Evidence map›Paper›PMID 42063766›Full record

ArticleFrontiers in medicine2026

Evaluation of a new droplet digital PCR for diagnosis of pulmonary tuberculosis and tuberculous pleurisy.

Xichao Ou, Huiwen Zheng, Xundi Bao, Peilei Hu, Zhou Liu, Jingwei Guo, Dongfang Xu, Yue Li, Jingjing Li, Bing Zhao and 5 more

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Frontiers in medicine, 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. 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

15 authors.

Xichao Ou *National Key Laboratory of Intelligent Tracking and Forecasting for Infectious Diseases, National Center for Tuberculosis Control and Prevention, Chinese Centre for Disease Control and Prevention, Beijing, China.
Huiwen Zheng *Beijing Key Laboratory of Pediatric Respiratory Infection Diseases, Key Laboratory of Major Diseases in Children, Ministry of Education, National Clinical Research Center for Respiratory Diseases, Laboratory of Respiratory Diseases, Beijing Pediatric Research Institute, Beijing Children's Hospital, Capital Medical University, National Center for Children's Health, Beijing, China.
Xundi Bao *Department of Clinical Laboratory, Anhui Chest Hospital, Hefei, China.
Peilei HuDepartment of Clinical Laboratory, Hunan Chest Hospital, Changsha, China.
Zhou LiuDepartment of Clinical Laboratory, Anhui Chest Hospital, Hefei, China.
Jingwei GuoDepartment of Clinical Laboratory, Hunan Chest Hospital, Changsha, China.
Dongfang XuDepartment of Clinical Laboratory, Anhui Chest Hospital, Hefei, China.
Yue LiDepartment of Clinical Laboratory, Anhui Chest Hospital, Hefei, China.
Jingjing LiBeijing Key Laboratory of Pediatric Respiratory Infection Diseases, Key Laboratory of Major Diseases in Children, Ministry of Education, National Clinical Research Center for Respiratory Diseases, Laboratory of Respiratory Diseases, Beijing Pediatric Research Institute, Beijing Children's Hospital, Capital Medical University, National Center for Children's Health, Beijing, China.
Bing ZhaoNational Key Laboratory of Intelligent Tracking and Forecasting for Infectious Diseases, National Center for Tuberculosis Control and Prevention, Chinese Centre for Disease Control and Prevention, Beijing, China.
Jie KangBeijing Key Laboratory of Pediatric Respiratory Infection Diseases, Key Laboratory of Major Diseases in Children, Ministry of Education, National Clinical Research Center for Respiratory Diseases, Laboratory of Respiratory Diseases, Beijing Pediatric Research Institute, Beijing Children's Hospital, Capital Medical University, National Center for Children's Health, Beijing, China.
Qi MaBeijing Key Laboratory of Pediatric Respiratory Infection Diseases, Key Laboratory of Major Diseases in Children, Ministry of Education, National Clinical Research Center for Respiratory Diseases, Laboratory of Respiratory Diseases, Beijing Pediatric Research Institute, Beijing Children's Hospital, Capital Medical University, National Center for Children's Health, Beijing, China.
Hui XiaNational Key Laboratory of Intelligent Tracking and Forecasting for Infectious Diseases, National Center for Tuberculosis Control and Prevention, Chinese Centre for Disease Control and Prevention, Beijing, China.
Yunhong TanDepartment of Clinical Laboratory, Hunan Chest Hospital, Changsha, China.
Yanlin ZhaoNational Key Laboratory of Intelligent Tracking and Forecasting for Infectious Diseases, National Center for Tuberculosis Control and Prevention, Chinese Centre for Disease Control and Prevention, Beijing, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Introduction: Digital droplet PCR (ddPCR) offers high sensitivity and absolute quantification without standard curves, making it promising for tuberculosis (TB) detection in paucibacillary samples. This study evaluated the diagnostic performance of a ddPCR assay targeting IS6110 and 23S rRNA for pulmonary tuberculosis (PTB) and tuberculous pleurisy (TP). Methods: A total of 436 patients (245 suspected PTB, 191 suspected TP) were prospectively enrolled. ddPCR was performed on sputum, bronchoalveolar lavage fluid, and pleural effusion samples. Diagnostic performance was compared with Xpert MTB/RIF and culture. Results: In suspected PTB, ddPCR showed significantly higher sensitivity than Xpert (49.70% vs. 38.10%, Discussion: ddPCR offers improved sensitivity for PTB and TP diagnosis, particularly in paucibacillary cases, though its lower specificity necessitates confirmatory testing. The dual-target design enables simultaneous MTB/NTM differentiation, providing clinical utility for guiding appropriate therapy.

Indexed as

diagnosisdigital droplet PCRpulmonary tuberculosistuberculous pleurisyXpert MTB/RIF

Identifiers

PMID42063766
PMCPMC13124612

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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.