Evidence map›Paper›PMID 42286723›Full record

ArticleJournal of medical case reports2026

Giant mediastinal lipoma with bilateral hemithoracic extension in a young woman: a case report.

Reza Jalli, Bijan Ziaian, Asal Seifaei, Seyed Sina Dehghani

Abstract readCase Reports
In one paragraph

Article in Journal of medical case reports, 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

4 authors.

Reza JalliMedical Imaging Research Center, Shiraz University of Medical Sciences, Shiraz, Iran.
Bijan ZiaianDepartment of Cardiothoracic Surgery, Shiraz University of Medical Sciences, Shiraz, Iran.
Asal SeifaeiStudent Research Committee, Shiraz University of Medical Sciences, Shiraz, Iran.
Seyed Sina DehghaniMedical Imaging Research Center, Department of Radiology, Shiraz University of Medical Sciences, Shiraz, Iran. dehghani.sina77@gmail.com.ORCID http://orcid.org/0000-0002-3436-8079

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundMediastinal lipomas are rare benign tumors that usually remain asymptomatic until they reach a considerable size. Giant mediastinal lipomas can cause progressive respiratory symptoms and present diagnostic challenges by mimicking malignant lipomatous tumors. CASE PRESENTATION: We report a 33-year-old Iranian woman presenting with progressive dyspnea for one year. Chest radiography and contrast-enhanced CT revealed a giant, well-encapsulated fat-density mass in the anterior mediastinum, measuring approximately 214 × 123 × 159 mm, extending to the diaphragmatic level and into the contralateral hemithorax, without invasive features. The patient underwent complete surgical excision via median sternotomy. Intraoperatively, a large encapsulated fatty mass with minimal adhesions and no signs of invasion was identified. Histopathological examination confirmed a benign lipoma composed of mature adipocytes. The postoperative course was uneventful, with complete resolution of symptoms.

conclusionsGiant mediastinal lipomas are rare but should be considered in the differential diagnosis of fat-containing mediastinal masses. Cross-sectional imaging plays a pivotal role in diagnosis, while complete surgical resection provides definitive treatment with excellent outcomes.

Indexed as

LipomaMediastinal NeoplasmsAdultDiagnosis, DifferentialDyspneaFemaleHumansSternotomyTomography, X-Ray ComputedTreatment OutcomeCase reportGiant lipomaMedian sternotomyMediastinal lipomaMediastinal mass

Identifiers

PMID42286723
PMCPMC13483599

What OpenQuestion holds

Textmetadata
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.