Adverse Drug Events Research Articles

Multidrug resistant tuberculosis risk factors in Makassar, Indonesia

Multidrug resistant tuberculosis (MDR-TB) is a significant public health concern in Indonesia, resulting in substantial morbidity and mortality rates. This study aimed to quantify the impact of risk factors of MDR-TB. A case-control study was conducted at Makassar Community Lung Health Center (BBKPM) in Makassar City. A total of 132 respondents, 66 cases, and 66 controls have participated in the study. Data was analyzed using the Stata version 14 tool, odds ratio (OR), and multiple logistic regression. Multiple logistic regression analysis identified significant risk factors for the occurrence of MDR-TB include previous TB treatment (OR=8.46, 95% CI: 3.278-21.858), positive acid-fast bacilli (AFB) sputum (OR=6.40, 95% CI: 2.525-16.260), and adverse drug event (OR=3.45, 95% CI: 1.008-11.867). The probability of developing MDR-TB is 95.9% if there is previous TB treatment with cases of relapse/loss to follow-up/failed treatment, positive AFB sputum, and adverse drug event. The most dominant risk factor for the occurrence of MDR-TB is a previous TB treatment. We suggest that an efficient directly observed treatment shortcourse (DOTS) strategy, particularly in the management of adverse drug event, overseeing and supporting patients who have recovered from MDR-TB, involves the collaboration of MDR-TB healthcare professionals and patient supporters in the Yamali TB community, moving synergistically as an effort to MDR-TB control and prevention.

MultiADE: A Multi-domain benchmark for Adverse Drug Event extraction

Objective:Active adverse event surveillance monitors Adverse Drug Events (ADE) from different data sources, such as electronic health records, medical literature, social media and search engine logs. Over the years, many datasets have been created, and shared tasks have been organised to facilitate active adverse event surveillance. However, most—if not all—datasets or shared tasks focus on extracting ADEs from a particular type of text. Domain generalisation—the ability of a machine learning model to perform well on new, unseen domains (text types)—is under-explored. Given the rapid advancements in natural language processing, one unanswered question is how far we are from having a single ADE extraction model that is effective on various types of text, such as scientific literature and social media posts. Methods:We contribute to answering this question by building a multi-domain benchmark for adverse drug event extraction, which we named MultiADE. The new benchmark comprises several existing datasets sampled from different text types and our newly created dataset—CADECv2, which is an extension of CADEC (Karimi et al., 2015), covering online posts regarding more diverse drugs than CADEC. Our new dataset is carefully annotated by human annotators following detailed annotation guidelines. Conclusion:Our benchmark results show that the generalisation of the trained models is far from perfect, making it infeasible to be deployed to process different types of text. In addition, although intermediate transfer learning is a promising approach to utilising existing resources, further investigation is needed on methods of domain adaptation, particularly cost-effective methods to select useful training instances.The newly created CADECv2 and the scripts for building the benchmark are publicly available at CSIRO’s Data Portal (https://data.csiro.au/collection/csiro:62387). These resources enable the research community to further information extraction, leading to more effective active adverse drug event surveillance.

Adverse event profiles of drug-induced decreased libido: an assessment of the US food and drug administration adverse event reporting system

ABSTRACT Background Drug-induced decreased libido significantly affects the quality of life and relationships of patients. However, no comprehensive study has examined the relationship between drugs and libido. This study assessed drug-induced decreased libido by mining data from the US Food and Drug Administration Adverse Event Reporting System (FAERS). Research Design and Methods Adverse drug event (ADE) reports from the first quarter of 2004 to the fourth quarter of 2023 in FAERS were collected and screened for reports of decreased libido and were subjected to medication signal mining by using the disproportionality analysis. Results Overall 10,773 ADE reports were obtained. Thirty-three of the top 50 drugs with the highest frequency of ADE reports did not mention the risk of reduced libido in their instructions. Fifty-eight drugs showed potential decreased libido risk based on the disproportionality analysis, with 40 of the drugs not mentioning the risk of reduced libido in their instructions. Of these 40 drugs, drugs used in genito urinary and sex hormones and nervous system were the drug class with the greatest number of ADE reports. Conclusion A data mining exercise using FAERS for drugs that cause decreased libido has identified 40 drugs with new signals of adverse effects that should be closely monitored in medical practice.

