Evidence map›Paper›PMID 35253079›Full record

ReviewEmergency radiology2022

Acutely presenting congenital chest lesions: a primer for the radiologist.

Apeksha Chaturvedi, Nina Klionsky, Deepa Biyyam, Mitchell A Chess, Nadia Sultan

Abstract readReview
PubMed Publisher
In one paragraph

Review in Emergency radiology, 2022. 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
0.4field-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, 2 citations in OpenAlex.

  1. Review
  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

5 authors at 2 institutions in 1 country.

Apeksha ChaturvediDepartment of Imaging Sciences, Division of Pediatric Radiology, University of Rochester Medical Center, Rochester, NY, 14642, USA. apeksha_chaturvedi@urmc.rochester.edu.ORCID http://orcid.org/0000-0002-1222-4795
Nina KlionskyDepartment of Imaging Sciences, Division of Pediatric Radiology, University of Rochester Medical Center, Rochester, NY, 14642, USA.
Deepa BiyyamPhoenix Children's Hospital, Phoenix, AZ, USA.
Mitchell A ChessDepartment of Imaging Sciences, Division of Pediatric Radiology, University of Rochester Medical Center, Rochester, NY, 14642, USA.
Nadia SultanDepartment of Imaging Sciences, Division of Pediatric Radiology, University of Rochester Medical Center, Rochester, NY, 14642, USA.
University of Rochester Medical Center · USPhoenix Children's Hospital · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Congenital chest lesions encompass several important entities. Without prompt intervention, many of these can culminate in serious complications. Timely and accurate radiologic interpretation of these entities is integral to patient management. Imaging can help characterize and prognosticate several of these entities, and may both suggest the need for and guide therapy. We overview the clinical presentation, associated complications, imaging characteristics, and prognostic indicators-both postnatal and antenatal-of the spectrum of emergently presenting congenital chest lesions. We also outline current and evolving management strategies, whether fetal, peripartum, or postnatal. The ultimate goal is to help radiologists formulate timely and effective diagnoses of these entities and boost the relevance of their input towards clinical decision-making.

Indexed as

Cystic Adenomatoid Malformation of Lung, CongenitalFemaleHumansPregnancyPrenatal DiagnosisRadiologistsThoraxUltrasonography, PrenatalChestCongenitalFetal MRIMalformationObstetric ultrasound

Identifiers

PMID35253079
OpenAlexW4220734390

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.