Evidence map›Paper›PMID 36714345›Full record

ArticleChinese journal of cancer research = Chung-kuo yen cheng yen chiu2022

Advances in surgical techniques for gastric cancer: Indocyanine green and near-infrared fluorescence imaging. Is it ready for prime time?

Erica Sakamoto, Adriana Vaz Safatle-Ribeiro, Ulysses Ribeiro Jr

Open access · diamondAbstract read
In one paragraph

Article in Chinese journal of cancer research = Chung-kuo yen cheng yen chiu, 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
1.1field-weighted citation impact, top 21% 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. Article
  2. Article
  3. Review
  4. Review
  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

3 authors at 1 institution in 1 country.

Erica SakamotoDepartment of Gastroenterology, Instituto do Cancer do Estado de São Paulo, Hospital das Clinicas, Faculdade de Medicina, Universidade de São Paulo, (ICESP-HCFMUSP) São Paulo, SP 01246-000, Brazil.
Adriana Vaz Safatle-RibeiroDepartment of Gastroenterology, Instituto do Cancer do Estado de São Paulo, Hospital das Clinicas, Faculdade de Medicina, Universidade de São Paulo, (ICESP-HCFMUSP) São Paulo, SP 01246-000, Brazil.
Ulysses Ribeiro JrDepartment of Gastroenterology, Instituto do Cancer do Estado de São Paulo, Hospital das Clinicas, Faculdade de Medicina, Universidade de São Paulo, (ICESP-HCFMUSP) São Paulo, SP 01246-000, Brazil.
Instituto do Câncer do Estado de São Paulo · BR

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Surgery is still the primary curative treatment for gastric cancer, which includes resection of the tumor with adequate margins and extended lymphadenectomy. In order to improve the operative results and the quality of life of patients, several endeavors have been made toward precision medicine through image-guided surgery, allowing access to real-time intraoperative anatomy and accurate tumor staging. The goal of the surgeon is to achieve a more precise, individualized, and less invasive surgery without compromising oncological efficiency and safety. In this perspective, we have demonstrated the role of indocyanine green (ICG) and near-infrared (NIR) fluorescence imaging method in gastric cancer surgery. This technique may be used to improve localization of the tumor, detection of sentinel lymph nodes (SLN), real-time lymphatic mapping, and blood flow assessment (anastomosis perfusion).

Indexed as

gastric cancerIndocyanine greenlymphatic mappingnear-infrared fluorescence imaging

Identifiers

PMID36714345
PMCPMC9829491
OpenAlexW4315565957

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.