Risk prediction models for adverse drug reactions and adverse drug events in older adults—a systematic review and meta-analysis

Risk prediction models for adverse drug reactions and adverse drug events in older adults—a systematic review and meta-analysis

Use of potentially inappropriate psychotropic medicines among older adults in 23 residential aged care facilities in Australia: a retrospective cohort study.

Psychotropic medications are frequently utilised in residential aged care facilities (RACFs). Longitudinal medication administration data can offer crucial insights into the potential inappropriate use of psychotropic medicines (PIPMs), guiding future quality improvement initiatives. This study aimed to determine the prevalence and predictors of PIPMs use and assess variation in PIPMs use by facility for residents of RACFs. We conducted a retrospective longitudinal cohort study using routinely collected electronic health data (2020-2021) relating to 3064 residents from 23 RACFs in New South Wales, Australia. The study included permanent residents aged ≥ 65 years and median length of stay was 483 days. The prevalence of PIPMs use was estimated using updated Beers criteria 2023. The extent of exposure to PIPMs was measured using two metrics i.e., number of days residents were exposed to PIPMs and the proportion of days covered by PIPMs. We used logistic regression model to determine factors associated with PIPM use. Funnel plots to visualised variation in PIPMs use across facilities. In total 40% (n = 1224) residents used at least one PIPM and 10% (n = 302) used ≥ 2. The most frequently used PIPMs categories were benzodiazepines and Z-drugs (27.4%), followed by first and second generation antipsychotics (17.2%). Certain diagnoses (dementia, pain, depression, anxiety, and endocrine disorders) were associated with the increased use of PIPMs. For example, residents with dementia were 1.94 times more likely to use ≥ 2 PIPMs (OR 1.94; 95% CI 1.50-2.51). The prevalence of at least one PIPM by residents in each facility ranged from 23.3 to 57.0% across facilities. The overall median number of days residents were exposed to PIPMs were 91 days (IQR 6-320) while the median proportion of days covered by at least one PIPM was 39.3% (IQR 2.6-86.6%). Residents in aged care facilities showed a high rate of PIPMs use with substantial variation across facilities. Quality improvement initiatives which target inappropriate psychotropic medication use are necessary, particularly considering the link between psychotropic drug use and adverse events such as falls.

Potential Adverse Drug Events Identified with Decision Support Algorithms from Janusmed Risk Profile—A Retrospective Population-Based Study in a Swedish Region

Adverse drug events (ADEs) occur frequently and are a common cause of suffering, hospitalizations, or death, and can be caused by harmful combinations of medications. One method used to prevent ADEs is by using clinical decision support systems (CDSSs). Janusmed Risk Profile is a CDSS evaluating the risk for nine common or serious ADEs resulting from combined pharmacodynamic effects. The aim of this study was to examine the prevalence of potential ADEs identified using CDSS algorithms from Janusmed Risk Profile. This retrospective, cross-sectional study covered the population of a Swedish region (n = 246,010 inhabitants in year 2020) using data on all medications dispensed and administered. More than 20% of patients had an increased risk of bleeding, constipation, orthostatism, or renal toxicity based on their medications. The proportion of patients with an increased risk varied from 3.5% to almost 30% across the nine categories of ADEs. A higher age was associated with an increased risk of potential ADEs and there were gender differences. A cluster analysis identified groups of patients with an increased risk for several categories of ADEs. This study shows that combinations of medications that could increase the risk of ADEs are common. Future studies should examine how this correlates with observed ADEs.

Real-world research on beta-blocker usage trends in China and safety exploration based on the FDA Adverse Event Reporting System (FAERS).

