disturb treatment effects. The aim of this study was to investigate the frequency of codispensing of potentially interacting or contraindicated drugs related to PH‐specific treatment in the Swedish pulmonary arterial hypertension (PAH) and chronic thromboembolic pulmonary hypertension (CTEPH) population. All prescribed drugs, on an individual level, dispensed 2016–2017 at pharmacies to patients with PAH or CTEPH were obtained from The National Board of Health and Welfare's pharmaceutical registry. Potential drug–drug interactions were investigated using the Drug Interaction tool in the IBM Micromedex® database. There were 4785 different dispensed drugs from 572 patients (mean age 61 ± 16 years, 61% female, mean number of drugs per patient 8.4 ± 4.2) resulting in 1842 different drug combinations involving a PH‐specific treatment. Of these drug combinations, 67 (3.5%) had a potential drug–drug interaction considered clinically relevant and it affected 232 patients (41%). The PH‐specific drugs with the highest number of potential drug–drug interactions was bosentan (n = 23, affected patients = 171) while the most commonly codispensed, potentially interacting drug combination was sildenafil/furosemide (119 patients affected). Other common codispensed and potentially interacting drugs were anticoagulants (n = 11, affected patients = 100) and antibiotic treatment (n = 12, affected patients = 26). In conclusion, codispensing of PH‐specific therapy and potentially interacting drugs was common, but codispensing of potentially contraindicated drugs was rare.

Use of Drug Claims Data and a Medication Risk Score to Assess the Impact of CYP2D6 Drug Interactions among Opioid Users on Healthcare Costs.

Cytochrome P450 2D6 (CYP2D6) activity is highly variable due to several factors, including genetic polymorphisms and drug-drug-gene interactions. Hydrocodone, oxycodone, codeine, and tramadol the most commonly prescribed CYP2D6-activated opioids for pain. However, the co-administration of CYP2D6 interacting drugs can modulate CYP2D6-medicated activation of these opioids, affecting drug analgesia, effectiveness, and safety, and can impact healthcare costs. A retrospective, observational cohort analysis was performed in a large (n = 50,843) adult population. This study used drug claims data to derive medication risk scores and matching propensity scores to estimate the effects of opioid use and drug-drug interactions (DDIs) on medical expenditures. 4088 individuals were identified as opioid users; 95% of those were prescribed CYP2D6-activated opioids. Among those, 15% were identified as being at risk for DDIs. Opioid users had a significant increase in yearly medical expenditure compared to non-opioid users ($2457 vs. $1210). In matched individuals, average healthcare expenditures were higher for opioid users with DDIs compared to those without DDIs ($7841 vs. $5625). The derived medication risk score was higher in CYP2D6 opioid users with interacting drug(s) compared to no DDI (15 vs. 12). Higher costs associated with CYP2D6 opioid use under DDI conditions suggest inadequate CYP2D6 opioid prescribing practices. Efforts to improve chronic opioid use in adults should reduce interacting drug combinations, especially among patients using CYP2D6 activated opioids.

Occurrence of possible drug related interactions in medical patients in out-patient departments of Pakistan

Background: Data regarding occurrence of drug-drug interactions in Pakistan is rare. In the current study, we have tried to find out the clinical adversity and frequency witnessed in prescriptions of a medical outpatient department.Methods: Patient prescriptions were analyzed for potential drug-drug interactions. A sample of 364 patients, visited outpatient department who were being prescribed at least two drugs simultaneously using a drug interaction program website.Results: The 364 patients (72.8% male, mean age 57.9±15.2 years) were prescribed a median of six drugs (range 2-13) at OPD visit. Three hundred forty nine patients (95.8%) had at least one potentially interacting drug combination. 2636 potential interactions were seen in the visiting patients. Out of these 124 (4.7%) were of major severity, 1730 (65.6%) moderate and 515 (19.5%). Out of 124 patients with a potential DDI with major severity, no patient was re-hospitalized within 2 months after discharge due to a probable drug-related problem associated with the potential DDI.Conclusions: A large percentage of patients were detected having one or more potential drug-drug interactions, using drug interaction detection program. However, the percentage of patients having clinically adverse consequences due to drug-drug interactions appears to be very low.

