The Differential Diagnostic Value of Chest Computed Tomography for the Identification of Pathogens Causing Pulmonary Infections in Patients with Hematological Malignancies

Qian Cheng,1 Yishu Tang,2 Jing Liu,1 FeiYang Liu,1,&ast; Xin Li1,&ast; 1Department of Hematology, The Third Xiangya Hospital, Central South University, Changsha, Hunan, People’s Republic of China; 2Department of Emergency, The Third Xiangya Hospital, Central South University, Changsha, Hunan, People’s Republic of China&ast;These authors contributed equally to this workCorrespondence: FeiYang Liu; Xin Li, Department of Hematology, The Third Xiangya Hospital, Central South University, Changsha, Hunan, 410013, People’s Republic of China, Tel +86-731-88618814 (88618214) ; Tel +86-731-88618814 (88618214), Email [email protected]; [email protected]: The role of chest computed tomography (CT) in distinguishing the causative pathogens of pulmonary infections in patients with hematological malignancies (HM) is unclear. The aim of our study was to compare and assess the clinical characteristics, radiologic features and potential differential diagnostic value of CT in HM patients and other different immune statuses patients with pulmonary infections.Methods: Patients were divided into immunocompetent (105 cases) and immunocompromised groups (99 cases) according to immune status. Immunocompromised patients included the HM group (63 cases) and the non-HM group (42 cases). The basic clinical data and CT findings were collected and statistically analyzed.Results: Regarding the pathogen distribution, viral, Pneumocystis jirovecii and mixed infections were more common in the immunocompromised group than the immunocompetent (p < 0.01), but viral infections were more common in the HM group than in the non-HM group (p=0.013). Immunocompromised patients had more diverse CT findings and more serious lesions (mostly graded 2– 4) than immunocompetent patients. The most common CT findings in HM patients were consolidation and ground-glass opacities (GGO), which were also found in the non-HM group. The overall diagnostic accuracy of CT was lower in immunocompromised patients than in immunocompetent patients (25.7% vs 50.5%, p< 0.01). CT had better diagnostic efficacy for fungi and Pneumocystis jirovecii in HM patients.Conclusion: CT diagnosis is less efficient in distinguishing the causative pathogens of HM patients. However, CT can help distinguish fungal pneumonia and Pneumocystis jirovecii pneumonia in HM patients.Clinical Relevance Statement: Our study might facilitate clinical decision-making in fungal pneumonia and Pneumocystis jirovecii pneumonia in HM patients.Keywords: pneumonia, hematological malignancies, computed tomography, diagnostic value

Publication Details

Journal
SHILAP Revista de lepidopterología
Published
2024-10-01
Primary Topic
Radiation Detection and Scintillator Technologies
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

The Differential Diagnostic Value of Chest Computed Tomography for the Identification of Pathogens Causing Pulmonary Infections in Patients with Hematological Malignancies

SHILAP Revista de lepidopterología
Radiation Detection and Scintillator Technologies
article

The Differential Diagnostic Value of Chest Computed Tomography for the Identification of Pathogens Causing Pulmonary Infections in Patients with Hematological Malignancies

article en

Abstract

Qian Cheng,1 Yishu Tang,2 Jing Liu,1 FeiYang Liu,1,&ast; Xin Li1,&ast; 1Department of Hematology, The Third Xiangya Hospital, Central South University, Changsha, Hunan, People’s Republic of China; 2Department of Emergency, The Third Xiangya Hospital, Central South University, Changsha, Hunan, People’s Republic of China&ast;These authors contributed equally to this workCorrespondence: FeiYang Liu; Xin Li, Department of Hematology, The Third Xiangya Hospital, Central South University, Changsha, Hunan, 410013, People’s Republic of China, Tel +86-731-88618814 (88618214) ; Tel +86-731-88618814 (88618214), Email [email protected]; [email protected]: The role of chest computed tomography (CT) in distinguishing the causative pathogens of pulmonary infections in patients with hematological malignancies (HM) is unclear. The aim of our study was to compare and assess the clinical characteristics, radiologic features and potential differential diagnostic value of CT in HM patients and other different immune statuses patients with pulmonary infections.Methods: Patients were divided into immunocompetent (105 cases) and immunocompromised groups (99 cases) according to immune status. Immunocompromised patients included the HM group (63 cases) and the non-HM group (42 cases). The basic clinical data and CT findings were collected and statistically analyzed.Results: Regarding the pathogen distribution, viral, Pneumocystis jirovecii and mixed infections were more common in the immunocompromised group than the immunocompetent (p < 0.01), but viral infections were more common in the HM group than in the non-HM group (p=0.013). Immunocompromised patients had more diverse CT findings and more serious lesions (mostly graded 2– 4) than immunocompetent patients. The most common CT findings in HM patients were consolidation and ground-glass opacities (GGO), which were also found in the non-HM group. The overall diagnostic accuracy of CT was lower in immunocompromised patients than in immunocompetent patients (25.7% vs 50.5%, p< 0.01). CT had better diagnostic efficacy for fungi and Pneumocystis jirovecii in HM patients.Conclusion: CT diagnosis is less efficient in distinguishing the causative pathogens of HM patients. However, CT can help distinguish fungal pneumonia and Pneumocystis jirovecii pneumonia in HM patients.Clinical Relevance Statement: Our study might facilitate clinical decision-making in fungal pneumonia and Pneumocystis jirovecii pneumonia in HM patients.Keywords: pneumonia, hematological malignancies, computed tomography, diagnostic value

SHILAP Revista de lepidopterología
Openalex Percentile: Top 45%
Radiation Detection and Scintillator Technologies
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.