Aioli: Standardising Drugs in the FDA Adverse Event Reporting System (FAERS) to RxNorm and Anatomical Therapeutic Chemical (ATC) Codes.

Purpose: The Food and Drug Administration Adverse Event Reporting System (FAERS) is an important source of information on suspected adverse drug reactions, but does not standardise drugs. The Adverse Event Open Learning Through Universal Standardization (AEOLUS) System Provides Standardisation of drugs in FAERS to RxNorm, but its coverage leaves room for improvement and mapping accuracy has not been established. Furthermore, drugs are not mapped to the Anatomical Therapeutic Chemical (ATC) Classification System, which is frequently used in pharmacovigilance studies.

Mapping between clinical and preclinical terminologies: eTRANSAFE's Rosetta stone approach.

Background: The eTRANSAFE project developed tools that support translational research. One of the challenges in this project was to combine preclinical and clinical data, which are coded with different terminologies and granularities, and are expressed as single pre-coordinated, clinical concepts and as combinations of preclinical concepts from different terminologies. This study develops and evaluates the Rosetta Stone approach, which maps combinations of preclinical concepts to clinical, pre-coordinated concepts, allowing for different levels of exactness of mappings.

Sex-specific performance of electrocardiographic criteria for left ventricular hypertrophy in elite athletes.

Background: In athletes, left ventricular hypertrophy (LVH) criteria based on electrocardiograms (ECGs) have been validated almost exclusively in men using echocardiography. Sex-specific cardiac magnetic resonance (CMR) validation is lacking.

Objective: To evaluate ECG-LVH criteria against contrast-enhanced CMR in male and female elite athletes.

Using Structured Codes and Free-Text Notes to Measure Information Complementarity in Electronic Health Records: Feasibility and Validation Study.

Background: Electronic health records (EHRs) consist of both structured data (eg, diagnostic codes) and unstructured data (eg, clinical notes). It is commonly believed that unstructured clinical narratives provide more comprehensive information. However, this assumption lacks large-scale validation and direct validation methods.

Disproportionality Analysis and Characterisation of Medication Errors in EudraVigilance: Exploring Findings on Sexes and Age Groups.

Background: While medication errors (MEs) have been studied in the European Medicines Agency's EudraVigilance, extensive characterisation and signal detection based on sexes and age groups have not been attempted.

Objectives: The aim of this study was to characterise all ME-related individual case safety reports in EudraVigilance and explore notable signals of disproportionate reporting (SDRs) among sexes and age groups for the 30 most frequently reported drugs.

Methods: Individual case safety reports were used from EudraVigilance reported between 2002 and 2021.

Arteriosclerotic Calcification and Atrial Fibrillation in the General Population: The Rotterdam Study.

Limited population-based data on the gender differences and association between arteriosclerotic calcification at different sites and atrial fibrillation (AF) exist. We aimed to investigate the (gender-specific) associations between arteriosclerotic calcification at different sites with the risk of AF in the general population. Arteriosclerotic calcification was quantified using computed tomography examinations between 2003 and 2006 in 2,259 participants free of AF from the population-based Rotterdam Study.

Prognostic value of the electrocardiogram in patients with bicuspid aortic valve disease.

Background: Identifying bicuspid aortic valve (BAV) patients at risk for cardiac events remains challenging and the role of the electrocardiogram (ECG) has not yet been described. Therefore, this study aims to describe ECG parameters in BAV patients, and investigate their prognostic value.

Methods: In this single-center prospective study patients with BAV without a prior aortic valve replacement (AVR) were included.

Annotation-preserving machine translation of English corpora to validate Dutch clinical concept extraction tools.

Objective: To explore the feasibility of validating Dutch concept extraction tools using annotated corpora translated from English, focusing on preserving annotations during translation and addressing the scarcity of non-English annotated clinical corpora.

Materials And Methods: Three annotated corpora were standardized and translated from English to Dutch using 2 machine translation services, Google Translate and OpenAI GPT-4, with annotations preserved through a proposed method of embedding annotations in the text before translation. The performance of 2 concept extraction tools, MedSpaCy and MedCAT, was assessed across the corpora in both Dutch and English.

Impact of QRS misclassifications on heart-rate-variability parameters (results from the CARLA cohort study).

Background: Heart rate variability (HRV), an important marker of autonomic nervous system activity, is usually determined from electrocardiogram (ECG) recordings corrected for extrasystoles and artifacts. Especially in large population-based studies, computer-based algorithms are used to determine RR intervals. The Modular ECG Analysis System MEANS is a widely used tool, especially in large studies.

The NOS1AP gene rs10494366 common genetic variant does not modify the risk of sudden cardiac death in users of digoxin.

Aims: Common genetic variations in the nitric oxide synthase-1 adaptor protein (NOS1AP) gene are associated with QT-interval prolongation. In a previous study, we observed an association between the rs10494366 variant of this gene and an increased QT-interval shortening in digoxin users. As QT-interval shortening is a risk factor for sudden cardiac death (SCD), in this study, we investigated whether the association between digoxin use and risk of SCD differs in participants with different NOS1AP rs10494366 genotypes.

Using clinical text to refine unspecific condition codes in Dutch general practitioner EHR data.

