Event Reports Research Articles

A Real-World Safety Analysis of Upadacitinib Based on FDA Adverse Event Reporting System (FAERS)

Objectives. To investigate adverse events (AEs) associated with upadacitinib in the real world using data mining from the FDA Adverse Event Reporting System (FAERS). Methods. Disproportionality analysis, including the reporting odds ratio (ROR), the proportional reporting ratio (PRR), the Bayesian confidence propagation neural network (BCPNN), and the multiitem gamma Poisson shrinker (MGPS) algorithms, was used to quantify the signals of upadacitinib-associated AEs. Results. The study found 23683 reports of AEs associated with upadacitinib. A total of 149 substantial disproportionality preferred terms (PTs) that complied with all algorithms were identified. The infections discovered matched those mentioned in the specification and clinical trials, including pneumonia, upper respiratory tract infection, herpes zoster, and acne. Malignant and thrombotic AEs were also noted. Diverticulitis, myocardial infarction, transient ischaemic attack, and dysstasia were among the new AEs found. Upadacitinib-related AEs had a median onset time of 237 days and an interquartile range (IQR) of 78–509 days. Conclusions. The findings of our study were in line with clinical observations, and we also identified potential novel and unexpected AEs signals for upadacitinib, indicating the necessity for prospective clinical trials to corroborate these findings and demonstrate their link. Our results offered significant support for additional upadacitinib safety research.

A Pharmacovigilance Study of Drug-Induced Glaucoma Utilizing the Japanese Adverse Event Reporting System.

Clinically, glaucoma is a serious problem because it is asymptomatic until a relatively late stage in most cases, which can lead to delays in the diagnosis and treatment of the disease. The purpose of this study was to clarify the rank-order of the association of glaucoma with the causative drugs using a spontaneous reporting system database. Data were extracted from the Japanese Adverse Drug Event Report database of the Pharmaceuticals and Medical Devices Agency (Japan). Based on reports of glaucoma caused by all drugs, we calculated the reporting odds ratio (ROR) and 95% confidence interval (CI) for glaucoma. Among 609 reports of adverse events corresponding to glaucoma (46%, women), the most frequently implicated drug were steroids (prednisolone, betamethasone sodium phosphate, triamcinolone acetonide, and fluorometholone), pregabalin, ranibizumab, crizotinib, tacrolimus hydrate, darbepoetin alfa, and foscarnet sodium hydrate. Among 207 reports involved in angle-closure glaucoma (86%, women), anticholinergic drug and antidepressants ranked high and showed signals. Signals were also detected in bromazepam (ROR, 69.7; 95% CI, 30.9-157.5), oral brotizolam (ROR, 16.6; 95% CI, 6.18-44.8), and oral milnacipran hydrochloride (ROR, 22.8; 95% CI, 8.46-61.4) for angle-closure glaucoma. A national pharmacovigilance database enabled us to identify the drugs that frequently induce glaucoma. The likelihood of the reporting of glaucoma varied among the drugs, which should be used carefully in clinical practice to avoid it.

Impact of the COVID-19 pandemic on the spontaneous reporting and signal detection of adverse drug events

AbstractExternal factors severely affecting in a short period of time the spontaneous reporting of adverse events (AEs) can significantly impact drug safety signal detection. Coronavirus disease 2019 (COVID-19) represented an enormous challenge for health systems, with over 767 million cases and massive vaccination campaigns involving over 70% of the worldwide population. This study investigates the potential masking effect on certain AEs caused by the substantial increase in reports solely related to COVID-19 vaccines within various spontaneous reporting systems (SRSs). Three SRSs were used to monitor AEs reporting before and during the pandemic, namely, the World Health Organisation (WHO) global individual case safety reports database (VigiBase®), the United States Food and Drug Administration Adverse Event Reporting System (FAERS) and the Japanese Adverse Drug Event Report database (JADER). Findings revealed a sudden over-reporting of 35 AEs (≥ 200%) during the pandemic, with an increment of the RRF value in 2021 of at least double the RRF reported in 2020. This translates into a substantial reduction in signals of disproportionate reporting (SDR) due to the massive inclusion of COVID-19 vaccine reports. To mitigate the masking effect of COVID-19 vaccines in post-marketing SRS analyses, we recommend utilizing COVID-19-corrected versions for a more accurate assessment.

