Evidence map›Paper›PMID 40155945›Full record

ArticleBMC pulmonary medicine2025

A scoring model based on the pleural effusion adenosine deaminase-to-serum C-reactive protein ratio for differentiating tuberculous pleural effusion from non-tuberculous benign pleural effusion.

Huan Hou, Jieying Li, Tingting Huang, Zhaohui Ruan, Xinjie Hui, Yilin Huang, Jinming Gao

Abstract read
In one paragraph

Article in BMC pulmonary medicine, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Development of a diagnostic nomogram for tuberculous pleural effusion.Journal of clinical tuberculosis and other mycobacterial diseases · 2026
    Article
  2. 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

7 authors.

Huan Hou *Departments of Pulmonary and Critical Care Medicine, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, 100730, China.
Jieying Li *Departments of Pulmonary and Critical Care Medicine, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, 100730, China.
Tingting Huang *Department of Pulmonary and Critical Care Medicine, National Center for Respiratory Medicine, State Key Laboratory of Respiratory Health and Multimorbidity, National Clinical Research Center for Respiratory Diseases, Institute of Respiratory Medicine, Center of Respiratory Medicine, Chinese Academy of Medical Sciences, China-Japan Friendship Hospital, Beijing, 100029, China.
Zhaohui RuanDepartment of Medical Oncology, Lung Cancer and Gastrointestinal Unit, The Affiliated Cancer Hospital of Xiangya School of Medicine, Hunan Cancer Hospital, Central South University, Changsha, 410013, China.
Xinjie HuiDepartments of Pulmonary and Critical Care Medicine, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, 100730, China.
Yilin HuangDepartments of Pulmonary and Critical Care Medicine, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, 100730, China.
Jinming GaoDepartments of Pulmonary and Critical Care Medicine, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, 100730, China. gao.jin.ming@hotmail.com.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundDifferentiating tuberculous pleural effusion (TPE) from non-tuberculous benign pleural effusion (non-TB BPE) can be challenging, especially in patients with low levels of pleural effusion adenosine deaminase (pADA) and negative etiological evidence. This study aimed to evaluate the diagnostic performance of the pADA to serum C-reactive protein ratio (pADA/sCRP) and to develop a scoring model for diagnosing TPE.

methodsThis retrospective study included 364 patients with pleural effusion, comprising 121 with TPE and 243 with non-TB BPE from Peking Union Medical College Hospital. Clinical, laboratory, and imaging data were collected, and comparisons were made between the two groups. The diagnostic performance of the pADA/sCRP ratio and other statistically significant variables was assessed. Six valuable factors were selected for multivariate regression analysis to establish a predictive model, which was displayed as a nomogram.

resultsThe pADA/sCRP ratio demonstrated superior diagnostic performance compared to pADA alone, with an area under the curve (AUC), sensitivity, and specificity for identifying TPE of 0.68, 71%, and 64%, respectively. Six variables were selected to develop a nomogram, including night sweats, calcification on chest computed tomography, pleural effusion lymphocyte ratio, pADA/sCRP, hemoglobin, and neutrophil. With a cutoff value of 20 points, the AUC, sensitivity, and specificity for distinguishing TPE from non-TB BPE were 0.836, 83.4%, and 64.9%, respectively. The validation cohort confirmed the model with the AUC, sensitivity, and specificity of 0.815, 61.1%, and 82.4%, respectively.

conclusionThe pADA/sCRP ratio exhibited improved diagnostic performance compared to pADA alone. The novel scoring system based on a nomogram demonstrated good diagnostic efficacy in differentiating TPE from non-TB BPE.

Indexed as

Adenosine DeaminaseC-Reactive ProteinPleural EffusionTuberculosis, PleuralAdultAgedBiomarkersDiagnosis, DifferentialFemaleHumansMaleMiddle AgedNomogramsRetrospective StudiesROC CurveSensitivity and SpecificityAdenosine DeaminaseBiomarkersC-Reactive ProteinAdenosine deaminaseC-reactive proteinNomogramScoring systemTuberculous pleural effusion

Identifiers

PMID40155945
PMCPMC11951641

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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.