Diagnostic accuracy of thoracic CT to differentiate transudative from exudative pleural effusion prior to thoracentesis.

Diagnosis Exudate Pleural effusion Thoracic CT Transudate

Journal

Respiratory research
ISSN: 1465-993X
Titre abrégé: Respir Res
Pays: England
ID NLM: 101090633

Informations de publication

Date de publication:
23 Jan 2024
Historique:
received: 08 10 2023
accepted: 04 01 2024
medline: 24 1 2024
pubmed: 24 1 2024
entrez: 23 1 2024
Statut: epublish

Résumé

Computed tomography (CT) scan is commonly performed for pleural effusion diagnostis in the clinic. However, there are limited data assessing the accuracy of thoracic CT for the separation of transudative from exudative effusions. The study aimed to determine the diagnostic value of thoracic CT in distinguishing transudates from exudates in patients with pleural effusion. This is a two-center retrospective analysis of patients with pleural effusion, a total of 209 patients were included from The First Affiliated Hospital of Henan University of Science and Technology as the derivation cohort (Luoyang cohort), and 195 patients from the First Affiliated Hospital of Zhengzhou University as the validation cohort (Zhengzhou cohort). Patients who underwent thoracic CT scan followed by diagnostic thoracentesis were enrolled. The optimal cut-points of CT value in pleural fluid (PF) and PF to blood CT value ratio for predicting a transudative vs. exudative pleural effusions were determined in the derivation cohort and further verified in the validation cohort. In the Derivation (Luoyang) cohort, patients with exudates had significantly higher CT value [13.01 (10.01-16.11) vs. 4.89 (2.31-9.83) HU] and PF to blood CT value ratio [0.37 (0.27-0.53) vs. 0.16 (0.07-0.26)] than those with transudates. With a cut-off value of 10.81 HU, the area under the curve (AUC), sensitivity, specificity, positive predictive value (PPV) and negative predictive value (NPV) of CT value were 0.85, 88.89%, 68.90%, 43.96%, and 95.76%, respectively. The optimum cut-value for PF to blood CT value ratio was 0.27 with AUC of 0.86, yielding a sensitivity of 61.11%, specificity of 86.36%, PPV of 78.57%, and NPV of 73.08%. These were further verified in the Validation (Zhengzhou) cohort. CT value and PF to blood CT value ratio showed good differential abilities in predicting transudates from exudates, which may help to avoid unnecessary thoracentesis.

Sections du résumé

BACKGROUND BACKGROUND
Computed tomography (CT) scan is commonly performed for pleural effusion diagnostis in the clinic. However, there are limited data assessing the accuracy of thoracic CT for the separation of transudative from exudative effusions. The study aimed to determine the diagnostic value of thoracic CT in distinguishing transudates from exudates in patients with pleural effusion.
METHODS METHODS
This is a two-center retrospective analysis of patients with pleural effusion, a total of 209 patients were included from The First Affiliated Hospital of Henan University of Science and Technology as the derivation cohort (Luoyang cohort), and 195 patients from the First Affiliated Hospital of Zhengzhou University as the validation cohort (Zhengzhou cohort). Patients who underwent thoracic CT scan followed by diagnostic thoracentesis were enrolled. The optimal cut-points of CT value in pleural fluid (PF) and PF to blood CT value ratio for predicting a transudative vs. exudative pleural effusions were determined in the derivation cohort and further verified in the validation cohort.
RESULTS RESULTS
In the Derivation (Luoyang) cohort, patients with exudates had significantly higher CT value [13.01 (10.01-16.11) vs. 4.89 (2.31-9.83) HU] and PF to blood CT value ratio [0.37 (0.27-0.53) vs. 0.16 (0.07-0.26)] than those with transudates. With a cut-off value of 10.81 HU, the area under the curve (AUC), sensitivity, specificity, positive predictive value (PPV) and negative predictive value (NPV) of CT value were 0.85, 88.89%, 68.90%, 43.96%, and 95.76%, respectively. The optimum cut-value for PF to blood CT value ratio was 0.27 with AUC of 0.86, yielding a sensitivity of 61.11%, specificity of 86.36%, PPV of 78.57%, and NPV of 73.08%. These were further verified in the Validation (Zhengzhou) cohort.
CONCLUSIONS CONCLUSIONS
CT value and PF to blood CT value ratio showed good differential abilities in predicting transudates from exudates, which may help to avoid unnecessary thoracentesis.