The Christmas adverse event syndrome: An analysis of the WHO pharmacovigilance database

We hypothesized that during the Christmas season the safety profile and the toxicity of some drugs may be exacerbated. We therefore assessed and characterized changes in drug safety profiles over the Christmas period. We performed a retrospective longitudinal analysis of adverse events reported in the World Health Organization (WHO) pharmacovigilance database between April 1st 2017 to March 31th 2023. We extracted cases reported by the 5 main contributors' countries of the WHO pharmacovigilance database with a Christmas tradition: USA, France, Germany, Italy and UK. We analyzed 4,999,459 individual case safety reports from USA (n=3,498,961), France (n=419,018), Germany (n=398,763), Italy (n=251,641) and UK (n=431,076), reported between April 1st 2017 to March 31th 2023. Monthly reports of adverse events were analyzed. Time trend, seasonal effect a Christmas effect (December-January) were explored. We found 91 adverse events significantly more frequently reported during the Christmas period, independently after controlling for winter effect and general tendency. The main type of adverse events were psychiatric disorders, infections and skin and subcutaneous disorders. The highest numbers of attributable cases to Christmas were found for drug dependence, emotional distress, and drug withdrawal syndrome. The most involved drugs were oxycodone in psychiatric disorders (n=47,527), docetaxel in skin disorders (n=9440) and social circumstances (n=1940), olmesartan in gastrointestinal disorders (n=1263), fentanyl in cardiac disorders (n=929), adalimumab in infections (n=11,316) and immune system disorders (n=3781), and collagenase clostridium histolyticum in reproductive system disorders (n=318). Our study shows that a range of drugs adverse events are more frequently reported at Christmas compared to other periods of the year, notably psychiatric disorders, infections, and skin disorders.

Impact of targeted education on adverse drug reaction documentation in cancer center sites.

395 Background: Allergic and infusion-related reactions represent a significant portion of reported adverse drug reactions (ADRs) at The University of Kansas Health System (TUKHS) Cancer Center sites. According to the TUKHS Allergy Documentation policy, all observed reactions are required to be documented in the electronic health record (EHR) and reported to the responsible provider. Insufficient documentation may result in preventable patient harm due to continued exposure to medications after known ADRs. An audit of patient EHRs demonstrated notable variability in documentation practices, which served as the impetus to implement a standardized ADR documentation workflow at Cancer Center sites. Methods: This multi-center, retrospective study included patients with ADRs submitted via safety reports from July 1st, 2022 to April 1st, 2023. Categorical data was analyzed using the chi-squared test. Duplicate reports and ADRs identified as side-effects were not included in the final analysis. Targeted education was provided via two online video modules, a workflow tips sheet, and an educational infographic. The primary outcome was frequency of allergy lists updated following submission of a safety event report. Secondary outcomes included frequency of standardized progress note writing, note routing, and accurate reaction type differentiation. Results: Targeted education significantly improved allergy list updating from 34.2% to 84.0% (P < 0.001), use of a standardized progress note from 47.4% to 64.2% (P = .008), and correct differentiation of reaction type from 57.7% to 76.4% (P = .02). Progress notes were routed to the responsible provider 58.5% of the time. Smaller community-based Cancer Center sites were significantly less likely to update allergy lists (7.5% vs. 24.5%, P = .017) and more likely to document incorrect reaction types (35.0% vs. 14.3%, P = .022). Conclusions: Targeted education for a standardized documentation workflow increased adherence to ADR documentation, ensuring future treatment plans are updated for patients with a history of reaction and the EHR accurately reflects ADR history. There is an opportunity to strengthen targeted education surrounding ADR documentation workflows for smaller community-based sites.

