Pub Date : 2023-10-01DOI: 10.1093/sleepadvances/zpad035.177
C Hartnett, A Kevat, G Williams
Abstract Introduction Asset management of laboratory equipment is essential to patient safety. Traceability enables any patient affected by equipment that has been recalled, or subsequently been found faulty, to be retested. Sleep equipment in home, ward or laboratory needs to be clearly documented but this paperwork is tedious and manual. Methods A portable barcode scanner with software was added to the laboratory asset management and the time efficiencies were evaluated. Results The time reduction of using a barcode scanner to manual data entry was found to decrease time approximately fourfold, from 8 mins (std 1.5mins) to 2.2 mins (std 0.5mins). This is for each sleep laboratory testing bed and can equate to 35 minutes in a six-bed sleep laboratory. Accuracy of data is assured with a barcode scanner, compared to manual input. Discussion Using automation to replace manual tasks in a sleep laboratory saves time and ensures data accuracy. Further advances in automation for tagging medical devices would improve this in areas with high use of home or ward devices.
{"title":"P092 Automation in Equipment Asset Management for Laboratory Efficiencies","authors":"C Hartnett, A Kevat, G Williams","doi":"10.1093/sleepadvances/zpad035.177","DOIUrl":"https://doi.org/10.1093/sleepadvances/zpad035.177","url":null,"abstract":"Abstract Introduction Asset management of laboratory equipment is essential to patient safety. Traceability enables any patient affected by equipment that has been recalled, or subsequently been found faulty, to be retested. Sleep equipment in home, ward or laboratory needs to be clearly documented but this paperwork is tedious and manual. Methods A portable barcode scanner with software was added to the laboratory asset management and the time efficiencies were evaluated. Results The time reduction of using a barcode scanner to manual data entry was found to decrease time approximately fourfold, from 8 mins (std 1.5mins) to 2.2 mins (std 0.5mins). This is for each sleep laboratory testing bed and can equate to 35 minutes in a six-bed sleep laboratory. Accuracy of data is assured with a barcode scanner, compared to manual input. Discussion Using automation to replace manual tasks in a sleep laboratory saves time and ensures data accuracy. Further advances in automation for tagging medical devices would improve this in areas with high use of home or ward devices.","PeriodicalId":21861,"journal":{"name":"SLEEP Advances","volume":"27 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"136054066","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-10-01DOI: 10.1093/sleepadvances/zpad035.155
S Sharma, H Reiter, A Conflitti
Abstract Introduction The study assessed the efficacy of oral appliance device O2Vent Optima and ExVent, an oral Expiratory Positive Airway Pressure (EPAP) accessory in the treatment of OSA. Methods A prospective, open-label study conducted at 3 sites in mild to moderate OSA (AHI ≥ 5 and ≤ 30). Screening Phase A diagnostic in-lab PSG study confirmed a diagnosis of mild to moderate OSA. Treatment I Subjects used O2Vent Optima for 6 weeks and underwent a PSG sleep night while using the O2Vent Optima. Treatment II Subjects used O2Vent Optima + ExVent for 6 weeks and underwent a PSG sleep night while using the O2Vent Optima + ExVent Primary Effectiveness Measure: Change in AHI between baseline vs. O2Vent Optima MAD vs. O2Vent Optima + ExVent Results Treatment with Optima, Optima + ExVent reduced AHI from 22.5±6.4/hr to 12.6±4.5/hr to 5.9±2.7 (p< 0.005 baseline vs. Optima and Optima + ExVent; p<0.05 Optima MAD vs. Optima + ExVent). Average reduction in AHI with Optima was 43% and with Optima + ExVent was 72%. The lowest oxygen during sleep increased from 84.6±2.7% to 88.6±2.9% to 91.6±3.2% (p< 0.005 baseline vs. Optima and Optima + ExVent; p<0.05 Optima vs. Optima + ExVent). During the trial patients on treatment with Optima and Optima + ExVent demonstrated no excessive adverse events or device malfunction. Conclusion Treatment with O2Vent Optima and O2Vent Optima + ExVent significantly improved OSA compared to the baseline. Even greater benefit was observed with addition of ExVent to the Optima in mild to moderate OSA.
