Evidence map›Paper›PMID 42052914›Full record

ArticleInternational wound journal2024

RETRACTED: Effect of body mass index on the wound infection and complications in patients with liver cancer: A meta-analysis.

Yan-Ping Li, Zhuo Gan, Bing Shi

RetractedAbstract readRetracted Publication
In one paragraph

Article in International wound journal, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It has been retracted, and should not be counted. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
  2. Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

3 authors.

Yan-Ping LiDepartment of Nuclear Medicine, The First Hospital of Hunan University of Chinese Medicine, Changsha, Hunan, China.
Zhuo GanDepartment of Nuclear Medicine, The First Hospital of Hunan University of Chinese Medicine, Changsha, Hunan, China.
Bing ShiDepartment of Nuclear Medicine, The First Hospital of Hunan University of Chinese Medicine, Changsha, Hunan, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

This study systematically evaluates the effect of body mass index on the occurrence of wound infections and complications in patients undergoing liver cancer surgery through a meta-analysis. A computerized search was conducted, from database inception to October 2023, in PubMed, Embase, Google Scholar, Cochrane Library, China National Knowledge Infrastructure and Wanfang databases for studies related to the impact of body mass index on patients undergoing liver cancer surgery. Two researchers independently selected studies based on inclusion and exclusion criteria, extracted data, and assessed the quality. Data analysis was performed using Stata 17.0 software. A total of 8 studies, encompassing 21 030 liver cancer surgery patients, were included. The analysis revealed that patients with a higher body mass index had a significantly higher incidence of wound infection (odds ratio [OR] = 2.36, 95% confidence interval [CI]: 1.21-4.60, p = 0.012) and complications (OR = 1.58, 95% CI: 1.11-2.24, p = 0.011) compared to the control group. Additionally, the hospital stay for higher body mass index patients was longer than that for the control group (standard mean difference [SMD] = -1.09, 95% CI: -4.71 to 2.53, p = 0.556), although this difference was not statistically significant. The study indicates that liver cancer surgery patients with higher body mass index were at an increased risk of postoperative wound infection and complications. This finding highlights the importance of considering body mass index as a factor in the management and care of patients undergoing liver cancer surgery.

Indexed as

body mass indexliver cancermeta‐analysiswound infection

Identifiers

PMID42052914
PMCPMC10827567

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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.