Evidence map›Paper›PMID 41710566›Full record

ArticleCanadian respiratory journal2026

The Value of the Near-Infrared Fluorescent Probe ErNP@SiO2-ICG in the Diagnosis of Malignant Pleural Effusion.

Chuchu Xu, Xiaoxia Wang, Xingya Yan, Xiaona Yin, Xi Wang, Fangbin Du, Yinling Jiang, Xiaoqiong Wang, Yongsheng Wang

Abstract read
In one paragraph

Article in Canadian respiratory journal, 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

9 authors.

Chuchu XuDepartment of Pulmonary and Critical Care Medicine, The Second People's Hospital of Hefei, Hefei Hospital Affiliated to Anhui Medical University, Hefei, 230011, Anhui, China, ahmu.edu.cn.ORCID 0009-0001-4029-538X
Xiaoxia WangDepartment of Respiratory and Critical Care Medicine, The Affiliated Hefei Hospital of Anhui Medical University (Hefei no. 2 People's Hospital), Hefei, 230011, Anhui, China.
Xingya YanDepartment of Respiratory and Critical Care Medicine, The Affiliated Hefei Hospital of Anhui Medical University (Hefei no. 2 People's Hospital), Hefei, 230011, Anhui, China.
Xiaona YinDepartment of Pulmonary and Critical Care Medicine, The Second People's Hospital of Hefei, Hefei Hospital Affiliated to Anhui Medical University, Hefei, 230011, Anhui, China, ahmu.edu.cn.
Xi WangDepartment of Pulmonary and Critical Care Medicine, The Second People's Hospital of Hefei, Hefei Hospital Affiliated to Anhui Medical University, Hefei, 230011, Anhui, China, ahmu.edu.cn.
Fangbin DuDepartment of Pulmonary and Critical Care Medicine, The Second People's Hospital of Hefei, Hefei Hospital Affiliated to Anhui Medical University, Hefei, 230011, Anhui, China, ahmu.edu.cn.
Yinling JiangDepartment of Pulmonary and Critical Care Medicine, The Second People's Hospital of Hefei, Hefei Hospital Affiliated to Anhui Medical University, Hefei, 230011, Anhui, China, ahmu.edu.cn.
Xiaoqiong WangDepartment of Pulmonary and Critical Care Medicine, The Second People's Hospital of Hefei, Hefei Hospital Affiliated to Anhui Medical University, Hefei, 230011, Anhui, China, ahmu.edu.cn.ORCID 0009-0004-2396-052X
Yongsheng WangDepartment of Pulmonary and Critical Care Medicine, The Second People's Hospital of Hefei, Hefei Hospital Affiliated to Anhui Medical University, Hefei, 230011, Anhui, China, ahmu.edu.cn.ORCID 0009-0009-7216-5406

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Objectives: Malignant pleural effusions (MPEs) present a significant clinical challenge and are associated with a poor prognosis, frequently observed in patients with advanced malignancies. Conventional diagnostic techniques for identifying MPEs exhibit limitations in both accuracy and sensitivity. To differentiate between benign and MPEs, the clinical applicability of the ErNP@SiO2-ICG rare earth nano-nano near-infrared (NIR) fluorescence probe was investigated. Methods: Through solution chemistry processes, vacuum treatment with heat, and the synthesis of a core-shell design, an exceptional rare earth nano NIR fluorescent probe was developed in this study, which showed the capacity to target tumors precisely. After that, a prospective research was conducted with a cohort of 90 patients; 20 of them were excluded because of unclear diagnoses. Every participant had a thoracoscopic biopsy for histological analysis, a cytological assessment of pleural effusions, and an evaluation of the recently developed dyes. R programming, GraphPad Prism, and Microsoft Excel were used when carrying out statistical inspection of the obtained data. Results: ErNP@SiO2-ICG particles experienced a size of 176.1 ± 0.2 nm. Their emission peak was located at 550 nm in relation to their fluorescence spectra, and their scanning electron microscopy image demonstrated uniform particle size and distribution with NIR fluorescence characteristics. The optimum time and concentration for color development were 2 μL and 1 h, respectively. The fluorescence imaging and cytological investigation of pleural effusions differed significantly ( Conclusion: The ErNP@SiO2-ICG rare earth-doped nano-probe for NIR fluorescence imaging exhibits exceptional accuracy in the detection of MPE, thereby providing an innovative technological approach for the future identification of this condition.

Indexed as

Fluorescent DyesIndocyanine GreenPleural Effusion, MalignantSilicon DioxideAgedFemaleHumansMaleMiddle AgedProspective StudiesSensitivity and SpecificityFluorescent DyesIndocyanine GreenSilicon DioxideErNP@SiO2-ICGindocyanine greenmalignant pleural effusionnear-infrared fluorescencerare earth nano

Identifiers

PMID41710566
PMCPMC12910513

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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.