The predictive value of socioeconomic status and migration background for complicated lower respiratory tract infections in primary care

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Abstract

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 ≈ 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.

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