Evidence map›Paper›PMID 35315291›Full record

ArticleThe British journal of radiology2023

Incidentalomas in chest CT.

Reginald Munden

Abstract read
In one paragraph

Article in The British journal of radiology, 2023. 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. Review
  3. Review
  4. Article
  5. 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

1 author.

Reginald MundenMUSC Medical Center, Charleston, United States.ORCID 0000-0003-3836-5067

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Advances in imaging technology have dramatically increased the resolution of CT and improved detection of disease; these advances also have led to an increase in incidentalomas or incidental findings that often do not represent significant disease. Incidental findings on thoracic CT are common and can be problematic and expensive to evaluate. Thoracic imagers often are having to make recommendations for appropriate management which adds to the burden. Thoracic CT incidental findings are broad and include those of the lungs, heart, mediastinum, pleura, chest wall, thoracic soft tissues as well as the lower neck and upper abdomen. Of these, incidental pulmonary nodules have garnered the most interest over the years, but all incidentals may be proven to represent significant disease. In the USA, the American College of Radiology has generated white papers on incidentals that have proven useful. Currently, a number of investigations to utilize artificial intelligence for qualification and management of incidentals are ongoing. Likewise, the radiology/imaging community must support efforts to collaboratively address incidental findings and management concerns. As such, continued efforts to establish guidelines for appropriate identification, classification and management of incidentals is important to improve patient care and assure fiscally responsible assessment.

Indexed as

Artificial IntelligenceThoracic WallHumansIncidental FindingsMediastinumNeckTomography, X-Ray Computed

Identifiers

PMID35315291
PMCPMC9975517

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.