Development of a predictive model of pulmonary hemorrhage in patients after CT-guided coaxial core needle lung biopsy

Linyun Yang; Ting Liang; Yonghao DU; Chenguang Guo; Jin Shang; Pokharel Saugat; Gang Niu

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Development of a predictive model of pulmonary hemorrhage in patients after CT-guided coaxial core needle lung biopsy

VernacularTitle:CT引导下同轴切割肺穿刺活检后肺出血预测模型的建立
Author: Linyun YANG ¹ ; Ting LIANG ¹ ; Yonghao DU ¹ ; Chenguang GUO ¹ ; Jin SHANG ¹ ; Pokharel SAUGAT ¹ ; Gang NIU ¹
Author Information

1. Department of Radiology, The First Affiliated Hospital of Xi’an Jiaotong University, Xi’an 710061, China
Publication Type:Journal Article
Keywords: CT guided; coaxial core needle lung biopsy; pulmonary hemorrhage; predictive model
From: Journal of Xi'an Jiaotong University(Medical Sciences) 2021;42(5):747-754
CountryChina
Language:Chinese
Abstract: 【Objective】 To establish a predictive model for patients with hemorrhage after CT-guided coaxial core needle lung biopsy （CCNB） based on logistic regression. 【Methods】 A total of 489 patients who had undergone CCNB were retrospectively recruited. The potential risk factors of hemorrhage after lung biopsy were analyzed by univariate and multivariate logistic regression， through which we screened the independent risk factors and established a prediction model for hemorrhage. We evaluated the discrimination， calibration and clinical usefulness of the model. 【Results】 There were 141 cases （42.6%） of hemorrhage in the development group and 66 cases （41.8%） of hemorrhage in the validation group； there was no case of severe hemorrhage or hemothorax. Multivariate logistic regression analysis showed that fibrinogen degradation products， pulmonary interstitial fibrosis， largest diameter and puncture depth were independent predictive factors of hemorrhage. Hemorrhage prediction model was established and presented in the form of a nomogram. Discrimination of the model： the AUC was 0.837 in the development group and 0.777 in the validation group. The calibration curve showed good agreement between predicted probability and actual probability of hemorrhage. The unreliability test yielded a P value of 0.849 in the development group and 0.147 in the validation group. The DCA curve showed that the hemorrhage predictive model could increase the benefit of patients. 【Conclusion】 The predictive model of hemorrhage in patients after CCNB based on logistic regression can be used in clinical practice.