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Adverse Drug Events in Ambulatory Care: A Cross-Sectional Study. 门诊药物不良事件:一项横断面研究。
IF 4 2区 医学 Q1 PHARMACOLOGY & PHARMACY Pub Date : 2025-04-01 Epub Date: 2024-12-02 DOI: 10.1007/s40264-024-01501-w
Joseph M Plasek, Mary G Amato, Abigail Salem, Dinah Foer, Stuart Lipsitz, Gretchen Purcell Jackson, David W Bates, Li Zhou

Background: Adverse drug events (ADEs) are understudied in the ambulatory care setting. We aim to estimate the prevalence and characteristics of ADEs in outpatient care using electronic health records (EHRs).

Methods: This cross-sectional study included EHR data for patients who had an outpatient encounter at an academic medical center from 1 October 2018 through 31 December 2019. We developed a stratified sampling strategy based on a comprehensive set of 994 ADE-related International Classification of Disease (ICD-10) codes to identify clinical encounters and notes likely to contain ADEs. Within each ICD-10 likelihood group, clinical notes were randomly sampled and annotated for present or possible ADE-drug relationships and severity. The overall estimated population prevalence of ADEs presenting in the outpatient setting was calculated. The generalizability of the findings was assessed by comparing ICD-10 code frequencies against a large commercial database.

Results: The study included 3126 notes (unique patient encounters) from 2882 unique patients. Of these, 1383 patient encounters (44.2%) had a present or possible ADE documented (6308 mentions). Of the 6038 ADEs mentioned, 14.1% were hypersensitivity reactions, 1.1% were life-threatening, 22.4% were serious, and 60.4% were significant. Main causal agents included anti-infectives (19.3%), central nervous system agents (12.8%), and cardiovascular agents (11.5%). The overall prevalence of present ADEs mentioned in the clinical notes was estimated to be 1.97 per 100 patient encounters (or 2.52 per 100 patient encounters when possible ADEs are included).

Conclusions: This study identified the overall population prevalence per encounter of ADEs in the outpatient population by leveraging ICD-10 codes and investigating ADEs documented in clinical notes. Understanding the ADE characteristics in a large corpus of outpatient documentation advances pharmacovigilance knowledge, enhancing the detection, monitoring, and prevention of ADEs in ambulatory care.

背景:药物不良事件(ADEs)在门诊护理机构的研究尚不充分。我们的目的是使用电子健康记录(EHRs)估计门诊护理中ade的患病率和特征。方法:本横断面研究包括2018年10月1日至2019年12月31日在学术医疗中心门诊就诊的患者的电子病历数据。我们根据994个与ade相关的国际疾病分类(ICD-10)代码制定了分层抽样策略,以识别可能包含ade的临床接触和记录。在每个ICD-10似然组中,随机抽取临床记录并注释当前或可能的ade与药物的关系和严重程度。计算了在门诊出现的ade的总体估计人群患病率。通过将ICD-10编码频率与大型商业数据库进行比较,评估了研究结果的普遍性。结果:该研究包括来自2882名独特患者的3126份记录(独特的患者遭遇)。其中,1383例(44.2%)患者存在或可能存在ADE(6308次提及)。其中,超敏反应占14.1%,危及生命反应占1.1%,严重反应占22.4%,严重反应占60.4%。主要病因包括抗感染药物(19.3%)、中枢神经系统药物(12.8%)和心血管药物(11.5%)。临床记录中提到的目前ade的总体患病率估计为每100例患者1.97例(如果包括可能的ade,则为每100例患者2.52例)。结论:本研究通过利用ICD-10代码和调查临床记录中的ade,确定了门诊人群中每次遇到ade的总体人群患病率。了解大量门诊文献中的ADE特征可以提高药物警戒知识,增强门诊护理中ADE的检测、监测和预防。
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引用次数: 0
Call to action: Pharmaceutical residues in the environment: threats to ecosystems and human health. 行动呼吁:环境中的药物残留:对生态系统和人类健康的威胁。
IF 4 2区 医学 Q1 PHARMACOLOGY & PHARMACY Pub Date : 2025-04-01 Epub Date: 2024-12-10 DOI: 10.1007/s40264-024-01497-3
Carlotta Lunghi, Maria Rosa Valetto, Anna Barra Caracciolo, Irene Bramke, Sergio Caroli, Paola Bottoni, Sara Castiglioni, Salvatore Crisafulli, Laura Cuzzolin, Paola Deambrosis, Valentina Giunchi, Jacopo Grisotto, Antonio Marcomini, Ugo Moretti, Vitalia Murgia, Jayesh Pandit, Stefano Polesello, Elisabetta Poluzzi, Roberto Romizi, Nicoletta Scarpa, Giovanna Scroccaro, Raffaella Sorrentino, Anders Sundström, John Wilkinson, Giovanna Paolone
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引用次数: 0
Prenatal and Early Childhood Exposure to Proton Pump Inhibitors and Antibiotics and the Risk of Childhood Cancer: A Nationwide Population-Based Cohort Study. 产前和儿童早期暴露于质子泵抑制剂和抗生素与儿童癌症的风险:一项基于全国人群的队列研究。
IF 4 2区 医学 Q1 PHARMACOLOGY & PHARMACY Pub Date : 2025-04-01 Epub Date: 2024-12-12 DOI: 10.1007/s40264-024-01500-x
Unnur Gudnadottir, Emma Fransson, Gustaf Ljungman, Anna Wikman, Erika Vlieghe, Lars Engstrand, Nele Brusselaers

