The Predictive Role of Subcutaneous Adipose Tissue in the Pathogenesis of Obstructive Sleep Apnoea
Introduction: Our aim was to investigate the applicability of artificial intelligence in predicting obstructive sleep apnoea (OSA) and upper airway obstruction using ultrasound (US) measurements of subcutaneous adipose tissues (SAT) in the regions of the neck, chest and abdomen. Methods: One hundred...
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MDPI AG
2022-09-01
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| author | Viktória Molnár Zoltán Lakner András Molnár Dávid László Tárnoki Ádám Domonkos Tárnoki László Kunos László Tamás |
| author_facet | Viktória Molnár Zoltán Lakner András Molnár Dávid László Tárnoki Ádám Domonkos Tárnoki László Kunos László Tamás |
| author_sort | Viktória Molnár |
| collection | DOAJ |
| description | Introduction: Our aim was to investigate the applicability of artificial intelligence in predicting obstructive sleep apnoea (OSA) and upper airway obstruction using ultrasound (US) measurements of subcutaneous adipose tissues (SAT) in the regions of the neck, chest and abdomen. Methods: One hundred patients were divided into mild (32), moderately severe-severe (32) OSA and non-OSA (36), according to the results of the polysomnography. These patients were examined using anthropometric measurements and US of SAT and drug-induced sleep endoscopy. Results: Using SAT US and anthropometric parameters, oropharyngeal obstruction could be predicted in 64% and tongue-based obstruction in 72%. In predicting oropharyngeal obstruction, BMI, abdominal and hip circumferences, submental SAT and SAT above the second intercostal space on the left were identified as essential parameters. Furthermore, tongue-based obstruction was predicted mainly by height, SAT measured 2 cm above the umbilicus and submental SAT. The OSA prediction was successful in 97% using the parameters mentioned above. Moreover, other parameters, such as US-based SAT, with SAT measured 2 cm above the umbilicus and both-sided SAT above the second intercostal spaces as the most important ones. Discussion: Based on our results, several categories of OSA can be predicted using artificial intelligence with high precision by using SAT and anthropometric parameters. |
| first_indexed | 2024-03-09T19:56:21Z |
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| institution | Directory Open Access Journal |
| issn | 2075-1729 |
| language | English |
| last_indexed | 2024-03-09T19:56:21Z |
| publishDate | 2022-09-01 |
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| record_format | Article |
| series | Life |
| spelling | doaj.art-0ae23ecc602245fca86f3e03c007aafb2023-11-24T00:55:56ZengMDPI AGLife2075-17292022-09-011210150410.3390/life12101504The Predictive Role of Subcutaneous Adipose Tissue in the Pathogenesis of Obstructive Sleep ApnoeaViktória Molnár0Zoltán Lakner1András Molnár2Dávid László Tárnoki3Ádám Domonkos Tárnoki4László Kunos5László Tamás6Department of Otolaryngology and Head and Neck Surgery, Semmelweis University, 1083 Budapest, HungarySzent István Campus, Hungarian University of Agriculture and Life Sciences, 2100 Gödöllő, HungaryDepartment of Otolaryngology and Head and Neck Surgery, Semmelweis University, 1083 Budapest, HungaryMedical Imaging Centre, Semmelweis University, 1083 Budapest, HungaryMedical Imaging Centre, Semmelweis University, 1083 Budapest, HungaryDepartment of Pulmonology, Pulmonology Hospital of Törökbálint, 2045 Törökbálint, HungaryDepartment of Otolaryngology and Head and Neck Surgery, Semmelweis University, 1083 Budapest, HungaryIntroduction: Our aim was to investigate the applicability of artificial intelligence in predicting obstructive sleep apnoea (OSA) and upper airway obstruction using ultrasound (US) measurements of subcutaneous adipose tissues (SAT) in the regions of the neck, chest and abdomen. Methods: One hundred patients were divided into mild (32), moderately severe-severe (32) OSA and non-OSA (36), according to the results of the polysomnography. These patients were examined using anthropometric measurements and US of SAT and drug-induced sleep endoscopy. Results: Using SAT US and anthropometric parameters, oropharyngeal obstruction could be predicted in 64% and tongue-based obstruction in 72%. In predicting oropharyngeal obstruction, BMI, abdominal and hip circumferences, submental SAT and SAT above the second intercostal space on the left were identified as essential parameters. Furthermore, tongue-based obstruction was predicted mainly by height, SAT measured 2 cm above the umbilicus and submental SAT. The OSA prediction was successful in 97% using the parameters mentioned above. Moreover, other parameters, such as US-based SAT, with SAT measured 2 cm above the umbilicus and both-sided SAT above the second intercostal spaces as the most important ones. Discussion: Based on our results, several categories of OSA can be predicted using artificial intelligence with high precision by using SAT and anthropometric parameters.https://www.mdpi.com/2075-1729/12/10/1504obstructive sleep apnoeaultrasoundobesitysubcutaneous adipose tissue thicknessartificial intelligencedrug-induced sleep endoscopy |
| spellingShingle | Viktória Molnár Zoltán Lakner András Molnár Dávid László Tárnoki Ádám Domonkos Tárnoki László Kunos László Tamás The Predictive Role of Subcutaneous Adipose Tissue in the Pathogenesis of Obstructive Sleep Apnoea Life obstructive sleep apnoea ultrasound obesity subcutaneous adipose tissue thickness artificial intelligence drug-induced sleep endoscopy |
| title | The Predictive Role of Subcutaneous Adipose Tissue in the Pathogenesis of Obstructive Sleep Apnoea |
| title_full | The Predictive Role of Subcutaneous Adipose Tissue in the Pathogenesis of Obstructive Sleep Apnoea |
| title_fullStr | The Predictive Role of Subcutaneous Adipose Tissue in the Pathogenesis of Obstructive Sleep Apnoea |
| title_full_unstemmed | The Predictive Role of Subcutaneous Adipose Tissue in the Pathogenesis of Obstructive Sleep Apnoea |
| title_short | The Predictive Role of Subcutaneous Adipose Tissue in the Pathogenesis of Obstructive Sleep Apnoea |
| title_sort | predictive role of subcutaneous adipose tissue in the pathogenesis of obstructive sleep apnoea |
| topic | obstructive sleep apnoea ultrasound obesity subcutaneous adipose tissue thickness artificial intelligence drug-induced sleep endoscopy |
| url | https://www.mdpi.com/2075-1729/12/10/1504 |
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