Concerns over safety profiles of tumor necrosis factor (TNF)-alfa inhibitors have been raised. The purpose of this study was to clarify the adverse events associated with TNF-alfa inhibitors using a ...spontaneous reporting system database.
A retrospective pharmacovigilance disproportionality analysis was conducted using the Japanese Adverse Drug Event Report (JADER) database. Adverse event reports submitted to the Pharmaceuticals and Medical Devices Agency between 2004 and 2017 were analyzed, and the reporting odds ratio (ROR) and 95% confidence interval (CI) for each adverse event were calculated.
Among the 34,031 reports of adverse events associated with TNF-alfa inhibitors, 65.8% were women, who were frequently in their 60s (28.2%). Signals were detected for pneumonia (ROR, 5.36; 95% CI, 5.14-5.6), interstitial lung disease (ROR, 2.04; 95% CI, 1.95-2.15), pneumocystis jirovecii pneumonia (ROR, 11.8; 95% CI, 11.1-12.5), and herpes zoster (ROR, 6.4; 95% CI, 5.92-6.91) for TNF-alfa inhibitors as a class. There was variability in their signal strength across individual TNF-alfa inhibitors.
The strength of the associations of TNF-alfa inhibitors with adverse events is variable, and further studies are required to evaluate the identified signals.
Abstract
Background
Trends in prescribing for nursing home (NH) residents, which may have been influenced by the coronavirus disease 2019 (COVID-19) pandemic, have not been characterized.
Methods
...Long-term care pharmacy data from 1944 US NHs were used to evaluate trends in prescribing of antibiotics and drugs that were investigated for COVID-19 treatment, including hydroxychloroquine, famotidine, and dexamethasone. To account for seasonal variability in antibiotic prescribing and decreased NH occupancy during the pandemic, monthly prevalence of residents with a prescription dispensed per 1000 residents serviced was calculated from January to October and compared as relative percent change from 2019 to 2020.
Results
In April 2020, prescribing was significantly higher in NHs for drugs investigated for COVID-19 treatment than 2019; including hydroxychloroquine (+563%, 95% confidence interval CI: 5.87, 7.48) and azithromycin (+150%, 95% CI: 2.37, 2.63). Ceftriaxone prescribing also increased (+43%, 95% CI: 1.34, 1.54). Prescribing of dexamethasone was 36% lower in April (95% CI: .55, .73) and 303% higher in July (95% CI: 3.66, 4.45). Although azithromycin and ceftriaxone prescribing increased, total antibiotic prescribing among residents was lower from May (−5%, 95% CI: .94, .97) through October (−4%, 95% CI: .94, .97) in 2020 compared to 2019.
Conclusions
During the pandemic, large numbers of residents were prescribed drugs investigated for COVID-19 treatment, and an increase in prescribing of antibiotics commonly used for respiratory infections was observed. Prescribing of these drugs may increase the risk of adverse events, without providing clear benefits. Surveillance of NH prescribing practices is critical to evaluate concordance with guideline-recommended therapy and improve resident safety.
During the coronavirus disease 2019 (COVID-19) pandemic, there was a higher prevalence of nursing home residents with a prescription dispensed for drugs that were investigated for COVID-19 treatment and antibiotics commonly used for respiratory infections than in the previous year.
BACKGROUNDThe safety profile of biologic drugs might present substantial regional differences. Since 2009, the Brazilian Society of Rheumatology has maintained BIOBADABRASIL (Brazilian Registry for ...Biologic Drugs), a registry for monitoring of biologic therapies in rheumatic diseases.
OBJECTIVESThe aim of this study was to verify the incidence rate (IR) of serious infections in rheumatoid arthritis (RA) and spondyloarthritis (SpA) patients on biologic drugs.
METHODSBIOBADABRASIL prospectively included patients with rheumatic diseases who started the first biologic drug or a synthetic disease-modifying antirheumatic drug as a parallel control group. This study focuses on serious infectious adverse events (SIAEs) in RA and SpA patients on biologic drugs compared with controls, from January 2009 to June 2015. Time of exposure was set from initiation of the drug to the date of last administration or censorship. Serious infectious adverse events IR was calculated per 1000 patient/years with 95% confidence interval (CI).