Background: Our microbiome is established during infancy, a time important for later health and long-term effects. Proton pump inhibitors and antibiotics are regularly prescribed during pregnancy. Both drugs cause microbiome disturbance and have been associated with increased cancer risk in adults, but effects of these drugs on the growing foetus and infant remain understudied.

Aim: The aim of this study is to study the association between prenatal and early life proton pump inhibitor and antibiotics exposure and the risk of childhood cancer.

Methods: This study is a retrospective population-based cohort design, using registry data on all births (n = 722,372) in Sweden between 2006 and 2016, according to the STROBE checklist. For women who had multiple children in the timeframe of the study, only the first child during the time period was included in the cohort. Exposure was defined as either ≥ 1 proton pump inhibitor or antibiotics prescription during pregnancy, or during the first 2 years of life. Outcome was defined as cancer at any time during the follow-up or cancer after the age of 2 years for early life exposure. Multivariable Cox proportional hazard models were used to calculate hazard ratios.

Results: In total, 1091 (0.2%) children were diagnosed with malignant cancer during the follow-up. Prenatal exposure to proton pump inhibitors and antibiotics were not associated with an increased risk of cancer. Regarding early life exposure, proton pump inhibitors were associated with an increased risk of cancer at age two or older (adjusted hazard ratio [aHR] 3.68, 95% confidence interval [CI] 2.24-6.06).

Conclusions: We did not find evidence that prenatal proton pump inhibitors and antibiotics were associated with overall childhood cancer. However, proton pump inhibitors during early life were associated with an increased risk of childhood cancer, but indication on drug use was not available and confounding by indication may be present.

背景:我们的微生物群是在婴儿期建立的,这一时期对以后的健康和长期影响很重要。质子泵抑制剂和抗生素在怀孕期间经常开处方。这两种药物都会引起微生物群紊乱,并与成人癌症风险增加有关,但这些药物对生长中的胎儿和婴儿的影响仍未得到充分研究。目的:本研究的目的是研究产前和生命早期质子泵抑制剂和抗生素暴露与儿童癌症风险的关系。方法:本研究采用基于人群的回顾性队列设计,根据STROBE检查表,使用瑞典2006年至2016年间所有出生的登记数据(n = 722,372)。对于在研究期间有多个孩子的女性,只有在这段时间内的第一个孩子被纳入队列。暴露被定义为在怀孕期间或生命的前2年内服用≥1种质子泵抑制剂或抗生素处方。结果被定义为随访期间的任何时间的癌症或2岁以后的癌症早期生活暴露。采用多变量Cox比例风险模型计算风险比。结果:随访期间确诊恶性肿瘤患儿1091例(0.2%)。产前暴露于质子泵抑制剂和抗生素与癌症风险增加无关。关于生命早期暴露,质子泵抑制剂与两岁或两岁以上癌症风险增加相关(校正风险比[aHR] 3.68, 95%可信区间[CI] 2.24-6.06)。结论:我们没有发现产前质子泵抑制剂和抗生素与总体儿童癌症相关的证据。然而,质子泵抑制剂在生命早期与儿童癌症风险增加有关,但药物使用的指征尚不明确,可能存在指征混淆。
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引用次数: 0
Use of Reporting Recommendation Intended for Pharmaceutical Risk Minimisation Evaluation Studies (RIMES) Checklist in Risk Minimisation/Mitigation Studies: A Review and Survey. 在风险最小化/缓解研究中使用药物风险最小化评估研究(RIMES)清单的报告建议:回顾和调查。
IF 4 2区 医学 Q1 PHARMACOLOGY & PHARMACY Pub Date : 2025-04-01 Epub Date: 2024-12-17 DOI: 10.1007/s40264-024-01504-7
Samantha E Duckworth, Sophie Druelles, Emily Brouwer, David A Brown, Katja M Hakkarainen, Sonia Guleria