Identifiants

pubmed: 38263145
doi: 10.1186/s12931-024-02681-w
pii: 10.1186/s12931-024-02681-w
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

53

Subventions

Organisme : Henan Provincial Medical Science and Technology Research Project
ID : LHGJ20220671
Organisme : Natural Science Foundation of Henan Province
ID : 232300421304
Organisme : Henan Provincial Science and Technology Research Project
ID : 222102310533, 222103810052
Organisme : Young Elite Scientists Sponsorship Program by Luoyang Association for Science and Technology
ID : 2022HLTJ18

Informations de copyright

© 2024. The Author(s).

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Auteurs

Yan Zhang (Y)

Department of General Medicine, The First Affiliated Hospital, College of Clinical Medicine, Henan University of Science and Technology, Luoyang, Henan, China.

Yang Zhang (Y)

Department of Respiratory and Critical Care Medicine, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, Henan, China.

Wei Wang (W)

Department of Respiratory and Critical Care Medicine, The First Affiliated Hospital, College of Clinical Medicine, Henan University of Science and Technology, 24 Jing Hua Road, Luoyang, 471003, Henan, China.

Xiaoyu Feng (X)

Department of Respiratory and Critical Care Medicine, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, Henan, China.

Jiahuan Guo (J)

Department of Respiratory and Critical Care Medicine, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, Henan, China.

Bo Chen (B)

Department of Respiratory and Critical Care Medicine, The First Affiliated Hospital, College of Clinical Medicine, Henan University of Science and Technology, 24 Jing Hua Road, Luoyang, 471003, Henan, China.

Fuyun Zhang (F)

Department of Respiratory and Critical Care Medicine, The First Affiliated Hospital, College of Clinical Medicine, Henan University of Science and Technology, 24 Jing Hua Road, Luoyang, 471003, Henan, China.

Huanhuan Wang (H)

Department of Respiratory and Critical Care Medicine, The First Affiliated Hospital, College of Clinical Medicine, Henan University of Science and Technology, 24 Jing Hua Road, Luoyang, 471003, Henan, China.

Mengnan Fan (M)

Department of Medical Record, The First Affiliated Hospital, College of Clinical Medicine, Henan University of Science and Technology, Luoyang, Henan, China.

Yingwei Zhu (Y)

Department of Respiratory and Critical Care Medicine, The First Affiliated Hospital, College of Clinical Medicine, Henan University of Science and Technology, 24 Jing Hua Road, Luoyang, 471003, Henan, China.

Yuxia Sun (Y)

Department of Respiratory and Critical Care Medicine, The First Affiliated Hospital, College of Clinical Medicine, Henan University of Science and Technology, 24 Jing Hua Road, Luoyang, 471003, Henan, China.

Tongsheng Wang (T)

Department of Respiratory and Critical Care Medicine, The First Affiliated Hospital, College of Clinical Medicine, Henan University of Science and Technology, 24 Jing Hua Road, Luoyang, 471003, Henan, China.

Yimin Mao (Y)

Department of Respiratory and Critical Care Medicine, The First Affiliated Hospital, College of Clinical Medicine, Henan University of Science and Technology, 24 Jing Hua Road, Luoyang, 471003, Henan, China.

Pengfei Gao (P)

Department of Respiratory and Critical Care Medicine, The First Affiliated Hospital, College of Clinical Medicine, Henan University of Science and Technology, 24 Jing Hua Road, Luoyang, 471003, Henan, China. gpf_working@163.com.

Classifications MeSH