Evidence map›Paper›PMID 36105121›Full record

ArticleFrontiers in surgery2022

A rare hepatic artery variant reporting and a new classification.

Xiaojing Wu, Jianxiong Kang, Yuwei Liu, Guodong Sun, Ying Shi, Junqi Niu

Open access · goldAbstract read
In one paragraph

Article in Frontiers in surgery, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed
1.3field-weighted citation impact, top 20% 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

7 citing papers in PubMed, 8 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

6 authors at 2 institutions in 1 country.

Xiaojing WuDepartment of Hepatology, First Bethune Hospital of Jilin University, Changchun, China.
Jianxiong KangGeneral Laboratory of Human Anatomy, Changzhi Medical College, Changzhi, China.
Yuwei LiuDepartment of Hepatology, First Bethune Hospital of Jilin University, Changchun, China.
Guodong SunGeneral Laboratory of Human Anatomy, Changzhi Medical College, Changzhi, China.
Ying ShiDepartment of Hepatology, First Bethune Hospital of Jilin University, Changchun, China.
Junqi NiuDepartment of Hepatology, First Bethune Hospital of Jilin University, Changchun, China.
First Bethune Hospital of Jilin University · CNChangzhi Medical College · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Variations of the hepatic artery are very common, but they greatly increase the difficulty of surgery and the risk of complications in perihepatic surgeries such as liver transplantation, liver segmentectomy, and gastroduodenal surgery. Thus, it is important to precisely define the type of hepatic artery variant before surgery. However, there are often rare variants that cannot be defined with existing classifications. For example, the type of hepatic artery variant in the current case could not be classified with conventional classifications, and no such variation has been reported to date, involving two accessory left hepatic arteries from the common hepatic and left inferior phrenic arteries, respectively. Based on the existing 3DCT technology and the CRL classification method, which is applicable to the most common hepatic artery variants, we reviewed many rare variant types and proposed a new classification method (ex-CRL classification) for hepatic artery variations that do not fit the classic scope. The ex-CRL classification can accurately classify the vast majority of rare cases in the literature, greatly compensates for the limitations of current hepatic artery classifications, improves the generalization and understanding of rare cases, and reduces surgical complications.

Indexed as

accessory hepatic arterycase reportclassificationphrenic arteryvascular variants

Identifiers

PMID36105121
PMCPMC9465518
OpenAlexW4293761290

What OpenQuestion holds

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LicenceCC BY
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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.