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<dc:title>Usefulness of Spectral Analysis of Respiratory Rate Variability to Help in Pediatric Sleep Apnea-Hypopnea Syndrome Diagnosis</dc:title>
<dc:creator>Barroso García, Verónica</dc:creator>
<dc:creator>Gutierrez Tobal, Gonzalo César</dc:creator>
<dc:creator>Kheirandish Gozal, Leila</dc:creator>
<dc:creator>Álvarez González, Daniel</dc:creator>
<dc:creator>Vaquerizo Villar, Fernando</dc:creator>
<dc:creator>Campo Matias, Félix del</dc:creator>
<dc:creator>Gozal, David</dc:creator>
<dc:creator>Hornero Sánchez, Roberto</dc:creator>
<dc:description>Producción Científica</dc:description>
<dc:description>The sleep apnea-hypopnea syndrome (SAHS) is a&#xd;
chronic respiratory disorder of high prevalence among children&#xd;
(up to 4%). Nocturnal polysomnography (PSG) is the gold&#xd;
standard method to diagnose SAHS, which is a complex,&#xd;
expensive, and time-consuming test. Consequently, alternative&#xd;
simplified methods are demanded. We propose the analysis of&#xd;
the respiratory rate variability (RRV) signal, directly obtained&#xd;
from the airflow (AF) signals. The aim of our study is to&#xd;
evaluate the usefulness of the spectral information obtained&#xd;
from RRV in the diagnosis of pediatric SAHS. A database&#xd;
composed of 946 AF and blood oxygen saturation (SpO2)&#xd;
recordings from children between 0 and 13 years old was used.&#xd;
Our database was divided into four severity groups according&#xd;
to the apnea-hipopnea index (AHI): no-SAHS (AHI &lt; 1&#xd;
events/h), mild (1 events/h ≤ AHI &lt; 5 events/h), moderate (5&#xd;
events/h ≤ AHI &lt; 10 events/h), and severe SAHS (AHI ≥ 10&#xd;
events/h). RRV and 3% oxygen desaturation index (ODI3) were&#xd;
obtained from AF and SpO2 recordings, respectively. A&#xd;
spectral band of interest was determined (0.09–0.20 Hz.) and a&#xd;
total of 12 spectral features were extracted. Nine of these&#xd;
features showed statistically significant differences (p-value &lt;&#xd;
0.05) among the four severity groups. The spectral features&#xd;
from RRV along with ODI3 were used as inputs to binary&#xd;
logistic regression (LR) classifiers. The diagnostic performance&#xd;
of LR models were evaluated for the AHI cut-off points of 1, 5,&#xd;
and 10 e/h, achieving 66.5%, 84.0%, and 88.5% accuracy,&#xd;
respectively. These results outperformed those obtained by&#xd;
single ODI3. The joint use of the spectral information from&#xd;
RRV and ODI3 achieved a high diagnostic capability in the&#xd;
most severely-affected children, thus showing their&#xd;
complementarity. These results suggest that the information&#xd;
contained in RRV spectrum together with ODI3 is useful to help&#xd;
identify moderate-to-severe SAHS.</dc:description>
<dc:date>2019-09-18T10:35:25Z</dc:date>
<dc:date>2019-09-18T10:35:25Z</dc:date>
<dc:date>2019</dc:date>
<dc:type>info:eu-repo/semantics/conferenceObject</dc:type>
<dc:identifier>978-1-5386-1311-5</dc:identifier>
<dc:identifier>http://uvadoc.uva.es/handle/10324/38000</dc:identifier>
<dc:language>eng</dc:language>
<dc:rights>info:eu-repo/semantics/restrictedAccess</dc:rights>
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