Medical Dictionary Research Articles

Dabigatran-related serious medication errors: an analysis using data from VigiBase

ObjectiveTo analyze the serious medication errors (MEs) on dabigatran, and their related factors, in order to avoid or reduce the occurrence of adverse events.MethodsSerious MEs related to dabigatran were extracted from the WHO global database of reported potential side effects of medicinal products (VigiBase) by using “Medication errors and other product use errors and issues” High Level Group Term (HLGT) of the international Medical Dictionary for Regulatory Activities (MedDRA). Well-documented reports, vigiGrade completeness score ≥ 0.80, or with an informative narrative were analyzed with a focus on the clinical features of the cases. The PCNE Classification for drug-related problems (DRP) was used to classify medication errors in our analysis of cases.ResultsUntil January 26, 2020, there were 453 cases with serious MEs related to dabigatran in VigiBase, and 113 were well-documented. Among these, 69 patients (61%) were hospitalized or had prolonged hospitalization, 16 (14%) had life-threatening events, and 12 (11%) died. The MEs occurred in the prescription phase in 77 cases, in administration in 35, and at the dispensing stage in one case. The MEs in prescription were related to a drug selection error in 44 cases (24 concerning contraindications and 20 drug interactions) and to dose error in 33 cases (17 with excessive dose; eight with insufficient frequency; four had an incorrect time; in three, the dose was too low; and in one, too frequent). The MEs in administration were medical-staff-related errors in five cases (three with wrong administration route, one administration omission, and one overdose), patient-related errors in 28 (14 insufficient dose or no administration, seven improper drug storage, four wrong administration method, and three over prescribed dose), and other errors in two (without efficacy monitoring). The dispensing error of a wrong drug strength occurred in a pharmacy. The main adverse events in the 113 patients were haemorrhage in 57 cases (50%) and ischemia in 29 cases (26%).ConclusionBased on the analysis of reports in VigiBase, serious MEs related to dabigatran mainly occurred during prescription and administration. Although the incidence of MEs with clinical consequences in the use of dabigatran cannot be determined, attention should be paid to selection of the appropriate dose to a right patient in the prescription, and to patient compliance and storage in drug administration. The patient harm mainly manifested itself as bleeding or ischemia including fatal outcome in rare patients.

A Model for Monitoring Spontaneously Reported Medication Errors Using the Adjuvanted Recombinant Zoster Vaccine as an Example.

A European legislation was put in place for the reporting of medication errors, and guidelines were drafted to help stakeholders in the reporting, evaluation, and, ultimately, minimization of these errors. As part of pharmacovigilance reporting, a proper classification of medication errors is needed. However, this process can be tedious, time-consuming, and resource-intensive. To fulfill this obligation regarding medication errors, we developed an algorithm that classifies the reported errors in an automated way into four categories: potential medication errors, intercepted medication errors, medication errors without harm (i.e., not associated with adverse reaction(s)), and medication errors with harm (i.e., associated with adverse reaction(s)). A fifth category ("conflicting category") was created for reported cases that could not be unambiguously classified as either potential or intercepted medication errors. Our algorithm defines medication error categories based on internationally accepted terminology using the Medical Dictionary for Regulatory Activities (MedDRA®) preferred terms. We present the algorithm and the strengths of this automated way of reporting medication errors. We also give examples of visualizations using spontaneously reported vaccination error data associated with the adjuvanted recombinant zoster vaccine. For this purpose, we used a customized web-based platform that uses visualizations to support safety signal detection. The use of the algorithm facilitates and ensures a consistent way of categorizing medication errors with MedDRA® terms, thereby saving time and resources and avoiding the risk of potential mistakes versus manual classification. This allows further assessment and potential prevention of medication errors. In addition, the algorithm is easy to implement and can be used to categorize medication errors from different databases.

Analysis of patients (pts) with unresectable hepatocellular carcinoma (uHCC) and Child–Pugh (CP)-B liver function treated with regorafenib in routine clinical practice in the observational REFINE study.