Introduction: The Reporting Recommendation Intended for Pharmaceutical Risk Minimisation Evaluation Studies (RIMES) checklist is endorsed by the European Network of Centres for Pharmacoepidemiology and Pharmacovigilance (ENCePP) and is tailored for studies assessing Risk Minimisation Measures and Risk Evaluation and Mitigation Strategy (RMM/REMS) effectiveness; however, its awareness and usage remain unknown. We evaluated the implementation of the RIMES checklist in RMM/REMS effectiveness studies registered in the EUPAS register during 01 December 2017- 01 January 2024. Furthermore, the awareness and utilization of the RIMES checklist among researchers conducting RMM/REMS effectiveness studies was assessed.

Methods: The European Union Post-Authorisation Study (EUPAS) Register was reviewed to identify studies conducted in at least one European country within the specified timeframe. Data were extracted from the online EUPAS registrations, including uploaded study documents. Additionally, a survey was distributed through at International Society of Pharmacoepidemiology (ISPE) to assess awareness and checklist utilisation among researchers. Findings from both the review and the survey were reported descriptively.

Results: Among 44 studies included in the review, cross-sectional questionnaire-based surveys (n = 28, 64%), and retrospective cohort studies using secondary data (n = 13, 30%) were frequently used study designs. Oncology (n = 12, 27%) and pregnancy-related conditions (n = 7, 16%) were frequently reported therapeutic areas. Most studies were required by regulators and typically evaluated the additional RMM/REMS. The awareness and usage of the RIMES checklist was low, while the ENCePP checklist was used frequently. Some researchers considered the ENCePP checklist adequate for RMM/REMS studies, while few advocated for the RIMES checklist.

Conclusion: The awareness and utilisation of the specific RIMES checklist designed for studies evaluating RMM/REMS was limited, indicating a need for improving awareness and utilisation of RIMES and harmonisation of existing guidance and frameworks for RMM/REMS effectiveness studies.

简介:用于药物风险最小化评估研究(RIMES)清单的报告建议由欧洲药物流行病学和药物警戒中心网络(ENCePP)批准,并为评估风险最小化措施和风险评估和缓解策略(RMM/REMS)有效性的研究量身定制;然而,它的意识和使用仍然未知。我们评估了2017年12月1日至2024年1月1日期间在EUPAS注册的RMM/REMS有效性研究中RIMES清单的实施情况。此外,还评估了开展RMM/REMS有效性研究的研究人员对RIMES检查表的认识和使用情况。方法:审查欧盟授权后研究(EUPAS)登记册,以确定在指定时间框架内至少在一个欧洲国家进行的研究。数据从在线EUPAS注册中提取,包括上传的研究文件。此外,通过国际药物流行病学学会(ISPE)分发了一项调查,以评估研究人员的意识和清单的使用情况。综述和调查的结果都是描述性的。结果:在纳入的44项研究中,以横断面问卷为基础的调查(n = 28, 64%)和采用二手资料的回顾性队列研究(n = 13, 30%)是常用的研究设计。肿瘤(n = 12.27%)和妊娠相关疾病(n = 7.16%)是经常报道的治疗领域。大多数研究是监管机构要求的,通常评估额外的RMM/REMS。RIMES检查表的认知度和使用率较低,而ENCePP检查表的使用率较高。一些研究人员认为ENCePP检查表足以用于RMM/REMS研究,而很少有人提倡使用RIMES检查表。结论:为评估RMM/REMS的研究而设计的特定RIMES清单的认识和利用是有限的,这表明需要提高对RIMES的认识和利用,并协调RMM/REMS有效性研究的现有指导和框架。
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引用次数: 0
Comment on: "The Use of Multiple Medications During Pregnancy Among an Ethnically Diverse Population in South-Eastern Melbourne: A Retrospective Analysis to Explore Potential Risks and Complications".
IF 4 2区 医学 Q1 PHARMACOLOGY & PHARMACY Pub Date : 2025-04-01 Epub Date: 2025-03-03 DOI: 10.1007/s40264-025-01532-x
Minh-Hoang Tran, Kim-Huong Truong-Nguyen
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引用次数: 0
Drug-Induced Cognitive Impairment. 药物性认知障碍。
IF 4 2区 医学 Q1 PHARMACOLOGY & PHARMACY Pub Date : 2025-04-01 Epub Date: 2024-12-24 DOI: 10.1007/s40264-024-01506-5
Arne Reimers, Per Odin, Hanna Ljung

