Application of a prediction model for work-related sensitisation in bakery workers

Autor: Meijer, E., Suarthana, E., Rooijackers, J.M., Grobbee, D.E., Jacobs, J.H., Meijster, T., de Monchy, J.G.R., van Otterloo, E., van Rooy, G.B.G.J., Spithoven, J.J., Zaat, V.A., Heederik, D.J.J., Risk Assessment of Toxic and Immunomodulatory Agents, Dep IRAS
Přispěvatelé: Risk Assessment of Toxic and Immunomodulatory Agents, Dep IRAS
Jazyk: angličtina
Rok vydání: 2010
Předmět:
Zdroj: European Respiratory Journal, 36(4), 735. European Respiratory Society
European Respiratory Journal, 36(4), 735-742. EUROPEAN RESPIRATORY SOC JOURNALS LTD
ISSN: 0903-1936
Popis: Identification of work-related allergy, particularly work-related asthma, in a (nationwide) medical surveillance programme among bakery workers requires an effective and efficient strategy.Bakers at high risk of having work-related allergy were indentified by use of a questionnaire-based prediction model for work-related sensitisation. The questionnaire was applied among 5,325 participating bakers. Sequential diagnostic investigations were performed only in those with an elevated risk. Performance of the model was evaluated in 674 randomly selected bakers who participated in the medical surveillance programme and the validation study. Clinical investigations were evaluated in the first 73 bakers referred at high risk.Overall 90% of bakers at risk of having asthma could be identified. Individuals at low risk showed 0.3-3.8% work-related respiratory symptoms, medication use or absenteeism. Predicting flour sensitisation by a simple questionnaire and score chart seems more effective at detecting work-related allergy than serology testing followed by clinical investigation in all immunoglobulin E class II-positive individuals.This prediction based stratification procedure appeared effective in detecting work-related allergy among bakers and can accurately be used for periodic examination, especially in small enterprises where delivery of adequate care is difficult. This approach may contribute to cost reduction.
Databáze: OpenAIRE