452 Background: Pts with HCC and compromised liver function are typically excluded from clinical trials. The REFINE real-world study (NCT03289273) assessed a more varied pt population treated with regorafenib than the phase 3 RESORCE trial.1 Median overall survival (OS) in REFINE was 13.2 months and treatment-emergent adverse events (TEAEs) were consistent with RESORCE. We present a subgroup analysis of outcomes in pts from REFINE with CP-B liver function. Methods: REFINE is an international, prospective observational study of pts with uHCC for whom the decision to treat with regorafenib according to the local health authority approved label was made by their physician before enrollment. The primary endpoints were safety (Medical Dictionary for Regulatory Activities v25) and dose modifications due to drug-related TEAEs. Secondary endpoints included OS and duration of treatment (DoT). Results: Of 1005 evaluable pts, 123 (12%) were classified as CP-B at study entry, with most being CP-B7 (Table). Of the CP-B pts, 40/123 (9%), 9/123 (18%), and 58/123 (15%) initiated regorafenib at 160 mg, 120 mg, and 80 mg, per day, respectively. Median DoT with regorafenib was 2.3 months in CP-B pts and 3.7 months in the overall cohort. Incidence rates of TEAEs in CP-B pts and the overall cohort were similar (93% and 92%) and TEAEs were drug-related in 70% and 74% of pts, respectively. Grade 3–4 TEAEs occurred in 41% of CP-B pts and 39% of the overall cohort and were drug-related in 27% and 26% of pts, respectively. Serious TEAEs were observed in 48% of CP-B pts and 37% of the overall cohort, and were drug-related in 11% and 9% of pts, respectively. Drug-related TEAEs led to less frequent dose modifications in CP-B pts than in the overall cohort (28% vs 37%), but more frequent permanent discontinuations (28% vs 16%). Median OS in CP-B pts was 6.3 (95% confidence interval [CI] 4.9, 7.8) months and in CP-B7 pts was 6.7 (95% CI 5.1, 8.7) months. Conclusions: In REFINE, pts with uHCC and CP-B liver function had similar rates of grade 3–4 TEAEs, but a higher occurrence of serious TEAEs due to underlying cirrhosis led to more frequent permanent discontinuations in CP-B pts. Median OS in CP-B7 pts was comparable with OS in CP-B pts overall. The evaluation of prognostic models to identify CP-B pt subgroups who may benefit from regorafenib treatment is a subject for further research. 1. Kim YJ, ILCA 2022. [Table: see text]

Tracheotomy versus tracheostomy, the need for lexicographical clarification

In the healthcare field, the terms “traqueotomía” and “traqueostomía” are frequently used, often leading to confusion among professionals regarding the appropriate definition for each term or which one should be considered more correct in specific cases. A search was conducted for the terms “traqueotomía” and “traqueostomía” in general Spanish-language dictionaries such as the Dictionary of the Royal Spanish Academy (DRAE) and the Historical Dictionary of the Spanish Language of the Royal Spanish Academy (DHLE), as well as for the English terms “tracheotomy” and “tracheostomy” in English general dictionaries like the Oxford Dictionary, the Cambridge Dictionary, and the Collins English Dictionary. Additionally, searches were performed in medical dictionaries in both Spanish, specifically the Dictionary of Medical Terms of the National Academy of Medicine (DTM), and English, including the Farlex Dictionary. The terms were also explored using the Google search engine. Definitions were analyzed from both lexicographical and etymological perspectives. Definitions found in general dictionaries, in both Spanish and English, were found to be imprecise, limited, and ambiguous, as they mixed outdated indications with criteria that deviated from etymology. In contrast, definitions in medical dictionaries in both languages were more aligned with etymology. “Traqueotomía” strictly identifies the surgical procedure of creating an opening in the anterior face of the trachea. “Traqueostomía” identifies the creation of an opening that connects the trachea to the exterior, involving a modification of the upper airway by providing an additional entry for the respiratory pathway. “Traqueostomía” becomes the sole means of entry to the airway in total laryngectomies. Both terms can be used synonymously when a traqueotomía culminates in a traqueostomía. However, it is not appropriate to use the term “traqueostomía” when the procedure concludes with the closure of the planes and does not result in the creation of a stoma. Traqueostomas can be qualified with adjectives indicating permanence (temporary/permanent), size (large/small), shape (round/elliptical), or depth, without being linked to any specific disease or surgical indication. Not all permanent traqueostomas are the result of total laryngectomies, and they do not necessarily have an irreversible character systematically.