Beta-blockers are widely used, with continuously updated clinical recommendations. However, their application faces challenges in personalized treatment and safety. The study aimed to investigate the frequency and patterns of prescribing beta-blockers in China and to explore potential adverse event risk signals associated with beta-blockers, providing reference for rational medication use in clinical settings. Prescription data for beta-blockers from January 2018 to June 2023 were extracted through the Hospital Prescription Analysis Collaborative Project in China to analyze clinical usage trends. While adverse drug reaction reports for beta-blockers were obtained from the FDA Adverse Event Reporting System (FAERS) database. The classification and standardization of adverse drug event (ADE) reports were based on the preferred terms (PT) and corresponding system organ classes (SOC) from the Medical Dictionary for Regulatory Activities (MedDRA). Signal detection utilized a proportion imbalance method. In clinical practice, metoprolol dominated beta-blocker prescriptions in China, accounting for 62.2%. Beta-blockers were primarily prescribed to the elderly (65.7%) and male patients (57.0%). However, off-label use of beta-blockers was relatively widespread. For instance, sotalol was prescribed for hypertension at 18.25%, while esmolol was used for angina and heart failure at rates of 12.94% and 14.98%, respectively. In addition, we identified newly discovered adverse reactions associated with beta-blockers, such as BRASH syndrome (metoprolol: n = 186, ROR = 391.285; carvedilol: n = 72, ROR = 256.459), acute kidney injury (bisoprolol: n = 247, ROR = 5.641), premature baby (labetalol: n = 110, ROR = 91.385), and sleep disorder (propranolol: n = 254, ROR = 10.98). Metoprolol led the beta-blocker market in China. Attention was warranted regarding the newly discovered adverse reactions, such as the risk of acute kidney injury with bisoprolol and the potential for BRASH syndrome with metoprolol and carvedilol.

Safety of inpatient care in surgical settings: cohort study

ObjectivesTo estimate the frequency, severity, and preventability of adverse events associated with perioperative care, and to describe the setting and professions concerned.DesignMulticenter retrospective cohort study.Setting11 US hospitals.Participants1009 patients from a...

Translation and Adaptation of the STOPP/START Criteria Version 3 for Potentially Inappropriate Prescribing in Older People to European Portuguese: A Study Protocol.

As the global population ages, managing medication use in older adults becomes increasingly complex due to polypharmacy and the associated risks of adverse drug events. To improve the safety and appropriateness of medication use in the older population, tools like the Screening Tool of Older Persons' Prescriptions (STOPP) and Screening Tool to Alert doctors to Right Treatment (START) criteria have been developed. The availability of updated criteria is crucial to better support healthcare professionals in Portuguese-speaking regions. The aim of this study is to translate and validate the STOPP/START version 3 criteria for Portuguese, providing an updated and useful tool for healthcare professionals. This study will be conducted through four phases: I) translation of the STOPP/START version 3 criteria to European Portuguese; II) collection of sociodemographic, clinical, and medication data; III) intrarater reliability study; and IV) interrater agreement study. This study obtained ethics approval by the Ethics Committee of the Administração Regional de Saúde do Centro, Portugal. The availability of the translated criteria will enable the integration of STOPP/START version 3 into clinical practice in Portugal, facilitating improved medication safety and appropriateness. This integration is expected to lead to better management of polypharmacy and a reduction in adverse drug events, ultimately enhancing patient outcomes and supporting evidence-based prescribing practices.

Integrating electronic health records with other data sources for postmarket drug safety signal identification: a review

Electronic health records (EHRs) have emerged as resources for both the identification of adverse drug events (ADEs) and general population health surveillance, however questions remain around how best to utilize EHR data for drug safety signal identification. While the majority of signal identification research has utilized spontaneous reports and health insurance claims, these data also have limitations. Pharmacovigilance approaches combining EHR data with other data sources have the potential to address many of the shortcomings of individual sources. This mini-review seeks to provide an overview of some of the recent research leveraging EHR data in combination with spontaneous reports, claims data, and other pharmacovigilance data sources for drug safety signal identification. Studies have shown that combining EHR data with these and other sources is often beneficial compared to the use of a single source alone, however the synergism or friction introduced is insufficiently explored in current literature. Our review explores how EHR data benefits signal identification when used in combination with other sources, what methods have been applied, and what considerations have previously been noted. Finally, we identify gaps in current research and highlight important considerations for future work using multiple real world data sources for drug safety surveillance.