STUDY OF POTENTIAL DRUG INTERACTIONS AMONG EIGHT MAJOR DEPARTMENTS-GENERAL MEDICINE, ORTHOPEDICS, GYNECOLOGY, PULMONOLOGY, GENERAL SURGERY, PSYCHIATRY, OTOLARYNGOLOGY AND DERMATOLOGY OF A TERTIARY CARE TEACHING HOSPITAL IN SOUTHERN INDIA

Objective: To identify frequency, type, severity and predictors of potential drug-drug interactions(pDDIs), potential drug-food interactions(pDFIs), potential drug-alcohol interactions(pDAIs) and potential drug-tobacco interactions(pDTIs) and most frequently interacting drug combination pairs in hospitalized patients from departments(depts) of General Medicine(GM), Orthopedic(Ortho), Gynecology(OBG), Pulmonology(Pulmo), General Surgery (GS), Psychiatry (Psych), Otolaryngology(ENT) and Dermatology (Derm) of study population.
 Methods: A Prospective Observational Study was conducted in eight major dept's of a tertiary care teaching hospital for a period of 6 mo. A sample size of 650 prescriptions reflecting admission no's for each department were used.
 Results: A total of 650 patients were included in the study. Among them, 282(43.4%) were males and 368(56.6%) were females. The mean age of the study population was 39.67±15.23. A total of 487 pDDIs, 734 pDFIs, 586 pDAIs and 159 pDTIs were found out of 650 hospitalized episodes. OBG showed the highest pDDIs and pDAIs. Highest pDFIs and pDTIs were seen in Pulmo. The majority of DDIs were minor, DFIs and DAIs were moderate and DTIs were of major in severity. Pharmacokinetic types of interactions were seen in the majority of the depts. Logistic regression analysis showed that Polypharmacy was associated with the occurrence of DIs. Most of the DIs repeated several times in particular depts and a list of these combinations was prepared.
 Conclusion: With the high occurrence of overall DIs and characteristic patterns of DIs combination pairs among different departments of the hospital, the presence of clinical pharmacists in hospitals can play a great role, especially in developing nations like India where their role in hospitalized settings is always controversial.

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

BackgroundElderly 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.MethodologyA 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.ResultsThe 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%).ConclusionA higher incidence of polypharmacy and increased risk of potential DDIs in elderly people with cardiovascular disease are major therapeutic issues at Yekatit 12 hospital.

Drug-drug interactions in patients undergoing chemoradiotherapy and the impact of an expert team intervention.

Background Several studies have examined the drug-drug interaction patterns in different patient populations and treatment settings; however, there is a need, particularly in the field of oncology and radiotherapy, for evaluating methods targeted towards preventing potential drug-drug interactions. One of the measures proposed is identifying potential interactions using computer programs and their evaluation by pharmacologists or clinical pharmacists, thereby providing clinically relevant information to the treating physician regarding the required prescription changes. Objective To determine the prevalence of potential drug-drug interactions in patients receiving chemoradiotherapy and assess the usefulness of expert team recommendations in minimizing interactions. Setting Patients admitted to the radiotherapy and oncology ward of a tertiary care teaching hospital in Karnataka, India. Method We conducted a prospective, cross-sectional study of prescriptions written for patients receiving chemoradiotherapy. Prescriptions containing two or more drugs, at least one of the drugs being an anticancer drug, were analyzed. They were screened for potential drug-drug interactions using the Lexicomp® drug interaction software. The interactions were classified as X, drug combination to be avoided; D, modification of therapy to be considered; and C, therapy to be monitored, as per the Lexicomp criteria. Main outcome measure The number of drug-drug interactions detected that were accepted by the treating radio-oncologist as requiring prescription change before and after the prescription review by an expert team. Results Two hundred twenty-three prescriptions were screened for the presence of drug-drug interactions; 106 prescriptions (47.53%) containing 620 drugs and 211 drug-drug interactions were identified. Of the 211 interactions identified, 6.64% (14/211), 18.48% (39/211), and 74.88% (158/211) drug-drug interactions belonged to category X, D, and C, respectively. Twenty-seven (50.94%) of the 53 category X and D interactions identified were accepted the oncologist as requiring a change in the prescription; an additional 13 (24.53%) interactions were identified as significant by the expert team, and 11 (84.62%) of these were accepted by the oncologist. Conclusion A system of alerting the treating physician to a potential drug-drug interaction leads to avoidance of prescription of the interacting drug combination, and the assistance by an expert team adds significantly to avoidance of clinically relevant drug interactions.

