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一种用于排除建筑工人尘肺病的简易诊断模型。

A simple diagnostic model for ruling out pneumoconiosis among construction workers.

作者信息

Suarthana Eva, Moons Karel G M, Heederik Dick, Meijer Evert

机构信息

IRAS (Institute for Risk Assessment Sciences), Division of Environmental Epidemiology, Utrecht University, Utrecht, The Netherlands.

出版信息

Occup Environ Med. 2007 Sep;64(9):595-601. doi: 10.1136/oem.2006.027904. Epub 2007 Apr 4.

Abstract

BACKGROUND

Construction workers exposed to silica-containing dust are at risk of developing silicosis even at low exposure levels. Health surveillance among these workers is commonly advised but the exact diagnostic work-up is not specified and therefore may result in unnecessary chest x ray investigations.

AIM

To develop a simple diagnostic model to estimate the probability of an individual worker having pneumoconiosis from questionnaire and spirometry results, in order to accurately rule out workers without pneumoconiosis.

METHODS

The study was performed using cross-sectional data of 1291 Dutch natural stone and construction workers with potentially high quartz dust exposure. A multivariable logistic regression model was developed using chest x ray with ILO profusion category > or =1/1 as the reference standard. The model's calibration was evaluated with the Hosmer-Lemeshow test; the discriminative ability was determined by calculating the area under the receiver operating characteristic curve (ROC area). Internal validity of the final model was assessed by a bootstrapping procedure. For clinical application, the diagnostic model was transformed into an easy-to-use score chart.

RESULTS

Age 40 years or older, current smoker, high-exposure job, working 15 years or longer in the construction industry, "feeling unhealthy" and FEV1 were independent predictors in the diagnostic model. The model showed good calibration (a non-significant Hosmer-Lemeshow test) and discriminative ability (ROC area 0.81, 95% CI 0.74 to 0.85). Internal validity was reasonable; the optimism corrected ROC area was 0.76. By using a cut-off point with a high negative predictive value the occupational physician can efficiently detect a large proportion of workers with a low probability of having pneumoconiosis and exclude them from unnecessary x ray investigations.

CONCLUSIONS

This diagnostic model is an efficient and effective instrument to rule out pneumoconiosis among construction workers. Its use in health surveillance among these workers can reduce the number of redundant x ray investigations.

摘要

背景

接触含硅粉尘的建筑工人即使在低暴露水平下也有患矽肺病的风险。通常建议对这些工人进行健康监测,但具体的诊断检查并未明确规定,因此可能会导致不必要的胸部X光检查。

目的

开发一种简单的诊断模型,根据问卷调查和肺活量测定结果估计个体工人患尘肺病的概率,以便准确排除没有尘肺病的工人。

方法

本研究使用了1291名荷兰天然石材和建筑工人的横断面数据,这些工人可能有较高的石英粉尘暴露。以国际劳工组织(ILO) profusion类别>或=1/1的胸部X光检查为参考标准,建立了多变量逻辑回归模型。用Hosmer-Lemeshow检验评估模型的校准;通过计算受试者操作特征曲线下的面积(ROC面积)来确定判别能力。通过自举程序评估最终模型的内部有效性。为了临床应用,将诊断模型转换为易于使用的评分表。

结果

年龄40岁及以上、当前吸烟者、高暴露工作、在建筑行业工作15年或更长时间、“感觉不健康”和第一秒用力呼气量(FEV1)是诊断模型中的独立预测因素。该模型显示出良好的校准(Hosmer-Lemeshow检验无显著性)和判别能力(ROC面积为0.81,95%可信区间为0.74至0.85)。内部有效性合理;乐观校正后的ROC面积为0.76。通过使用具有高阴性预测值的截断点,职业医生可以有效地检测出很大一部分患尘肺病概率较低的工人,并将他们排除在不必要的X光检查之外。

结论

该诊断模型是排除建筑工人尘肺病的一种有效工具。在这些工人的健康监测中使用该模型可以减少冗余X光检查的数量。

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