Evaluation of neuroleptic malignant syndrome induced by antipsychotic drugs using spontaneous reporting system

Adverse events (AEs) of antipsychotic drugs include neuroleptic malignant syndrome (NMS), which presents complex clinical symptoms, resulting in a fatal outcome. In this study, the association between antipsychotic drugs and NMS was comprehensively evaluated by cluster and association analyses using the Japanese Adverse Drug Event Report (JADER) database.The analyses were performed using 20 typical antipsychotics (TAPs) alongside 9 atypical antipsychotics (AAPs). The Standardised MedDRA Queries (SMQ) database was used to analyze NMS (SMQ code: 20000044). Reporting odds ratios (RORs) were used for AE signal detection. The relationship between antipsychotic drugs and AEs for NMS was investigated by performing hierarchical cluster analysis using Ward's method.Between April 2004 and September 2021, the total number of JADER reports was 705,294. RORs (95 % confidence interval) of NMS for haloperidol, chlorpromazine, risperidone, and aripiprazole were 12.1 (11.1–13.3), 6.3 (5.7–7.0), 6.2 (5.8–6.6), and 4.7 (4.4–5.1), respectively. Three clusters were formed, with characteristics as follows: Cluster 1 consisted of only TAPs, such as bromperidol and fluphenazine, whilst having a high reporting rate of hypotension, tachycardia, dyskinesia, and dystonia. Cluster 2 consisted of all AAPs alongside several TAPs, such as haloperidol and chlorpromazine, with higher reporting rates of disturbance of consciousness, extrapyramidal disorders (excluding dyskinesia and dystonia), and serotonin syndrome. Cluster 3 consisted of only perphenazine, whilst having a higher reporting rate of coma, leukocytosis, and Parkinsonism.The results of this study may therefore aid in the management of NMS using antipsychotic drugs.

Analysis of Opioid-Related Adverse Events in Japan Using FAERS Database.

Adverse events associated with opioid use in palliative care have been extensively studied. However, predicting the occurrence of adverse events based on the specific opioid used remains difficult. This study aimed to comprehensively analyze the adverse events related to µ-opioid receptor stimulation of opioids approved in Japan and investigate the tendencies of adverse event occurrence among different opioids. We utilized the FDA Adverse Event Reporting System database to extract reported adverse events for opioids approved in Japan. Cluster analysis was performed on reporting odds ratios (RORs) of adverse event names among opioids to visualize relationships between opioids and adverse events, facilitating a comparative study of their classifications. We calculated the RORs of adverse events for the target opioids. Cluster analysis based on these RORs resulted in five broad clusters based on the reported adverse events: i.e., strong opioids, weak opioids, loperamide, tapentadol, and remifentanil. This study provides a comprehensive classification of the association between μ-opioid-receptor-stimulating opioids and adverse events.

Breed, smaller weight, and multiple injections are associated with increased adverse event reports within three days following canine vaccine administration.

To evaluate patient and vaccine factors associated with adverse events (AEs) recorded within 3 days of vaccine administration in a large cohort of dogs. 4,654,187 dogs vaccinated in 16,087,455 office visits in a 5-year period at 1,119 hospitals of a corporate practice. Electronic medical records of dogs vaccinated between January 1, 2016, and December 31, 2020, were searched for diagnoses of possible AEs recorded within 3 days of administration of vaccines without concurrent injectable heartworm preventative. Patient risk factors (age, sex, breed, and weight) and number and type of vaccine were extracted from records. ORs (and 95% CIs) for risk factors were estimated via multivariable logistic regression mixed models with patient as a random effect. AEs were recorded following 31,197 vaccination visits (0.19%, or 19.4/10,000 visits). Reported AE rates increased from 1 to 4 vaccines administered and among individual vaccines were greatest for rabies vaccine. AE rate was generally inversely related to body weight, with largest rates in dogs ≤ 5 kg. The largest AE rates were noted in French Bulldogs and Dachshunds (ORs > 4 compared to mixed-breed dogs). Risk factor information can be used to update vaccination protocols and client communication. Breed differences may indicate genetics as the primary risk factor for adverse vaccine reactions following vaccinations.

