Predicting the Risk of Developing Silicosis in Refractory Workers

Abstract

We conducted a study of refractory workers exposed to multiple occupational hazards, the most important of which being dust aerosols of predominantly fibrogenic action. Our objective was to identify the spectrum of predictors of the occupational disease in refractory workers and to build a predictive mathematical model using multivariate analysis to assess the likelihood of developing silicosis. Materials and methods: The case reports of 172 refractory production workers were analyzed. The main group consisted of 75 silicosis patients and the control cohort consisted of 97 experienced workers without this occupational disease. The groups were comparable in gender (p=0.052), dust exposure (p=0.862), and the severity of the work process (p=0.147). We assessed a wide specter of factors related to refractory workers’ health and occupational conditions significantly affecting the timing of developing occupational pulmonary fibrosis. Results: In the silicosis patients, arterial hypertension (p=0.005), left ventricular myocardial hypertrophy (p=0.002), coronary heart disease (p=0.010), chronic circulatory depression (p=0.010), low hemoglobin level (p=0.022), and low speed and volume criteria of external respiration function were significantly more prevalent. We established four important independent factors associated with the development of silicosis in refractory workers including age, time-weighted average and maximum one-time dust concentrations, and the forced expiratory volume in the first second. Conclusions: We observed a medium work-relatedness of hypertension, a strong work-relatedness of left ventricular myocardial hypertrophy, sinus node tachycardia syndrome and obesity, and a very strong work-relatedness of impaired fasting glycemia. Using a logistic regression, we built a silicosis development predictive model having high predictive ability (82.8 %), sufficient sensitivity (85.2 %) and specificity (80.0 %). The model was tested and verified on clinical examples and can be used to predict the probability of silicosis in refractory workers.