Evaluation of context-specific alerts for potassium-increasing drug-drug interactions: A pre-post study

ObjectiveTo investigate whether context-specific alerts for potassium-increasing drug-drug interactions (DDIs) in a clinical decision support system reduced the alert burden, increased alert acceptance, and had an effect on the occurrence of hyperkalemia. Materials and MethodsIn the pre-intervention period all alerts for potassium-increasing DDIs were level 1 alerts advising absolute contraindication, while in the post-intervention period the same drug combinations could trigger a level 1 (absolute contraindication), a level 2 (monitor potassium values), or a level 3 alert (informative, not shown to physicians) based on the patient’s recent laboratory value of potassium. Alert acceptance was defined as non-prescription or non-administration of the interacting drug combination for level 1 alerts and as monitoring of the potassium levels for level 2 alerts. ResultsThe alert burden decreased by 92.8%. The relative risk (RR) for alert acceptance based on prescription rates for level 1 alerts and monitoring rates for level 2 alerts was 15.048 (86.5% vs 5.7%; 95% CI 12.037–18.811; P < 0.001). With alert acceptance for level 1 alerts based on actual administration and for level 2 alerts on monitoring rates, the RR was 3.597 (87.6% vs 24.4%; 95% CI 3.192–4.053; P < 0.001). In the generalized linear mixed model the effect of the intervention on the occurrence of hyperkalemia was not significant (OR 1.091, 95% CI 0.172–6.919). ConclusionThe proposed strategy seems effective to get a grip on the delicate balance between over- and under alerting.

Prescription Medication Use Among Children and Adolescents in the United States.

Information on the use of prescription medications among children and adolescents in the United States is lacking. We estimate the prevalence of prescription medication use, concurrent use, and potential major drug-drug interactions (DDIs) in this population. We conducted descriptive analyses using nationally representative data for people ≤19 years old from NHANES. Data were derived from a medication log administered by direct observation during in-home interviews. Acute medications were used for ≤30 days. Concurrent use was defined as use of ≥2 prescription medications. Micromedex was used to identify potentially major DDIs. During 2013-2014, 19.8% of children and adolescents used at least 1 prescription medication, and 7.1% used acute medications. Concurrent use of prescription medications was 7.5% overall and was highest among boys 6 to 12 years old (12%) and among boys and girls ages 13 to 19 years old (10% for both). Using pooled 2009-2014 data, we found that 8.2% of concurrent users of prescription medications were at risk for a potentially major DDI. The vast majority of interacting regimens involved antidepressants and were more common among adolescent girls than boys (18.1% vs 6.6%; P < .05), driven largely by greater rates of use of acute medications. Many US children and adolescents use prescription medications with nearly 1 in 12 concurrent users of prescription medications potentially at risk for a major DDI. Efforts to prevent adverse drug events in children and adolescents should consider the role of interacting drug combinations, especially among adolescent girls.

