Dataset Information

Reports of Symptoms Associated with Supraventricular Arrhythmias as a Serious Adverse Drug Reaction in the Spanish Pharmacovigilance Database.

ABSTRACT: This study aimed to determine the type of drugs reported as suspected of causing severe supraventricular arrhythmias from the Spanish Human Pharmacovigilance System database. A total of 1053 reports were analysed, of which 526 (50%) were on men and 516 (49%) were on women. The most affected age group was the over-65s, with 593 reports (56%). Of the 1613 drugs, those belonging to the cardiovascular system (ATC Group C) were the most numerous (414 reports, 26%), with digoxin being the most frequent drug (49 reports, 12%). Other common groups were antiinfectives for systemic use (ATC Group J; 306 reports, 19%), antineoplastic and immunomodulating agents (ATC Group L; 198 reports, 12%), and nervous system drugs (ATC Group N; 185 reports, 11%). The most common supraventricular arrhythmia was atrial fibrillation (561 reports, 51%). Regarding outcomes, 730 (66%) patients recovered, 76 (7%) did not recover, 25 (3%) recovered but with sequelae, and 23 (2%) resulted in death. This study revealed that certain drugs have reported to be associated more frequently to supraventricular arrhythmias as serious adverse reactions, especially in the older population. Proper clinical management and effective strategies to ensure medication appropriateness should always be considered to improve patient safety when prescribing drugs.

SUBMITTER: Pueyo-Val J

PROVIDER: S-EPMC10457936 | biostudies-literature | 2023 Aug

REPOSITORIES: biostudies-literature

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Reports of Symptoms Associated with Supraventricular Arrhythmias as a Serious Adverse Drug Reaction in the Spanish Pharmacovigilance Database.

Pueyo-Val Javier J Avedillo-Salas Ana A Berdún-Viñegra Pablo P Pueyo-Val Olga María OM Fanlo-Villacampa Ana A Navarro-Pemán Cristina C Lanuza-Giménez Francisco Javier FJ Ioakeim-Skoufa Ignatios I Vicente-Romero Jorge J

Pharmaceuticals (Basel, Switzerland) 20230815 8

This study aimed to determine the type of drugs reported as suspected of causing severe supraventricular arrhythmias from the Spanish Human Pharmacovigilance System database. A total of 1053 reports were analysed, of which 526 (50%) were on men and 516 (49%) were on women. The most affected age group was the over-65s, with 593 reports (56%). Of the 1613 drugs, those belonging to the cardiovascular system (ATC Group C) were the most numerous (414 reports, 26%), with digoxin being the most frequen ...[more]

PMID: 37631076

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Project description:BackgroundBenzimidazole derivatives are widely used anthelmintic drugs, particularly in mass campaigns for intestinal parasitosis treatment. Despite their generally good safety profile, serious adverse reactions have been reported. This study aims to identify potential pharmacovigilance signals for benzimidazole derivatives using disproportionality analysis in the WHO database.MethodologyA case/non-case study was conducted using data from the WHO VigiBase database (2000-2023). Cases were individual case safety reports (ICSRs) where at least one suspected serious adverse event of interest was reported, while non-cases were ICSRs reporting any adverse events other than the serious adverse events of interest. Reporting Odds Ratios (RORs) and 95% confidence intervals were calculated to assess disproportionate reporting. Analyses were adjusted for potential confounding factors and a sensitivity analysis with imputed missing data was performed.Principal findingsAmong 19,068 serious reports analyzed, significant disproportionality signals were found for benzimidazole derivatives compared to other anthelmintic drugs, notably for bone marrow failure and hypoplastic anemia (adjusted ROR 9.44 [5.01-18.9]), serious leukopenia (3.89 [2.64-5.76]), serious hepatic disorders (3.10 [2.59-3.71]), hepatitis (2.88, 95% CI 2.29-3.63) and serious urticaria (2.02, 95% CI 1.36-2.99). We have also highlighted a new signal not mentioned in the summaries of product characteristics for seizures with benzimidazole derivatives. Secondary analysis revealed these signals were primarily reported with albendazole.Conclusions/significanceThis study identified potential pharmacovigilance signals for serious hematological and hepatic adverse events for benzimidazole derivatives, particularly albendazole. New signal for benzimidazole derivatives has been described for seizures. These findings underscore the need for vigilant monitoring during benzimidazole derivatives use and warrant further pharmacoepidemiologic studies to confirm these signals and investigate underlying mechanisms.

