一种用于预测矽肺患者肺栓塞的列线图。
A Nomogram for Predicting Pulmonary Embolism in Silicosis Patients.
作者信息
Zhou Jiaqing, Du Wen, Liu Jin, Peng Lijun
机构信息
Department of Respiratory Medicine, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, China.
Department of Epidemiology, School of Public Health, Fudan University, Shanghai, China.
出版信息
Clin Respir J. 2025 Mar;19(3):e70059. doi: 10.1111/crj.70059.
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.
背景
作为几十年来预防工作所关注的最严重职业病之一，矽肺病仍是一个缺乏肺栓塞预测模型的公共卫生问题。
方法
总共162例确诊为矽肺病的患者均纳入训练队列，采用逻辑回归构建列线图，以CTPA诊断结果作为结局。单因素分析和LASSO分析用于选择列线图的变量。
结果
mMRC、胸痛、VTE病史、活动性肿瘤、单侧下肢疼痛或水肿、激素治疗、活动能力下降以及心力衰竭/呼吸衰竭被纳入构建矽肺病合并肺栓塞的列线图。
结论
开发了一种新型列线图以预测矽肺病患者的肺栓塞。内部验证表明临床医生可利用该预测模型辅助决策和患者管理。
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