Evidence map›Paper›PMID 30174897›Full record

ArticleJournal of thoracic disease2018

Uniportal video-assisted thoracoscopic S

Guofei Zhang, Zipu Yu, Lian Wang, Gang Shen, Ying Chai

Abstract read
In one paragraph

Article in Journal of thoracic disease, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing 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

6 citing papers in PubMed.

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  6. Uniportal video-assisted thoracoscopic SJournal of thoracic disease · 2018
    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.

Guofei ZhangDepartment of Thoracic Surgery, the Second Affiliated Hospital, College of Medicine, Zhejiang University, Hangzhou 310009, China.
Zipu YuDepartment of Thoracic Surgery, the Second Affiliated Hospital, College of Medicine, Zhejiang University, Hangzhou 310009, China.
Lian WangDepartment of Thoracic Surgery, the Second Affiliated Hospital, College of Medicine, Zhejiang University, Hangzhou 310009, China.
Gang ShenDepartment of Thoracic Surgery, the Second Affiliated Hospital, College of Medicine, Zhejiang University, Hangzhou 310009, China.
Ying ChaiDepartment of Thoracic Surgery, the Second Affiliated Hospital, College of Medicine, Zhejiang University, Hangzhou 310009, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

With the increasing incidence of synchronous multiple primary lung cancers (SMPLC), difficulties in diagnosis and decision making for treating patients with SMPLC can result in clinical dilemmas for clinicians. To simplify the diagnostic and treatment course, the less-invasive technique of video-assisted thoracic surgery (VATS) segmentectomy and subsegmentectomy can be selected preferentially. However, segmentectomy and subsegmentectomy are technically more sophisticated compared to lobectomy, and they involve the identification of the nodule locations, confirmation of the targeted structures and ensuring the surgical margin. Here, we describe the performance of uniportal VATS segmentectomy and subsegmentectomy technique in a patient with SMPLC in the right upper lobe with the assistance of three-dimensional (3D) navigation. We detected the intersegmental planes using infrared thoracoscopy with an intravenous injection of indocyanine green (ICG). The patient was discharged with no complication. We think that uniportal VATS segmentectomy is a feasible alternative and technically safe for treating patients with SMPLC.

Indexed as

indocyanine green (ICG)Multiple primary lung cancers (SMPLC)segmentectomysubsegmentectomythree-dimensional computed reconstruction (3D computed reconstruction)uniportal surgeryvideo-assisted thoracic surgery (VATS)

Identifiers

PMID30174897
PMCPMC6106009

What OpenQuestion holds

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Registered trials

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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.