Assessment of safety profile of secukinumab in real-world scenario using United States food and drug administration adverse event reporting system database

Secukinumab is an anti-IL-17 monoclonal antibody approved for treating psoriasis and various arthritides. A comprehensive evaluation of its safety, especially in a real-world setting, is necessary. This study aimed to describe the adverse events (AE) associated with secukinumab use using the United States Food and Drug Administration Adverse Event Reporting System (FAERS) database. FAERS data files containing AE reports from 2015 to 2021 were downloaded for data mining. Primary or secondary suspect medications indicated for psoriasis were identified and analyzed. Medical dictionary for regulatory activities (MedDRA version 24.1) was used to analyze the AE terms. To detect potential safety signals of AE from secukinumab use, disproportionality analysis was used. A total of 365,590 adverse event reports were identified; of these, 44,761 reports involved the use of secukinumab. Safety signals were identified for ocular infections and gastrointestinal adverse events at the standardised MedDRA query level. Safety signals for oral candidiasis, oral herpes, conjunctivitis, eye infections, and ulcerative colitis were identified at the preferred term level. The findings of our study are consistent with those of earlier studies, such as the increased risk of infections and inflammatory bowel disease. However, our study also identified additional safety signals that need to be further evaluated.

Otorhinolaryngologic complications after COVID-19 vaccination, vaccine adverse event reporting system (VAERS).

There have been reports of otolaryngological adverse event following immunization (AEFI) such as instances of olfactory and gustatory dysfunction following COVID-19 vaccination. This study aimed to analyze otolaryngological AEFIs following COVID-19 vaccination. This study was conducted with a secondary data analysis that the Vaccine Adverse Events Reporting System (VAERS) and the COVID-19 Data Tracker, which are both administered by the Centers for Disease Control and Prevention in the US. Using Medical Dictionary for Regulatory Activities (MedDRA) concepts, AEFIs included: Considering the overall frequency and similarity of symptoms in the first 153 PTs, they were grouped into major 19 AEFIs groups. The incidence rates (IRs) of AEFIs per 100,000 were calculated on individual and cumulative AEFIs levels, involving people who received complete primary series and an updated bivalent booster dose with one of the available COVID-19 vaccines in the US. The proportions of AEFIs by age, sex, and vaccine manufacturer were reported. We also calculated the proportional reporting ratio (PRR) of AEFIs. We identified 106,653 otorhinolaryngologic AEFIs from the VAERS database, and a total of 226,593,618 people who received complete primary series in the US. Overall, the IR of total Otorhinolaryngologic AEFIs was 47.068 of CPS (completed primary series) and 7.237 UBB (updated bivalent booster) per 100,000. For most symptoms, being female was associated with statistically significant higher AEFIs. Upon examining the impact of different vaccine manufacturers, the researchers found that Janssen's vaccine exhibited higher IRs for hearing loss (5.871), tinnitus (19.182), ear infection (0.709), dizziness (121.202), sinusitis (2.088), epistaxis (4.251), anosmia (5.264), snoring (0.734), allergies (5.555), and pharyngitis (5.428). The highest PRRs were for Anosmia (3.617), Laryngopharyngeal Reflux - Acid Reflux (2.632), and Tinnitus -Ringing in the ears (2.343), in that order, with these three significantly incidence than other background noises. This study, utilizing an extensive sample sizes, represents a significant step toward comprehensively characterizing the otolaryngological AEFIs associated with COVID-19 vaccinations. This large-scale analysis aims to move beyond isolated case reports and anecdotal evidence, providing a robust and detailed portrait of the otolaryngological AEFIs landscape in response to COVID-19 vaccinations.

Enhancing antidepressant safety surveillance: comparative analysis of adverse drug reaction signals in spontaneous reporting and healthcare claims databases.

