896 resultados para Adverse Drug Reactions
Resumo:
Objectives: To assess the extent of teaching about the Committee on Safety of Medicine's Yellow Card scheme and adverse drug reactions within UK Schools of Medicine and Pharmacy. Methods: A self-completed questionnaire sent to all heads of undergraduate schools of medicine and pharmacy within the UK. Results: The majority of undergraduate syllabuses feature the Yellow Card Scheme. Knowledge of the Yellow Card Scheme was assessed in 79% of pharmacy programmes and 57% of medical schools. Specialist speakers on the Yellow Card Scheme were infrequently used. Fewer than half of respondents provided students with a guide to reporting ADRs (43% pharmacy and 43% medical). There is some disagreement about the value of supplying students with printed material about the Yellow Card Scheme. Half of medical Schools did not think that supplying 'Current Problems In Pharmacovigilance' would be useful. Conclusions: It was found that in both medicine and pharmacy, courses differed substantially in teaching about the Yellow Card Scheme and adverse drug reactions (ADRs). There is scope for increased involvement of the Medicines and Healthcare products Regulatory Agency in undergraduate education, in line with recommendations from the National Audit Office.
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We study the problem of detecting sentences describing adverse drug reactions (ADRs) and frame the problem as binary classification. We investigate different neural network (NN) architectures for ADR classification. In particular, we propose two new neural network models, Convolutional Recurrent Neural Network (CRNN) by concatenating convolutional neural networks with recurrent neural networks, and Convolutional Neural Network with Attention (CNNA) by adding attention weights into convolutional neural networks. We evaluate various NN architectures on a Twitter dataset containing informal language and an Adverse Drug Effects (ADE) dataset constructed by sampling from MEDLINE case reports. Experimental results show that all the NN architectures outperform the traditional maximum entropy classifiers trained from n-grams with different weighting strategies considerably on both datasets. On the Twitter dataset, all the NN architectures perform similarly. But on the ADE dataset, CNN performs better than other more complex CNN variants. Nevertheless, CNNA allows the visualisation of attention weights of words when making classification decisions and hence is more appropriate for the extraction of word subsequences describing ADRs.
Resumo:
Observation of adverse drug reactions during drug development can cause closure of the whole programme. However, if association between the genotype and the risk of an adverse event is discovered, then it might suffice to exclude patients of certain genotypes from future recruitment. Various sequential and non-sequential procedures are available to identify an association between the whole genome, or at least a portion of it, and the incidence of adverse events. In this paper we start with a suspected association between the genotype and the risk of an adverse event and suppose that the genetic subgroups with elevated risk can be identified. Our focus is determination of whether the patients identified as being at risk should be excluded from further studies of the drug. We propose using a utility function to? determine the appropriate action, taking into account the relative costs of suffering an adverse reaction and of failing to alleviate the patient's disease. Two illustrative examples are presented, one comparing patients who suffer from an adverse event with contemporary patients who do not, and the other making use of a reference control group. We also illustrate two classification methods, LASSO and CART, for identifying patients at risk, but we stress that any appropriate classification method could be used in conjunction with the proposed utility function. Our emphasis is on determining the action to take rather than on providing definitive evidence of an association. Copyright (C) 2008 John Wiley & Sons, Ltd.
Resumo:
The accumulation of deficits with increasing age results in a decline in the functional capacity of multiple organs and systems. These changes can have a significant influence on the pharmacokinetics and pharmacodynamics of prescribed drugs. Although alterations in body composition and worsening renal clearance are important considerations, for most drugs the liver has the greatest effect on metabolism. Age-related change in hepatic function thereby causes much of the variability in older people’s responses to medication. In this review, we propose that a decline in the ability of the liver to inactivate toxins may contribute to a proinflammatory state in which frailty can develop. Since inflammation also downregulates drug metabolism, medication prescribed to frail older people in accordance with disease-specific guidelines may undergo reduced systemic clearance, leading to adverse drug reactions, further functional decline and increasing polypharmacy, exacerbating rather than ameliorating frailty status. We also describe how increasing chronological age and frailty status impact liver size, blood flow and protein binding and enzymes of drug metabolism. This is used to contextualise our discussion of appropriate prescribing practices. For example, while the general axiom of ‘start low, go slow’ should underpin the initiation of medication (titrating to a defined therapeutic goal), it is important to consider whether drug clearance is flow or capacity-limited. By summarising the effect of age-related changes in hepatic function on medications commonly used in older people, we aim to provide a guide that will have high clinical utility for practising geriatricians.
