Abstract:Objectives:To identify and compare the prevalence of drug-drug interactions (DDIs) in the intensive cardiac care units (CCUs) of 2 tertiary care hospitals and analyze their association with various predictors.Methods:This one-year prospective cross-sectional study was conducted in 2 tertiary care hospitals of Peshawar, Khyber Teaching Hospital (KTH) and Hayatabad Medical Complex (HMC), Peshawar, Pakistan, between January 2014 to Janury 2015. The patient medication profiles from the respective CCUs were evaluat… Show more
“…Such results are similar to those of international research studies in the specialty of cardiology, which point to a frequency of serious interactions ranging from 30% to 86%, polypharmacy as a risk factor for interactions, and anticoagulants, antiplatelet agents, and statins as the main classes involved in interactions (19)(20)(21) .…”
Section: Discussionsupporting
confidence: 87%
“…In one, it was sought to identify drug-drug interactions in patients admitted to cardiac intensive care units in two tertiary hospitals in Pakistan, subsequently comparing the prevalence of these interactions. 260 patients from each hospital who had been hospitalized for at least 24 hours were included, most of them diagnosed with myocardial infarction (19) .…”
Section: Discussionmentioning
confidence: 99%
“…The drug pairs with the most frequent interactions were the follwoing: aspirin + clopidogrel, aspirin + enoxaparin, and clopidogrel + enoxaparin, all with increased risk of bleeding. The interactions were associated with the number of medications prescribed (19) .…”
Objective: To assess the occurrence of adverse drug reactions associated with potential serious drug interactions identified in prescriptions of hospitalized patients with cardiovascular disease. Method: A documentary, quantitative, and cross-sectional research study. Between August and September 2016, ninety-nine prescriptions of patients hospitalized for more than 48 hours in the cardiology ward of a hospital in Rio de Janeiro were analyzed. Drug interactions were evaluated by Micromedex®, and adverse events were identified through trackers and analyzed by specialists using the Naranjo Algorithm, by means of descriptive statistics. Results: Eighteen potential serious interactions were detected in 22 drug pairs, mainly simvastatin x anlodipine (18%) and enoxaparin x clopidogrel (18%). Of the 18 medical records investigated, four trackers were found and three probable adverse events (16.6%) were defined due to hemorrhagic changes in patients. Conclusion: Drug interactions are likely to cause harm to the patient, which requires implementing barriers for the safety of the medication system.
“…Such results are similar to those of international research studies in the specialty of cardiology, which point to a frequency of serious interactions ranging from 30% to 86%, polypharmacy as a risk factor for interactions, and anticoagulants, antiplatelet agents, and statins as the main classes involved in interactions (19)(20)(21) .…”
Section: Discussionsupporting
confidence: 87%
“…In one, it was sought to identify drug-drug interactions in patients admitted to cardiac intensive care units in two tertiary hospitals in Pakistan, subsequently comparing the prevalence of these interactions. 260 patients from each hospital who had been hospitalized for at least 24 hours were included, most of them diagnosed with myocardial infarction (19) .…”
Section: Discussionmentioning
confidence: 99%
“…The drug pairs with the most frequent interactions were the follwoing: aspirin + clopidogrel, aspirin + enoxaparin, and clopidogrel + enoxaparin, all with increased risk of bleeding. The interactions were associated with the number of medications prescribed (19) .…”
Objective: To assess the occurrence of adverse drug reactions associated with potential serious drug interactions identified in prescriptions of hospitalized patients with cardiovascular disease. Method: A documentary, quantitative, and cross-sectional research study. Between August and September 2016, ninety-nine prescriptions of patients hospitalized for more than 48 hours in the cardiology ward of a hospital in Rio de Janeiro were analyzed. Drug interactions were evaluated by Micromedex®, and adverse events were identified through trackers and analyzed by specialists using the Naranjo Algorithm, by means of descriptive statistics. Results: Eighteen potential serious interactions were detected in 22 drug pairs, mainly simvastatin x anlodipine (18%) and enoxaparin x clopidogrel (18%). Of the 18 medical records investigated, four trackers were found and three probable adverse events (16.6%) were defined due to hemorrhagic changes in patients. Conclusion: Drug interactions are likely to cause harm to the patient, which requires implementing barriers for the safety of the medication system.
“…We found no studies correlating the Brazilian system used to classify patients according to the degree of dependence on nursing with risk of pDDIs; however, previous studies have shown that critical care patients are at increased risk of pDDIs because they present with severe and life-threatening illnesses. Most of them suffer from various comorbidities, and they usually receive complex pharmacotherapy which increases the risk of DDIs [32,34–36].…”
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.
“…DDI avoidance in this population is critically important as fluctuations in drug concentrations and effects may be particularly harmful to ICU patients 7 . The prevalence of DDIs in intensive care units ranges from 27% to 95% [8][9][10][11] , depending on the ICU setting, study population, hospital's systems for DDI detection, and severity level that is considered a DDI.…”
Objective To determine the prevalence of clinically relevant drug-drug
interactions in an intensive care unit of a tertiary care hospital in
the United States and to compare to an intensive care unit at a
Pakistani hospital, which lacks electronic medical record-based
drug-drug interaction screening. Study setting A retrospective
cross-sectional analysis was conducted in the cardiovascular intensive
care unit (CVICU) at Michigan Medicine (MM), Ann Arbor, MI, USA between
Jan 2018 – Jan 2019. Study Design Analysis of 300 MM patients was
conducted to identify drug-drug interactions using Micromedex® and
Lexicomp®. Descriptive statistics and multivariate binary logistic
regression was used. Independent samples t-test was used to compare
prevalence between MM and in a similar cohort of patients in the cardiac
intensive care (CCU) at KTH, Pakistan from a previously published study.
Data Collection Data was collected for patients who were admitted to the
CVICU for at least 24 hours and were prescribed at least 2 drugs from
the electronic health record of MM. Principal Findings In the intensive
care unit of the US hospital, 58% of patients had at least one
drug-drug interaction, while 16% had a clinically relevant drug-drug
interaction. Significantly fewer patients had drug-drug interactions at
the US hospital than the Pakistani hospital (58% vs. 95%, p
< 0.01). Polypharmacy and length of stay increased drug-drug
interaction occurrence in the US hospital (p <0.01).
Conclusion The prevalence of drug-drug interactions in the intensive
care unit at the US hospital was high but lower than the Pakistani
hospital, likely due to electronic medical record-based screening.
Despite electronic medical record-based screening at the US hospital, 8
clinically relevant drug-drug interaction pairs were undetected.
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