Evidence mapPaperPMID 40734925Full record

ArticleFrontiers in surgery2025

Visceral fat: the hidden culprit behind thoracolumbar surgery infections.

Dan Su, Ruiling Wang, Jucai Li, Xiaohui An, Lingling Sun, Yi Cui, Di Zhang

Abstract read
In one paragraph

Article in Frontiers in surgery, 2025. 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
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.

  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

7 authors.

Dan SuDepartment of Spinal Surgery, Third Hospital of Hebei Medical University, Shijiazhuang, China.
Ruiling WangDepartment of Spinal Surgery, Third Hospital of Hebei Medical University, Shijiazhuang, China.
Jucai LiDepartment of Spinal Surgery, Third Hospital of Hebei Medical University, Shijiazhuang, China.
Xiaohui AnDepartment of Spinal Surgery, Third Hospital of Hebei Medical University, Shijiazhuang, China.
Lingling SunDepartment of Spinal Surgery, Third Hospital of Hebei Medical University, Shijiazhuang, China.
Yi CuiDepartment of Spinal Surgery, Third Hospital of Hebei Medical University, Shijiazhuang, China.
Di ZhangDepartment of Spinal Surgery, Third Hospital of Hebei Medical University, Shijiazhuang, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Objective: This study aimed to explore the relationship between visceral fat area (VFA) and the risk of surgical site infection (SSI) after thoracolumbar posterior surgery. Methods: A retrospective analysis was conducted on 1,491 patients who had undergone posterior thoracolumbar surgery from January 1, 2022, through May 30, 2023. Inclusion criteria were age ≥18 years, undergoing thoracolumbar posterior surgery, and having complete clinical data with a follow-up duration exceeding 1 year. Exclusion criteria included minimally invasive surgery, preoperative infections, traumatic skin injuries, combined tumors, and patients with long-term steroid use or immune system diseases. VFA was measured using CT scans, and patients were categorized based on VFA ≥100 cm Results: The incidence of SSI was 2.4% (36 out of 1,491 patients). Multivariate logistic regression analysis showed that VFA was the most significant predictor of SSI [ Conclusion: VFA is a significant risk factor for SSI following thoracolumbar posterior surgery. Preoperative assessment of VFA can help identify high-risk patients and guide preventive measures to reduce SSI incidence and improve surgical outcomes.

Indexed as

infection risk factorsobesitysurgical site infection (SSI)thoracolumbar surgeryvsceral fat area (VFA)

Identifiers

PMID40734925
PMCPMC12303955

What Socratic 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 Socratic graph.