Background/Objective: Spontaneous reporting systems (SRS) such as the Korea Adverse Event Reporting System (KAERS) are limited in their ability to detect adverse drug reaction (ADR) signals due to their limited data on drug use. Conversely, the national health insurance claim (NHIC) data include drug use information for all qualifying residents. This study aimed to compare ADR signal profiles for antidepressants between KAERS and NHIC, evaluating the extent to which detected signals belong to common ADRs and labeling information. Materials and Methods: ADR signal detection in KAERS and NHIC databases, spanning January to December 2017, employed disproportionality analysis. Signal classes were determined based on System Organ Class (SOC) of the Medical Dictionary for Regulatory Activities (MedDRA). Also, Common ADR Coverage (CAC), the proportion of detected signals deemed common ADRs, and labeling information coverage (LIC) represented by mean average precision (mAP) were calculated. Additionally, protopathic bias and relative risk (RR) evaluation were performed to check for signal robustness. Results: Signal detection revealed 51 and 62 signals in KAERS and NHIC databases, respectively. Both systems predominantly captured signals related to nervous system disorders, comprising 33.3% (N = 17) in KAERS and 50.8% (N = 31) in NHIC. Regarding the type of antidepressants, KAERS predominantly reported signals associated with tricyclic antidepressants (TCAs) (N = 21, 41.2%), while NHIC produced most signals linked to selective serotonin reuptake inhibitors (SSRIs) (N = 22, 35.5%). KAERS exhibited higher CAC (68.63% vs. 29.03%) than NHIC. LIC was also higher in KAERS than in NHIC (mAP for EB05: 1.00 vs. 0.983); i.e., NHIC identified 5 signals not documented in drug labeling information, while KAERS found none. Among the unlabeled signals, one (Duloxetine-Myelopathy) was from protopathic bias, and two (duloxetine-myelopathy and tianeptine-osteomalacia) were statistically significant in RR. Conclusion: NHIC exhibited greater capability in detecting ADR signals associated with antidepressant use, encompassing unlabeled ADR signals, compared to KAERS. NHIC also demonstrated greater potential for identifying less common ADRs. Further investigation is needed for signals detected exclusively in NHIC but not covered by labeling information. This study underscores the value of integrating different sources of data, offering substantial regulatory insights and enriching the scope of pharmacovigilance.

Lessons learned from annotation of VAERS reports on adverse events following influenza vaccination and related to Guillain-Barré syndrome

BackgroundVaccine Adverse Events ReportingSystem (VAERS) is a promising resource of tracking adverse events following immunization. Medical Dictionary for Regulatory Activities (MedDRA) terminology used for coding adverse events in VAERS reports has several limitations. We focus on developing an automated system for semantic extraction of adverse events following vaccination and their temporal relationships for a better understanding of VAERS data and its integration into other applications. The aim of the present studyis to summarize the lessons learned during the initial phase of this project in annotating adverse events following influenza vaccination and related to Guillain-Barré syndrome (GBS). We emphasize on identifying the limitations of VAERS and MedDRA.ResultsWe collected 282 VAERS reports documented between 1990 and 2016 and shortlisted those with at least 1,100 characters in the report. We used a subset of 50 reports for the preliminary investigation and annotated all adverse events following influenza vaccination by mapping to representative MedDRA terms. Associated time expressions were annotated when available. We used 16 System Organ Class (SOC) level MedDRA terms to map GBS related adverse events and expanded some SOC terms to Lowest Level Terms (LLT) for granular representation. We annotated three broad categories of events such as problems, clinical investigations, and treatments/procedures. The inter-annotator agreement of events achieved was 86%. Incomplete reports, typographical errors, lack of clarity and coherence, repeated texts, unavailability of associated temporal information, difficulty to interpret due to incorrect grammar, use of generalized terms to describe adverse events / symptoms, uncommon abbreviations, difficulty annotating multiple events with a conjunction / common phrase, irrelevant historical events and coexisting events were some of the challenges encountered. Some of the limitations we noted are in agreement with previous reports.ConclusionsWe reported the challenges encountered and lessons learned during annotation of adverse events in VAERS reports following influenza vaccination and related to GBS. Though the challenges may be due to the inevitable limitations of public reporting systems and widely reported limitations of MedDRA, we emphasize the need to understand these limitations and extraction of other supportive information for a better understanding of adverse events following vaccination.

A patient safety knowledge graph supporting vaccine product development

BackgroundKnowledge graphs are well-suited for modeling complex, unstructured, and multi-source data and facilitating their analysis. During the COVID-19 pandemic, adverse event data were integrated into a knowledge graph to support vaccine safety surveillance and nimbly respond to urgent health authority questions. Here, we provide details of this post-marketing safety system using public data sources. In addition to challenges with varied data representations, adverse event reporting on the COVID-19 vaccines generated an unprecedented volume of data; an order of magnitude larger than adverse events for all previous vaccines. The Patient Safety Knowledge Graph (PSKG) is a robust data store to accommodate the volume of adverse event data and harmonize primary surveillance data sources.MethodsWe designed a semantic model to represent key safety concepts. We built an extract-transform-load (ETL) data pipeline to parse and import primary public data sources; align key elements such as vaccine names; integrated the Medical Dictionary for Regulatory Activities (MedDRA); and applied quality metrics. PSKG is deployed in a Neo4J graph database, and made available via a web interface and Application Programming Interfaces (APIs).ResultsWe import and align adverse event data and vaccine exposure data from 250 countries on a weekly basis, producing a graph with 4,340,980 nodes and 30,544,475 edges as of July 1, 2022. PSKG is used for ad-hoc analyses and periodic reporting for several widely available COVID-19 vaccines. Analysis code using the knowledge graph is 80% shorter than an equivalent implementation written entirely in Python, and runs over 200 times faster.ConclusionsOrganizing safety data into a concise model of nodes, properties, and edge relationships has greatly simplified analysis code by removing complex parsing and transformation algorithms from individual analyses and instead managing these centrally. The adoption of the knowledge graph transformed how the team answers key scientific and medical questions. Whereas previously an analysis would involve aggregating and transforming primary datasets from scratch to answer a specific question, the team can now iterate easily and respond as quickly as requests evolve (e.g., “Produce vaccine-X safety profile for adverse event-Y by country instead of age-range”).

