Evidence map›Paper›PMID 37087723›Full record

ArticleSurgical and radiologic anatomy : SRA2023

Structural equation modelling to estimate facial soft tissue thickness parameters based on ethnicity, gender and body mass index: a secondary study on an Iranian dataset.

Mohammad Javad Nourmohammadi, Seyyed Amir Yasin Ahmadi, Jafar Rezaian

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Article in Surgical and radiologic anatomy : SRA, 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
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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.

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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

1 citing paper in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

3 authors.

Mohammad Javad NourmohammadiStudent Research Committee, Lorestan University of Medical Sciences, Khorramabad, Iran.
Seyyed Amir Yasin AhmadiPreventive Medicine and Public Health Research Center, Psychosocial Health Research Institute, Iran University of Medical Sciences, Tehran, Iran.
Jafar RezaianResearch Office for the History of Persian Medicine, Department of Anatomical Sciences, School of Medicine, Lorestan University of Medical Sciences, Khorramabad, Iran. jafarrezaian@gmail.com.

Funding

Lorestan University of Medical Sciences 2124
6 · The paper itself

Abstract

purposeAccording to the anthropological importance of soft facial tissue thickness parameters, we aimed to find the association of these parameters with Lur and Arab ethnicities, gender and body mass index (BMI). Structural equation modeling (SEM) was used.

methodsAs a secondary analysis, SEM was performed on a dataset of 100 participants. The participants were from Lur and Arab populations of Ahvaz province, Iran, from those who referred for magnetic resonance imaging (MRI) due to headache.

resultsMultivariate regression illustrated that mental eminence (ME), chain-lip fold (CLF) and end of nasals (END) could not be predicted by the independent variables (p > 0.05). Right masseteric region (RMST) had the maximum predictability with R

conclusionMID parameter can be predicted by gender, BMI and Arab ethnicity. By carrying out such studies and creating database, such information can be used in plastic surgery, corpse identification, and facial reconstruction software in archeology.

Indexed as

EthnicitySex CharacteristicsBody Mass IndexForensic AnthropologyHumansIranLatent Class AnalysisEthnicityMedical anthropologyStatistical modelingStructural equation modelling

Identifiers

PMID37087723

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