Resumo:
OBJECTIVES: To determine the extent to which the use of a clinical informatics tool that implements prospective monitoring plans reduces the incidence of potential delirium, falls, hospitalizations potentially due to adverse drug events, and mortality.
DESIGN: Randomized cluster trial.
SETTING: Twenty-five nursing homes serviced by two long-term care pharmacies.
PARTICIPANTS: Residents living in nursing homes during 2003 (1,711 in 12 intervention; 1,491 in 13 usual care) and 2004 (1,769 in 12 intervention; 1,552 in 13 usual care).
INTERVENTION: The pharmacy automatically generated Geriatric Risk Assessment MedGuide (GRAM) reports and automated monitoring plans for falls and delirium within 24 hours of admission or as part of the normal time frame of federally mandated drug regimen review.
MEASUREMENTS: Incidence of potential delirium, falls, hospitalizations potentially due to adverse drug events, and mortality.
RESULTS: GRAM triggered monitoring plans for 491 residents. Newly admitted residents in the intervention homes experienced a lower rate of potential delirium onset than those in usual care homes (adjusted hazard ratio (HR)=0.42, 95% confidence interval (CI)=0.35–0.52), overall hospitalization (adjusted HR=0.89, 95% CI=0.72–1.09), and mortality (adjusted HR=0.88, 95% CI=0.66–1.16). In longer stay residents, the effects of the intervention were attenuated, and all estimates included unity.
CONCLUSION: Using health information technology in long-term care pharmacies to identify residents who might benefit from the implementation of prospective medication monitoring care plans when complex medication regimens carry potential risks for falls and delirium may reduce adverse effects associated with appropriate medication use.
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Background: Previous studies have not demonstrated a consistent association between potentially inappropriate medicines (PIMs) in older patients as defined by Beers criteria and avoidable adverse drug events (ADEs). This study aimed to assess whether PIMs defined by new STOPP (Screening Tool of Older Persons’ potentially inappropriate Prescriptions) criteria are significantly associated with ADEs in older people with acute illness.
Methods: We prospectively studied 600 consecutive patients 65 years or older who were admitted with acute illness to a university teaching hospital over a 4-month interval. Potentially inappropriate medicines were defined by both Beers and STOPP criteria. Adverse drug events were defined by World Health Organization–Uppsala Monitoring Centre criteria and verified by a local expert consensus panel, which also assessed whether ADEs were causal or contributory to current hospitalization. Hallas criteria defined ADE avoidability.Wecompared the proportions of patients taking Beers criteria PIMs
and STOPP criteria PIMs with avoidable ADEs that were causal or contributory to admission.
Results: A total of 329 ADEs were detected in 158 of 600 patients (26.3%); 219 of 329 ADEs (66.6%) were considered causal or contributory to admission. Of the 219 ADEs, 151(68.9%)considered causal or contributory to admission were avoidable or potentially avoidable. After adjusting for age, sex, comorbidity, dementia, baseline activities of daily living function, and number of medications, the likelihood of a serious avoidable ADE increased significantly when STOPP PIMs were prescribed (odds ratio, 1.847; 95% confidence interval [CI], 1.506-2.264; P.001); prescription of Beers criteria PIMs did not significantly increase ADE risk (odds ratio, 1.276; 95% CI, 0.945-1.722; P=.11).
Conclusion: STOPP criteria PIMs,unlike Beers criteria PIMs, are significantly associated with avoidable ADEs in older people that cause or contribute to urgent hospitalization.
Resumo:
The aim of this study was to develop a predictive model for adverse drug events (ADEs) in elderly patients. Socio-demographic and medical data were collected from chart reviews, computerised information and a patient interview, for a population of 929 elderly patients (aged greater than or equal to 65 years) whose admission to the Waveney/B raid Valley Hospital in Northern Ireland was not scheduled. A further 204 patients formed a validation group. An ADE score was assigned to each patient using a modified Naranjo algorithm scoring system. The ADE scores ranged from 0 to 8. For the purposes of developing a risk model, scores of 4 or more were considered to constitute a high risk of an ADE.
