The decreasing prevalence of the thyroid ima artery: A systematic review and machine learning assisted meta-analysis

Laphatrada Yurasakpong; Chanin Nantasenamat; Sirorat Janta; Pinthusorn Eiamratchanee; James Coey; Arada Chaiyamoon; Nutmethee Kruepunga; Thanyaporn Senarai; Martin Franz Langer; Krai Meemon; Athikhun Suwannakhan

doi:10.1016/j.aanat.2021.151803

The decreasing prevalence of the thyroid ima artery: A systematic review and machine learning assisted meta-analysis

Ann Anat. 2022 Jan:239:151803. doi: 10.1016/j.aanat.2021.151803. Epub 2021 Jul 12.

Affiliations

¹ Department of Anatomy, Faculty of Science, Mahidol University, Bangkok, Thailand.
² Center of Data Mining and Biomedical Informatics, Faculty of Medical Technology, Mahidol University, Bangkok, Thailand.
³ St. George's International School of Medicine Keith B. Taylor Global Scholars Program, Northumbria University, Newcastle-upon-Tyne, United Kingdom; Department of Anatomical Sciences, St. George's University, School of Medicine, Grenada, West Indies.
⁴ Department of Anatomy, Faculty of Medicine, Khon Kaen University, Khon Kaen, Thailand.
⁵ Department of Traumatology and Hand Surgery, University Hospital Münster, Albert-Schweitzer-Campus, Münster, Germany.
⁶ Department of Anatomy, Faculty of Science, Mahidol University, Bangkok, Thailand. Electronic address: athikhun.suw@mahidol.edu.

PMID: 34265384
DOI: 10.1016/j.aanat.2021.151803

Abstract

Introduction: Thyroid ima artery is a variant artery found on the anterior surface of the trachea. The aim of this meta-analysis was to obtain pooled prevalence data of the thyroid ima artery and discuss its clinical importance especially for tracheostomy.

Methods: A systematic literature search was performed through five electronic databases until May 2021. A set of inclusion and exclusion criteria based on AQUA guidelines were used to select relevant studies. Meta-analysis, subgroup analyses, meta-regression, and tests for publication bias were performed. Factors that influence the prevalence of the thyroid ima artery were detected using simple and interpretable machine learning (linear regression and K means).

Results: Thirty-six studies with a total of 4335 subjects met the inclusion criteria. The prevalence of the thyroid ima artery was 3.8% (95% CI: 0.027-0.049, I²=56.2%). Machine learning identified age, region and year of publication as potential covariates. Subgroup analysis showed that the prevalence of the thyroid ima artery was 4.5 times higher in fetuses (14.8%) than adults (3.3%) (z=-6.76, p<0.01). There was a significant negative correlation between the adult prevalence of the thyroid ima artery and the year of publication (Pearson's r=-0.354, p=0.040) thereby suggesting a decline in thyroid ima artery prevalence over time. This artery, if present, may originate from the brachiocephalic trunk (74%), right common carotid artery (9.6%), arch of aorta (7.7%), right internal thoracic artery (4.8%), left common carotid artery (1.9%) and left internal thoracic artery (1.9%).

Conclusion: In addition to evidence-based synthesis of the thyroid ima artery, this study is the first ever study to report the decreasing prevalence over time of a human body structure in the postnatal life. Knowledge of the thyroid ima artery is of vital importance for surgeons to avoid accidental hemorrhage during tracheostomy.

Keywords: Machine learning; Meta-analysis; Systematic review; Thyroid ima artery; Tracheostomy.

Publication types

Meta-Analysis
Systematic Review

MeSH terms

Adult
Brachiocephalic Trunk*
Carotid Artery, Common
Humans
Machine Learning
Prevalence
Thyroid Gland*