Evidence map›Paper›PMID 41971276›Full record

ArticleFrontiers in public health2026

A comprehensive diagnostic model for tuberculous PE: integration of clinical and immunological biomarkers.

Tingting Li, Huanqing Liu, Guolian Zhao, Qian Lei, Zhuhong You, Jianying Li

Abstract read
In one paragraph

Article in Frontiers in public health, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

6 authors.

Tingting LiDrug Clinical Trial Institution Office, Xi'an Chest Hospital, Xi'an, Shaanxi, China.
Huanqing LiuInformation Management Office, Northwestern Polytechnical University, Xi'an, Shaanxi, China.
Guolian ZhaoLaboratory Department, Xi'an Chest Hospital, Xi'an, Shaanxi, China.
Qian LeiDepartment of Pharmacy, Xi'an Chest Hospital, Xi'an, Shaanxi, China.
Zhuhong YouSchool of Computer Science, Northwestern Polytechnical University, Xi'an, Shaanxi, China.
Jianying LiDrug Clinical Trial Institution Office, Xi'an Chest Hospital, Xi'an, Shaanxi, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Tuberculous pleurisy represents a prevalent form of extrapulmonary tuberculosis and constitutes a significant diagnostic challenge in clinical practice, particularly in endemic regions where it accounts for approximately 20-30% of all PEs. The nonspecific clinical presentation and the limitations of conventional diagnostic methods-including the low sensitivity and prolonged turnaround time of pleural fluid culture-often result in delayed diagnosis and treatment, potentially compromising patient outcomes. Objective: To develop and validate a comprehensive, evidence-based predictive model that integrates readily available clinical and immunological biomarkers to enhance the early and accurate diagnosis of tuberculous pleurisy, thereby supporting timely clinical decision-making and optimized patient management. Methods: We conducted a retrospective cohort study of 523 consecutive patients presenting with PE at a tertiary care center between 2010 and 2021, including 375 patients with confirmed tuberculous pleurisy and 148 with non-tuberculous effusions. Demographics, biochemical markers (adenosine deaminase, lactate dehydrogenase, C-reactive protein, D-dimer), immunological parameters (T-SPOT.TB, T-cell subsets), and clinical indicators were systematically evaluated. Statistical analyses encompassed descriptive and comparative tests, multivariate logistic regression, and receiver operating characteristic curve analysis. Missing data were addressed using median imputation (Rivalta test, 4.4%) and case-wise deletion (T-cell subsets, 14.9%). Results: Five independent predictors were significantly associated with tuberculous pleurisy: younger age, elevated adenosine deaminase, lower C-reactive protein, positive Rivalta test, and positive T-SPOT.TB result. The multivariate logistic regression model demonstrated excellent discriminative performance (pseudo Conclusion: This study presents a robust and clinically applicable diagnostic model that effectively distinguishes tuberculous pleurisy from non-tuberculous PEs by integrating multiple routinely available biomarkers. The model offers a practical, cost-effective tool for early diagnosis, with the potential to improve therapeutic timeliness and patient outcomes across varied healthcare settings.

Indexed as

BiomarkersTuberculosis, PleuralAdenosine DeaminaseAdultAgedFemaleHumansMaleMiddle AgedRetrospective StudiesROC CurveAdenosine DeaminaseBiomarkersadenosine deaminasediagnostic markerspredictive modelT-SPOT.TBtuberculous PE

Identifiers

PMID41971276
PMCPMC13066118

What OpenQuestion holds

Textmetadata
LicenceCC BY
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 OpenQuestion graph.