1. Recurrent Hemoptysis After Bronchial Artery Embolization: Prediction Using a Nomogram and Artificial Neural Network Model
- Author
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Li-Jun Guan, Sheng Xu, Xue-Jun Zhang, Bao-Qi Shi, and Yong-Sheng Tan
- Subjects
Male ,Hemoptysis ,medicine.medical_specialty ,medicine.medical_treatment ,Artificial neural network model ,Bronchial Arteries ,030218 nuclear medicine & medical imaging ,03 medical and health sciences ,0302 clinical medicine ,Recurrence ,Internal medicine ,medicine.artery ,Humans ,Medicine ,Radiology, Nuclear Medicine and imaging ,Embolization ,Lung cancer ,Aged ,Retrospective Studies ,Receiver operating characteristic ,business.industry ,Hazard ratio ,General Medicine ,Middle Aged ,Nomogram ,medicine.disease ,Embolization, Therapeutic ,Training cohort ,Nomograms ,030220 oncology & carcinogenesis ,Female ,Neural Networks, Computer ,business ,Bronchial artery - Abstract
OBJECTIVE. The purpose of this study was to develop an effective nomogram and artificial neural network (ANN) model for predicting recurrent hemoptysis after bronchial artery embolization (BAE). MATERIALS AND METHODS. The institutional ethics review boards of the two participating hospitals approved this study. Patients with hemoptysis who were treated with BAE were allocated to either the training cohort (Hospital A) or the validation cohort (Hospital B). The predictors of recurrent hemoptysis were identified by univariable and multivariable analyses in the training cohort. A nomogram and ANN model were then developed, and the accuracy was validated by the Harrell C statistic and ROC curves in both the training and validation cohorts. RESULTS. A total of 242 patients (training cohort, 141; validation cohort, 101) were enrolled in this study. The univariable and multivariable analyses revealed that age of 60 years old or older (hazard ratio [HR], 3.921; 95% CI, 1.267-12.127; p = 0.018), lung cancer (HR, 18.057; 95% CI, 4.124-79.068; p 0.16) according to the nomogram.
- Published
- 2020
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