A real-world analysis of tyrosine receptor kinase inhibitor-related toxicities in cancer treatment.

Background: This study analyzed real-world data from 2004 to 2023 to evaluate the toxicity profile of tyrosine receptor kinase (TRK) inhibitor therapy. Method: A retrospective analysis of USFDA Adverse Event Reporting System data was conducted to identify adverse events in patients receiving TRK inhibitor therapy. Result: Entrectinib demonstrated toxicities primarily in the cardiovascular and nervous systems, followed by the renal and urinary system. Common adverse effects included dizziness, renal impairment, constipation, heart failure and taste disorders. Larotrectinib induced adverse events mainly in the hepatobiliary and nervous systems, with peripheral neuropathy, myalgia, renal impairment and increased alanine aminotransferase commonly reported. Conclusion: Careful monitoring and supportive care strategies are essential for managing adverse events associated with TRK inhibitor therapy.

Evidence-based clinical engineering: Health information technology adverse events identification and classification with natural language processing

The primary goal of this project is to create a framework to extract Real-World Evidence to support Health Technology Assessment, Health Technology Management, Evidence-Based Maintenance, and Post Market Surveillance (as outlined in the EU Medical Device Regulation 2017/745) of medical devices using Natural Language Processing (NLP) and Artificial Intelligence. An initial literature review on Spontaneous Reporting System databases, Health Information Technologies (HIT) fault classification, and Natural Language Processing has been conducted, from which it clearly emerges that adverse events related to HIT are increasing over time. The proposed framework uses NLP techniques and Explainable Artificial Intelligence models to automatically identify HIT-related adverse event reports. The designed model employs a pre-trained version of ClinicalBERT that has been fine-tuned and tested on 3,075 adverse event reports extracted from the FDA MAUDE database and manually labelled by experts.

Neuropsychiatric adverse drug reactions with oral tyrosine kinase inhibitors in metastatic colorectal cancer: an analysis from the FDA Adverse Event Reporting System.

New oral tyrosine kinase inhibitors (TKIs) are approved for metastatic colorectal cancer (mCRC). The aim of this study was to assess the neuropsychiatric adverse drug reactions (ADRs) of these drugs reported in the FDA Adverse Event Reporting System (FAERS) database. All reports with regorafenib (REG) and encorafenib (ENC) as the primary suspect, and reported in the FAERS between 2012 and 2022, were collected. A descriptive and disproportionality analyses were conducted. Out of 4,984 cases, 1,357 (30.2%) reported at least one neuropsychiatric ADR. New potential signals for REG included neuropathy peripheral (n = 265; reporting odds ratio, ROR = 19.48, 95% confidence interval, CI 95% = 17.52-22.47; information component, IC = 2.89, IC025-IC075=2.77-3.02), hyperesthesia (n = 18; ROR = 12.56, CI 95% = 7.90-19.96; IC = 2.25, IC025-IC075=1.79-2.72), taste disorder (n = 41; ROR = 9.91, CI 95% = 7.29-13.49; IC = 2.18, IC025-IC075=1.88-2.49), poor quality sleep (n = 18; ROR = 6.56, CI 95% = 4.13-10.42; IC = 1.74, IC025-IC075=1.27-2.20), altered state of consciousness (n = 15; ROR = 5.50, CI 95% = 3.31-9.14; IC = 1.57, IC025-IC075=1.06-2.07), depressed mood (n = 13; ROR = 1.85, CI 95% = 1.07-3.19; IC = 0.58, IC025-IC075=0.04-1.13) and insomnia (n = 63; ROR = 1.48, CI 95% = 1.15-1.89; IC = 0.38, IC025-IC075=0.13-0.63). For ENC comprised depressed mood (n = 4; ROR = 5.75, CI 95% = 2.15-15.39; IC = 1.74, IC025-IC075=0.76-2.73) and cognitive disorders (n = 3; ROR = 4.71, CI 95% = 1.51-14.66; IC = 1.54, IC025-IC075=0.41-2.68). This study identified new unknown potential neuropsychiatric ADRs. Further investigations are required to better define the neurotoxicity of TKIs in mCRC patients.