Analysis of clinical factors associated with Kampo formula-induced pseudoaldosteronism based on self-reported information from the Japanese Adverse Drug Event Report database.

Drug-induced pseudoaldosteronism is a typical adverse effect of Kampo formulas. Previous research described the potential risks of Kampo formula-linked pseudoaldosteronism. However, few studies assessed the risk factors using a real-world database and a data-mining approach. Using the Japanese Adverse Drug Event Report database, we extracted pseudoaldosteronism reports for 148 Kampo formulas covered by Japanese national health insurance. Adverse events were decided according to the preferred terminology of the Medical Dictionary for Regulatory Activities/Japanese version 25.1. We calculated reporting odds ratio (RORs) and identified Kampo formulas as suspected causes of pseudoaldosteronism. Moreover, we evaluated clinical factors associated with Kampo formula-induced pseudoaldosteronism via logistic regression. From April 2004 to November 2022, 6334 adverse events related to the Kampo formulas were reported. We selected 2471 reports containing complete clinical data, including 210 reports on pseudoaldosteronism. In the pseudoaldosteronism group, 69.0% of patients were female, and 85.2% were ≥70 years old. The formulas most commonly associated with pseudoaldosteronism were Shakuyakukanzoto, Yokukansan, and Ryokeijutsukanto (ROR [95% confidence interval {CI}] = 18.3 [13.0-25.9], 8.1 [5.4-12.0], and 5.5 [1.4-21.9], respectively). Logistic analysis identified female sex (odds ratio [OR] [95% CI] = 1.7 [1.2-2.6]; P = 0.006), older age (≥70, 5.0 [3.2-7.8]; P < 0.001), low body weight (<50 kg, 2.2 [1.5-3.2]; P < 0.001), diuretics usage (2.1 [1.3-4.8]; P = 0.004), hypertension (1.6 [1.1-2.4]; P = 0.014), and dementia (7.0 [4.2-11.6]; P < 0.001) as pseudoaldosteronism-related factors. Additionally, the daily Glycyrrhiza dose (OR = 2.1 [1.9-2.3]; P < 0.001) and duration of administration (>14 days, OR = 2.8 [1.7-4.5]; P < 0.001) were associated with adverse events. We did not observe an interaction between aging and hypertension. Careful follow-up is warranted during long-term Glycyrrhiza-containing Kampo formula use in patients with multiple clinical factors for pseudoaldosteronism.

Utility analysis and demonstration of real-world clinical texts: A case study on Japanese cancer-related EHRs.

Real-world data (RWD) in the medical field, such as electronic health records (EHRs) and medication orders, are receiving increasing attention from researchers and practitioners. While structured data have played a vital role thus far, unstructured data represented by text (e.g., discharge summaries) are not effectively utilized because of the difficulty in extracting medical information. We evaluated the information gained by supplementing structured data with clinical concepts extracted from unstructured text by leveraging natural language processing techniques. Using a machine learning-based pretrained named entity recognition tool, we extracted disease and medication names from real discharge summaries in a Japanese hospital and linked them to medical concepts using medical term dictionaries. By comparing the diseases and medications mentioned in the text with medical codes in tabular diagnosis records, we found that: (1) the text data contained richer information on patient symptoms than tabular diagnosis records, whereas the medication-order table stored more injection data than text. In addition, (2) extractable information regarding specific diseases showed surprisingly small intersections among text, diagnosis records, and medication orders. Text data can thus be a useful supplement for RWD mining, which is further demonstrated by (3) our practical application system for drug safety evaluation, which exhaustively visualizes suspicious adverse drug effects caused by the simultaneous use of anticancer drug pairs. We conclude that proper use of textual information extraction can lead to better outcomes in medical RWD mining.

