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Development and validation of a predictive model for pulmonary hemorrhage in computed tomography-guided percutaneous lung biopsy.
Yang, Song; Li, Jie; Wang, Wangjia; Lou, Lejing; Jin, Xiao; Wang, Shijia; Cai, Jihao; Cai, Chang.
Afiliação
  • Yang S; Department of Nephrology, Wenzhou Central Hospital, Wenzhou, 325000, China.
  • Li J; Department of Respiratory and Critical Care Medicine, The First Affiliated Hospital of Wenzhou Medical University, Wenzhou, 325000, China.
  • Wang W; Key Laboratory of Diagnosis and Treatment of Severe Hepato-Pancreatic Diseases of Zhejiang Province, The First Affiliated Hospital of Wenzhou Medical University, Wenzhou, 325000, China.
  • Lou L; Department of Respiratory and Critical Care Medicine, The First Affiliated Hospital of Wenzhou Medical University, Wenzhou, 325000, China.
  • Jin X; Department of Respiratory and Critical Care Medicine, The First Affiliated Hospital of Wenzhou Medical University, Wenzhou, 325000, China.
  • Wang S; Department of Respiratory and Critical Care Medicine, The First Affiliated Hospital of Wenzhou Medical University, Wenzhou, 325000, China.
  • Cai J; Department of Respiratory and Critical Care Medicine, The First Affiliated Hospital of Wenzhou Medical University, Wenzhou, 325000, China.
  • Cai C; Renji College, Wenzhou Medical University, Wenzhou, 325000, China.
Postgrad Med J ; 99(1177): 1173-1181, 2023 Oct 19.
Article em En | MEDLINE | ID: mdl-37516454
ABSTRACT

PURPOSE:

This study aimed to identify risk factors for pulmonary hemorrhage (PH) and higher-grade PH that complicate computed tomography (CT)-guided percutaneous lung biopsy (CT-PNLB) and establish predictive models to quantify the risk.

METHODS:

A total of 2653 cases of CT-PNLB were enrolled. Multivariate logistic regression was used to identify independent risk factors to develop a nomogram prediction model. The model was assessed using the area under the curve (AUC) of the receiver operator characteristic (ROC) and calibration curves and validated in the validation group.

RESULTS:

PH occurred in 23.52% (624/2653) of cases, and higher-grade PH occurred in 7.09% (188/2653) of cases. The parameters of lesion size, puncture depth, and contact to pleura were identified as risk factors of PH and higher-grade PH in the logistic regression model, besides the position as a risk factor for PH. The AUC of the PH prediction model was 0.776 [95% confidence interval (CI) 0.752-0.800], whereas that of the validation group was 0.743 (95% CI 0.706-0.780). The AUC of the higher-grade PH prediction model was 0.782 (95% CI 0.742-0.832), whereas that of the validation group was 0.769 (95% CI 0.716-0.822). The calibration curves of the model showed good agreement between the predicted and actual probability in the development and validation groups.

CONCLUSION:

We identified risk factors associated with PH and higher-grade PH after PNLBs. Furthermore, we developed and validated two risk prediction models for PNLB-related PH and higher-grade PH risk prediction and clinical decision support. Key messages What is already known on this topic Pulmonary hemorrhage (PH) and other hemorrhagic complications are the most common complication in CT-guided percutaneous lung biopsy (CT-PNLB), except pneumothorax. However, the risk factors associated with PH remain controversial, and research on models of PH and higher-grade PH is also limited. What this study adds The parameters of lesion size, puncture depth, and contact to pleura were identified as risk factors of PH and higher-grade PH in the logistic regression model, besides the position as a risk factor for PH. In addition, we developed and validated two risk prediction models for PNLB-related PH and higher-grade PH risk prediction and clinical decision support. How this study might affect research, practice, or policy Of all the predictors, the position is the key factor to be considered by the operator. Moreover, two risk prediction models show good discrimination and calibration characteristics to identify patients at high risk of hemorrhage and higher-grade PH after PNLB, so these could assist clinicians in avoiding risk factors in advance.
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Texto completo: 1 Base de dados: MEDLINE Tipo de estudo: Prognostic_studies / Risk_factors_studies Idioma: En Revista: Postgrad Med J Ano de publicação: 2023 Tipo de documento: Article País de afiliação: China

Texto completo: 1 Base de dados: MEDLINE Tipo de estudo: Prognostic_studies / Risk_factors_studies Idioma: En Revista: Postgrad Med J Ano de publicação: 2023 Tipo de documento: Article País de afiliação: China