S221. QUANTITATIVE SYSTEMS PHARMACOLOGY AS AN ALTERNATIVE TO CHLORPROMAZINE EQUIVALENTS: PREDICTIVE VALIDATION FROM A CRIS DATABASE EXPERIMENT

BackgroundPolypharmacy is common in real clinical practice and in pharma-sponsored clinical trials. Chlorpromazine equivalents do not take into account pharmacodynamic interactions of drug combinations. If there is a sufficiently deep calibration set available, bio-informatics approaches can build classifiers for clinical phenotypes. However, this is not always the case which severely limits the generalizability of the predictions.MethodsWe applied a mechanism-based computer model of a cortico-striatal-thalamocortical loop of the dorsal motor circuit that has been calibrated with clinical data on the prevalence of extrapyramidal symptoms after antipsychotic treatment in schizophrenia patients and therapeutic interventions in Parkinson’s patients[1]. The Quantitative Systems Pharmacology (QSP) model is based on the appropriate connections between basal ganglia regions and consists of 220 neurons (8 different cell types), 3500 synapses and implementations of 32 CNS active targets, based on their unique locations and coupling with intracellular pathways. Modulation of the various CNS targets were calculated on simulating the competition between the endogenous neurotransmitter and the two drugs at their appropriate concentrations and affinity.The model was challenged to blindly predict the extrapyramidal symptoms liability of 1,124 patients prescribed two antipsychotics for six or more months (772 unique combinations). Anonymized data were derived from South London and Maudsley NHS Foundation Trust (SLAM) electronic health records (EHR). Extrapyramidal side effects were captured and identified using a combination of Natural Language Processing and a bespoke algorithm [2]. Only names and doses of the two drugs were made available without any calibration set.ResultsBlind prediction of the outcomes using a Receiver Operating Characteristic curve with the QSP model resulted in an Area-Under-the Curve of 0.64 (p<0.01), compared to an AUC of 0.52 for the sum of the chlorpromazine equivalents, 0.53 for the sum of affinity constants or the sum of D2R occupancies of the individual antipsychotics (AUC=0.52).DiscussionQSP is a powerful approach to predict PD-PD interactions in the absence of any calibration set or with limited and unique data and is superior to chlorpromazine equivalents for predicting EPS liability. A major application is the simulation of pharmacodynamic interactions of comedications in clinical trials with novel compounds leading to possible better balance between the different treatment arms

Exposure to potential drug-antimicrobial agent interactions in primary health care

Background/Aim. Drug-drug interactions involving antimicrobials present important and often unrecognized complications of pharmacotherapy which can be prevented. The aim of the present study was to identify the frequency and type of potential drug-antimicrobial agent interactions among outpatients and to define recommendations for their management. Methods. Crosssectional prescription database study was conducted. The analysis randomly included 823 patients who visited Health Center Novi Sad over 1-month period (November 1?30, 2011) and had prescribed ? 2 drugs where at least one drug was antimicrobial agent for systemic use. All interacting drug combinations involving antimicrobials were identified according to Drug Interaction Facts. Additionally, based on the compendium, potential interactions were classified into categories: pharmacological mechanisms, potential clinical outcomes and management advice. Results. Overall, 88 potential clinically significant drug-antimicrobial agent interactions were identified among 69 (8.4%) exposed outpatients [the mean age 61.7 years (SD ? 15.4); the mean number of prescribed drugs 7.5 (SD ? 2.9); 56.5% females]. The most common identified potential interacting pairs were benzodiazepines undergoing oxidative metabolism and clarithromycin or erythromycin, and aminophylline and ciprofloxacin. In 83.0% of all cases underlying mechanism was pharmacokinetic involving primary inhibition of metabolic pathways mediated by CYP3A4 and CYP1A2 isoenzymes. Excessive sedation (22.7%), cardiotoxicity (20.5%), miscellaneous aminophylline adverse effects (13.6%), and bleeding (10.2%) were the most frequently implicated potential clinical outcomes. Risk for adverse interactions could be managed by close monitoring of simultaneous administration of drugs (37.5%), different risk-modifyng strategies (31.8%), and avoiding combinations (30.7%). Conclusion. Among outpatients, there was common potential for clinically significant interactions involving antimicrobials. Information based on the results of the present study could be integrated in existing computerized physician order entry system in the Health Center as a form of clinical support.