Design and Implementation of a Medical Device Data Dictionary System Based on Software Engineering Theory

Design and Implementation of a Medical Device Data Dictionary System Based on Software Engineering Theory

Cross-Cancer Type Evaluation of Potential Interstitial Lung Disease Complications of Immune Checkpoint Inhibitors Using JADER.

Interstitial lung disease (ILD) is a serious adverse event caused by the administration of immune checkpoint inhibitors (ICIs). However, only few large-scale studies have explored the association among ICI use, underlying cancer type, and ILD complications. This study aimed to analyze the association between the primary cancer type and ICI-induced ILD in a cross-sectional manner using the Japanese Adverse Drug Event Report (JADER) database. Nivolumab and pembrolizumab (anti-programmed cell death 1 (PD-1) antibodies) and durvalumab, avelumab, and atezolizumab (anti-programmed cell death ligand 1 (PD-L1) antibodies) were included as ICIs in this study. Adverse events were identified based on the preferred terms of Medical Dictionary for Regulatory Activities (MedDRA) version 27.0/J listed in the Standardized MedDRA Queries (SMQ) "interstitial lung disease." The reporting odds ratio was calculated to detect the association between ICI use and ILD complications, and a signal was detected if the lower limit of the 95% confidence interval exceeded 1. In the analysis of all cancer types, a signal was detected for all ICIs except avelumab. An association between ICI and ILD was detected for all cancer types with nivolumab. However, pembrolizumab exhibited a signal only in colorectal cancer. In contrast, anti-PD-L1 antibodies displayed signals in five cancer types, excluding head and neck cancer, which was not reported in JADER. Among these cancer types, atezolizumab exhibited a signal only in breast cancer. The results of this study will help guide the safe use of ICIs based on the underlying cancer type in terms of ILD complications.

Adverse events following COVID-19 vaccination: A comprehensive analysis of spontaneous reporting data in Ghana.

Vaccines are important public health tools and formed part of the fight against the COVID-19 pandemic. Five COVID-19 vaccines were given Emergency Use Authorization in Ghana and deployed during the pandemic. Early phase trials of the vaccines were mostly not conducted in Africans. This study examines safety data during their deployment under real-life conditions in Ghana. This study analysed secondary data on COVID-19 vaccine-related adverse events following immunization (AEFI) reported to the Ghana Food and Drugs Authority (GFDA) between March 2021 and June 2022 using STATA. AEFIs were coded with their Preferred Terms using the Medical Dictionary for Regulatory Activities, version 24.0. Statistical tests examined associations between demographic characteristics, vaccine types, seriousness, and AEFI outcomes. Binary logistic regression model assessed factors associated with serious AEFIs, while the GFDA's Joint COVID-19 Vaccine Safety Review Committee provided causality assessments of serious AEFIs. Overall cumulative incidence of AEFIs was about 25 per 100,000 persons vaccinated. Across the five vaccines, majority of the AEFIs reported were not serious (98.7%) with higher incidences in those below 50 years (74.0%) and females (51.2%). The most common AEFIs recorded were headache (52.9%), pains (44.4%), pyrexia (35.1%), chills (16.7%) and injection site pain (15.6%). Relative to those 50 years and above, the odds of serious AEFI were 60% less among those aged <30 years (aOR = 0.40, CI: [0.19, 0.86], p = 0.019). However, a causality assessment of the 57 serious AEFIs indicated only 8 (14%) were vaccine product-related. There was a low incidence of AEFIs following deployment of the vaccines in Ghana with a much lower incidence of serious AEFIs. Informing the public about the safety of the vaccines and potential side effects may increase trust and acceptance, decreasing hesitancy in current and future vaccination programmes.

Polypharmacy and Elevated Risk of Severe Adverse Events in Older Adults Based on the Korea Institute of Drug Safety and Risk Management-Korea Adverse Event Reporting System Database.

