Evidence map›Paper›PMID 38389756›Full record

ReviewIndian journal of thoracic and cardiovascular surgery2024

Management of screening-detected ground glass nodules: a narrative review.

Willis Wasonga Omindo

Open access · greenAbstract readReview
In one paragraph

Review in Indian journal of thoracic and cardiovascular surgery, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
0.3field-weighted citation impact, top 36% 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

1 citing paper in PubMed, 1 citations in OpenAlex.

  1. 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 at 1 institution in 1 country.

Willis Wasonga OmindoDepartment of Thoracic Surgery, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, No. 1095, Jiefang Avenue, Wuhan, 430030 Hubei China.
Tongji Hospital · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Wide-scale application of low-dose computed tomography (LDCT) in lung cancer screening has led to an increased detection of ground glass nodule (GGN) lesions. However, there is still no clear management plan for these lesions after detection. Clinicians are usually faced with a dilemma in choosing the best initial management approach that not only limits overtreatment but also avoids the possibility of lesions growing into invasive carcinoma. Most current and past guidelines favor surveillance with computed tomography (CT) as the initial management approach based on the notion that the majority of GGN lesions are indolent tumors. Immediate surgery is generally considered overtreatment and is usually only recommended when the lesion grows in size, persists, or increases its solid component during follow-up CT surveillance. However, due to evolution of surgery to minimal invasive procedures, such as uniportal video-assisted thoracic surgery, and the development of enhanced recovery after thoracic surgery protocols, modern surgery is now safer and associated with less postoperative mortality. Additionally, intraoperative frozen sections can be used to guide resection, making initial management via surgery more attractive than before. Based on these developments, this review recommends that immediate surgery should be considered at the same level as follow-up CT surveillance when making multidisciplinary team decisions for screening-detected GGNs, as it provides both a diagnostic and treatment role.

Indexed as

Follow-up CT surveillanceGGNGround glass nodulesGround glass opacityImmediate surgerySubsolid nodules

Identifiers

PMID38389756
PMCPMC10879480
OpenAlexW4386778647

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.