The Allergy Prevention L·OVE: a public repository for allergy prevention research

Article type
Authors
Apfelbacher C1, Ávila-Oliver C2, Hasenpusch C1, Kuper P1, Kuper P3, Rada G1, Sprenger A4, Sprenger A, Veloso V
1Institute of Social Medicine and Health Systems Research, Medical Faculty, Otto Von Guericke University, Magdeburg, Germany
2Epistemonikos Foundation/ Facultad de Odontología y Ciencias de la Rehabilitación, Universidad San Sebastián, Santiago, Chile; Escuela de Odontología, Facultad de Odontología y Ciencias de la Rehabilitación, Universidad San Sebastián, Santiago, Chile
3Epistemonikos Foundation/ Facultad de Odontología y Ciencias de la Rehabilitación, Universidad San Sebastián, Santiago, Chile
4Epistemonikos Foundation/ Facultad de Odontología y Ciencias de la Rehabilitación, Universidad San Sebastián, Santiago, Chile; Universidad del Desarrollo, Facultad de Medicina Clínica Alemana, Santiago, Chile
Abstract
Introduction: The field of allergy prevention is rapidly evolving, with emerging interventions showing great promise.

Objective: To present the best available evidence, the Epistemonikos Foundation and Otto von Guericke University of Magdeburg aimed to develop a continuously curated and updated evidence repository focusing on allergy prevention research. Additionally, we aimed to provide an interactive evidence map representing available evidence in a clear and intuitive manner.

Methods: A repository for allergy prevention evidence is being constructed within the Living Overview of Evidence (L·OVE), a system designed to organize evidence pertinent to a specific health condition. The process began by constructing a taxonomy encompassing various populations and interventions to prevent allergies in an iterative process between methodologists and field experts. Search strategies were formulated for each term to retrieve relevant records. Subsequently, potentially eligible systematic reviews (SRs) focusing on allergy prevention interventions were manually screened, and their included randomized controlled trials (RCTs) were incorporated into the repository. To streamline this process, automated classifiers were developed for precise evidence identification, ensuring that the Allergy Prevention L·OVE stays updated. This artificial intelligence–driven approach is designed to reduce the manual effort involved in article selection.

Results: The first year of the project is ongoing, with results displayed in the Allergy Prevention L·OVE (app.iloveevidence.com/loves/63166a1d79ce3600094bd7c0). Overall, approximately 2,000 SRs and 3,700 RCTs have been identified. Populations were categorized by life-cycle stage (eg, children, pregnant women), pre-existing allergic conditions (eg, asthma, food allergies), and people at risk of developing allergies. Interventions were organized into pharmacological, dietary, and by exposure route (eg, oral, environmental, skin). For the second year, an evidence map will be implemented to inform the number of references between populations and the corresponding interventions, detailing study designs (eg, systematic reviews, trials) at each intersection.

Conclusions: The future map visualization will allow users such as researchers, health care professionals, and people at risk of allergies to navigate and explore the evidence and to identify research gaps easily.