Older adults are at a higher risk of severe adverse drug events (ADEs) because of multimorbidity, polypharmacy, and lower physiological function. This study aimed to determine whether polypharmacy, defined as the use of ≥ 5 active drug ingredients, was associated with severe ADEs in this population. We used ADE reports from the Korea Institute of Drug Safety and Risk Management-Korea Adverse Event Reporting System Database, a national spontaneous ADE report system, from 2012 to 2021 to examine and compare the strength of association between polypharmacy and severe ADEs in older adults (≥ 65 years) and younger adults (20-64 years) using disproportionality analysis. We found a significant association between severe ADEs of cardiac and renal/urinary Medical Dictionary for Regulatory Activities System Organ Classes (MedDRA SOC) with polypharmacy in older adults. Regarding individual-level ADEs included in these MedDRA SOCs, acute cardiac arrest and renal failure were more significantly associated with polypharmacy in older adults compared with younger adults. The addition of new drugs to the regimens of older adults warrants close monitoring of renal and cardiac symptoms.

A real-world disproportionality analysis of FDA adverse event reporting system (FAERS) events for denosumab.

Denosumab is authorized to treat several diseases, including cancer and bone disorders. Nevertheless, its use in clinical practice has been affected by safety concerns. The work retrospectively investigated adverse events (AEs) of denosumab to better understand toxicities. The FAERS data base data from Q1 of 2010 to Q3 of 2023 was chosen. The definition of Medical Dictionary for Regulatory Activities (MedDRA) was dependent on preferred terms (PTs) and system organ class (SOCs). Following the removal of duplicate reports, a disproportionality analysis was conducted to identify safety signals through the calculation of reporting odds ratios (ROR). During the reporting period, 130611 denosumab-related cases were identified; 670pTs with a substantial disproportionality were retained. The connective and musculoskeletal tissue disorders, poisoning, injury, and procedural complications, as well as medical and surgical procedures, were among the important SOCs that satisfied the criteria. Reports at PT levels including off-label use, death, osteonecrosis of the jaw, arthralgia, and pain in extremities were determined. Severe consequences in terms of life-threatening injuries and death accounted for 841 and 19704 cases, respectively of the reported cases. These findings underscore the critical importance of pharmacovigilance and are consistent with established clinical observations. Notably, osteonecrosis of the jaw, arthralgia, pain in extremities, back pain, myalgia, and bone pain were identified as the most prevalent risk signals associated with denosumab.

Efficient analysis of adverse drug events and toxicological mechanisms of newly marketed drugs by integrating pharmacovigilance and network toxicology: selumetinib as an example.

To integrate pharmacovigilance and network toxicology methods to explore the potential adverse drug events (ADEs) and toxic mechanisms of selumetinib, and to provide a reference for quickly understanding the safety and toxicological mechanisms of newly marketed drugs. Taking selumetinib as an example, this study integrated pharmacovigilance methods based on real-world data and network toxicology methods to analyze its ADE and its potential toxicological mechanism. First, the ADE reports of selumetinib were extracted from the US Food and Drug Administration (FDA) adverse event reporting system (FAERS), and the ADE signals were detected by reporting odds ratio (ROR) and UK medicines and healthcare products regulatory agency (MHRA) methods. The ADE signals were classified and described according to the preferred terms (PTs) and system organ class (SOC) derived from the Medical Dictionary for Regulatory Activities (MedDRA). The network toxicology method was used to analyze the toxicological mechanism of the interested SOCs. The specific steps included predicting the potential targets of selumetinib using TOXRIC, STITCH, ChEMBL, CTD, SwissTargetPreditcion, and Super-PRED databases, collecting the targets of SOC using GeneCards database, conducting protein-protein interaction (PPI) analysis through STRING database, conducting gene ontology (GO) and Kyoto encyclopedia of genes and genomes (KEGG) analysis through DAVID database, and testing the molecular affinity using AutoDock software. A total of 1388 ADE reports related to selumetinib were extracted, and 53 positive signals were detected by ROR and MHRA methods, of which 20 signals were not mentioned in the package insert, including ingrowing nail, hyperphosphatemia, cardiac valve disease, hematuria, neutropenia, etc. Analysis of the toxicological mechanism of six SOCs involved in positive ADE signals revealed that the key targets included EGFR, STAT3, AKT1, IL6, BCL2, etc., and the key pathways included PI3K/Akt pathway, apoptosis, ErbB signaling pathway, and EGFR tyrosine kinase inhibitor resistance, etc. Molecular docking assays showed spontaneous binding of selumetinib to key targets in these pathways. The pharmacovigilance analysis identified some new potential ADEs of selumetinib, and the network toxicology analysis showed that the toxic effects of selumetinib may be related to PI3K/Akt pathway, apoptosis, ErbB signaling pathway, EGFR tyrosine kinase inhibitor resistance and other pathways.