Predicting adverse drug event using machine learning based on electronic health records: a systematic review and meta-analysis

IntroductionAdverse drug events (ADEs) pose a significant challenge in current clinical practice. Machine learning (ML) has been increasingly used to predict specific ADEs using electronic health record (EHR) data. This systematic review provides a comprehensive overview of the application of ML in predicting specific ADEs based on EHR data.MethodsA systematic search of PubMed, Web of Science, Embase, and IEEE Xplore was conducted to identify relevant articles published from the inception to 20 May 2024. Studies that developed ML models for predicting specific ADEs or ADEs associated with particular drugs were included using EHR data.ResultsA total of 59 studies met the inclusion criteria, covering 15 drugs and 15 ADEs. In total, 38 machine learning algorithms were reported, with random forest (RF) being the most frequently used, followed by support vector machine (SVM), eXtreme gradient boosting (XGBoost), decision tree (DT), and light gradient boosting machine (LightGBM). The performance of the ML models was generally strong, with an average area under the curve (AUC) of 76.68% ± 10.73, accuracy of 76.00% ± 11.26, precision of 60.13% ± 24.81, sensitivity of 62.35% ± 20.19, specificity of 75.13% ± 16.60, and an F1 score of 52.60% ± 21.10. The combined sensitivity, specificity, diagnostic odds ratio (DOR), and AUC from the summary receiver operating characteristic (SROC) curve using a random effects model were 0.65 (95% CI: 0.65–0.66), 0.89 (95% CI: 0.89–0.90), 12.11 (95% CI: 8.17–17.95), and 0.8069, respectively. The risk factors associated with different drugs and ADEs varied.DiscussionFuture research should focus on improving standardization, conducting multicenter studies that incorporate diverse data types, and evaluating the impact of artificial intelligence predictive models in real-world clinical settings.Systematic Review Registrationhttps://www.crd.york.ac.uk/prospero/display_record.php?ID=CRD42024565842, identifier CRD42024565842.

A Pharmacovigilance Study on Psychotropic Agent-Induced Urinary Retention Using the Japanese Adverse Drug Event Report Database.

Psychotropic drugs have been reported to cause urinary retention (UR) via anticholinergic and other mechanisms. However, UR has not received much attention because of its non-fatal symptoms. We investigated the occurrence of UR associated with psychotropic drugs using the Japanese Adverse Drug Event Report (JADER) database. Using the JADER database, we calculated reporting odds ratios for UR for 74 psychotropic drugs. Multivariate logistic regression analysis was used to adjust for the effects of sex, underlying disease, and age on UR. Variable selection included forced entry for sex, age, benign prostatic hyperplasia (BPH), depression, and backward-forward stepwise selection for each drug. A total of 887,704 cases were reported, of which 4653 (0.52%) had UR. In terms of sex, 0.79% (3401/429,372 cases) and 0.43% (1797/415,358 cases) of male and female patients had UR. In terms of age, 0.31% (892/288,676 cases) and 0.68% (3463/506,907 cases) of patients aged < 60 years and 60 years or older had UR. Among the underlying diseases, 8.22% (930/11,316 cases) and 0.43% (3723/876,388 cases) of patients with BPH and without BPH had UR, respectively. Further, 1.99% (337/16,959 cases) and 0.50% (4316/870,745 cases) of patients with depression and without depression had UR, respectively. Overall, 38 psychotropic drugs met the criteria for signal detection. In logistic regression, a total of 783,083 patients of discernible age and sex were included. The selected variables were sex, age, BPH, depression, and 23 drugs, including quetiapine [adjusted reporting odds ratio (ROR) 95% confidence interval (CI): 1.46-2.81], chlorpromazine (adjusted ROR 95%CI: 1.29-3.13), etizolam (adjusted ROR 95%CI: 1.47-3.09), maprotiline (adjusted ROR 95%CI: 1.99-8.34), mirtazapine (adjusted ROR 95%CI: 1.37-2.88), and duloxetine (adjusted ROR 95%CI: 2.15-4.21). Many psychotropic drugs induce UR, which may be owing to their pharmacological effects. Appropriate monitoring is needed, especially in patients with other risk factors for UR.

