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      Correlation between cone-beam computed tomographic findings and the apnea-hypopnea index in obstructive sleep apnea patients: A cross-sectional study

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      https://www.riss.kr/link?id=A109867386

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      다국어 초록 (Multilingual Abstract) kakao i 다국어 번역

      Purpose: The aim of this study was to explore the correlations of cone-beam computed tomographic findings with the apnea-hypopnea index in patients with obstructive sleep apnea.
      Materials and Methods: Forty patients with obstructive sleep apnea were selected from the ear-nose-throat (ENT) outpatient clinic, Faculty of Medicine, Mansoura University. Cone-beam computed tomography was performed for each patient at the end of both inspiration and expiration. Polysomnography was carried out, and the apnea- hypopnea index was obtained. Linear measurements, including cross-sectional area and the SNA and SNB angles, were obtained. Four oral and maxillofacial radiologists categorized pharyngeal and retropalatal airway morphology and calculated the airway length and volume. Continuous data were tested for normality using the Kolmogorov- Smirnov test and reported as the mean and standard deviation or as the median and range. Categorical data were presented as numbers and percentages, and the significance level was set at P<0.05.
      Results: The minimal value of the cross-sectional area, SNB angle, and airway morphology at the end of inspiration demonstrated a statistically significant association (P<0.05) with the apnea-hypopnea index, with excellent agreement. No statistically significant difference was found in the airway volume, other linear measurements, or retropalatal airway morphology.
      Conclusion: Cone-beam computed tomographic measurements in obstructive sleep apnea patients may be used as a supplement to a novel radiographic classification corresponding to the established clinical apnea-hypopnea index classification.
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      Purpose: The aim of this study was to explore the correlations of cone-beam computed tomographic findings with the apnea-hypopnea index in patients with obstructive sleep apnea. Materials and Methods: Forty patients with obstructive sleep apnea were s...

      Purpose: The aim of this study was to explore the correlations of cone-beam computed tomographic findings with the apnea-hypopnea index in patients with obstructive sleep apnea.
      Materials and Methods: Forty patients with obstructive sleep apnea were selected from the ear-nose-throat (ENT) outpatient clinic, Faculty of Medicine, Mansoura University. Cone-beam computed tomography was performed for each patient at the end of both inspiration and expiration. Polysomnography was carried out, and the apnea- hypopnea index was obtained. Linear measurements, including cross-sectional area and the SNA and SNB angles, were obtained. Four oral and maxillofacial radiologists categorized pharyngeal and retropalatal airway morphology and calculated the airway length and volume. Continuous data were tested for normality using the Kolmogorov- Smirnov test and reported as the mean and standard deviation or as the median and range. Categorical data were presented as numbers and percentages, and the significance level was set at P<0.05.
      Results: The minimal value of the cross-sectional area, SNB angle, and airway morphology at the end of inspiration demonstrated a statistically significant association (P<0.05) with the apnea-hypopnea index, with excellent agreement. No statistically significant difference was found in the airway volume, other linear measurements, or retropalatal airway morphology.
      Conclusion: Cone-beam computed tomographic measurements in obstructive sleep apnea patients may be used as a supplement to a novel radiographic classification corresponding to the established clinical apnea-hypopnea index classification.

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      참고문헌 (Reference)

      1 Rodrigues MM, "Volumetric evaluation of pharyngeal segments in obstructive sleep apnea patients" 84 : 89-94, 2018

      2 Nagappa M, "Validation of the STOP-Bang questionnaire as a screening tool for obstructive sleep apnea among different populations : a systematic review and meta-analysis" 10 : e0143697-, 2015

      3 Massillamani F, "Upper aerodigestive space analysis in obstructive sleep apnea : an overview" 7 : 1-7, 2018

      4 Eastwood PR, "Treating obstructive sleep apnea with hypoglossal nerve stimulation" 34 : 1479-1486, 2011

      5 Eckert DJ, "Trazodone increases the respiratory arousal threshold in patients with obstructive sleep apnea and a low arousal threshold" 37 : 811-819, 2014

      6 Baz H, "The role of video-fluoroscopy in the assessment of obstructive sleep apnea patients : comparative study" 39 : 89-, 2023

      7 Sharkey KM, "Subjective sleepiness and daytime functioning in bariatric patients with obstructive sleep apnea" 17 : 267-274, 2013

      8 Miller JN, "Screening and assessment for obstructive sleep apnea in primary care" 29 : 41-51, 2016

      9 Damstra J, "Reliability and the smallest detectable differences of lateral cephalometric measurements" 138 : 546-, 2010

      10 Johns MW, "Reliability and factor analysis of the Epworth Sleepiness Scale" 15 : 376-381, 1992

      1 Rodrigues MM, "Volumetric evaluation of pharyngeal segments in obstructive sleep apnea patients" 84 : 89-94, 2018

      2 Nagappa M, "Validation of the STOP-Bang questionnaire as a screening tool for obstructive sleep apnea among different populations : a systematic review and meta-analysis" 10 : e0143697-, 2015