Cardiovascular adverse events associated with targeted therapies for multiple myeloma: a pharmacovigilance study.

Multiple myeloma (MM) is a leading cause of hematopoietic cancer-related mortality, accounting for 20% of deaths. MM-targeted therapies have demonstrated efficacy, and since 2015, the United States Food and Drug Administration (FDA) has approved five targeted drugs. However, their cardiovascular safety has not been comprehensively evaluated. This study aimed to investigate the association between MM-targeted therapy and cardiovascular adverse events (AEs). Disproportionality analysis was conducted on reports from the FDA AE Reporting System database from 2014 to the second quarter of 2023. Cardiovascular AEs were grouped into nine narrow categories using the Standardized Medical Dictionary for Regulatory Activities Queries (SMQs). A total of 3,228 cardiovascular AE cases involving MM-targeted therapy were extracted and analyzed. Significant disproportionality was identified for daratumumab, elotuzumab, and isatuximab. Among the nine narrow SMQ categories, the three most reported cardiovascular AEs were cardiomyopathy, cardiac arrhythmias, and embolic and thrombotic events. Noninfectious myocarditis/pericarditis, cardiac arrhythmias, and embolic and thrombotic events exhibited the strongest signal strengths. The cardiovascular AE risk was higher within the first month and gradually decreased thereafter; however, it increased rapidly again after 1 year. This trend was observed for all cardiovascular AEs. The Kaplan-Meier curve and the log-rank test revealed that isatuximab and elotuzumab exhibited a significantly lower probability of cardiovascular AEs than daratumumab (p < 0.001). MM-targeted therapy is significantly associated with an increased risk of previously unknown cardiovascular AE profiles, with the range and onset differing among various drugs, thereby warranting specific monitoring and appropriate management.

Polish Anthropological Terminology in Słownik terminologii lekarskiej polskiej from 1881

The aim of the article is to preliminarily analyse the Polish anthropological terminology included in the most important 19th-century Kraków Słownik terminologii lekarskiej polskiej [Dictionary of Polish Medical Terminology] by S. Janikowski, J. Oettinger and A. Kremer, which was created during the period when anthropology was emerging as a new science. Anthropological terms had appeared in Kraków’s medical dictionaries before (over 40%), but it was in S 1881 that they were first distinguished from medical terminology and marked with the qualifier antr. The anthropological terminology for S 1881 was prepared by prominent anthropologists who were also physicians: I. Kopernicki and J. Majer. Out of 195 Polish terms, over 70% apply to craniology and craniometry, reflecting the main direction of the development in Polish anthropology. The Polish terms are definitely indigenous. More than 80% are one- (55.4%) and two-element terms (26.2%). Synonymy is present in the analysed terminology (40.4%), although there is a visible tendency to limit the number of Polish terms in synonymic series to two (73.7%).

Descriptive analysis on disproportionate medication errors and associated patient characteristics in the Food and Drug Administration's Adverse Event Reporting System.

Medication errors (MEs) are a major public health concern which can cause harm and financial burden within the healthcare system. Characterizing MEs is crucial to develop strategies to mitigate MEs in the future. To characterize ME-associated reports, and investigate signals of disproportionate reporting (SDRs) on MEs in the Food and Drug Administration's Adverse Event Reporting System (FAERS). FAERS data from 2004 to 2020 was used. ME reports were identified with the narrow Standardised Medical Dictionary for Regulatory Activities® (MedDRA®) Query (SMQ) for MEs. Drug names were converted to the Anatomical Therapeutic Chemical (ATC) classification. SDRs were investigated using the reporting odds ratio (ROR). In total 488 470 ME reports were identified, mostly (59%) submitted by consumers and mainly (55%) associated with females. Median age at time of ME was 57 years (interquartile range: 37-70 years). Approximately 1 out of 3 reports stated a serious health outcome. The most prevalent reported drug class was "antineoplastic and immunomodulating agents" (25%). The most common ME type was "incorrect dose administered" (9%). Of the 1659 SDRs obtained, adalimumab was the most common drug associated with MEs, noting a ROR of 1.22 (95% confidence interval: 1.21-1.24). This study offers a first of its kind characterization of MEs as reported to FAERS. Reported MEs are frequent and may be associated with serious health outcomes. This FAERS data provides insights on ME prevention and offers possibilities for additional in-depth analyses.