The role of antipsychotics and other drugs on the development and progression of neuroleptic malignant syndrome

Neuroleptic malignant syndrome (NMS) is a rare but serious and sometimes fatal complication in patients taking antipsychotic drugs, and its underlying mechanism still remains unclear. The pharmacotherapy for psychotic disorders is complicated and often involves a combination of two or more drugs, including drugs other than antipsychotics. In the present study, we used the Japanese Adverse Drug Event Report (JADER) database to broadly investigate the drugs associated with NMS, following their related pathways, as well as the drug-drug interactions (DDIs) in NMS. All analyses were performed using data from the JADER database from April 2004 to May 2022. Single-drug signals were evaluated using the reporting odds ratio (ROR) and proportional reporting ratio (PRR), and drug pathways were investigated using the Kyoto Encyclopedia of Genes and Genomes (KEGG). DDIs were evaluated using the Ω shrinkage measure and Chi-square statistics models. All drugs associated with 20 or more NMS cases in the JADER database exhibited signals for NMS, including non-antipsychotics. Pathways associated with the drugs included the dopaminergic or serotonergic synapses related to antipsychotics. DDIs leading to NMS were confirmed for several drug combinations exhibiting single-drug signals. This study confirmed the significant association of various drugs, including non-psychotics, with NMS and suggested that various pathways related to these drugs may be involved in the progression of NMS. In addition, several combinations of these drugs were found to interact (DDI), increasing the risk of NMS, which suggests that appropriate caution should be taken when administering these drugs.

A pharmacovigilance study of etoposide in the FDA adverse event reporting system (FAERS) database, what does the real world say?

Introduction: Etoposide is a broad-spectrum antitumor drug that has been extensively studied in clinical trials. However, limited information is available regarding its real-world adverse reactions. Therefore, this study aimed to assess and evaluate etoposide-related adverse events in a real-world setting by using data mining method on the U.S. Food and Drug Administration Adverse Event Reporting System (FAERS) database.Methods: Through the analysis of 16,134,686 reports in the FAERS database, a total of 9,892 reports of etoposide-related adverse drug events (ADEs) were identified. To determine the significance of these ADEs, various disproportionality analysis algorithms were applied, including the reporting odds ratio (ROR), the proportional reporting ratio (PRR), the Bayesian confidence propagation neural network (BCPNN), and the multi-item gamma Poisson shrinker (MGPS) algorithms.Results: As a result, 478 significant disproportionality preferred terms (PTs) that were identified by all four algorithms were retained. These PTs included commonly reported adverse events such as thrombocytopenia, leukopenia, anemia, stomatitis, and pneumonitis, which align with those documented in the drug’s instructions and previous clinical trials. However, our analysis also uncovered unexpected and significant ADEs, including thrombotic microangiopathy, ototoxicity, second primary malignancy, nephropathy toxic, and ovarian failure. Furthermore, we examined the time-to-onset (TTO) of these ADEs using the Weibull distribution test and found that the median TTO for etoposide-associated ADEs was 10 days (interquartile range [IQR] 2–32 days). The majority of cases occurred within the first month (73.8%) after etoposide administration. Additionally, our analysis revealed specific high-risk signals for males, such as pneumonia and cardiac infarction, while females showed signals for drug resistance and ototoxicity.Discussion: These findings provide valuable insight into the occurrence of ADEs following etoposide initiation, which can potentially support clinical monitoring and risk identification efforts.