RESULTSA total of 1698 patients (RA, 1121; SpA, 577) were included, 7119 patient/years. Serious infectious adverse events were more common among patients on tumor necrosis factor inhibitors (TNFiʼs) than controls (adjusted IR ratio, 2.96 95% CI, 2.01–4.36; p < 0.001). Subsequent TNFi was associated with a higher SIAEs incidence when compared with first TNFI (adjusted IR ratio, 1.55 95% CI, 1.15–2.08; p = 0.004). Serious infectious adverse events were associated with age and corticosteroids intake. Serious infectious adverse events were more frequent in the respiratory tract in all subgroups.
CONCLUSIONSIn BIOBADABRASIL, biologic drugs, especially the subsequent TNFi, were associated with a higher risk of serious infections compared with synthetic DMARDs. Corticosteroid intake and age represented risk factors for SIAEs. Constant monitoring is required to follow the safety profile of drugs in the clinical setting of rheumatic conditions in Brazil.
Introduction: Drug abuses have become an important part of the emergency service admissions. As a result of MDMA (3,4-methylenedioxy-methamphetamine) intake, various side effects may occur; from ...minor to major conditions. After using cannabis alone is cardiovascular symptoms, respiratory symptoms, nausea/vomiting and neurological symptoms. We presented the MDMA and cannabis intake case which resulted in multiple major adverse events and death in the emergency department.Case report: A nineteen-year-old male patient was brought to the emergency department with generalized tonic-clonic seizure. On admission, the patient had hypoglycemia and his urine was positive for cannabis and amphetamine. Liver, renal failure, DIC and methemoglobinemia developed. Although he received noradrenaline and dopamine infusion due to hypotension, his hypotension deepened. During the follow-up, cardiac arrest developed and after 30 minutes of cardiopulmonary resuscitation, death was accepted.Discussion: It is a phenomenon in which severe side effects occur after intake of MDMA and cannabis and result in death. MDMA is inhibited by the CYP2D6 enzyme and is excreted renally. The presence of drugs that inhibit this enzyme, the development of kidney failure, and the genetic polymorphism of the enzyme may cause these effects.Conclusion: The use of street drugs can cause death with many serious side effects.
To better monitor patients on outpatient parenteral antimicrobial therapy (OPAT), we need an improved understanding of risk factors for and timing of OPAT-associated adverse drug events (ADEs).
We ...analyzed a prospective cohort of patients on OPAT discharged from 2 academic medical centers. Patients underwent chart abstraction and a telephone survey. Multivariable analyses estimated adjusted incident rate ratios (aIRR) between clinical and demographic risk factors and clinician-determined clinically significant ADEs. Descriptive data were used to present patient-reported ADEs.
Of 339 patients enrolled in the study, 18.0% experienced an ADE (N = 65), of which 49 were significant (14.5%, 2.24/1000 home-OPAT days). Patients with longer courses of therapy had lower rates of ADEs compared with patients treated for 0-13 days (14-27 days: aIRR, 0.44; 95% confidence interval CI, 0.20-0.99; at least 28 days: aIRR, 0.11; 95% CI, 0.056-0.21). Risk factors for ADEs included female gender and receipt of daptomycin or vancomycin, while treatment for uncomplicated bacteremia and empiric treatment were associated with lower rates of ADEs.
OPAT-related ADEs were common and often occurred within 2 weeks of hospital discharge. Patients on OPAT should be monitored more closely for ADEs, including clinical assessment and laboratory monitoring, especially within the first weeks after hospital discharge and particularly among women and patients who receive vancomycin.
Aims
Medication harm has negative clinical and economic consequences, contributing to hospitalisation, morbidity and mortality. The incidence ranges from 4 to 14%, of which up to 50% of events may be ...preventable. A predictive model for identifying high‐risk inpatients can guide a timely and systematic approach to prioritisation. The aim of this study is to develop and internally validate a risk prediction model for prioritisation of hospitalised patients at risk of medication harm.