Project description:IntroductionAdverse drug reaction reports are usually manually assessed by pharmacovigilance experts to detect safety signals associated with drugs. With the recent extension of reporting to patients and the emergence of mass media-related sanitary crises, adverse drug reaction reports currently frequently overwhelm pharmacovigilance networks. Artificial intelligence could help support the work of pharmacovigilance experts during such crises, by automatically coding reports, allowing them to prioritise or accelerate their manual assessment. After a previous study showing first results, we developed and compared state-of-the-art machine learning models using a larger nationwide dataset, aiming to automatically pre-code patients' adverse drug reaction reports.ObjectivesWe aimed to determine the best artificial intelligence model identifying adverse drug reactions and assessing seriousness in patients reports from the French national pharmacovigilance web portal.MethodsReports coded by 27 Pharmacovigilance Centres between March 2017 and December 2020 were selected (n = 11,633). For each report, the Portable Document Format form containing free-text information filled by the patient, and the corresponding encodings of adverse event symptoms (in Medical Dictionary for Regulatory Activities Preferred Terms) and seriousness were obtained. This encoding by experts was used as the reference to train and evaluate models, which contained input data processing and machine-learning natural language processing to learn and predict encodings. We developed and compared different approaches for data processing and classifiers. Performance was evaluated using receiver operating characteristic area under the curve (AUC), F-measure, sensitivity, specificity and positive predictive value. We used data from 26 Pharmacovigilance Centres for training and internal validation. External validation was performed using data from the remaining Pharmacovigilance Centres during the same period.ResultsInternal validation: for adverse drug reaction identification, Term Frequency-Inverse Document Frequency (TF-IDF) + Light Gradient Boosted Machine (LGBM) achieved an AUC of 0.97 and an F-measure of 0.80. The Cross-lingual Language Model (XLM) [transformer] obtained an AUC of 0.97 and an F-measure of 0.78. For seriousness assessment, FastText + LGBM achieved an AUC of 0.85 and an F-measure of 0.63. CamemBERT (transformer) + Light Gradient Boosted Machine obtained an AUC of 0.84 and an F-measure of 0.63. External validation for both adverse drug reaction identification and seriousness assessment tasks yielded consistent and robust results.ConclusionsOur artificial intelligence models showed promising performance to automatically code patient adverse drug reaction reports, with very similar results across approaches. Our system has been deployed by national health authorities in France since January 2021 to facilitate pharmacovigilance of COVID-19 vaccines. Further studies will be needed to validate the performance of the tool in real-life settings.

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Project description:Objective: Between 2012 and 2017, the U.S. Food and Drug Administration (FDA) approved 10 antidiabetic indicated therapies. Due to the limited literature on voluntarily reported safety outcomes for recently approved antidiabetic drugs, this study investigated adverse drug reactions (ADRs) reported in the FDA Adverse Event Reporting System (FAERS). Research Design and Methods: A disproportionality analysis of spontaneously reported ADRs was conducted. FAERS reports from January 1, 2012 to March 31, 2022 were compiled, allowing a 5-year buffer following drug approval in 2017. Reporting odds ratios were calculated for the top 10 ADRs, comparing new diabetic agents to the other approved drugs in their therapeutic class. Results: 127,525 reports were identified for newly approved antidiabetic medications listed as the primary suspect (PS). For sodium-glucose co-transporter-2 (SGLT-2) inhibitors, the odds of blood glucose increased, nausea, and dizziness being reported was greater for empagliflozin. Dapagliflozin was associated with greater reports of weight decreased. Canagliflozin was found to have a disproportionally higher number of reports for diabetic ketoacidosis, toe amputation, acute kidney injury, fungal infections, and osteomyelitis. Assessing glucagon-like peptide-1 (GLP-1) receptor agonists, dulaglutide and semaglutide were associated with greater reports of gastrointestinal adverse drug reactions. Exenatide was disproportionally associated with injection site reactions and pancreatic carcinoma reports. Conclusion: Pharmacovigilance studies utilizing a large publicly available dataset allow an essential opportunity to evaluate the safety profile of antidiabetic drugs utilized in clinical practice. Additional research is needed to evaluate these reported safety concerns for recently approved antidiabetic medications to determine causality. Plain language summary Adverse drug reactions reported for antidiabetic medications Introduction: This study investigated the trends in voluntary reporting of adverse drug reactions for recently approved antidiabetic medications. Methods: Data from the FDA Adverse Events Reporting System were evaluated. The top 10 adverse drug reactions were compared between antidiabetic medications in the same therapeutic class. Results: We identified 127,525 adverse drug reaction reports for the newer approved antidiabetic medications. For SGLT-2 inhibitors, empagliflozin was associated with greater reports of blood glucose increase, nausea, and dizziness; weight decreased was reported more often for dapagliflozin; and diabetic ketoacidosis, toe amputation, acute kidney injury, fungal infections, and osteomyelitis were reported more commonly for canagliflozin. Assessing GLP-1 receptor agonists, the odds of gastrointestinal adverse drug reactions being reported was greater for dulaglutide and semaglutide. Exenatide was disproportionally associated with injection site reactions and pancreatic carcinoma reports. Conclusion: Medication safety studies using a large publicly available dataset allows an essential opportunity to evaluate the safety profile of antidiabetic drugs in the real-world setting. Additional research is needed to determine if the reported safety concerns for recently approved antidiabetic medications to determine causality.

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Dataset Information

Reports of Symptoms Associated with Supraventricular Arrhythmias as a Serious Adverse Drug Reaction in the Spanish Pharmacovigilance Database.

Publications

Reports of Symptoms Associated with Supraventricular Arrhythmias as a Serious Adverse Drug Reaction in the Spanish Pharmacovigilance Database.

Similar Datasets

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