Evidence map›Paper›PMID 41645073›Full record

ArticleBMC infectious diseases2026

Respiratory and blood samples metagenomic sequencing in diagnosing pulmonary infections in hematologic patients.

Chunhui Xu, Lining Zhang, Teng Liu, Guoqing Zhu, Hui Wei, Yizhou Zheng, Jun Shi, Lugui Qiu, Zhijian Xiao, Xiaofan Zhu and 6 more

Abstract read
In one paragraph

Article in BMC infectious diseases, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

16 authors.

Chunhui Xu *State Key Laboratory of Experimental Hematology, National Clinical Research Center for Blood Diseases, Haihe Laboratory of Cell Ecosystem, Institute of Hematology & Blood Diseases Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, No. 288 Nanjing Road, Tianjin, 300020, China.
Lining Zhang *State Key Laboratory of Experimental Hematology, National Clinical Research Center for Blood Diseases, Haihe Laboratory of Cell Ecosystem, Institute of Hematology & Blood Diseases Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, No. 288 Nanjing Road, Tianjin, 300020, China.
Teng LiuMicrobiology laboratory, Tianjin Union Precision Medical Diagnostic Co., Ltd, Tianjin, 301617, China.
Guoqing ZhuState Key Laboratory of Experimental Hematology, National Clinical Research Center for Blood Diseases, Haihe Laboratory of Cell Ecosystem, Institute of Hematology & Blood Diseases Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, No. 288 Nanjing Road, Tianjin, 300020, China.
Hui WeiState Key Laboratory of Experimental Hematology, National Clinical Research Center for Blood Diseases, Haihe Laboratory of Cell Ecosystem, Institute of Hematology & Blood Diseases Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, No. 288 Nanjing Road, Tianjin, 300020, China.
Yizhou ZhengState Key Laboratory of Experimental Hematology, National Clinical Research Center for Blood Diseases, Haihe Laboratory of Cell Ecosystem, Institute of Hematology & Blood Diseases Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, No. 288 Nanjing Road, Tianjin, 300020, China.
Jun ShiState Key Laboratory of Experimental Hematology, National Clinical Research Center for Blood Diseases, Haihe Laboratory of Cell Ecosystem, Institute of Hematology & Blood Diseases Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, No. 288 Nanjing Road, Tianjin, 300020, China.
Lugui QiuState Key Laboratory of Experimental Hematology, National Clinical Research Center for Blood Diseases, Haihe Laboratory of Cell Ecosystem, Institute of Hematology & Blood Diseases Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, No. 288 Nanjing Road, Tianjin, 300020, China.
Zhijian XiaoState Key Laboratory of Experimental Hematology, National Clinical Research Center for Blood Diseases, Haihe Laboratory of Cell Ecosystem, Institute of Hematology & Blood Diseases Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, No. 288 Nanjing Road, Tianjin, 300020, China.
Xiaofan ZhuState Key Laboratory of Experimental Hematology, National Clinical Research Center for Blood Diseases, Haihe Laboratory of Cell Ecosystem, Institute of Hematology & Blood Diseases Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, No. 288 Nanjing Road, Tianjin, 300020, China.
Jianxiang WangState Key Laboratory of Experimental Hematology, National Clinical Research Center for Blood Diseases, Haihe Laboratory of Cell Ecosystem, Institute of Hematology & Blood Diseases Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, No. 288 Nanjing Road, Tianjin, 300020, China.
Jian GuoDepartment of Laboratory Medicine, Shanghai East Hospital, School of Life Sciences and Technology, Tongji University, Shanghai, China.
Yuping FanState Key Laboratory of Experimental Hematology, National Clinical Research Center for Blood Diseases, Haihe Laboratory of Cell Ecosystem, Institute of Hematology & Blood Diseases Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, No. 288 Nanjing Road, Tianjin, 300020, China.
Yijun SongState Key Laboratory of Experimental Hematology, National Clinical Research Center for Blood Diseases, Haihe Laboratory of Cell Ecosystem, Institute of Hematology & Blood Diseases Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, No. 288 Nanjing Road, Tianjin, 300020, China. songyijun@ihcams.ac.cn.
Erlie JiangState Key Laboratory of Experimental Hematology, National Clinical Research Center for Blood Diseases, Haihe Laboratory of Cell Ecosystem, Institute of Hematology & Blood Diseases Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, No. 288 Nanjing Road, Tianjin, 300020, China. jiangerlie@ihcams.ac.cn.
Sizhou FengState Key Laboratory of Experimental Hematology, National Clinical Research Center for Blood Diseases, Haihe Laboratory of Cell Ecosystem, Institute of Hematology & Blood Diseases Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, No. 288 Nanjing Road, Tianjin, 300020, China. szfeng@ihcams.ac.cn.

