Evidence map›Paper›PMID 36164358›Full record

ArticleMediastinum (Hong Kong, China)2022

Giant mediastinal teratoma in a young infant: a case report.

Raelina S Howell, Margret S Magid, Keith A Kuenzler, T K Susheel Kumar

Abstract readCase Reports
In one paragraph

Article in Mediastinum (Hong Kong, China), 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
–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

5 citing papers in PubMed.

  1. Article
  2. Article
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  5. Review
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.

Raelina S HowellDepartment of Surgery, NYU Langone Hospital-Long Island, Mineola, NY, USA.
Margret S MagidDepartment of Pathology, NYU Langone Hospital, New York, NY, USA.
Keith A KuenzlerDepartment of Surgery, NYU Langone Hospital, New York, NY, USA.
T K Susheel KumarDepartment of Surgery, NYU Langone Hospital, New York, NY, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Giant mediastinal tumors in the pediatric population can pose unique challenges for resection such as cardiovascular collapse on induction of anesthesia and injury to surrounding structures that may be compressed, displaced, or invaded by the mass. Principles that must be borne in mind during removal of giant mediastinal masses include: appropriate cross-sectional imaging to define extent of mass; airway control during induction of anesthesia; a multidisciplinary collaborative approach including cardiothoracic surgery; preparation for urgent sternotomy; plan for peripheral cannulation to institute cardiopulmonary bypass if needed; preservation of neurovasculature structures during dissection; complete resection whenever possible. While complete resection is desirable and results in an excellent prognosis, it may not be achievable especially if the tumor encases coronary arteries, and it is acceptable to leave small amounts of tumor behind. Case Description: Here we present a case describing surgical management of a giant mediastinal teratoma in a two-month-old female. The patient was found to have a large mediastinal mass during workup for cough and noisy breathing. She underwent preoperative echocardiogram demonstrating normal cardiac function followed by uncomplicated, open resection of the mass. Conclusions: Giant mediastinal tumors give rise to unique challenges for resection in small infants. The principles of airway control, preparation for urgent sternotomy, preparation for peripheral cardiopulmonary bypass cannulation, and preservation of neurovasculature during dissection must be borne in mind.

Indexed as

Anterior mediastinumcase reportpediatric thoracic massteratoma

Identifiers

PMID36164358
PMCPMC9385876

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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.