Evidence map›Paper›PMID 41816416›Full record

ReviewJournal of thoracic disease2026

Research progress on imaging prediction of pleural adhesion: a narrative review.

Yun Wang, Deng Lyu, Wenting Tu, Xiuxiu Zhou, Yi Xiao, Li Fan, Shiyuan Liu

Abstract readReview
In one paragraph

Review in Journal of thoracic disease, 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

7 authors.

Yun Wang *Department of Radiology, The Second Affiliated Hospital of Navy Medical University, Shanghai, China.ORCID https://orcid.org/0000-0001-8914-9861
Deng Lyu *Department of Radiology, The Second Affiliated Hospital of Navy Medical University, Shanghai, China.ORCID https://orcid.org/0000-0002-2205-6107
Wenting Tu *Department of Radiology, The Second Affiliated Hospital of Navy Medical University, Shanghai, China.ORCID https://orcid.org/0000-0003-1010-7189
Xiuxiu ZhouDepartment of Radiology, The Second Affiliated Hospital of Navy Medical University, Shanghai, China.ORCID https://orcid.org/0000-0003-2405-0566
Yi XiaoDepartment of Radiology, The Second Affiliated Hospital of Navy Medical University, Shanghai, China.ORCID https://orcid.org/0000-0002-3212-2892
Li FanDepartment of Radiology, The Second Affiliated Hospital of Navy Medical University, Shanghai, China.ORCID https://orcid.org/0000-0003-4722-3933
Shiyuan LiuDepartment of Radiology, The Second Affiliated Hospital of Navy Medical University, Shanghai, China.ORCID https://orcid.org/0000-0003-3420-0310

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background and Objective: Pleural adhesion is a significant risk factor that can lead to a poor prognosis in thoracic surgery. The extent of these adhesions directly affects the selection of preoperative surgical approaches, the progress of the intraoperative surgical process, and the occurrence of serious postoperative complications. Accurate preoperative judgment of pleural adhesions and their severity is of great significance for formulating perioperative treatment plans and achieving precision medicine. This article focuses on summarizing and synthesizing various imaging methods for preoperative prediction of pleural adhesions and discusses the challenges and prospects facing future research. The aim is to improve preoperative diagnostic accuracy and risk stratification, thereby enhancing surgical safety and efficacy. Methods: A comprehensive, non-systematic review of the latest literature was carried out in order to investigate the progress of predicting pleural adhesions. PubMed database was being examined, and the last run was on December 17 Key Content and Findings: This article reviews the definition, classification, and clinical significance of pleural adhesions, and summarizes the latest research progress of imaging prediction of pleural adhesions in the past 10 years. It was found that ultrasound, chest X-ray, computed tomography (CT), and Conclusions: Pleural adhesions influence the survival prognosis of patients with thoracic surgery. Effective preoperative prediction of the state of pleural adhesions can help to improve the preoperative surgical plan formulation and reduce the occurrence of postoperative complications. Ultrasound, chest X-ray, CT, and

Indexed as

imagingPleural adhesionpredictionpreoperative

Identifiers

PMID41816416
PMCPMC12972925

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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.