Funding

Chinese Academy of Medical Sciences Innovation Fund for Medical Sciences 2021-I2M-1-017Chinese Academy of Medical Sciences Innovation Fund for Medical Sciences 2021-I2M-1-039Fundamental Research Funds for the Central Universities, Peking Union Medical College 3332024210National Natural Sciences Foundation of China 82470208Noncommunicable Chronic Diseases-National Science and Technology Major Project 2023ZD0510400
6 · The paper itself

Abstract

backgroundBacterial and fungal pulmonary infections (BFPI) are common in hematological patients and pose significant diagnostic challenges. Metagenomic next-generation sequencing (mNGS) is valuable for diagnosing BFPI. However, for hematological patients with limited access to lower respiratory tract samples (LRTS), the clinical value of blood-mNGS compared to LRTS-mNGS requires further investigation.

methodsA retrospective analysis was conducted on 160 cases with suspected pneumonia who underwent both blood-mNGS and LRTS-mNGS within one week. Diagnostic performance and impacts on antimicrobial adjustments were evaluated using clinical composite diagnosis (CCD) as the reference.

resultsCompared to CCD, LRTS-mNGS showed significantly higher positive percent agreement (PPA) than blood-mNGS [93.7% (119/127) vs. 34.6% (44/127), P < 0.001], with negative percent agreements (NPA) of 87.5% (21/24) and 91.7% (22/24), respectively. Blood-mNGS showed higher PPA in neutropenic than non-neutropenic patients [56.8% (21/37) vs. 25.6% (23/90), P = 0.001], with unique fungal detection advantages, identifying additional fungi in 7 cases: Mucorales (3), Aspergillus spp. (2), both Mucorales and Aspergillus spp. (1), and Pneumocystis spp. (1). Resistance genes were detected only by LRTS-mNGS. mNGS positively influenced antimicrobial adjustments in 54.3% (69/127) of cases, particularly for pathogens with low empirical coverage, such as Legionella spp. (0.0%, 0/7), Pneumocystis spp. (52.4%, 11/21), and Mucorales (55.6%, 5/9). Blood-mNGS detected these pathogens at rates of 71.4% (5/7), 23.8% (5/21), and 77.8% (7/9), respectively.

conclusionLRTS-mNGS outperformed blood-mNGS in diagnostic performance and resistance detection. Blood-mNGS identified pathogens in one-third of BFPI cases, with value for certain fungal infections, especially in hematologic patients with limited LRTS access.

trial registrationNot applicable. This study is a retrospective analysis and does not require clinical trial registration.

Indexed as

Hematologic DiseasesLung Diseases, FungalMetagenomicsPneumoniaRespiratory Tract InfectionsAdultAgedBacteriaFemaleFungiHigh-Throughput Nucleotide SequencingHumansMaleMiddle AgedRetrospective StudiesBacterial and fungal infectionHematological diseasesMetagenomic next-generation sequencingPulmonary infections

Identifiers

PMID41645073
PMCPMC12964966

What Socratic holds

Textmetadata
LicenceCC BY-NC-ND
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.