Jonaid Badri Sadat, Rooyackers Jos, Stigter Erik, Portengen Lützen, Krop Esmeralda, Heederik Dick
Division of Environmental Epidemiology, Institute for Risk Assessment Sciences (IRAS), Utrecht University, Utrecht, The Netherlands.
Arak University of Medical Sciences, Arak, Iran.
Occup Environ Med. 2017 Aug;74(8):564-572. doi: 10.1136/oemed-2016-103934. Epub 2017 Mar 17.
Occupational allergic diseases are a major problem in some workplaces like in the baking industry. Diagnostic rules have been used in surveillance but not yet in the occupational respiratory clinic.
To develop diagnostic models predicting baker's asthma and rhinitis among bakery workers at high risk of sensitisation to bakery allergens referred to a specialised clinic.
As part of a medical surveillance programme, clinical evaluation was performed on 436 referred Dutch bakery workers at high risk for sensitisation to bakery allergens. Multivariable logistic regression analyses were developed to identify the predictors of onset of baker's asthma and rhinitis using a self-administered questionnaire and compared using a structured medical history. Performance of models was assessed by discrimination (area under the receiver operating characteristics curve) and calibration (Hosmer-Lemeshow test). Internal validity of the models was assessed by a bootstrapping procedure.
The prediction models included the predictors of work-related upper and lower respiratory symptoms, the presence of allergy and allergic symptoms, use of medication (last year), type of job, type of shift and working years with symptoms (≥10 years). The developed models derived from both self-administered questionnaire and the medical history showed a relatively good discrimination and calibration. The internal validity showed that the models developed had satisfactory discrimination. To improve calibrations of models, shrinkage factors were applied to model coefficients.
The probability of allergic asthma and rhinitis in referred bakers could be estimated by diagnostic models based on both a self-administered questionnaire and by taking a structured medical history.
职业性过敏性疾病是烘焙行业等一些工作场所的主要问题。诊断规则已用于监测,但尚未应用于职业呼吸诊所。
建立诊断模型,以预测转诊至专科诊所的、对烘焙过敏原致敏风险较高的烘焙工人患面包师哮喘和鼻炎的情况。
作为一项医学监测计划的一部分,对436名转诊的、对烘焙过敏原致敏风险较高的荷兰烘焙工人进行了临床评估。使用一份自填式问卷进行多变量逻辑回归分析,以确定面包师哮喘和鼻炎发病的预测因素,并与结构化病史进行比较。通过辨别力(受试者操作特征曲线下面积)和校准(Hosmer-Lemeshow检验)评估模型的性能。通过自助法评估模型的内部效度。
预测模型包括与工作相关的上、下呼吸道症状、过敏及过敏症状的存在、用药情况(去年)、工作类型、轮班类型以及出现症状的工作年限(≥10年)。从自填式问卷和病史得出的模型均显示出较好的辨别力和校准度。内部效度表明所建立的模型具有令人满意的辨别力。为了改善模型的校准,对模型系数应用了收缩因子。
基于自填式问卷和结构化病史的诊断模型可估计转诊面包师患过敏性哮喘和鼻炎的概率。