Objective: Observational studies using electronic health record (EHR) databases often face challenges due to unspecific clinical codes that can obscure detailed medical information, hindering precise data analysis. In this study, we aimed to assess the feasibility of refining these unspecific condition codes into more specific codes in a Dutch general practitioner (GP) EHR database by leveraging the available clinical free text.

Methods: We utilized three approaches for text classification-search queries, semi-supervised learning, and supervised learning-to improve the specificity of ten unspecific International Classification of Primary Care (ICPC-1) codes.

Real-world treatment trajectories of adults with newly diagnosed asthma or COPD.

Background: There is a lack of knowledge on how patients with asthma or chronic obstructive pulmonary disease (COPD) are globally treated in the real world, especially with regard to the initial pharmacological treatment of newly diagnosed patients and the different treatment trajectories. This knowledge is important to monitor and improve clinical practice.

Methods: This retrospective cohort study aims to characterise treatments using data from four claims (drug dispensing) and four electronic health record (EHR; drug prescriptions) databases across six countries and three continents, encompassing 1.

Parasitic infections related to anti-type 2 immunity monoclonal antibodies: a disproportionality analysis in the food and drug administration's adverse event reporting system (FAERS).

Monoclonal antibodies (mAbs) targeting immunoglobulin E (IgE) [omalizumab], type 2 (T2) cytokine interleukin (IL) 5 [mepolizumab, reslizumab], IL-4 Receptor (R) α [dupilumab], and IL-5R [benralizumab]), improve quality of life in patients with T2-driven inflammatory diseases. However, there is a concern for an increased risk of helminth infections. The aim was to explore safety signals of parasitic infections for omalizumab, mepolizumab, reslizumab, dupilumab, and benralizumab.

Heart rate: an accessible risk indicator in adult congenital heart disease.

Background: Higher resting heart rate has been described as a risk factor for adverse outcome in healthy individuals and cardiovascular patients. The aim of this study was to evaluate resting heart rate as risk factor in adult congenital heart disease (ACHD).

Methods: In this prospective observational cohort study, patients with moderate or complex ACHD were included at routine outpatient visit.

The added value of text from Dutch general practitioner notes in predictive modeling.

Objective: This work aims to explore the value of Dutch unstructured data, in combination with structured data, for the development of prognostic prediction models in a general practitioner (GP) setting.

Materials And Methods: We trained and validated prediction models for 4 common clinical prediction problems using various sparse text representations, common prediction algorithms, and observational GP electronic health record (EHR) data. We trained and validated 84 models internally and externally on data from different EHR systems.

Electrocardiographic parameters and the risk of new-onset atrial fibrillation in the general population: the Rotterdam Study.

Aims: We aimed to assess the (shape of the) association and sex differences in the link between electrocardiographic parameters and new-onset atrial fibrillation (AF).

Methods And Results: A total of 12 212 participants free of AF at baseline from the population-based Rotterdam Study were included. Up to five repeated measurements of electrocardiographic parameters including PR, QRS, QT, QT corrected for heart rate (QTc), JT, RR interval, and heart rate were assessed at baseline and follow-up examinations.

Does Using a Stacking Ensemble Method to Combine Multiple Base Learners Within a Database Improve Model Transportability?

We investigated a stacking ensemble method that combines multiple base learners within a database. The results on external validation across four large databases suggest a stacking ensemble could improve model transportability.

Challenges of Estimating Global Feature Importance in Real-World Health Care Data.

Feature importance is often used to explain clinical prediction models. In this work, we examine three challenges using experiments with electronic health record data: computational feasibility, choosing between methods, and interpretation of the resulting explanation. This work aims to create awareness of the disagreement between feature importance methods and underscores the need for guidance to practitioners how to deal with these discrepancies.

The reporting of neuropsychiatric symptoms in electronic health records of individuals with Alzheimer's disease: a natural language processing study.

Background: Neuropsychiatric symptoms (NPS) are prevalent in the early clinical stages of Alzheimer's disease (AD) according to proxy-based instruments. Little is known about which NPS clinicians report and whether their judgment aligns with proxy-based instruments. We used natural language processing (NLP) to classify NPS in electronic health records (EHRs) to estimate the reporting of NPS in symptomatic AD at the memory clinic according to clinicians.

Heart Rate Variability and Incident Type 2 Diabetes in General Population.

Context: Hyperglycemia and autonomic dysfunction are bidirectionally related.

Objective: We investigated the association of longitudinal evolution of heart rate variability (HRV) with incident type 2 diabetes (T2D) among the general population.

Methods: We included 7630 participants (mean age 63.

ECG Changes during Adult Life in Fabry Disease: Results from a Large Longitudinal Cohort Study.

Fabry disease (FD) is an X-linked, lysosomal storage disorder leading to severe cardiomyopathy in a significant proportion of patients. To identify ECG markers that reflect early cardiac involvement and disease progression, we conducted a long term retrospective study in a large cohort of FD patients. A total of 1995 ECGs from 133 patients with classical FD (64% females, 80% treated with enzyme replacement therapy), spanning 20 years of follow-up, were compared to ECGs from 3893 apparently healthy individuals.