Drug-induced cognitive impairment (DICI) is a well-established, yet under-recognised, complication of many types of pharmacological treatment. While there is a large body of scientific literature on DICI, most papers are about drug-induced dementia in the elderly and one specific drug class. However, DICI also comprises subclinical symptoms, domain-specific forms of cognitive impairment as well as mild cognitive impairment (MCI), and delirium. Even mild forms of DICI, if not recognised as such, can have deleterious and life-long consequences. In addition, DICI also occurs in younger adults and in children, and has been reported with many different drug classes. The aim of this review is to raise awareness of DICI by providing an overview on the type(s) and symptoms of observed DICI and the suspected underlying mechanism(s) for various drug classes: antiseizure medications, antidepressants, antiparkinsonian drugs, antipsychotics, lithium, benzodiazepines/Z-drugs, opioids, first-generation antihistamines, drugs for urinary incontinence, proton pump inhibitors, glucocorticoids, NSAIDs, statins, antihypertensives, and chemotherapeutic agents.

药物性认知障碍(DICI)是一种公认的,但尚未得到充分认识的多种药物治疗并发症。虽然有大量关于DICI的科学文献,但大多数论文都是关于老年人的药物性痴呆和一种特定的药物类别。然而,DICI也包括亚临床症状、领域特定形式的认知障碍、轻度认知障碍(MCI)和谵妄。即使是轻度的DICI,如果不加以认识,也会造成有害的终身后果。此外,DICI也发生在年轻人和儿童中,据报道与许多不同的药物类别有关。本综述的目的是通过概述观察到的DICI的类型和症状以及各种药物类别(抗癫痫药物、抗抑郁药物、抗帕金森药物、抗精神病药物、锂、苯二氮卓类药物/ z类药物、阿片类药物、第一代抗组胺药、尿失禁药物、质子泵抑制剂、糖皮质激素、非甾体抗炎药、他汀类药物、降压药和化疗药物)的潜在机制来提高对DICI的认识。
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引用次数: 0
Leveraging Natural Language Processing and Machine Learning Methods for Adverse Drug Event Detection in Electronic Health/Medical Records: A Scoping Review. 利用自然语言处理和机器学习方法在电子健康/医疗记录中检测药物不良事件:范围审查。
IF 4 2区 医学 Q1 PHARMACOLOGY & PHARMACY Pub Date : 2025-04-01 Epub Date: 2025-01-09 DOI: 10.1007/s40264-024-01505-6
Su Golder, Dongfang Xu, Karen O'Connor, Yunwen Wang, Mahak Batra, Graciela Gonzalez Hernandez

Background: Natural language processing (NLP) and machine learning (ML) techniques may help harness unstructured free-text electronic health record (EHR) data to detect adverse drug events (ADEs) and thus improve pharmacovigilance. However, evidence of their real-world effectiveness remains unclear.

Objective: To summarise the evidence on the effectiveness of NLP/ML in detecting ADEs from unstructured EHR data and ultimately improve pharmacovigilance in comparison to other data sources.

