Evidence map›Paper›PMID 39350096›Full record

ArticleBMC infectious diseases2024

Clinical characteristics and outcome analysis of pulmonary nocardiosis in southern China: a two-center retrospective study.

Li-Da Chen, Hong-Yuan Li, Jian-Jun Xie, Miao-Fen Hu, Xiang-Xing Chen, Zhi-Ming Cai, Li Lin, Xiao-Bin Zhang, Gong-Ping Chen, Kai-Xiong Liu

Abstract readMulticenter Study
In one paragraph

Article in BMC infectious diseases, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed, 1 pooled it
–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

7 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Article
  3. Article
  4. Cross-Reactivity of GeneXpert MTB/RIF Probe C withInfection and drug resistance · 2026
    Article
  5. Review
  6. Frontiers in medicine · 2025
    Article
  7. Article
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

10 authors.

Li-Da Chen *Department of Respiratory and Critical Care Medicine, Zhangzhou Affiliated Hospital of Fujian Medical University, Zhangzhou, Fujian Province, China.
Hong-Yuan Li *Department of Respiratory and Critical Care Medicine, Zhangzhou Affiliated Hospital of Fujian Medical University, Zhangzhou, Fujian Province, China.
Jian-Jun Xie *Department of Radiation Oncology, Zhangzhou Affiliated Hospital of Fujian Medical University, Zhangzhou, Fujian Province, China.
Miao-Fen HuDepartment of Respiratory and Critical Care Medicine, Zhangzhou Affiliated Hospital of Fujian Medical University, Zhangzhou, Fujian Province, China.
Xiang-Xing ChenDepartment of Pulmonary and Critical Care Medicine, Zhongshan Hospital, Xiamen University, Xiamen, Fujian Province, China.
Zhi-Ming CaiDepartment of Respiratory and Critical Care Medicine, Zhangzhou Affiliated Hospital of Fujian Medical University, Zhangzhou, Fujian Province, China.
Li LinDepartment of Respiratory and Critical Care Medicine, Zhangzhou Affiliated Hospital of Fujian Medical University, Zhangzhou, Fujian Province, China.
Xiao-Bin ZhangDepartment of Pulmonary and Critical Care Medicine, Zhongshan Hospital, Xiamen University, Xiamen, Fujian Province, China.
Gong-Ping ChenDepartment of Respiratory and Critical Care Medicine, The First Affiliated Hospital of Fujian Medical University, No 20, Chazhong Road, Taijiang District, Fuzhou, 350005, Fujian Province, People's Republic of China.
Kai-Xiong LiuDepartment of Respiratory and Critical Care Medicine, The First Affiliated Hospital of Fujian Medical University, No 20, Chazhong Road, Taijiang District, Fuzhou, 350005, Fujian Province, People's Republic of China. lkxfpt@163.com.

Funding

Climbing Fund for scientific research from Zhangzhou Municipal Hospital of Fujian Province PDB202202Fujian Provincial Health Technology Project 2020GGA053Joint Funds for the Innovation of Science and Technology of Fujian Province No.2060304Natural Sciences Foundation of Fujian Province 2021J01228
6 · The paper itself

Abstract

backgroundPulmonary nocardiosis (PN) is a rare and opportunistic infection. This study aimed to analyze clinical, radiological, and microbiological features, treatment and outcome of PN in southern china.

methodsClinical, laboratory, imaging, treatment and outcome data of PN patients at two tertiary hospitals from January 1, 2018, to January 1, 2024 were collected. Factors associated with clinical outcomes were determined by multivariate logistic regression analysis.

results67 PN patients including 53 with clinical improvement and 14 with treatment failure were enrolled. Bronchiectasis was the most common respiratory disease in patients with PN (31.3%). The major symptoms of PN were cough (89.6%) and sputum (79.1%). Lung nodules, bronchiectasis, consolidation, pleural involvement, mass, cavity, and lymph node enlargement were the frequent computed tomography findings of PN. Among the Nocardia species detected, N. farcinica was the most common pathogen. Neutrophil-to-lymphocyte ratio (OR = 1.052, p = 0.010), concurrent bacterial infection (OR = 7.706, p = 0.016), and the use of carbapenems (OR = 9.345, p = 0.023) were independently associated with poor prognosis in patients with PN.

conclusionsThis study provides important insights into the clinical features of PN in southern china. neutrophil-to-lymphocyte ratio, concurrent bacterial infection, and the use of carbapenems were independently associated with poor prognosis in patients with PN.

Indexed as

NocardiaNocardia InfectionsAdultAgedAnti-Bacterial AgentsBronchiectasisCarbapenemsChinaFemaleHumansMaleMiddle AgedPrognosisRetrospective StudiesSputumTomography, X-Ray ComputedAnti-Bacterial AgentsCarbapenemsBronchiectasisNeutrophil-to-lymphocyte ratioPrognosisPulmonary nocardiosis

Identifiers

PMID39350096
PMCPMC11441091

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Registered trials

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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 OpenQuestion graph.