Prevalence of potentially serious drug-drug interactions among South African elderly private health sector patients using the Mimica Matanović/Vlahović-Palčevski protocol.

To determine the prevalence of potentially serious drug-drug interactions (DDIs) and their relationship with gender and age, among elderly in South Africa. A cross-sectional study was conducted using pharmaceutical claims data for 2013, for a total of 103 420 medical scheme beneficiaries' ≥65 years. All medications dispensed within one calendar month where the days' supply of medication dispensed overlapped, were grouped as one prescription. DDIs per prescription were then identified using the Mimica Matanović/Vlahović-Palčevski DDI protocol. Results were interpreted using effect sizes, that is Cramér's V, Cohen's d and Cohen's ƒ2 . A total of 331 659 DDIs were identified on 235 870 (25.8%, N = 912 713) prescriptions (mean 0.36 (SD 0.7) (95% CI, 0.36 to 0.37)). Women encountered 63.5% of all DDIs. Effect sizes for the association between DDIs and age group (Cramér's V = 0.06), and gender (Cramér's V = 0.05) was negligible. There was no difference between men and women regarding the mean number of DDIs identified per prescription (Cohen's d = 0.10). The number of medicine per prescription (ƒ2 = 0.51) was the biggest predictor of the DDIs. The most frequent interacting drug combinations were between central nervous system medicines (30.6%). Our study is the first to report the prevalence of potentially serious DDIs among an elderly population in the South African private health sector utilising the Mimica Matanović/Vlahović-Palčevski DDI protocol. Overall, we identified DDIs in approximately 26% of the prescriptions in our study. Age and gender were not found to be predictors of potentially serious DDIs.

Use of nystatin and chlorhexidine in oral medicine: Properties, indications and pitfalls with focus on geriatric patients.

The aim of this work was to review the scientific literature on the properties, indications and pitfalls related to nystatin and chlorhexidine in oral medicine and also to compare these to other topical antifungal agents, considering the elderly population. Nystatin is a polyene antifungal widely used as a topical formulation to treat candidiasis, whereas chlorhexidine is a wide-spectrum antimicrobial, especially used against bacteria, but also effective in treating some fungal infections including those caused by Candida spp. These compounds have been prescribed for immunocompromised patients, hospitalized or not, some of them undergoing head and neck radiation therapy and/or chemotherapy, including elderly patients. Dental and medical literature concerning the use of nystatin and chlorhexidine in oral medicine were selected and reviewed. Nystatin and chlorhexidine are gold-standard antimicrobial mouthrinses respectively for Candida spp. and bacteria. Although recognized as effective in cotrolling oral infections, both nystatin and chlorhexidine are just complementary to systemic therapy in cases of systemic infections already established. The prescriber should also take into account that some commercial nystatin and chlorhexidine formulations contain compounds such as sugar and ethanol, which can be associated with side effects. Meanwhile, alternative formulations in which these compounds are absent are available and should be considered. Further studies investigating new drugs and interactions of drug combinations are necessary to improve the therapeutic management of oral infections.

A pilot study on the impact of known drug-drug interactions in cancer patients.