Methods: A scoping review was conducted by searching six databases in July 2023. Studies leveraging NLP/ML to identify ADEs from EHR were included. Titles/abstracts were screened by two independent researchers as were full-text articles. Data extraction was conducted by one researcher and checked by another. A narrative synthesis summarises the research techniques, ADEs analysed, model performance and pharmacovigilance impacts.

Results: Seven studies met the inclusion criteria covering a wide range of ADEs and medications. The utilisation of rule-based NLP, statistical models, and deep learning approaches was observed. Natural language processing/ML techniques with unstructured data improved the detection of under-reported adverse events and safety signals. However, substantial variability was noted in the techniques and evaluation methods employed across the different studies and limitations exist in integrating the findings into practice.

Conclusions: Natural language processing (NLP) and machine learning (ML) have promising possibilities in extracting valuable insights with regard to pharmacovigilance from unstructured EHR data. These approaches have demonstrated proficiency in identifying specific adverse events and uncovering previously unknown safety signals that would not have been apparent through structured data alone. Nevertheless, challenges such as the absence of standardised methodologies and validation criteria obstruct the widespread adoption of NLP/ML for pharmacovigilance leveraging of unstructured EHR data.

背景:自然语言处理(NLP)和机器学习(ML)技术可以帮助利用非结构化自由文本电子健康记录(EHR)数据来检测药物不良事件(ADEs),从而提高药物警惕性。然而,它们在现实世界中的有效性尚不清楚。目的:总结NLP/ML从非结构化电子病历数据中检测ade的有效性,并与其他数据来源进行比较,最终提高药物警惕性。方法:于2023年7月检索6个数据库进行范围综述。纳入了利用NLP/ML从电子病历中识别ade的研究。题目/摘要与全文文章一样由两名独立研究人员筛选。数据提取由一名研究员进行,并由另一名研究员进行检查。一篇叙述性综合综述了研究技术、ADEs分析、模型性能和药物警戒影响。结果:7项研究符合纳入标准,涵盖了广泛的不良事件和药物。观察到基于规则的NLP,统计模型和深度学习方法的使用。具有非结构化数据的自然语言处理/ML技术改进了对未报告的不良事件和安全信号的检测。然而,在不同的研究中使用的技术和评价方法存在很大的差异,并且在将研究结果纳入实践方面存在局限性。结论:自然语言处理(NLP)和机器学习(ML)在从非结构化电子病历数据中提取有关药物警戒的有价值的见解方面具有很大的可能性。这些方法已证明在识别特定不良事件和发现以前未知的安全信号方面的熟练程度,这些信号仅通过结构化数据是不明显的。然而,诸如缺乏标准化方法和验证标准等挑战阻碍了NLP/ML在利用非结构化电子病历数据进行药物警戒方面的广泛采用。
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引用次数: 0
Clinical Relatedness and Stability of vigiVec Semantic Vector Representations of Adverse Events and Drugs in Pharmacovigilance. 药物警戒中不良事件和药物的vivivec语义向量表示的临床相关性和稳定性。
IF 4 2区 医学 Q1 PHARMACOLOGY & PHARMACY Pub Date : 2025-04-01 Epub Date: 2025-01-20 DOI: 10.1007/s40264-024-01509-2
Nils Erlanson, Joana Félix China, Henric Taavola, G Niklas Norén

Introduction: Individual case reports are essential to identify and assess previously unknown adverse effects of medicines. On these reports, information on adverse events (AEs) and drugs are encoded in hierarchical terminologies. Encoding differences may hinder the retrieval and analysis of clinically related reports relevant to a topic of interest. Recent studies have explored the use of data-driven semantic vector representations to support analysis of pharmacovigilance data.

Objective: This study aims to evaluate the stability and clinical relatedness of vigiVec, a semantic vector representation for codes of AEs and drugs.

Methods: vigiVec is a published adaptation to pharmacovigilance of the publicly available Word2Vec model, applied to structured data instead of free text. It provides vector representations for MedDRA® Preferred Terms and WHODrug Global active ingredients, learned from reporting patterns in VigiBase, the WHO global database of adverse event reports for medicines and vaccines. For this study, a 20-dimensional Skip-gram architecture with window size 250 was used. Our evaluation focused on nearest neighbors identified by the cosine similarity of vigiVec vector representations. Clinical relatedness was measured through term intruder detection, whereby a medical doctor was tasked to identify a randomly selected term-the intruder-included among the four nearest neighbors to a specific AE or drug. Stability was measured as the average overlap in the ten nearest neighbors for each AE or drug, in repeated fittings of vigiVec.

