Evidence map›Paper›PMID 37701173›Full record

ArticlePolish journal of radiology2023

Computed tomographic abdominal fat volume estimation - a handy tool to predict the risk of metabolic syndrome.

G C Navaneeth, Rudresh Hiremath, Shweta Raviraj Poojary, Divya Vishwanatha Kini, Kavitha B Chittaragi

Abstract read
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Article in Polish journal of radiology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
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1 · What the graph read from it

What it found

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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

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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. Review
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4 · The record

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5 · Who and what money

Authors and funding

5 authors.

G C NavaneethJSS Medical College, Mysuru, Karnataka, India.
Rudresh HiremathJSS Medical College, Mysuru, Karnataka, India.
Shweta Raviraj PoojaryJSS Medical College, Mysuru, Karnataka, India.
Divya Vishwanatha KiniJSS Medical College, Mysuru, Karnataka, India.
Kavitha B ChittaragiJSS Medical College, Mysuru, Karnataka, India.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Purpose: Abdominal obesity plays a significant role in the development of metabolic syndrome, with individual metabolic risk profiles for visceral and subcutaneous adipose tissues. This study aimed to calculate and correlate the subcutaneous, visceral, and total fat compartment volume in metabolic and non-metabolic syndrome patients. Material and methods: This was a cross-sectional study conducted on 112 patients categorized into Group A (with metabolic syndrome) and Group B (without metabolic syndrome). They were subjected to computed tomography (CT) study of the abdomen using a 128-slice MDCT scanner. Body mass index (BMI), visceral fat volume (VFV), subcutaneous fat volume (SFV), and total fat volume (TFV) were calculated and correlated with biochemical evidence of metabolic syndrome. Results: The mean age of patients in Group A was 60.91 ± 12.23 years as compared to Group B, which was 50.12 ± 16.30 years. Overall, a male predominance was observed, i.e. 69 cases (61.6%). BMI was proven to be an inaccurate risk predictor. However, mean VFV, SFV, and TFV was statistically higher in patients with metabolic syndrome ( Conclusions: Abdominal CT is a commonly performed yet unexplored tool for the risk assessment of metabolic syndrome. Through the results obtained in this study, we have proven the need for calculating SFV, VFV, and TFV as predictors of metabolic syndrome in comparison to the conventional practice of BMI assessment. The radiologist can thus work with the clinician to effectively detect and treat this health condition.

Indexed as

abdominal subcutaneous fatabdominal visceral fatbody mass indexcomputed tomographymetabolic syndrome

Identifiers

PMID37701173
PMCPMC10493863

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