Abstract
European legislation brings about a new responsibility for occupational medicine. However, with the commercial approach and the focus on sickness absence management the attention for detection and prevention of work-related health effects has been shifted away.
In the last decade, the association between industrial dust exposure and COPD, and exposure
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to respiratory allergens and (respiratory) allergic diseases has been clearly demonstrated. Many different high-molecular weight (HMW) aeroallergens from different occupations (bakers, laboratory animal workers, and hospital workers) have been identified as inducing occupational asthma.
For exposure to aeroallergens no save health-based exposure standards have been identified. This leaves workers inadequately protected from developing respiratory disease. Early detection of workers developing COPD as well as allergic diseases is therefore needed. However, validated methods for early diagnosis of workers at risk are sparsely developed.
With the use of statistical methods a diagnostic process can be imitated. Prediction rules reflect the sequential diagnostic process and evaluate which of the findings contribute to the estimation of the diagnostic probability. The rules either estimate the probability of a diagnostic outcome or link personal characteristics and objective factors for prognostic purposes.
This thesis is directed towards the question how all putative diagnostic data collected in occupational health practice can be used to formulate which combination of findings may contribute to the prediction of the likelihood of presence of an occupational (allergic) respiratory disease. Probability estimation can be assessed using questionnaires, data from medical tests, and results from exposure measurements. Using diagnostic and prognostic rules, the probability of the presence or occurrence of an occupational (respiratory or allergic) disease can be predicted in an individual worker and can be used to identify worker groups at different risk levels.
A diagnostic study demonstrated that, early detection of workers with COPD can be based on predictors derived from a standard questionnaire. Stratification into risk groups showed a valid and cost reducing method to be used in occupational health practice.
For the detection of workers sensitized to high-molecular weight allergens stratifying workers into a group with a high and a group with a low sensitization rate, is the most appropriate first step. Medical examination and occupational hygiene interventions can be based on this stratification. In workers with a high sensitization rate, medical examination can concentrate on occupational allergic diseases responsible for absenteeism and doctors visit. The individual medical investigation can focus on allergic rhinitis, conjunctivitis, contact urticaria, asthma, and lung functiom. In workers with a low sensitization rate at baseline, the probability of future sensitization can be estimated by a two-step prognostic rule based on questionnaire items and IgE serology (indicating atopy). By applying the rule, workers at high, medium and low risk of becoming sensitized can be detected and preselected for health surveillance objectives.
Implementation of these rules in workers exposed to other HMW allergens (latex, flour) needs specific validation. However, these rules may initially be applied in conditions of exposure to HMW allergens of unknown origin (biotechnology).
The described algorithms may contribute to convincing decisions by occupational physicians.
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