BackgroundWhen a patient concomitantly uses two or more drugs, a drug-drug interaction (DDI) can possibly occur, potentially leading to an increased or decreased clinical effect of a given treatment. Cancer patients are at high risk of such interactions because they commonly receive multiple medications. Moreover, most cancer patients are elderly and require additional medications for comorbidities. Aim of this preliminary observational study was to evaluate the incidence of well known and established DDIs in a cohort of cancer outpatients undergoing multiple treatments.MethodsAnamnestic and clinical data were collected for 64 adult patients in the ambulatory setting with malignant solid tumors who were receiving systemic anticancer treatment.Patients also declared all drugs prescribed by other specialists or self-taken in the previous 2 weeks. DDIs were divided into two different groups: ‘neoplastic DDIs’ (NDDIs), involving antitumoral drugs, and ‘not neoplastic DDIs’ (nDDIs), involving all other classes of drugs. The severity of DDIs was classified as major, moderate and minor, according to the ‘Institute for Pharmacological Research Mario Negri’ definition.ResultsAbout 34 % of cancer outpatients within our cohort were prescribed/assumed interacting drug combinations. The most frequent major NDDIs involved the anticoagulant warfarin (33 % of total NDDIs) that, in association with tamoxifen, or capecitabine and paclitaxel, increased the risk of haemorrhage. About 60 % of nDDIs involved acetylsalicylic acid.ConclusionsOverall, 16 % of DDIs were related to an A-level strength of recommendation to be avoided. The lack of effective communication among specialists and patients might have a role in determining therapeutic errors. Our pilot study, although limited by a small cohort size, highlights the urgent need of implementing the clinical management of cancer outpatients with new strategies to prevent or minimize potential harmful DDIs.

Frequency, types and factors associated with potentially harmful drug interactions in ambulatory elderly patients in Nigeria.

To determine the frequency, types and factors associated with potentially harmful drug interactions among ambulatory elderly (≥65 years) patients in Ibadan, Nigeria. A 4-week cross-sectional study was conducted among 229 elderly patients who consented and were prescribed two or more medicines within a 4-week study period at a major 256-bed secondary care facility in Ibadan, Nigeria. Chi-square and risk ratio were used to identify the factors associated with the potentially harmful drug-drug interactions. Potentially harmful drug-drug interactions were identified in about two-thirds (65%, 149/229) of the patients. The risk of occurrence drug interactions was significantly higher among patients who had at least six prescribed medicines (relative risk: 7.8 (95% confidence interval, 6.9 to 9.5) (P < 0.001)), and a significant majority were also females (73.8%) (110) (P < 0.001). The most frequent interacting drug combination was angiotensin-converting enzyme inhibitors and amiloride + hydrochlorothiazide (34.7%). Potentially harmful drug interactions that are significantly associated with high multiple prescribing are considerable among elderly patients in Nigeria.

A limited number of prescribed drugs account for the great majority of drug-drug interactions.

The purpose of this study was to investigate the prevalence of prescribed combinations of interacting drugs in the Swedish population. This study design was retrospective and cross-sectional, based on a national register of dispensed prescription drugs during the period from January 1 to April 30, 2010. Prescription data was linked to the drug-drug interaction database SFINX to yield the prevalence of interacting combinations dispensed in the population. The study focused in particular on C- (clinically relevant interactions that can be handled, e.g. by dose adjustments), and D-interactions (clinically relevant interactions that should be avoided). Thirty-eight and 3.8 % of the population were dispensed combinations of drugs classified as C- or D- interactions, respectively, i.e. clinically relevant, involving all therapeutic areas. Half of the D-interactions were associated with increased risk of adverse drug reactions whereas the other half were considered interactions with a potential to cause therapeutic failure. We identified a top 15 list of D-interactions that included 80 % of the total number of interacting drug combinations. Regarding individual drugs, a group of only ten drugs was involved in as much as 94 % of all D-interactions. This study reveals that the majority of prescribed interacting drug combinations in Sweden involve a limited number of drugs. The findings may increase the awareness among prescribers of these most common drug interactions in clinical practice and highlight an area for pharmacological education. It may also serve as an inventory of potential interactions within different therapeutic areas for further research.

A study of potential drug-drug interactions among hospitalized cardiac patients in a teaching hospital in Western Nepal.