Evaluation of pitolisant, sodium oxybate, solriamfetol, and modafinil for the management of narcolepsy: a retrospective analysis of the FAERS database

ObjectiveNarcolepsy, a rare neurological disorder believed to have an autoimmune etiology, necessitates lifelong management. This study aimed to provide evidence supporting the safety of pharmacological treatment for narcolepsy.MethodsFive-year data on pitolisant, sodium oxybate, solriamfetol, and modafinil were extracted from the FDA Adverse Event Reporting System (FAERS) self-reporting database for the period spanning from 2019 to 2023. Various statistical methods, including the reporting odds ratio (ROR), proportional reporting ratio (PRR), Bayesian confidence propagation neural network analysis (BCPNN), and multi-item gamma Poisson shrinker (MGPS), were employed to quantify the signals. Finally, a comparative analysis was conducted between demographic data, outcomes, and inherent associations among the medications and the signals.ResultsAfter data analysis, we obtained 50 signals (a cumulative count of 762 cases) for pitolisant, 640 signals (corresponding to 46,962 cases) for sodium oxybate, 40 signals (equivalent to 1,228 cases) for solriamfetol, and finally, 72 signals (representing 632 cases) for modafinil. The majority of these patients were female. Psychiatric and nervous system disorders were identified as the predominant adverse drug events (ADEs). For sodium oxybate, it is crucial to consider psychiatric disorders (such as suicidal ideation), respiratory disorders (including sleep apnea syndrome and respiratory depression), and signs of pregnancy and congenital familial diseases. For solriamfetol, noteworthy new ADEs include drug inefficacy, suicidal ideation, restless legs syndrome, and somnambulism. Furthermore, a relationship has been observed between modafinil use and restricted fetal growth, spontaneous abortion, cognitive disorders, and drug inefficacy and abuse.ConclusionThe majority of observed adverse reactions in this study were consistent with those listed in the product instructions. However, potential novel or notable ADE signals were identified through real-world pharmacovigilance analysis. It is anticipated that this paper will offer additional information regarding safe and rational medication for narcolepsy.

Efficacy and safety of osimertinib plus bevacizumab versus osimertinib alone for advanced non-small-cell lung cancer with EGFR mutations: A meta-analysis of randomized controlled trials.

To systematically evaluate the efficacy and safety of osimertinib plus bevacizumab in treating advanced non-small-cell lung cancer (NSCLC) with epidermal growth factor receptor (EGFR) mutations. Up to May 26, 2024, the databases of PubMed, EMBASE, Cochrane Library, ClinicalTrials.gov, China National Knowledge Infrastructure, Chinese Biomedical Literature, China Science and Technology Journal, and Wanfang were searched, and the randomized controlled clinical trials (RCTs) of osimertinib plus bevacizumab in the treatment of advanced EGFR-mutant NSCLC were included. Two researchers independently screened the literature, assessed the quality of the included literature, and extracted the literature data. Revman5.4 software was used for meta-analysis. A total of 824 patients were included in 10 RCTs. The results of meta-analysis showed that compared with the control group (osimertinib alone), the experimental group (osimertinib plus bevacizumab) had a higher objective response rate (ORR) (relative risk [RR] = 1.23, 95% confidence interval [CI] = 1.03-1.47, P = .02), and the experimental group could significantly reduce the expression levels of carcinoembryonic antigen (mean difference [SMD] = 0.82, 95% CI = 0.30-1.35, P = .002), vascular endothelial growth factor (SMD = 0.43, 95% CI = 0.13-0.73, P = .005), neuron-specific enolase (SMD = 0.88, 95% CI = 0.60-1.17, P < .00001), cytokeratin 19 fragments (SMD = 1.33, 95% CI = 0.34-2.33, P = .009), and carbohydrate antigen 125 (SMD = 0.46, 95% CI = 0.15-0.77, P = .004) in serum. However, the experimental group did not significantly improve the disease control rate (DCR) (RR = 1.17, 95% CI = 1.00-1.36, P = .05), 1- and 2-year progression-free survival (PFS) rates (RR = 1.15, 95% CI = 1.00-1.33, P = .05; RR = 1.02, 95% CI = 0.74-1.40, P = .92), 1- and 2-year overall survival (OS) rates (RR = 1.11, 95% CI = 0.92-1.36, P = .28; RR = 0.99, 95% CI = 0.84-1.18, P = .95). Interestingly, the results of subgroup analysis showed that the experimental group significantly improved ORR, DCR, 1-year PFS, and OS rates in the Chinese population and patients under 65 years old (P < .05). In addition, when the dose of bevacizumab was 7.5 mg/kg q3w in the experimental group, ORR, DCR, 1-year PFS, and OS rates were significantly better than those in the control group (P < .05). In terms of adverse events of drugs, the incidence of proteinuria, hypertension, oral mucositis, bleeding, nausea, and vomiting in the experimental group was higher than that in the control group (P < .05). For patients with advanced EGFR-mutant NSCLC, osimertinib plus bevacizumab has some clinical benefit compared with osimertinib alone. Still, it does not provide additional long-term survival benefits and has higher toxicity. More well-designed, multicenter RCTs are needed to identify the subgroups of patients most likely to benefit from this combination regimen and to validate the optimal dose of this combination regimen.

