Publications by authors named "P R Rijnbeek"
Purpose: The generation of representative disease phenotypes is important for ensuring the reliability of the findings of observational studies. The aim of this manuscript is to outline a reproducible framework for reliable and traceable phenotype generation based on real world data for use in the Data Analysis and Real-World Interrogation Network (DARWIN EU). We illustrate the use of this framework by generating phenotypes for two diseases: pancreatic cancer and systemic lupus erythematosus (SLE).
View Article and Find Full Text PDFBackground: 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.
Article Synopsis
- Researchers aimed to create and validate new models to predict the risk of dementia over the next five years, focusing on ease of implementation and lower complexity.
- They used logistic regression models across five observational databases, employing regularization methods like L1 and Broken Adaptive Ridge (BAR) to improve model performance with different sets of predictors, including age, sex, and disease-related factors.
- The study found that BAR was more effective for variable selection compared to L1 and that adding relevant predictors improved model accuracy, although results varied between German and US data, with the BAR model on the clinically relevant predictor set performing best overall.
Purpose: A lifestyle front office (LFO) in the hospital is a not yet existing, novel concept that can refer patients under treatment in the hospital to community-based lifestyle interventions (CBLI). The aim of this study was to identify implementation barriers and facilitators regarding the implementation of an LFO in the hospital from the perspective of CBLI-professionals and to develop evidence-based implementation strategies to reduce these identified barriers.
Methods: We conducted semi-structured interviews until data saturation, with 23 lifestyle professionals working in the community.
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.