Evidence map›Paper›PMID 38527990›Full record

ReviewRomanian journal of morphology and embryology = Revue roumaine de morphologie et embryologie

Pulmonary Epstein-Barr virus-associated smooth muscle tumor after kidney transplantation: two case reports with review of differential diagnosis.

Xiao-Yu Fu, Xia Gao, Chun-Lei Zhao, Xing-Feng Qi, Xiao-Juan Ouyang, Ling-Hua Zhu, Dong Wang, Li-Juan Qu, Xian-Zong Ye

Open access · diamondAbstract readCase ReportsReview
In one paragraph

Review in Romanian journal of morphology and embryology = Revue roumaine de morphologie et embryologie. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
0.3field-weighted citation impact, top 40% of its field
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

2 citing papers in PubMed, 1 citations in OpenAlex.

  1. Article
  2. 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 at 1 institution in 1 country.

Xiao-Yu FuDepartment of Pathology, The 900th Hospital of the Joint Logistics Support Force, Fuzhou City, China; qljuan6516@sina.com, yexianzong@126.com.
Xia Gao
Chun-Lei Zhao
Xing-Feng Qi
Xiao-Juan Ouyang
Ling-Hua Zhu
Dong Wang
Li-Juan Qu
Xian-Zong Ye
Fujian Medical University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Pulmonary nodules are a common complication in solid organ transplant recipients, and may have various underlying causes, with Epstein-Barr virus-associated smooth muscle tumor (EBV-SMT) being one of them. Given the rarity of this entity, we describe the diagnosis and therapeutic interventions for post-transplant EBV-SMT in two individuals. Both cases involved female patients who were diagnosed with multiple pulmonary nodules 60 months and 116 months, respectively, after receiving living-related kidney transplantation. Pathological examination revealed a spindle cell tumor, with immunophenotype and EBV in situ hybridization supporting the diagnosis of EBV-SMT. After diagnosis, these two patients underwent intervention by decreasing their intake of immunosuppressants. As of the latest follow-up, the patients' lesion size remained stable, and their overall condition was favorable. We also reviewed literature about the morphological and molecular pathological features of EBV-SMT and highlighted the diagnosis and differential diagnosis of pulmonary spindle cell lesions especially in the setting of immunosuppression.

Indexed as

Epstein-Barr Virus InfectionsKidney TransplantationSmooth Muscle TumorDiagnosis, DifferentialFemaleHerpesvirus 4, HumanHumans

Identifiers

PMID38527990
PMCPMC11146452
OpenAlexW4394739068

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-SA
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.