A text mining approach to categorize patient safety event reports by medication error type

Patient safety reporting systems give healthcare provider staff the ability to report medication related safety events and errors; however, many of these reports go unanalyzed and safety hazards go undetected. The objective of this study is to examine whether natural language processing can be used to better categorize medication related patient safety event reports. 3,861 medication related patient safety event reports that were previously annotated using a consolidated medication error taxonomy were used to develop three models using the following algorithms: (1) logistic regression, (2) elastic net, and (3) XGBoost. After development, models were tested, and model performance was analyzed. We found the XGBoost model performed best across all medication error categories. ‘Wrong Drug’, ‘Wrong Dosage Form or Technique or Route’, and ‘Improper Dose/Dose Omission’ categories performed best across the three models. In addition, we identified five words most closely associated with each medication error category and which medication error categories were most likely to co-occur. Machine learning techniques offer a semi-automated method for identifying specific medication error types from the free text of patient safety event reports. These algorithms have the potential to improve the categorization of medication related patient safety event reports which may lead to better identification of important medication safety patterns and trends.

Reinforcement learning and blockchain‐based intelligent and secure vaccine recommender system

AbstractBy combining blockchain technology (BT) and reinforcement learning (RL), the proposed work addresses the difficulties associated with vaccine recommendations. The need for individualized recommendations is obvious as vaccine schedules become more complicated and there are more vaccines available. The proposed work presents a novel approach that combines the adaptability of RL with the security, privacy, and transparency of BT. Layers for data processing, application, consensus, and smart contracts are included in the system architecture. It provides user‐managed secure access, individualized vaccine recommendations, and decentralized data storage. The system aims to improve public health outcomes by using smart contracts to automate procedures and RL to improve recommendations. Using 10‐fold cross‐validation on the Vaccine Adverse Event Reporting System (VAERS) dataset, the experimental study verifies the performance of the system. The study focuses on metrics like accuracy, sensitivity, specificity, and F‐measure when contrasting the proposed model with current solutions. The ability of proposed model to offer precise and well‐informed vaccine recommendations is demonstrated by its consistent outperformance of competitors in accuracy and sensitivity.

A descriptive analysis of spontaneous reports of antipsychotic-induced tardive dyskinesia and other extrapyramidal symptoms in the Japanese Adverse Drug Event Report database.

AimThe aim of this study is to summarize the spontaneous reports of tardive dyskinesia (TD) and extrapyramidal symptoms (EPSs) that occurred in Japan over the past decade. MethodsThe study analyzed TD and EPS cases reported in the Japanese Adverse Drug Event Report database between April 2011 and March 2021. The cases were stratified by the diagnoses of schizophrenia, bipolar disorders, and depressive disorders. ResultsIn total, 800 patients including a total of 171 TD cases and 682 EPS cases were reported in the JADER database across psychiatric diagnosis. The cases were caused by first-generation antipsychotics (FGA, TD: n = 105, EPS: n = 245) and second-generation antipsychotics (SGA, TD: n = 144, EPS: n = 598). The SGA were categorized based on Neuroscience-based Nomenclature (NbN) regarding pharmacological domain and mode of action, which were reported evenly as the offending agents. Among reported treatment and outcome in TD cases (n = 67, 37.6%) and EPS cases (n = 405, 59.3%), the relatively limited number of TD cases were reported as recovered/improved was also limited (n = 32, 47.8%) compared to those of EPS cases (n = 266, 65.7%). Some cases still had residual symptoms or did not recover fully (TD: n = 21, 31.3%, EPS: n = 77, 19.0%). CONCLUSION: Tardive dyskinesia and EPS have been widely reported in Japan over the past decade across psychiatric diagnoses and antipsychotic classes. LIMITATIONS: It is important to acknowledge the presence of reporting bias and the lack of comparators to accurately assess risks. Owing to the nature of spontaneous reporting, the estimation of prevalence is not feasible.

10570 The Robotic Tenaculum: A Review of Adverse Event Reports to the Food and Drug Administration

10570 The Robotic Tenaculum: A Review of Adverse Event Reports to the Food and Drug Administration

Signal detection statistics of adverse drug events in hierarchical structure for matched case-control data.

