Evidence map›Paper›PMID 37096062›Full record

ArticlePeerJ2023

Intra-abdominal fat volume estimation by multi-detector rows computed tomography: relevance in surgical fellowship training program in Shanghai: a retrospective study.

Jenifei Shah, Suyue Yu, Jingyi Huang, Lu Zang, Tian Li, Zhenglun Zhu

Open access · goldAbstract read
In one paragraph

Article in PeerJ, 2023. 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
–field-weighted citation impact, top 85% 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, 0 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

6 authors at 3 institutions in 1 country.

Jenifei Shah *Department of General Surgery, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China.
Suyue Yu *Department of General Surgery, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China.
Jingyi HuangDepartment of Urology, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China.
Lu ZangDepartment of General Surgery, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China.
Tian LiSchool of Basci Med, Fouth Military Medical University, Xi'an, China.
Zhenglun ZhuDepartment of General Surgery, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China.
Ruijin Hospital · CNShanghai Jiao Tong University · CNAir Force Medical University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Intra-abdominal fat volume (IFV) has been shown to have a negative impact on surgical outcomes in gastric cancer (GC) and other gastrointestinal surgeries. The purpose of this study is to look into the relationship between IFV and perioperative outcomes in GC patients using multi-detector rows computed tomography (MDCT) and assess the importance of implementing this observation in current surgical fellowship training programs. Methods: Patients with GC who underwent open D2 gastrectomy between May 2015 and September 2017 were included in the study. Based on MDCT estimation, patients were divided into high IFV (IFV ≥ 3,000 ml) and low IFV (IFV < 3,000 ml) groups. Perioperative outcomes for cancer staging, type of gastrectomy, intraoperative blood loss (IBL), anastomotic leakage, and hospital stay were compared between the two groups. This study was registered as CTR2200059886. Results: Out of 226 patients, 54 had early gastric carcinoma (EGC), while 172 had advanced gastric carcinoma (AGC). There were 64 patients in the high IFV group and 162 in the low IFV group. The high IFV group had significantly higher IBL mean values ( Conclusions: High IFV estimated by MDCT prior to GC surgery was associated with increased IBL and postoperative complications. Incorporating this CT-IFV estimation into surgical fellowship programs may aid aspiring surgeons in selecting patients during independent practice in their learning curve and surgical practice for the most appropriate approach for treating GC patients.

Indexed as

CarcinomaStomach NeoplasmsBlood Loss, SurgicalChinaFellowships and ScholarshipsHumansIntra-Abdominal FatMultidetector Computed TomographyRetrospective StudiesBlood lossD2 gastrectomyFellowship trainingGastric cancerIntra-abdominal fat volumeObesity

Identifiers

PMID37096062
PMCPMC10122455
OpenAlexW4366421208

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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.