Evidence map›Paper›PMID 39161672›Full record

ArticleClinical case reports2024

Approaching a patient with poststernal pain after eating: A case report.

Yanjun Feng, Yayan Niu, Jinyu Yan, Meiying Wu, Peijun Tang

Abstract readCase Reports
In one paragraph

Article in Clinical case reports, 2024. 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

5 authors.

Yanjun FengDepartment of Tuberculosis, The Fifth People's Hospital of Suzhou The Affiliated Infectious Diseases Hospital of Soochow University Suzhou China.ORCID https://orcid.org/0009-0001-7547-0117
Yayan NiuDepartment of Tuberculosis, The Fifth People's Hospital of Suzhou The Affiliated Infectious Diseases Hospital of Soochow University Suzhou China.
Jinyu YanDepartment of Tuberculosis, The Fifth People's Hospital of Suzhou The Affiliated Infectious Diseases Hospital of Soochow University Suzhou China.
Meiying WuDepartment of Tuberculosis, The Fifth People's Hospital of Suzhou The Affiliated Infectious Diseases Hospital of Soochow University Suzhou China.
Peijun TangDepartment of Tuberculosis, The Fifth People's Hospital of Suzhou The Affiliated Infectious Diseases Hospital of Soochow University Suzhou China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

This article reports a case of mediastinal lymph node tuberculosis with no obvious symptoms and a concealed focus. This patient, a 33-year-old male, suffered from pain behind the sternum after eating. He underwent three gastroscopic examinations and two fine needle punctures guided by ultrasound gastroscopy but was not diagnosed. Chest-enhanced CT revealed a mediastinal mass compressing the adjacent esophagus, suggesting the possibility of enlarged lymph nodes. Furthermore, T cells from patients infected with tuberculosis tested positive. Ultrasound bronchoscopy revealed enlarged lymph nodes in area 7, and then EBUS-TBNA was performed in that region. Only a few scattered lymphocytes and necrotic tissue were found under the biopsy microscope. The EBUS-TBNA biopsy Xpert MTB/RIF showed low positive results, and the EBUS-TBNA puncture fluid Xpert MTB/RIF was positive. Therefore, he was diagnosed with mediastinal lymph node tuberculosis. After antituberculosis treatment with the 2HREZ/10HRE regimen, the patient's pain behind the sternum gradually alleviated, and the enlarged mediastinal lymph nodes gradually narrowed.

Indexed as

EBUS‐TBNAmediastinal lymph nodespoststernal paintuberculosisXpert MTB/RIF

Identifiers

PMID39161672
PMCPMC11331029

What OpenQuestion holds

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Registered trials

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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.