Sleep apnea diagnosis in children using software-generated apnea-hypopnea index (AHI) derived from data recorded with a single photoplethysmogram sensor (PPG)
ObjectiveSleep quality is vital for healthy development in children. Sleep disorders are prevalent and negatively affect sleep quality. Early identification and appropriate intervention can improve children’s health and quality of life. The current reference standard, polysomnography (PSG) has limit...
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| Veröffentlicht in: | Sleep & breathing 2020-12, Vol.24 (4), p.1739-1749 |
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| creator | Hugi, Hilmisson Berman, Stephen Magnusdottir Solveig |
| description | ObjectiveSleep quality is vital for healthy development in children. Sleep disorders are prevalent and negatively affect sleep quality. Early identification and appropriate intervention can improve children’s health and quality of life. The current reference standard, polysomnography (PSG) has limitations regarding availability, cost, and access and may not replicate normal sleep patterns in the home. Simple, accurate sleep tests, available for repeated testing should be beneficial in management of sleep disorders.MethodSecondary analysis of PSG data from the prospective multicenter Childhood Adenotonsillectomy Trial (CHAT) to evaluate FDA-cleared cloud-based software (Software-as-a-Medical-Device), which is based on analysis of photoplethysmogram data (PPG; plethysmogram-signal (PLETH) and oxygen saturation data (SpO2)), to automatically generate a novel apnea-hypopnea index (sAHI). sAHI is compared to manually scored AHI from PSG.ResultsSignificant correlation is observed comparing the software-generated sAHI and manually derived AHI from the in-laboratory PSG-studies (Pearson correlation = 0.954, p |
| doi_str_mv | 10.1007/s11325-020-02049-6 |
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Sleep disorders are prevalent and negatively affect sleep quality. Early identification and appropriate intervention can improve children’s health and quality of life. The current reference standard, polysomnography (PSG) has limitations regarding availability, cost, and access and may not replicate normal sleep patterns in the home. Simple, accurate sleep tests, available for repeated testing should be beneficial in management of sleep disorders.MethodSecondary analysis of PSG data from the prospective multicenter Childhood Adenotonsillectomy Trial (CHAT) to evaluate FDA-cleared cloud-based software (Software-as-a-Medical-Device), which is based on analysis of photoplethysmogram data (PPG; plethysmogram-signal (PLETH) and oxygen saturation data (SpO2)), to automatically generate a novel apnea-hypopnea index (sAHI). sAHI is compared to manually scored AHI from PSG.ResultsSignificant correlation is observed comparing the software-generated sAHI and manually derived AHI from the in-laboratory PSG-studies (Pearson correlation = 0.954, p < 0.0001) and receiver operating characteristics (ROC) demonstrate strong agreement in all OSA categories (mild, moderate, severe) 91.4%[CI95%89.5, 93.4]; 96.7%[CI95%95.4, 97.9]; 98.6%[CI95%97.8, 99.4], sensitivities 95.4%[CI95%93.2, 97.0]; 86.5%[CI95%80.3, 91.3]; 88.4%[CI95%78.4, 94.9] and specificities 84.4%[CI95%79.7, 88.4]; 99.2%[CI95%98.2, 99.7]; 99.6%[CI95%98.8, 99.9], respectively.ConclusionsAHI is comparable to manual scoring of AHI from in-laboratory PSG studies and effective to rule-in and rule-out obstructive sleep apnea (OSA) in all disease categories, providing safe and convenient approach for diagnosis and management of OSA in children. The data is recorded with a single-sensor, making the method suitable for multi-night testing in the child’s home at considerably lower cost. This technology provides a simple tool to adhere to guidelines for diagnosis and management of OSA