While socioeconomic status (SES) and migration background have been linked to complicated lower respiratory tract infections (LRTIs) in population-based studies, their predictive value in primary care remains unclear. Using routine care data from Dutch general practices (Leiden-The Hague-Zoetermeer region, n approx 750,000 adult patients, 2014 to 2023, excluding COVID-19 years), linked to sociodemographic and hospital claims data, we developed a multivariable logistic regression model to predict 30-day hospitalisation or death following LRTI. Among 186,094 LRTI episodes, 2.19% were classified as complicated. After adjusting for established clinical factors, SES was a strong predictor, whereas migration background was not. Patients in the lowest SES category had an adjusted odds ratio of 1.46 (95%CI: 1.31 – 1.62) for a complicated course compared to the highest. The incorporation of SES into clinical decision tools and guidelines has the potential to enhance risk-stratification of patients with LRTI in daily practice of primary care, thereby supporting more equitable care.
OptoLoop: An optogenetic tool to probe the functional role of genome organization
The genome folds inside the cell nucleus into hierarchical architectural features, such as chromatin loops and domains. If and how this genome organization influences the