Evidence map›Paper›PMID 35035652›Full record

ArticleRadiology case reports2022

Acute axillary lymphadenopathy detected shortly after COVID-19 vaccination found to be due to newly diagnosed metastatic melanoma.

David M Gullotti, Evan J Lipson, Elliot K Fishman, Steven P Rowe

Open access · goldAbstract readCase Reports
In one paragraph

Article in Radiology case reports, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
1.3field-weighted citation impact, top 22% 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

5 citing papers in PubMed, 7 citations in OpenAlex.

  1. Review
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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 at 1 institution in 1 country.

David M GullottiThe Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, 600 North Wolfe Street, Radiology Room 118, 21287 Baltimore, MD, USA.
Evan J LipsonDepartment of Oncology, Sidney Kimmel Comprehensive Cancer Center, Johns Hopkins University School of Medicine, Baltimore, MD, USA.
Elliot K FishmanThe Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, 600 North Wolfe Street, Radiology Room 118, 21287 Baltimore, MD, USA.
Steven P RoweThe Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, 600 North Wolfe Street, Radiology Room 118, 21287 Baltimore, MD, USA.
Johns Hopkins University · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

As the administration of COVID-19 vaccines continues to increase, so too does awareness of the associated ipsilateral axillary lymphadenopathy. This has created a diagnostic challenge in the field of radiology, in particular among patients with cancer, as post-vaccination reactive adenopathy has been reported to be mistakenly interpreted as malignancy. As radiology departments improve their protocols for obtaining vaccine-related patient history, and radiologists become acclimated to attributing axillary lymphadenopathy to recent COVID-19 vaccination, there is a risk of the pendulum swinging too far and under-diagnosing true oncologic disease. This report describes an otherwise healthy 53-year-old man who presented with discomfort due to ipsilateral axillary lymphadenopathy shortly after receiving a COVID-19 vaccine. Fine needle aspiration performed within 2 months of receiving the vaccine revealed metastatic melanoma and subsequent

Indexed as

COVID-19COVID-19 vaccineLymphadenopathyPET/CTSARS-CoV2

Identifiers

PMID35035652
PMCPMC8747434
OpenAlexW4206452420

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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.