Pharmacogenetic testing: current state of the issue

Aim. The purpose of this work is to emphasize the importance and practical benefits of pharmacogenetics in medicine, demonstrating how the integration of pharmacogenetics into clinical practice can improve treatment outcomes and enhance the safety of therapies. Pharmacogenetics is a rapidly developing branch of pharmacology that studies how genetic variation affects an individual’s response to drugs. By understanding these genetic differences, healthcare providers can tailor drug therapy to maximize efficacy and minimize adverse drug reactions. The field aims to move away from the traditional one-size-fits-all approach and instead personalize medical treatment based on a person’s genetic makeup. The ability to predict a person’s response to medication based on their genetic profile has profound implications. For example, pharmacogenetic testing can identify patients at risk for life-threatening adverse drug reactions, such as drug-induced liver injury. This proactive approach can prevent adverse events, improving patient safety and the overall quality of care. In addition, pharmacogenetics aids in the development of new drugs by identifying genetic markers associated with drug responses, optimizing the drug development process, and reducing the time and costs associated with bringing new drugs to market. Key advances in pharmacogenetics include the identification of genetic polymorphisms in enzymes, such as cytochrome P450, that affect drug metabolism, thereby influencing both safety and efficacy. Pharmacogenetic testing allows doctors to predict the best drug and dosage for a patient, improving treatment outcomes and reducing the risk of adverse drug events. Despite its potential, the integration of pharmacogenetics into clinical practice faces challenges, including a lack of reliable clinical evidence, inadequate physician education, and the need for a comprehensive health IT infrastructure to support the use of genetic data. Ethical and legal issues, such as patient privacy and the risk of genetic discrimination, also present significant obstacles. However, continued research, the development of genetic testing technologies, and interdisciplinary collaborations are paving the way for more widespread adoption of pharmacogenetics, which promises to significantly improve patient care and healthcare efficiency. Key resources such as PharmGKB, CPIC, and the NIH provide valuable information and guidance for clinicians, researchers, and students, helping bridge the gap between genetics research and clinical application. Conclusions. Pharmacogenetics represents a significant advancement in personalized medicine, offering the potential to tailor drug therapies to individual genetic profiles. Although the field has made substantial progress, challenges remain in the form of insufficient clinical evidence, implementation barriers, and ethical concerns. Continued research and collaboration among stakeholders are essential to fully realize the benefits of pharmacogenetic testing in clinical practice.

System-Wide, Electronic Health Record-Based Medication Alerts for Appropriate Prescribing of Direct Oral Anticoagulants: Pilot Randomized Controlled Trial.

While direct oral anticoagulants (DOACs) have improved oral anticoagulation management, inappropriate prescribing remains prevalent and leads to adverse drug events. Antithrombotic stewardship programs seek to enhance DOAC prescribing but require scalable and sustainable strategies. We present a pilot, prescriber-level randomized controlled trial to assess the effectiveness of electronic health record (EHR)-based medication alerts in a large health system. The pilot assessed prescriber responses to alerts for initial DOAC prescription errors (apixaban and rivaroxaban). A user-centered, multistage design process informed alert development, emphasizing clear indication, appropriate dosing based on renal function, and drug-drug interactions. Alerts appeared whenever a DOAC was being prescribed in a way that did not follow package label instructions. Clinician responses measured acceptability, accuracy, feasibility, and utilization of the alerts. The study ran from August 1, 2022, through April 30, 2023. Only 1 prescriber requested trial exclusion, demonstrating acceptability. The error rate for false alerts due to incomplete data was 6.6% (16/243). Two scenarios with alert design and/or execution errors occurred but were quickly identified and resolved, underlining the importance of a responsive quality assurance process in EHR-based interventions. Trial feasibility issues related to alert-data capture were identified and resolved. Trial feasibility was also assessed with balanced randomization of prescribers and the inclusion of various alerts across both medications. Assessing utilization, 34.2% (83/243) of the encounters (with 134 prescribers) led to a prescription change. The pilot implementation study demonstrated the acceptability, accuracy, feasibility, and estimates of the utilization of EHR-based medication alerts for DOAC prescriptions and successfully established just-in-time randomization of prescribing clinicians. This pilot study sets the stage for large-scale, randomized implementation evaluations of EHR-based alerts to improve medication safety. ClinicalTrials.gov NCT05351749; https://clinicaltrials.gov/study/NCT05351749.

