Evidence map›Paper›PMID 35782807›Full record

ReviewIndian journal of surgical oncology2022

Thoracic Duct Lymphography by Near-Infrared Indocyanine Green Fluorescence imaging in Thoracic Surgery. A Review.

Syed Nusrath, Subramanyeshwar Rao Thammineedi, Ajesh Raj Saksena, Sujit Chyau Patnaik, Pratap Reddy, Zeeba Usofi, Santhosh Kumar

Open access · greenAbstract readReview
In one paragraph

Review in Indian journal of surgical oncology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing papers in PubMed
2.4field-weighted citation impact, top 12% 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

9 citing papers in PubMed, 13 citations in OpenAlex.

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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

7 authors at 1 institution in 1 country.

Syed NusrathDepartment of Surgical Oncology, Basavatarakam Indo American Cancer Hospital and Research Institute, Hyderabad, India.ORCID 0000-0001-7287-5488
Subramanyeshwar Rao ThammineediDepartment of Surgical Oncology, Basavatarakam Indo American Cancer Hospital and Research Institute, Hyderabad, India.
Ajesh Raj SaksenaDepartment of Surgical Oncology, Basavatarakam Indo American Cancer Hospital and Research Institute, Hyderabad, India.
Sujit Chyau PatnaikDepartment of Surgical Oncology, Basavatarakam Indo American Cancer Hospital and Research Institute, Hyderabad, India.
Pratap ReddyDepartment of Surgical Oncology, Basavatarakam Indo American Cancer Hospital and Research Institute, Hyderabad, India.
Zeeba UsofiDepartment of Surgical Oncology, Basavatarakam Indo American Cancer Hospital and Research Institute, Hyderabad, India.
Santhosh KumarDepartment of Surgical Oncology, Basavatarakam Indo American Cancer Hospital and Research Institute, Hyderabad, India.
Basavatarakam Indo American Cancer Hospital and Research Institute · IN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Near-infrared (NIR) fluorescence imaging with indocyanine green dye (ICG) is an emerging technology in detecting the anatomy of the thoracic duct; hence, it can be useful for the identification of the thoracic duct in real time and prevention of its injury during thoracic surgery. It helps to localize thoracic duct injury, identifying chyle leaks in difficult, recurrent, and refractory cases. This review paper provides insights regarding the current applications, advantages, and potential developments of NIR fluorescence imaging with ICG in recognizing thoracic duct during thoracic surgery.

Indexed as

Near-infrared indocyanine green fluorescenceThoracic duct lymphographyThoracic surgery

Identifiers

PMID35782807
PMCPMC9240143
OpenAlexW4206487180

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.