in children.Clinical trial registration name and numberChildhood Adenotonsillectomy Study for Children with OSA (CHAT) https://clinicaltrials.gov/ct2/show/NCT00560859</description><identifier>ISSN: 1520-9512</identifier><identifier>EISSN: 1522-1709</identifier><identifier>DOI: 10.1007/s11325-020-02049-6</identifier><language>eng</language><publisher>Heidelberg: Springer Nature B.V</publisher><subject>Apnea ; Children ; Computer programs ; Diagnosis ; Laboratories ; Medical equipment ; Quality of life ; Sleep ; Sleep apnea ; Sleep disorders ; Software</subject><ispartof>Sleep & breathing, 2020-12, Vol.24 (4), p.1739-1749</ispartof><rights>Springer Nature Switzerland AG 2020.</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c775-733e487117cd2a574d880503bda2eb765ed909fb634f258d91208fcaaea240443</citedby></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><link.rule.ids>314,777,781,27905,27906</link.rule.ids></links><search><creatorcontrib>Hugi, Hilmisson</creatorcontrib><creatorcontrib>Berman, Stephen</creatorcontrib><creatorcontrib>Magnusdottir Solveig</creatorcontrib><title>Sleep apnea diagnosis in children using software-generated apnea-hypopnea index (AHI) derived from data recorded with a single photoplethysmogram sensor (PPG)</title><title>Sleep & breathing</title><description>ObjectiveSleep quality is vital for healthy development in children. Sleep disorders are prevalent and negatively affect sleep quality. Early identification and appropriate intervention can improve children’s health and quality of life. The current reference standard, polysomnography (PSG) has limitations regarding availability, cost, and access and may not replicate normal sleep patterns in the home. Simple, accurate sleep tests, available for repeated testing should be beneficial in management of sleep disorders.MethodSecondary analysis of PSG data from the prospective multicenter Childhood Adenotonsillectomy Trial (CHAT) to evaluate FDA-cleared cloud-based software (Software-as-a-Medical-Device), which is based on analysis of photoplethysmogram data (PPG; plethysmogram-signal (PLETH) and oxygen saturation data (SpO2)), to automatically generate a novel apnea-hypopnea index (sAHI). sAHI is compared to manually scored AHI from PSG.ResultsSignificant correlation is observed comparing the software-generated sAHI and manually derived AHI from the in-laboratory PSG-studies (Pearson correlation = 0.954, p < 0.0001) and receiver operating characteristics (ROC) demonstrate strong agreement in all OSA categories (mild, moderate, severe) 91.4%[CI95%89.5, 93.4]; 96.7%[CI95%95.4, 97.9]; 98.6%[CI95%97.8, 99.4], sensitivities 95.4%[CI95%93.2, 97.0]; 86.5%[CI95%80.3, 91.3]; 88.4%[CI95%78.4, 94.9] and specificities 84.4%[CI95%79.7, 88.4]; 99.2%[CI95%98.2, 99.7]; 99.6%[CI95%98.8, 99.9], respectively.ConclusionsAHI is comparable to manual scoring of AHI from in-laboratory PSG studies and effective to rule-in and rule-out obstructive sleep apnea (OSA) in all disease categories, providing safe and convenient approach for diagnosis and management of OSA in children. The data is recorded with a single-sensor, making the method suitable for multi-night testing in the child’s home at considerably lower cost. This technology provides a simple tool to adhere to guidelines for diagnosis and management of OSA in children.Clinical trial registration name and numberChildhood Adenotonsillectomy Study for Children with OSA (CHAT) https://clinicaltrials.gov/ct2/show/NCT00560859</description><subject>Apnea</subject><subject>Children</subject><subject>Computer programs</subject><subject>Diagnosis</subject><subject>Laboratories</subject><subject>Medical equipment</subject><subject>Quality of life</subject><subject>Sleep</subject><subject>Sleep apnea</subject><subject>Sleep