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A Clinical Prediction Formula for Apnea-Hypopnea Index
Objectives. There are many studies regarding unnecessary polysomnography (PSG) when obstructive sleep apnea syndrome (OSAS) is suspected. In order to reduce unnecessary PSG, this study aims to predict the apnea-hypopnea index (AHI) via simple clinical data for patients who complain of OSAS symptoms....
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Hindawi Publishing Corporation
2014
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4199210/ https://www.ncbi.nlm.nih.gov/pubmed/25349613 http://dx.doi.org/10.1155/2014/438376 |
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author | Sahin, Mustafa Bilgen, Cem Tasbakan, M. Sezai Midilli, Rasit Basoglu, Ozen K. |
author_facet | Sahin, Mustafa Bilgen, Cem Tasbakan, M. Sezai Midilli, Rasit Basoglu, Ozen K. |
author_sort | Sahin, Mustafa |
collection | PubMed |
description | Objectives. There are many studies regarding unnecessary polysomnography (PSG) when obstructive sleep apnea syndrome (OSAS) is suspected. In order to reduce unnecessary PSG, this study aims to predict the apnea-hypopnea index (AHI) via simple clinical data for patients who complain of OSAS symptoms. Method. Demographic, anthropometric, physical examination and laboratory data of a total of 390 patients (290 men, average age 50 ± 11) who were subject to diagnostic PSG were obtained and evaluated retrospectively. The relationship between these data and the PSG results was analyzed. A multivariate linear regression analysis was performed step by step to identify independent AHI predictors. Results. Useful parameters were found in this analysis in terms of body mass index (BMI), waist circumference (WC), neck circumference (NC), oxygen saturation measured by pulse oximetry (SpO(2)), and tonsil size (TS) to predict the AHI. The formula derived from these parameters was the predicted AHI = (0.797 × BMI) + (2.286 × NC) − (1.272 × SpO(2)) + (5.114 × TS) + (0.314 × WC). Conclusion. This study showed a strong correlation between AHI score and indicators of obesity. This formula, in terms of predicting the AHI for patients who complain about snoring, witnessed apneas, and excessive daytime sleepiness, may be used to predict OSAS prior to PSG and prevent unnecessary PSG. |
format | Online Article Text |
id | pubmed-4199210 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2014 |
publisher | Hindawi Publishing Corporation |
record_format | MEDLINE/PubMed |
spelling | pubmed-41992102014-10-27 A Clinical Prediction Formula for Apnea-Hypopnea Index Sahin, Mustafa Bilgen, Cem Tasbakan, M. Sezai Midilli, Rasit Basoglu, Ozen K. Int J Otolaryngol Research Article Objectives. There are many studies regarding unnecessary polysomnography (PSG) when obstructive sleep apnea syndrome (OSAS) is suspected. In order to reduce unnecessary PSG, this study aims to predict the apnea-hypopnea index (AHI) via simple clinical data for patients who complain of OSAS symptoms. Method. Demographic, anthropometric, physical examination and laboratory data of a total of 390 patients (290 men, average age 50 ± 11) who were subject to diagnostic PSG were obtained and evaluated retrospectively. The relationship between these data and the PSG results was analyzed. A multivariate linear regression analysis was performed step by step to identify independent AHI predictors. Results. Useful parameters were found in this analysis in terms of body mass index (BMI), waist circumference (WC), neck circumference (NC), oxygen saturation measured by pulse oximetry (SpO(2)), and tonsil size (TS) to predict the AHI. The formula derived from these parameters was the predicted AHI = (0.797 × BMI) + (2.286 × NC) − (1.272 × SpO(2)) + (5.114 × TS) + (0.314 × WC). Conclusion. This study showed a strong correlation between AHI score and indicators of obesity. This formula, in terms of predicting the AHI for patients who complain about snoring, witnessed apneas, and excessive daytime sleepiness, may be used to predict OSAS prior to PSG and prevent unnecessary PSG. Hindawi Publishing Corporation 2014 2014-10-01 /pmc/articles/PMC4199210/ /pubmed/25349613 http://dx.doi.org/10.1155/2014/438376 Text en Copyright © 2014 Mustafa Sahin et al. https://creativecommons.org/licenses/by/3.0/ This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Research Article Sahin, Mustafa Bilgen, Cem Tasbakan, M. Sezai Midilli, Rasit Basoglu, Ozen K. A Clinical Prediction Formula for Apnea-Hypopnea Index |
title | A Clinical Prediction Formula for Apnea-Hypopnea Index |
title_full | A Clinical Prediction Formula for Apnea-Hypopnea Index |
title_fullStr | A Clinical Prediction Formula for Apnea-Hypopnea Index |
title_full_unstemmed | A Clinical Prediction Formula for Apnea-Hypopnea Index |
title_short | A Clinical Prediction Formula for Apnea-Hypopnea Index |
title_sort | clinical prediction formula for apnea-hypopnea index |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4199210/ https://www.ncbi.nlm.nih.gov/pubmed/25349613 http://dx.doi.org/10.1155/2014/438376 |
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