Aim:Drug-drug interaction (DDI) is of major concern in patients with complex therapeutic regimens. The involvement of cardiovascular medicines in drug interaction is even higher. However, reports of DDI between these groups of drugs are few. The study aims to identify the potential DDI among hospitalized cardiac patients. Furthermore, we assessed the possible risk factors associated with these interactions.Subjects and Methods:The Type of study prospective observational study was conducted from May 2012 to August 2012 among hospitalized cardiac patients. Cardiac patients who were taking at least two drugs and who had a hospital stay of at least 24 h were enrolled. The medications of the patients were analyzed for possible interactions using the standard drug interaction database - Micromedex -2 (Thomson Reuters) × 2.0.Results:From a total of 150 enrolled patients, at least one interacting drug combination was identified among 32 patients. The incidence of potential DDI was 21.3%. A total of 48 potentially hazardous drug interactions were identified. Atorvastatin/azithromycin (10.4%), enalapril/metformin (10.4%), enalapril/potassium chloride (10.4%), atorvastatin/clarithromycin (8.3%) and furosemide/gentamicin (6.3%) were the most common interacting pairs. Drugs most commonly involved were atorvastatin, enalapril, digoxin, furosemide, clopidogrel and warfarin. Majority of interactions were of moderate severity (62.5%) and pharmacokinetic (58.3%) in nature. Increased number of medicines, prolonged hospital stays and comorbid conditions were the risk factors found associated with the potential DDI.Conclusions:This study highlighted the need of intense monitoring of patients who have identified risk factors to help detect and prevent them from serious health hazards associated with drug interactions.

Drug-drug interactions and their predictors: results from Indian elderly inpatients

In view of the multiple co-morbidities, the elderly patients receiving drugs are prone to suffer with drug interactions since they receive a greater number of drugs. The study was undertaken to determine the prevalence of drug interactions, as well as their predictors. The prescriptions of a total of 1510 inpatients were collected prospectively for 1.5 years from inpatients wards of public tertiary care teaching hospital. All the prescriptions were checked for drug interactions using the Micromedex® Drug-Reax database-2010 and Stockley's Drug Interactions. Regression analyses sought to determine predictors for the drug interaction. The patients, with the average age of 67.2 ±0.2 years, were prescribed an average of 9.15 ±0.03 medications. It was found that out of 1510 prescriptions of inpatients, 126 (8.3%) prescriptions had one or more than one drug interaction. All the identified interactions were severe in nature. The top most interacting drugs were acetylsalicylic acid and anticoagulant (n=59). The second top most interacting drug combination was clopidogrel and proton pump inhibitors (n=51). The most commonly involved drugs in interactions were C (cardiovascular system) and A (alimentary tract and metabolism). Using multivariate binary logistic regression, multiple drugs (Odds Ratio=4.5; 95% Confidence Interval: - 2.38 -9.47) and multiple diagnoses (Odds Ratio=2.6; 95%CI: -1.40 -5.57) were found to be significant predictors for drug interaction. The results of this study substantiate the occurrence of severe drug interactions among Indian elderly inpatients. In order to provide safer pharmaceutical care, the active involvement of clinical pharmacists is a potential option.

POSSIBLE TOXIC EFFECTS OF BENZODIAZEPINES;