disorders</subject><subject>Software</subject><issn>1520-9512</issn><issn>1522-1709</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2020</creationdate><recordtype>article</recordtype><sourceid>ABUWG</sourceid><sourceid>AFKRA</sourceid><sourceid>AZQEC</sourceid><sourceid>BENPR</sourceid><sourceid>CCPQU</sourceid><sourceid>DWQXO</sourceid><sourceid>GNUQQ</sourceid><recordid>eNotjc1OwkAURhujiYi-gKtJ3OBidH477ZIQBRISSWRPhs5tO6TM1Jki8jI-qwVc3NybL985N0keKXmhhKjXSClnEhNGTiNynF4lAyoZw1SR_Pp8E5xLym6Tuxi3hFCR5XSQ_H42AC3SrQONjNWV89FGZB0qatuYAA7to3UVir7sDjoArsBB0B2YC4TrY-vPtHUGftBoPJs_IwPBfveVMvgdMrrTKEDhg-mjg-1qpNFJ2gBqa9_5toGuPsadr4LeoQgu-oBGy-X0-T65KXUT4eF_D5PV-9tqMsOLj-l8Ml7gQimJFecgMkWpKgzTUgmTZUQSvjGawUalEkxO8nKTclEymZmcMpKVhdagmSBC8GHydNG2wX_tIXbrrd8H139cM9HbecqJ5H-Va20b</recordid><startdate>20201201</startdate><enddate>20201201</enddate><creator>Hugi, Hilmisson</creator><creator>Berman, Stephen</creator><creator>Magnusdottir Solveig</creator><general>Springer Nature B.V</general><scope>0-V</scope><scope>3V.</scope><scope>7T5</scope><scope>7TK</scope><scope>7X7</scope><scope>7XB</scope><scope>88E</scope><scope>88G</scope><scope>88J</scope><scope>8AO</scope><scope>8FI</scope><scope>8FJ</scope><scope>8FK</scope><scope>ABUWG</scope><scope>AFKRA</scope><scope>ALSLI</scope><scope>AZQEC</scope><scope>BENPR</scope><scope>CCPQU</scope><scope>DWQXO</scope><scope>FYUFA</scope><scope>GHDGH</scope><scope>GNUQQ</scope><scope>H94</scope><scope>K9.</scope><scope>M0S</scope><scope>M1P</scope><scope>M2M</scope><scope>M2R</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>PRINS</scope><scope>PSYQQ</scope><scope>Q9U</scope></search><sort><creationdate>20201201</creationdate><title>Sleep apnea diagnosis in children using software-generated apnea-hypopnea index (AHI) derived from data recorded with a single photoplethysmogram sensor (PPG)</title><author>Hugi, Hilmisson ; Berman, Stephen ; Magnusdottir Solveig</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c775-733e487117cd2a574d880503bda2eb765ed909fb634f258d91208fcaaea240443</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2020</creationdate><topic>Apnea</topic><topic>Children</topic><topic>Computer programs</topic><topic>Diagnosis</topic><topic>Laboratories</topic><topic>Medical equipment</topic><topic>Quality of life</topic><topic>Sleep</topic><topic>Sleep apnea</topic><topic>Sleep disorders</topic><topic>Software</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Hugi, Hilmisson</creatorcontrib><creatorcontrib>Berman, Stephen</creatorcontrib><creatorcontrib>Magnusdottir Solveig</creatorcontrib><collection>ProQuest Social Sciences Premium Collection</collection><collection>ProQuest Central (Corporate)</collection><collection>Immunology Abstracts</collection><collection>Neurosciences Abstracts</collection><collection>Health & Medical Collection</collection><collection>ProQuest Central (purchase pre-March 2016)</collection><collection>Medical Database (Alumni Edition)</collection><collection>Psychology Database (Alumni)</collection><collection>Social Science Database (Alumni Edition)</collection><collection>ProQuest Pharma Collection</collection><collection>Hospital Premium Collection</collection><collection>Hospital Premium Collection (Alumni Edition)</collection><collection>ProQuest Central (Alumni) (purchase pre-March 2016)</collection><collection>ProQuest Central (Alumni Edition)</collection><collection>ProQuest Central UK/Ireland</collection><collection>Social Science Premium Collection</collection><collection>ProQuest Central Essentials</collection><collection>ProQuest Central</collection><collection>ProQuest One Community College</collection><collection>ProQuest Central Korea</collection><collection>Health Research Premium Collection</collection><collection>Health Research Premium Collection (Alumni)</collection><collection>ProQuest Central Student</collection><collection>AIDS and Cancer Research Abstracts</collection><collection>ProQuest Health & Medical Complete (Alumni)</collection><collection>Health & Medical Collection (Alumni Edition)</collection><collection>Medical Database</collection><collection>ProQuest Psychology</collection><collection>Social Science Database</collection><collection>ProQuest One Academic Eastern Edition (DO NOT USE)</collection><collection>ProQuest One Academic</collection><collection>ProQuest One Academic UKI Edition</collection><collection>ProQuest Central China</collection><collection>ProQuest One Psychology</collection><collection>ProQuest Central Basic</collection><jtitle>Sleep & breathing</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Hugi, Hilmisson</au><au>Berman, Stephen</au><au>Magnusdottir Solveig</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Sleep apnea diagnosis in children using software-generated apnea-hypopnea index (AHI) derived from data recorded with a single photoplethysmogram sensor (PPG)</atitle><jtitle>Sleep & breathing</jtitle><date>2020-12-01</date><risdate>2020</risdate><volume>24</volume><issue>4</issue><spage>1739</spage><epage>1749</epage><pages>1739-1749</pages><issn>1520-9512</issn><eissn>1522-1709</eissn><abstract>ObjectiveSleep quality is vital for healthy development in children. Sleep disorders are prevalent and negatively affect sleep quality. Early identification and appropriate intervention can improve children’s health and quality of life. The current reference standard, polysomnography (PSG) has limitations regarding availability, cost, and access and may not replicate normal sleep patterns in the home. Simple, accurate sleep tests, available for repeated testing should be beneficial in management of sleep disorders.MethodSecondary analysis of PSG data from the prospective multicenter Childhood Adenotonsillectomy Trial (CHAT) to evaluate FDA-cleared cloud-based software (Software-as-a-Medical-Device), which is based on analysis of photoplethysmogram data (PPG; plethysmogram-signal (PLETH) and oxygen saturation data (SpO2)), to automatically generate a novel apnea-hypopnea index (sAHI). sAHI is compared to manually scored AHI from PSG.ResultsSignificant correlation is observed comparing the software-generated sAHI and manually derived AHI from the in-laboratory PSG-studies (Pearson correlation = 0.954, p < 0.0001) and receiver operating characteristics (ROC) demonstrate strong agreement in all OSA categories (mild, moderate, severe) 91.4%[CI95%89.5, 93.4]; 96.7%[CI95%95.4, 97.9]; 98.6%[CI95%97.8, 99.4], sensitivities 95.4%[CI95%93.2, 97.0]; 86.5%[CI95%80.3, 91.3]; 88.4%[CI95%78.4, 94.9] and specificities 84.4%[CI95%79.7, 88.4]; 99.2%[CI95%98.2, 99.7]; 99.6%[CI95%98.8, 99.9], respectively.ConclusionsAHI is comparable to manual scoring of AHI from in-laboratory PSG studies and effective to rule-in and rule-out obstructive sleep apnea (OSA) in all disease categories, providing safe and convenient approach for diagnosis and management of OSA in children. The data is recorded with a single-sensor, making the method suitable for multi-night testing in the child’s home at considerably lower cost. This technology provides a simple tool to adhere to guidelines for diagnosis and management of OSA in children.Clinical trial registration name and numberChildhood Adenotonsillectomy Study for Children with OSA (CHAT) https://clinicaltrials.gov/ct2/show/NCT00560859</abstract><cop>Heidelberg</cop><pub>Springer Nature B.V</pub><doi>10.1007/s11325-020-02049-6</doi><tpages>11</tpages></addata></record> |
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| subjects | Apnea Children Computer programs Diagnosis Laboratories Medical equipment Quality of life Sleep Sleep apnea Sleep disorders Software |
| title | Sleep apnea diagnosis in children using software-generated apnea-hypopnea index (AHI) derived from data recorded with a single photoplethysmogram sensor (PPG) |
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