Methods
A retrospective cohort study was conducted in general medical and geriatric specialties at an Australian hospital over six months. Medication harm was identified using International Classification of Disease (ICD‐10) codes and the hospital's incident database. Sixty‐eight variables, including medications and laboratory results, were extracted from the hospital's databases. Multivariable logistic regression was used to develop the final risk model. Performance was evaluated using area under the receiver operative characteristic curve (AuROC) and clinical utility was determined using decision curve analysis.
Results
The study cohort included 1982 patients with median age 74 years, of which 136 (7%) experienced at least one adverse medication event(s). The model included: length of stay, hospital re‐admission within 12 months, venous or arterial thrombosis and/or embolism, ≥ 8 medications, serum sodium < 126 mmol/L, INR > 3, anti‐psychotic, antiarrhythmic and immunosuppressant medications, and history of medication allergy. Validation gave an AuROC of 0.70 (95% CI: 0.65–0.74). Decision curve analysis identified that the AIME may be clinically useful to help guide decision making in practice.
Conclusion
We have developed a predictive model with reasonable performance. Future steps include external validation and impact evaluation.
Abstract
Aims
It is Class I recommendation that congenital long QT syndrome (cLQTS) patients should avoid drugs that can cause torsades de pointes (TdP). We determined use of TdP risk drugs after ...cLQTS diagnosis and associated risk of ventricular arrhythmia and all-cause mortality.
Methods and results
Congenital long QT syndrome patients (1995–2015) were identified from four inherited cardiac disease clinics in Denmark. Individual-level linkage of nation-wide registries was performed to determine TdP risk drugs usage (www.crediblemeds.org) and associated risk of ventricular arrhythmias and all-cause mortality. Risk analyses were performed using Cox-hazards analyses. During follow-up, 167/279 (60%) cLQTS patients were treated with a TdP risk drug after diagnosis. Most common TdP risk drugs were antibiotics (34.1%), proton-pump inhibitors (15.0%), antidepressants (12.0%), and antifungals (10.2%). Treatment with a TdP risk drug decreased 1 year after diagnosis compared with 1 year before (28.4% and 23.2%, respectively, P < 0.001). Five years after diagnosis, 33.5% were in treatment (P < 0.001). Risk factors for TdP risk drug treatment were age at diagnosis (5-year increment) hazard ratio (HR) = 1.07, confidence interval (CI) 1.03–1.11 and previous TdP risk drug treatment (HR = 2.57, CI 1.83–3.61). During follow-up, nine patients were admitted with ventricular arrhythmia (three were in treatment with a TdP risk drug). Eight patients died (four were in treatment with a TdP risk drug). No significant association between TdP risk drug use and ventricular arrhythmias or all-cause mortality was found (P = 0.53 and P = 0.93, respectively), but events were few.
Conclusion
Torsades de pointes risk drug usage was common among cLQTS patients after time of diagnosis and increased over time. A critical need for more awareness in prescribing patterns for this high-risk patient group is needed.
Abstract
Objective
Identification of drugs, associated medication entities, and interactions among them are crucial to prevent unwanted effects of drug therapy, known as adverse drug events. This ...article describes our participation to the n2c2 shared-task in extracting relations between medication-related entities in electronic health records.
Materials and Methods
We proposed an ensemble approach for relation extraction and classification between drugs and medication-related entities. We incorporated state-of-the-art named-entity recognition (NER) models based on bidirectional long short-term memory (BiLSTM) networks and conditional random fields (CRF) for end-to-end extraction. We additionally developed separate models for intra- and inter-sentence relation extraction and combined them using an ensemble method. The intra-sentence models rely on bidirectional long short-term memory networks and attention mechanisms and are able to capture dependencies between multiple related pairs in the same sentence. For the inter-sentence relations, we adopted a neural architecture that utilizes the Transformer network to improve performance in longer sequences.