Introduction: Benzodiazepines and its derivatives are used widely as anxiolytics, hypnotics, seizure control and as musclerelaxants. Design: The prescriptions of 270 patients were evaluated for moderate to severe drug interactions using drug interactiondetection software. Setting: Teaching hospital in Gujrat, Pakistan. Objective: This study is used to evaluate the possible toxic effects ofbenzodiazepine related drug-drug interactions in prescriptions of indoor patients. Material &amp; Methods: The prescriptions wereprocessed through a software program named, The Medical Letter Adverse Drug Interaction program. The randomly collected patientchart profiles included both male and female patients ranging from age of few months old children to old aged patients. Result: Out of 270patients medication charts 210 medication charts were having at least one or more drug interactions ranging from moderate to severe.Out of 80 interacting drug combinations found, 15 were benzodiazepine related drug interactions. So, percentage of benzodiazepinesrelated drug interactions was 18.75%.Moreover, the data also showed that the percentage of DDIs increases as the prescription sizeincreases. Our results indicate that hospitalized patients in Pakistan are at risk of ADRs caused by potential DDIs. Moreover, there arechances that the safe therapeutic doses of benzodiazepines may become toxic or ineffective due to drug-drug interactions andpolypharmacy. Conclusions: So, the use of DDIs detection software programs in hospitals and pharmacies should be promoted in orderto minimize drugs especially benzodiazepines related injuries and to ensure patient safety.

Prevalence of the Coprescription of Clinically Important Interacting Drug Combinations Involving Oral Anticancer Agents in Singapore: A Retrospective Database Study

BackgroundThere has been a recent increase in the availability and use of oral anticancer agents (OAAs). Drug–drug interactions (DDIs) involving OAAs pose a major concern in oncology practice due to these drugs' narrow therapeutic indices and potential for compromised efficacy and fatal adverse events. ObjectiveTo assess the prevalence of the coprescription of potentially interacting drug combinations involving OAAs in Singapore. MethodsA retrospective review of physicians' electronic prescription records between the years 2007 and 2009 was performed in the largest cancer center in Singapore. An overall prevalence rate of potential DDIs and a prevalence rate for each individual DDI pair were calculated. Logistic regression was used to identify risk factors for potential DDIs. ResultsFifty-eight clinically significant DDIs were selected for evaluation from Drug Interaction Facts and Micromedex DrugDex. A total of 39,772 OAA prescriptions prescribed to 8837 patients were reviewed. Potential DDI coprescription was found in 5.4% of the patients on OAAs and in 4.7% of the OAA prescriptions. The drug pair prescribed to the largest number of patients was prednisolone and aspirin. About half (53.3%) of the observed DDIs were found on the same prescription. On multivariate analysis, older patients, males, and those taking prednisolone had a higher risk for potential DDIs. ConclusionAlthough limited by the data available, the analysis of prescription records found that ∼5% of patients taking OAAs in Singapore were exposed to ≥1 potentially interacting drug combination.

Use of systemic antifungals in daily clinical practice in the haematology and oncology setting: results of a prospective observational analysis

To assess the role of systemic antifungal drugs as well as the frequency of potential drug interactions and adverse drug events of commonly used antifungals in an unselected haematology/oncology patient cohort. A prospective analysis was performed in our haematology/oncology department between October 2006 and September 2009. Data were obtained from 250 consecutive patients who received treatment and/or prophylaxis with fluconazole (n = 191), liposomal amphotericin B (n = 105), voriconazole (n = 62), caspofungin (n = 27) and/or posaconazole (n = 22). We performed detailed reviews of patient charts and laboratory values in close cooperation with treating physicians and nursing staff and participated regularly in ward and chart rounds. Potential drug interactions were assessed using the electronic database Micromedex® 1.0 (Healthcare Series). In terms of adverse drug events, caspofungin (56%) and voriconazole (58%) revealed a slightly more favourable safety profile than liposomal amphotericin B (66%) and posaconazole (64%). We confirmed frequent nephrotoxic effects with the use of liposomal amphotericin B (20%). Regarding potential drug interactions, 97 (66%) of 147 evaluated patients were exposed to at least 1 of 22 different potentially interacting drug combinations involving systemic antifungal agents. Cyclosporine was the most prevalent potentially interacting drug in our cohort. Systemic antifungal drugs are widely used in the haematology/oncology setting and exhibit numerous potential drug interactions and adverse events in cancer patients. Our results highlight the challenges related to antifungal drugs and should valuably contribute to a safe and efficient application of this increasingly important class of drugs.