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Clinical Predictors of Pediatric Obstructive Sleep Apnea Syndrome.

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Title: Clinical Predictors of Pediatric Obstructive Sleep Apnea Syndrome.
Authors: Lai, Chi-Chih, Lin, Pei-Wen, Lin, Hsin-Ching, Friedman, Michael, Chang, Hsueh-Wen, Salapatas, Anna M., Lin, Meng-Chih, Wang, Pa-Chun
Source: Annals of Otology, Rhinology & Laryngology. Sep2018, Vol. 127 Issue 9, p608-613. 6p.
Subjects: Statistical correlation, Regression analysis, Research funding, Sleep apnea syndromes, Video recording, Polysomnography, Visual analog scale, Data analysis software, Descriptive statistics, Friedman test (Statistics), Symptoms, Children
Abstract: Objective: To develop an adequate model using reliable clinical and physical factors to predict pediatric obstructive sleep apnea/hypopnea syndrome (OSAS). Methods: Complete anthropometric measurements including BMI z score, tonsil size grading, and updated Friedman tongue position (uFTP) were evaluated. Subjective assessments of clinical symptoms/signs, including snoring visual analog scale (VAS), nasal obstruction, and mouth breathing, were recorded. Results: Eighty-eight children (57 boys and 31 girls, mean age = 9.0 years) were confirmed to have OSAS by comprehensive polysomnography (PSG). When the aforementioned variables were analyzed individually, the results indicated that snoring VAS, nasal obstruction, mouth breathing, and BMI z score were reliable predictors of apnea/hypopnea index (AHI/h) values (correlation coefficient r = 0.386, P < .001; r = 0.416, P < .001; r = 0.255, P = .02; and r = 0.243, P = .02, respectively). When all significant factors were included in the stepwise multiple linear regression analysis, the final predictive model is: Pediatric AHI = 0.108 + 0.103 snoring VAS + 0.894 nasal obstruction + 0.207 BMI z score (F = 4.06, P = .01). Conclusion: The proposed noninvasive, simple, inexpensive, and easy to perform screening tool could be used to predict pediatric OSAS. An abnormal calculated AHI may prompt clinical physicians to conduct further PSG diagnostics and treatment. [ABSTRACT FROM AUTHOR]
Copyright of Annals of Otology, Rhinology & Laryngology is the property of Sage Publications Inc. and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
Database: Psychology and Behavioral Sciences Collection
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  Data: Clinical Predictors of Pediatric Obstructive Sleep Apnea Syndrome.
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  Data: Objective: To develop an adequate model using reliable clinical and physical factors to predict pediatric obstructive sleep apnea/hypopnea syndrome (OSAS). Methods: Complete anthropometric measurements including BMI z score, tonsil size grading, and updated Friedman tongue position (uFTP) were evaluated. Subjective assessments of clinical symptoms/signs, including snoring visual analog scale (VAS), nasal obstruction, and mouth breathing, were recorded. Results: Eighty-eight children (57 boys and 31 girls, mean age = 9.0 years) were confirmed to have OSAS by comprehensive polysomnography (PSG). When the aforementioned variables were analyzed individually, the results indicated that snoring VAS, nasal obstruction, mouth breathing, and BMI z score were reliable predictors of apnea/hypopnea index (AHI/h) values (correlation coefficient r = 0.386, P &lt; .001; r = 0.416, P &lt; .001; r = 0.255, P = .02; and r = 0.243, P = .02, respectively). When all significant factors were included in the stepwise multiple linear regression analysis, the final predictive model is: Pediatric AHI = 0.108 + 0.103 snoring VAS + 0.894 nasal obstruction + 0.207 BMI z score (F = 4.06, P = .01). Conclusion: The proposed noninvasive, simple, inexpensive, and easy to perform screening tool could be used to predict pediatric OSAS. An abnormal calculated AHI may prompt clinical physicians to conduct further PSG diagnostics and treatment. [ABSTRACT FROM AUTHOR]
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  Data: &lt;i&gt;Copyright of Annals of Otology, Rhinology &amp; Laryngology is the property of Sage Publications Inc. and its content may not be copied or emailed to multiple sites without the copyright holder&#39;s express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.&lt;/i&gt; (Copyright applies to all Abstracts.)
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        Value: 10.1177/0003489418781961
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      – Code: eng
        Text: English
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        StartPage: 608
    Subjects:
      – SubjectFull: Statistical correlation
        Type: general
      – SubjectFull: Regression analysis
        Type: general
      – SubjectFull: Research funding
        Type: general
      – SubjectFull: Sleep apnea syndromes
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      – SubjectFull: Video recording
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      – SubjectFull: Polysomnography
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      – SubjectFull: Visual analog scale
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      – SubjectFull: Data analysis software
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      – SubjectFull: Descriptive statistics
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      – SubjectFull: Friedman test (Statistics)
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      – SubjectFull: Symptoms
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      – SubjectFull: Children
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    Titles:
      – TitleFull: Clinical Predictors of Pediatric Obstructive Sleep Apnea Syndrome.
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            NameFull: Lai, Chi-Chih
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              M: 09
              Text: Sep2018
              Type: published
              Y: 2018
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