Analysis of tirzepatide in the US FDA adverse event reporting system (FAERS): a focus on overall patient population and sex-specific subgroups

ObjectiveTirzepatide, a novel GIP and GLP1 agonist, has been extensively examined in clinical trials. However, specific data on its adverse drug events (ADEs) remain limited. This study aims to comprehensively assess real-world ADEs associated with tirzepatide by mining data from the U.S. Food and Drug Administration Adverse Event Reporting System (FAERS) database.MethodsADE reports from the FAERS database were retrieved for the second quarter of 2022 through the first quarter of 2024. Significant associations between ADEs and tirzepatide were evaluated using proportional disproportionality analyses, including the Reporting Odds Ratio (ROR), Proportional Reporting Ratio (PRR), Bayesian Confidence Propagation Neural Network (BCPNN), and Multi-item Gamma Poisson Shrinkage (MGPS).ResultsA total of 37,827 ADE reports associated with tirzepatide were identified, with 100 significantly disproportionate preferred terms (PTs) recognized by all four algorithms. The top five PTs with the highest reporting rates were incorrect dose administered, injection site pain, off-label use, nausea, and injection site hemorrhage. Additionally, unexpected signals such as starvation ketoacidosis were identified. The median time to onset for all ADEs was 23 days. Furthermore, sex-specific high-intensity signals were found, with males primarily experiencing gastrointestinal disorders and females experiencing general disorders and administration site conditions.ConclusionThis study provides valuable insights into the occurrence of ADEs following tirzepatide administration, potentially supporting clinical monitoring and risk identification efforts.

The roles and patterns of critical care pharmacists: a literature review and practical operation model in China

Drug-related problems (DRPs) are prevalent in critically ill patients and may significantly increase mortality risks. The participation of critical care pharmacists (CCPs) in the medical team has demonstrated a benefit to healthcare quality. Research indicates that CCP medication order evaluations can reduce DRPs, while their participation in rounds can reduce adverse drug events and shorten hospital stays. Pharmacist medication reconciliation often proves more effective than physicians, and CCPs play a crucial role in antimicrobial management and reducing treatment costs. Despite these benefits, there is a noticeable lack of practical guidance for implementing CCP roles effectively. Their workflow heavily influences the efficiency of CCPs. Integrating results from the literature with our practical experience, we have detailed workflows and critical entry points that CCPs can refer to. Pharmacists should be proactive rather than passive consultants. Pre-round medication order evaluations are crucial for determining the depth of a pharmacist’s involvement in patient care. These evaluations should cover the following aspects: medication indication, dosage, treatment duration, detection of DRPs, implementation of therapeutic drug monitoring, dosing of sedatives and analgesics, and pharmaceutical cost containment. Beyond identifying medication issues, a primary task during rounds is gathering additional information and building trust with the medical team. Post-round responsibilities for CCPs include patient and caregiver education on medication, medication reconciliation for transitioning patients, and follow-up care for post-ICU patients. Establishing a rationalized and standardized workflow is essential to minimize daily work omissions and maximize the pharmacist’s value. A multidisciplinary pharmacist-led team can significantly promote the rational use of antibiotics. Participation in post-ICU outpatient follow-ups can reduce drug-induced injuries after discharge. This review provides a detailed overview of the tasks performed by CCPs before, during, and after medical rounds, serving as a valuable reference for establishing an efficient workflow for CCPs.

Views on the Development and Use of a New Digital Adverse Drug Event Reporting Platform in Australia: A Qualitative Study.