Results: Among the ten nearest neighbors, 1.8 AEs on average belonged to the same MedDRA High Level Term (HLT; e.g., coagulopathies), and 1.3 drugs belonged to the same Anatomical Therapeutic Chemical level 3 (ATC-3; e.g., opioids). In the intruder detection task, when neighbors and intruders were both chosen from the same HLT, the intruder detection rate was 46%. When selected from different HLTs, it was 79%. By random chance, we should expect 20% (1 in 5). Corresponding rates for drugs were 42% in same ATC-3 and 65% in different ATC-3. The stability of nearest neighbors was 80% for AEs and 64% for drugs.

Conclusion: Nearest neighbors identified with vigiVec are stable and show high level of clinical relatedness. They are often from different parts of the existing hierarchies and complement these.

个人病例报告对于识别和评估以前未知的药物不良反应至关重要。在这些报告中,有关不良事件(ae)和药物的信息以分层术语编码。编码差异可能会阻碍检索和分析与感兴趣的主题相关的临床相关报告。最近的研究探索了使用数据驱动的语义向量表示来支持药物警戒数据的分析。目的:评价用于ae和药物编码的语义向量表示方法vigiVec的稳定性和临床相关性。方法:vigiVec是一个公开的Word2Vec模型的药物警戒改编,应用于结构化数据而不是自由文本。它从世卫组织药物和疫苗不良事件报告全球数据库VigiBase的报告模式中学习,为MedDRA®优选术语和世卫组织药物全球活性成分提供了载体表示。在本研究中,使用了窗口大小为250的20维Skip-gram架构。我们的评估集中在通过vigiVec向量表示的余弦相似性识别的最近邻上。临床相关性是通过术语侵入检测来测量的,医生的任务是在特定AE或药物的四个最近邻居中随机选择一个术语——侵入者。稳定性测量为每个AE或药物的十个近邻的平均重叠,在重复的vivivec中。结果:在10个最近邻中,平均有1.8个ae属于同一MedDRA高水平项(HLT);例如,凝血功能),1.3种药物属于相同的解剖治疗化学3级(ATC-3;例如,阿片类药物)。在入侵者检测任务中,当邻居和入侵者都从同一HLT中选择时,入侵者检测率为46%。当从不同的hlt中选择时,它是79%。随机概率为20%(1 / 5)。相同ATC-3的药物对应率为42%,不同ATC-3的药物对应率为65%。ae的近邻稳定性为80%,药物的近邻稳定性为64%。结论:vigiVec鉴定的最近邻居关系稳定,具有较高的临床亲缘关系。它们通常来自现有层次结构的不同部分,并对这些部分进行补充。
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引用次数: 0
Trends in Proton Pump Inhibitor Use in Sweden by Sex and Age: A Drug Utilisation Study. 瑞典按性别和年龄分类的质子泵抑制剂使用趋势:一项药物利用研究。
IF 4 2区 医学 Q1 PHARMACOLOGY & PHARMACY Pub Date : 2025-04-01 Epub Date: 2024-12-08 DOI: 10.1007/s40264-024-01502-9
Nele Brusselaers, Unnur Gudnadottir, Lars Engstrand, Helene E Lilja

Background: Proton pump inhibitors (PPIs) are among the most popular drugs worldwide. Yet, there are concerns on long-term safety and poor adherence to prescription guidelines. Off-label use in children and increasing maintenance use in older adults may be particularly worrisome.

Objectives: To assess differences in PPI use by age, sex calendar year and PPI type, and to explore potential underlying indications (ulcerogenic drugs, and indications) in Sweden.

Methods: Proton pump inhibitor drug utilisation study based on the Swedish nationwide prescribed drug (2006-2023) and patient registries (2006-2022).