Resumo:
OBJECTIVE - To assess drug reactions and report the drugs involved and the most frequent types of skin reactions.METHODS - A retrospective and descriptive study. Data of inpatients at the Dermatology Ward with initial diagnosis of adverse drug reactions were evaluated from January 1999 to June 2004. Patients with confirmed diagnosis were included in the study based on clinical and histopathological criteria, after analysis of medical charts.RESULTS - Initial diagnosis of adverse drug reactions was confirmed in 121 patients. Forty-three patients were included in the study; 51.2% were females and 86% were caucasians. A total of 48,8% were on one drug only. Antibiotics were the most commonly used drug (20%) and accounted for 33% of the drug eruptions. The second group comprised anti-inflammatory drugs (16 7%), followed by anticonvulsants (13%), analgesic/antipyretic (13%.) agents. Skin eruption manifested as maculopapular exanthema in 41.9% patients, erythrodermia in 25.6%, and urticaria in 23.3%.CONCLUSION - Maculopapular exanthema was the main type of skin reaction triggered by use of drugs, and these reactions were most frequently caused by antibiotics.
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OBJECTIVES: Drug safety problems can lead to hospital admission. In Brazil, the prevalence of hospitalization due to adverse drug events is unknown. This study aims to estimate the prevalence of hospitalization due to adverse drug events and to identify the drugs, the adverse drug events, and the risk factors associated with hospital admissions. METHOD: A cross-sectional study was performed in the internal medicine ward of a teaching hospital in São Paulo State, Brazil, from August to December 2008. All patients aged ≥18 years with a length of stay ≥24 hours were interviewed about the drugs used prior to hospital admission and their symptoms/complaints/causes of hospitalization. RESULTS: In total, 248 patients were considered eligible. The prevalence of hospitalization due to potential adverse drug events in the ward was 46.4%. Overprescribed drugs and those indicated for prophylactic treatments were frequently associated with possible adverse drug events. Frequently reported symptoms were breathlessness (15.2%), fatigue (12.3%), and chest pain (9.0%). Polypharmacy was a risk factor for the occurrence of possible adverse drug events. CONCLUSION: Possible adverse drug events led to hospitalization in a high-complexity hospital, mainly in polymedicated patients. The clinical outcomes of adverse drug events are nonspecific, which delays treatment, hinders causality analysis, and contributes to the underreporting of cases.
Resumo:
Objective: Identifying the main causes for underreporting of Adverse Drug Reaction (ADR) by health professionals. Method: A systematic review carried out in the following databases: LILACS, PAHO, SciELO, EMBASE and PubMed in the period between 1992 and 2012. Descriptors were used in the search for articles, and the identified causes of underreporting were analyzed according to the classification of Inman. Results: In total, were identified 149 articles, among which 29 were selected. Most studies were carried out in hospitals (24/29) for physicians (22/29), and pharmacists (10/29). The main causes related to underreporting were ignorance (24/29), insecurity (24/29) and indifference (23/29). Conclusion: The data show the eighth sin in underreporting, which is the lack of training in pharmacovigilance. Therefore, continuing education can increase adherence of professionals to the service and improve knowledge and communication of risks due to drug use.
Resumo:
Objective: Identifying the main causes for underreporting of Adverse Drug Reaction (ADR) by health professionals. Method: A systematic review carried out in the following databases: LILACS, PAHO, SciELO, EMBASE and PubMed in the period between 1992 and 2012. Descriptors were used in the search for articles, and the identified causes of underreporting were analyzed according to the classification of Inman. Results: In total, were identified 149 articles, among which 29 were selected. Most studies were carried out in hospitals (24/29) for physicians (22/29), and pharmacists (10/29). The main causes related to underreporting were ignorance (24/29), insecurity (24/29) and indifference (23/29). Conclusion: The data show the eighth sin in underreporting, which is the lack of training in pharmacovigilance. Therefore, continuing education can increase adherence of professionals to the service and improve knowledge and communication of risks due to drug use.