Reporting of adverse drug events (ADEs) to regulatory authorities remains low, particularly among consumers. To explore stakeholders' views on the development and use of a digital platform to improve ADE reporting by consumers to the regulatory authority in Australia, i.e., the Therapeutic Goods Administration. A qualitative study was conducted using semi-structured interviews, focus group discussions (FGDs), and co-design workshops with consumers, healthcare professionals (HCPs), and regulators. The interview recordings were transcribed verbatim, coded, and analysed thematically according to the Capability, Opportunity, Motivation, Behaviour model. Findings of the FGDs and co-design workshops were incorporated to enhance and complement the insights gathered from the interviews. A total of 39 participants took part in the study (54 % consumers, 41 % HCPs, and 5 % regulators). Uncovered themes related to ADE reporting in general were: difficulty recognizing ADEs and health literacy, awareness about reporting ADEs (Capability); visibility of ADE reporting, professionals' views on consumer ADE reporting, consumer education (Opportunity); the common good, benefit to the reporter, identifying ADEs worth reporting, and concern about reporting (Motivation). Additional identified themes specific to a new digital platform were: physical abilities (Capability); features that facilitate intuitive use, convenience and accessibility, user experience, integration with existing systems, trust, sharing experiences with others (Opportunity); and concern about using a reporting platform, and feedback loop (Motivation). A cross-section of attitudes and values were obtained regarding ADE reporting in general and a new ADE reporting digital platform for consumers in Australia, which will inform its development, implementation and evaluation.

Adverse drug events in cost-effectiveness models of pharmacological interventions for diabetes, diabetic retinopathy, and diabetic macular edema: a scoping review.

The objective of this review was to examine the role of adverse drug events (ADEs) caused by pharmacological interventions in cost-effectiveness models for diabetes mellitus, diabetic retinopathy, and diabetic macular edema. Guidelines for economic evaluation recognize the importance of including ADEs in the analysis, but in practice, consideration of ADEs in cost-effectiveness models seem to be vague. Inadequate inclusion of these harmful outcomes affects the reliability of the results, and the information provided by economic evaluation could be misleading. Reviewing whether and how ADEs are incorporated in cost-effectiveness models is necessary to understand the current practices of economic evaluation. Studies included were published between 2011-2022 in English, representing cost-effectiveness analyses using modeling framework for pharmacological interventions in the treatment of diabetes mellitus, diabetic retinopathy, or diabetic macular edema. Other types of analyses and other types of conditions were excluded. The databases searched included MEDLINE (PubMed), CINAHL (EBSCOhost), Scopus, Web of Science Core Collection, and NHS Economic Evaluation Database. Gray literature was searched via the National Institute for Health and Care Excellence, European Network for Health Technology Assessment, the National Institute for Health and Care Research, and the International Network of Agencies for Health Technology Assessment. The search was conducted on January 1, 2023. Titles and abstracts were screened for inclusion by 2 independent reviewers. Full-text review was conducted by 3 independent reviewers. A data extraction form was used to extract and analyze the data. Results were presented in tabular format with a narrative summary, and discussed in the context of existing literature and guidelines. A total of 242 reports were extracted and analyzed in this scoping review. For the included analyses, type 2 diabetes was the most common disease (86%) followed by type 1 diabetes (10%), diabetic macular edema (9%), and diabetic retinopathy (0.4%). The majority of the included analyses used a health care payer perspective (88%) and had a time horizon of 30 years or more (75%). The most common model type was a simulation model (57%), followed by a Markov simulation model (18%). Of the included cost-effectiveness analyses, 26% included ADEs in the modeling, and 13% of the analyses excluded them. Most of the analyses (61%) partly considered ADEs; that is, only 1 or 2 ADEs were included. No difference in overall inclusion of ADEs between the different conditions existed, but the models for diabetic retinopathy and diabetic macular edema more often omitted the ADE-related impact on quality of life compared with the models for diabetes mellitus. Most analyses included ADEs in the models as probabilities (55%) or as a submodel (40%), and the most common source for ADE incidences were clinical trials (65%). The inclusion of ADEs in cost-effectiveness models is suboptimal. The ADE-related costs were better captured than the ADE-related impact on quality of life, which was most pronounced in the models for diabetic retinopathy and diabetic macular edema. Future research should investigate the potential impact of ADEs on the results, and identify the criteria and policies for practical inclusion of ADEs in economic evaluation.