Results: Proton pump inhibitors were used by 14.4% (women) and 10.5% (men) of adults; and 1.0-1.5% of children and adolescents (aged < 20 years). Proton pump inhibitor use was higher in women in all age-groups except small children (aged < 5 years). Proton pump inhibitor use has increased in all age groups, especially in young children (aged < 10 years) and the oldest groups (aged > 65 years). Proton pump inhibitor users aged > 85 years filled most prescriptions with an annual average of 9.5 (men), 11.6 (women) prescriptions. Most prescriptions were for omeprazole and esomeprazole: 63.7% and 23.5% in adults; 23.5% and 44.7% in children (2023). Prescriptions for other drugs for peptic ulcers/reflux became rare, with 99% of prescriptions in this category being PPIs by 2023. Gastro-intestinal diagnoses were predominantly recorded in men, became less prevalent and only explained part of PPI use, while ulcerogenic drugs were common (particularly in women), suggesting PPIs are regularly used for gastroprotection.

Conclusion: Proton pump inhibitor use has doubled in children and increased 50% in adults over the study period, in both sexes, while recorded gastrointestinal indications decreased. Alternative therapies were rarely prescribed in Sweden.

背景:质子泵抑制剂(PPIs)是世界上最流行的药物之一。然而,人们担心长期的安全性和对处方指南的不严格遵守。儿童超说明书使用和老年人维持使用的增加可能特别令人担忧。目的:评估年龄、性别、日历年和PPI类型在PPI使用方面的差异,并探讨瑞典潜在的潜在适应症(溃疡性药物和适应症)。方法:基于瑞典全国处方药(2006-2023)和患者登记(2006-2022)的质子泵抑制剂药物利用研究。结果:14.4%(女性)和10.5%(男性)的成年人使用质子泵抑制剂;儿童和青少年(年龄< 20岁)患病率为1.0-1.5%。质子泵抑制剂的使用在所有年龄组的女性中都较高,除了小孩(小于5岁)。质子泵抑制剂的使用在所有年龄组中都有所增加,特别是在幼儿(年龄< 10岁)和老年组(年龄在50 - 65岁)中。50 ~ 85岁的质子泵抑制剂使用者处方最多,平均每年处方9.5张(男性),11.6张(女性)。处方以奥美拉唑和埃索美拉唑居多,分别占成人处方的63.7%和23.5%;儿童23.5%和44.7%(2023年)。治疗消化性溃疡/反流的其他药物处方变得罕见,到2023年,这类处方中99%是ppi。胃肠道诊断主要记录在男性中,变得不那么普遍,只能解释部分PPI的使用,而溃疡性药物很常见(特别是在女性中),这表明PPI经常用于胃保护。结论:在研究期间,质子泵抑制剂在儿童中的使用翻了一番,在成人中的使用增加了50%,在两性中都是如此,而记录的胃肠道适应症减少了。替代疗法在瑞典很少被开处方。
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引用次数: 0
OpenPVSignal Knowledge Graph: Pharmacovigilance Signal Reports in a Computationally Exploitable FAIR Representation.
IF 4 2区 医学 Q1 PHARMACOLOGY & PHARMACY Pub Date : 2025-04-01 Epub Date: 2025-02-08 DOI: 10.1007/s40264-024-01503-8
Achilleas Chytas, George Gavriilides, Anargyros Kapetanakis, Alix de Langlais, Marie-Christine Jaulent, Pantelis Natsiavas

Introduction: Pharmacovigilance signal report (PVSR) documents contain valuable condensed information published by drug monitoring organizations, typically in a free-text format. They provide initial insights into potential links between drugs and harmful effects. Still, their unstructured format prevents this valuable information from being integrated into data-processing pipelines (e.g., to support either the investigation of drug safety signals or decision-making in the clinical context).

Objective: OpenPVSignal is a data model designed specifically to publish PVSRs via a computationally exploitable format, compliant with the FAIR (Findable, Accessible, Interoperable, Reusable) principles to promote ease of access and reusability of these valuable data.

Methods: This paper outlines the procedure for converting pharmacovigilance signals published by the World Health Organization Uppsala Monitoring Centre (WHO-UMC) into the OpenPVSignal data model, resulting in a Knowledge Graph (KG). It details each step of the process, including the technical validation by KG engineers and the qualitative verification by medical and pharmacovigilance experts, leading to the finalized KG.

Results: A total of 101 PVSRs from 2011 to 2019 were incorporated into the openly available KG.

Conclusion: The presented KG could be useful in various data-processing pipelines, including systems that support drug safety activities.

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Drug Safety
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