The tree-based scan statistic is a data mining method used to identify signals of adverse drug reactions in a database of spontaneous reporting systems. It is particularly beneficial when dealing with hierarchical data structures. One may use a retrospective case-control study design from spontaneous reporting systems (SRS) to investigate whether a specific adverse event of interest is associated with certain drugs. However, the existing Bernoulli model of the tree-based scan statistic may not be suitable as it fails to adequately account for dependencies within matched pairs. In this article, we propose signal detection statistics for matched case-control data based on McNemar's test, Wald test for conditional logistic regression, and the likelihood ratio test for a multinomial distribution. Through simulation studies, we demonstrate that our proposed methods outperform the existing approach in terms of the type I error rate, power, sensitivity, and false detection rate. To illustrate our proposed approach, we applied the three methods and the existing method to detect drug signals for dizziness-related adverse events related to antihypertensive drugs using the database of the Korea Adverse Event Reporting System.

Thyroid dysfunction associated with iodine-contrast media: A real-world pharmacovigilance study based on the FDA adverse event reporting system

ObjectiveTo comprehensively analyze characteristics of thyroid dysfunction associated with iodine contrast media (ICM) based on data from the FDA adverse event reporting system (FAERS). MethodsDisproportionate analysis was employed to identify signals of thyroid dysfunction caused by ICM, and descriptive analysis was performed to examine the clinical characteristics of reported cases involving ICM-related thyroid dysfunctions. ResultsA total of 83 adverse event reports were identified, documenting thyroid dysfunctions associated with ICM agents. Treatment with ICM was significantly associated with higher reporting of hypothyroidism ([ROR] = 2.21, 95 % CI: 1.59–3.08; IC025 = 0.58) and hyperthyroidism (ROR = 3.49, 95 % CI: 2.37–5.13; IC025 = 1.14). Among the six ICM agents investigated, iodixanol demonstrated the highest signal strength in both hypothyroidism (ROR = 9.47) and hyperthyroidism (ROR = 5.44). Hypothyroidism and hyperthyroidism almost occurred in the first 30 days after ICM administration (76.9 % and 70 % of patients, respectively). Furthermore, the proportion of severe outcomes in hyperthyroidism was significantly higher than that in hypothyroidism (12/26 vs. 2/35, P = 0.009). ConclusionThe present study highlights the varying risks of thyroid dysfunction associated with different ICM agents, with iodixanol exhibiting the highest signal intensity. Hypothyroidism and hyperthyroidism associated with ICM generally manifest within the first month following administration. Consequently, monitoring of thyroid function during this period is strongly recommended for ICM agents presenting higher risk profiles.

A 10-Year Retrospective Cohort Study of Real-World Effectiveness of Sofosbuvir-Based Regimens for Hepatitis C in a Single Center in China

Abstract This study aimed to review the trends of hepatitis C virus (HCV) treatment over the past decade and to analyze the effectiveness of sofosbuvir (SOF)–based direct-acting antiviral regimens in the heterogeneous population of patients with chronic hepatitis C (CHC) in clinical practice. This retrospective cohort study included CHC patients attending the Sir Run Run Shaw Hospital between January 1, 2012, and December 31, 2022. All of the 194 patients treated with SOF-based regimens completed 12 weeks of treatment and were followed up for at least 12 weeks after completion of the therapy. Sustained virologic response (SVR) 12 weeks after the end of treatment was the primary endpoint. A total of 194 patients treated with SOF-based regimens were included, among which 121, 56, 10 and 7 patients received SOF + velpatasvir ± ribavirin, SOF + daclatasvir, SOF + ledipasvir or SOF + ribavirin, respectively. With 36.1%, HCV Genotype 1 predominated in CHC patients treated with SOF-based regimens, followed by Genotype 2a with 17.5% and Genotype 3 with 14.9%. Comorbidities among patients included hypertension (4.1%), diabetes (2.1%), depression (1.0%) and neoplastic disease (2.6%). All patients treated with SOF-based regimens achieved SVR. There was no association between SVR and factors such as HCV genotype, sex, age, presence of cirrhosis or previous treatment history. There were no reports of any serious adverse events in the study. This single-center retrospective study represented the latest 10-year treatment trends for HCV in real-world clinical practice and provided useful information on the excellent efficacy of SOF-based direct-acting antiviral regimens for treatment of CHC patients in Eastern China.