      3 Massillamani F, "Upper aerodigestive space analysis in obstructive sleep apnea : an overview" 7 : 1-7, 2018

      4 Eastwood PR, "Treating obstructive sleep apnea with hypoglossal nerve stimulation" 34 : 1479-1486, 2011

      5 Eckert DJ, "Trazodone increases the respiratory arousal threshold in patients with obstructive sleep apnea and a low arousal threshold" 37 : 811-819, 2014

      6 Baz H, "The role of video-fluoroscopy in the assessment of obstructive sleep apnea patients : comparative study" 39 : 89-, 2023

      7 Sharkey KM, "Subjective sleepiness and daytime functioning in bariatric patients with obstructive sleep apnea" 17 : 267-274, 2013

      8 Miller JN, "Screening and assessment for obstructive sleep apnea in primary care" 29 : 41-51, 2016

      9 Damstra J, "Reliability and the smallest detectable differences of lateral cephalometric measurements" 138 : 546-, 2010

      10 Johns MW, "Reliability and factor analysis of the Epworth Sleepiness Scale" 15 : 376-381, 1992

      11 Hirshkowitz M, "Polysomnography challenges" 11 : 403-411, 2016

      12 Eckert DJ, "Phenotypic approaches to obstructive sleep apnoea-new pathways for targeted therapy" 37 : 45-59, 2018

      13 Iwasaki T, "Oropharyngeal airway in children with Class III malocclusion evaluated by cone-beam computed tomography" 136 : 318-, 2009

      14 Maspero C, "Obstructive sleep apnea syndrome : a literature review" 64 : 97-109, 2015

      15 Gurgel ML, "Methodological parameters for upper airway assessment by cone-beam computed tomography in adults with obstructive sleep apnea : a systematic review of the literature and meta-analysis" 0 : 1-30, 2022

      16 Brown AA, "Linear accuracy of cone beam CT derived 3D images" 79 : 150-157, 2009

      17 Peppard PE, "Increased prevalence of sleep-disordered breathing in adults" 177 : 1006-1014, 2013

      18 Stewart SA, "Improvement in obstructive sleep apnea diagnosis and management wait times : A retrospective analysis of a home management pathway for obstructive sleep apnea" 22 : 167-170, 2015

      19 Younes M, "Genioglossus activity available via non-arousal mechanisms vs. that required for opening the airway in obstructive apnea patients" 112 : 249-258, 2011

      20 Woodson BT, "Expiratory pharyngeal airway obstruction during sleep : a multiple element model" 113 : 1450-1459, 2003

      21 Ogawa T, "Evaluation of cross-section airway configuration of obstructive sleep apnea" 103 : 102-108, 2007

      22 Ogawa T, "Evaluation of 3D airway imaging of obstructive sleep apnea with conebeam computed tomography" 111 : 365-368, 2005

      23 Benjafield AV, "Estimation of the global prevalence and burden of obstructive sleep apnoea : a literature-based analysis" 7 : 687-698, 2019

      24 Semelka M, "Diagnosis and treatment of obstructive sleep apnea in adults" 94 : 355-360, 2016

      25 Lavigne G, "Critical issues in dental and medical management of obstructive sleep apnea" 99 : 26-35, 2020

      26 Jaffray D, "Cone-beam computed tomography with a flat-panel imager : initial performance characterization" 27 : 1311-1323, 2000

      27 Enciso R, "Comparison of cone-beam CT parameters and sleep questionnaires in sleep apnea patients and control subjects" 109 : 285-293, 2010

      28 Markun LC, "Clinician-focused overview and developments in polysomnography" 6 : 309-321, 2020

      29 Kapur VK, "Clinical practice guideline for diagnostic testing for adult obstructive sleep apnea : an American Academy of Sleep Medicine clinical practice guideline" 13 : 479-504, 2017

      30 Epstein LJ, "Clinical guideline for the evaluation, management and long-term care of obstructive sleep apnea in adults" 5 : 263-276, 2009

      31 Susarla SM, "Cephalometric measurement of upper airway length correlates with the presence and severity of obstructive sleep apnea" 68 : 2846-2855, 2010

      32 De Cort S, "Cardiac output, oxygen consumption and arteriovenous oxygen difference following a sudden rise in exercise level in humans" 441 : 501-512, 1991

      33 Brennan HL, "Barriers of artificial intelligence implementation in the diagnosis of obstructive sleep apnea" 51 : 16-, 2022

      34 Berry RB, "Auto-adjusting positive airway pressure treatment for sleep apnea diagnosed by home sleep testing" 12 : 1269-1275, 2014

      35 Jordan AS, "Airway dilator muscle activity and lung volume during stable breathing in obstructive sleep apnea" 32 : 361-368, 2009

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