Results
Our team ranked third with a micro-averaged F1 score of 94.72% and 87.65% for relation and end-to-end relation extraction, respectively (Tracks 2 and 3). Our ensemble effectively takes advantages from our proposed models. Analysis of the reported results indicated that our proposed approach is more generalizable than the top-performing system, which employs additional training data- and corpus-driven processing techniques.
Conclusions
We proposed a relation extraction system to identify relations between drugs and medication-related entities. The proposed approach is independent of external syntactic tools. Analysis showed that by using latent Drug-Drug interactions we were able to significantly improve the performance of non–Drug-Drug pairs in EHRs.
This study aims to analysis adverse drug events (ADE) related to Brexpiprazole from the third quarter of 2015 to the first quarter of 2023 from FAERS database.
The ADE data related to Brexpiprazole ...from 2015 Q3 to 2023 Q1 were collected. After standardizing the data, a variety of signal quantification techniques, including ROR, PRR, BCPNN, and MGPS were used for analysis.
Among the 8559 ADE reports with Brexpiprazole as the primary suspected drug, 178 preferred terms (PT) of adverse reactions spanning 27 different system organ classes (SOC) were identified. Specifically, Metabolism and nutrition disorders and Reproductive system and breast disorders were unique adverse reactions to Brexpiprazole, with the latter not mentioned in the official drug label. Moreover, uncommon but significantly strong ADE signals, such as Egocentrism, Pharmacophobia, and Compulsions were observed. Notably, Tardive dyskinesia (n = 317, ROR 103.87, PRR 102.21, IC 6.21, EBGM 96.17) and Extrapyramidal disorder (n = 104, ROR 31.17, PRR 31.00, IC 4.57, EBGM 30.44) exhibited relatively high occurrence rates and signal strengths. Additionally, Lactation disorder (n = 6, ROR 48.09, PRR 48.07, IC 2.63, EBGM 46.71) and Breast discharge (n = 10, ROR 23.18, PRR 23.17, IC 2.94, EBGM 22.86) were observed, both presenting strong ADE signals.
Brexpiprazole poses risks of various adverse reactions while providing therapeutic effects. In clinical applications, practitioners should closely monitor occurrences of Psychiatric disorders, Metabolism and nutrition disorders, Reproductive system and breast disorders, and other events.
This work describes the Medication and Adverse Drug Events from Electronic Health Records (MADE 1.0) corpus and provides an overview of the MADE 1.0 2018 challenge for extracting medication, ...indication, and adverse drug events (ADEs) from electronic health record (EHR) notes.
The goal of MADE is to provide a set of common evaluation tasks to assess the state of the art for natural language processing (NLP) systems applied to EHRs supporting drug safety surveillance and pharmacovigilance. We also provide benchmarks on the MADE dataset using the system submissions received in the MADE 2018 challenge.
The MADE 1.0 challenge has released an expert-annotated cohort of medication and ADE information comprising 1089 fully de-identified longitudinal EHR notes from 21 randomly selected patients with cancer at the University of Massachusetts Memorial Hospital. Using this cohort as a benchmark, the MADE 1.0 challenge designed three shared NLP tasks. The named entity recognition (NER) task identifies medications and their attributes (dosage, route, duration, and frequency), indications, ADEs, and severity. The relation identification (RI) task identifies relations between the named entities: medication-indication, medication-ADE, and attribute relations. The third shared task (NER-RI) evaluates NLP models that perform the NER and RI tasks jointly. In total, 11 teams from four countries participated in at least one of the three shared tasks, and 41 system submissions were received in total.
The best systems F
scores for NER, RI, and NER-RI were 0.82, 0.86, and 0.61, respectively. Ensemble classifiers using the team submissions improved the performance further, with an F
score of 0.85, 0.87, and 0.66 for the three tasks, respectively.
MADE results show that recent progress in NLP has led to remarkable improvements in NER and RI tasks for the clinical domain. However, some room for improvement remains, particularly in the NER-RI task.
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