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Published on: September 6, 2024
A Nomogram for Predicting Pulmonary Embolism in Silicosis Patients
Jiaqing Zhou1, Wen Du1, Jin Liu2
1Department of Respiratory Medicine, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, China.
Background:
As one of the most severe occupational diseases that prevention efforts have supported for several decades, silicosis is still a public health issue that lacks a prediction model for pulmonary embolism.
Methods:
A total of 162 patients confirmed to have silicosis were all involved in a training cohort to construct a nomogram with the outcome diagnosed by the CTPA using logistic regression. Univariate and LASSO analyses were used to select variables for the nomogram.
Result:
mMRC, pectoralgia, history of VTE, active tumor, unilateral lower limb pain or edema, hormonotherapy, reduced mobility, and heart failure/respiratory failure were selected for the establishment of the nomogram for silicosis with pulmonary embolism.
Conclusion:
A novel nomogram was developed to predict pulmonary embolism in silicosis patients. The internal validation indicated that clinicians could utilize this predictive model to help decision-making and patient management.