{"title":"P070 Efficacy of the ExVent Accessory with the O2Vent Optima Oral Appliance in the Treatment of Obstructive Sleep Apnea – A Clinical Trial","authors":"S Sharma, H Reiter, A Conflitti","doi":"10.1093/sleepadvances/zpad035.155","DOIUrl":"https://doi.org/10.1093/sleepadvances/zpad035.155","url":null,"abstract":"Abstract Introduction The study assessed the efficacy of oral appliance device O2Vent Optima and ExVent, an oral Expiratory Positive Airway Pressure (EPAP) accessory in the treatment of OSA. Methods A prospective, open-label study conducted at 3 sites in mild to moderate OSA (AHI ≥ 5 and ≤ 30). Screening Phase A diagnostic in-lab PSG study confirmed a diagnosis of mild to moderate OSA. Treatment I Subjects used O2Vent Optima for 6 weeks and underwent a PSG sleep night while using the O2Vent Optima. Treatment II Subjects used O2Vent Optima + ExVent for 6 weeks and underwent a PSG sleep night while using the O2Vent Optima + ExVent Primary Effectiveness Measure: Change in AHI between baseline vs. O2Vent Optima MAD vs. O2Vent Optima + ExVent Results Treatment with Optima, Optima + ExVent reduced AHI from 22.5±6.4/hr to 12.6±4.5/hr to 5.9±2.7 (p&lt; 0.005 baseline vs. Optima and Optima + ExVent; p&lt;0.05 Optima MAD vs. Optima + ExVent). Average reduction in AHI with Optima was 43% and with Optima + ExVent was 72%. The lowest oxygen during sleep increased from 84.6±2.7% to 88.6±2.9% to 91.6±3.2% (p&lt; 0.005 baseline vs. Optima and Optima + ExVent; p&lt;0.05 Optima vs. Optima + ExVent). During the trial patients on treatment with Optima and Optima + ExVent demonstrated no excessive adverse events or device malfunction. Conclusion Treatment with O2Vent Optima and O2Vent Optima + ExVent significantly improved OSA compared to the baseline. Even greater benefit was observed with addition of ExVent to the Optima in mild to moderate OSA.","PeriodicalId":21861,"journal":{"name":"SLEEP Advances","volume":"131 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"136054071","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-10-01DOI: 10.1093/sleepadvances/zpad035.078
K Nguyen, C Dunbar, A Guyett, K Bickley, P Nguyen, H Scott, A Reynolds, M Hughes, R Adams, L Lack, P Catcheside, J Cori, M Howard, C Anderson, D Stevens, N Lovato, A Vakulin
Abstract Introduction Subjective sleepiness and driving performance are generally associated but show inter-individual variability. Specifically, some people are more vulnerable, while others are more resistant to driving impairment during extended wakefulness. We examined the relationship between subjective sleepiness and driving performance in groups resistant versus vulnerable to driving impairment during extended wakefulness. Methods Thirty-two adults (female=18, mean age=33.0yrs, SD=14.6) completed five 60-minute driving simulator assessments across 29 hours of extended wakefulness. Perceived sleepiness (Karolinska sleepiness scale, KSS) and driving performance (nine-point Likert scale) were assessed at 10-minute intervals while driving. Through cluster analysis, participants were categorised as vulnerable (n=16) or resistant (n=16) using steering deviation and crash data. Correlations, stepwise regressions, and ROC curves were used to identify predictors of driving impairment. Results Perceived sleepiness and driving impairment increased across the drives during wakefulness and within drives, regardless of grouping (p<0.001). The exception was the drive at 25-hours into wakefulness, where the vulnerable group showed higher perceived driving impairment within the drive (p=0.001). Pre-drive KSS, total sleep time, age and gender were not significant predictors of crashes at drives undertaken at 1-hour, 7-hours, 13-hours, or 25-hours, but were significant at 19-hours into wakefulness, together explaining 44% of the variance in crashes. Discussion Self-reports are sensitive to driving impairment but not differential vulnerability to performance decrements during extended wakefulness. However, the findings support that both groups can perceive their sleepiness and ideally employ appropriate countermeasures (e.g., stop driving, nap, caffeine). Future studies should target more objective predictors of vulnerable versus resistant groups.
{"title":"O078 A Comparison of Subjective Sleepiness and Subjective driving Performance between People Vulnerable Versus Resistant to Driving Impairment following Extended Wakefulness.","authors":"K Nguyen, C Dunbar, A Guyett, K Bickley, P Nguyen, H Scott, A Reynolds, M Hughes, R Adams, L Lack, P Catcheside, J Cori, M Howard, C Anderson, D Stevens, N Lovato, A Vakulin","doi":"10.1093/sleepadvances/zpad035.078","DOIUrl":"https://doi.org/10.1093/sleepadvances/zpad035.078","url":null,"abstract":"Abstract Introduction Subjective sleepiness and driving performance are generally associated but show inter-individual variability. Specifically, some people are more vulnerable, while others are more resistant to driving impairment during extended wakefulness. We examined the relationship between subjective sleepiness and driving performance in groups resistant versus vulnerable to driving impairment during extended wakefulness. Methods Thirty-two adults (female=18, mean age=33.0yrs, SD=14.6) completed five 60-minute driving simulator assessments across 29 hours of extended wakefulness. Perceived sleepiness (Karolinska sleepiness scale, KSS) and driving performance (nine-point Likert scale) were assessed at 10-minute intervals while driving. Through cluster analysis, participants were categorised as vulnerable (n=16) or resistant (n=16) using steering deviation and crash data. Correlations, stepwise regressions, and ROC curves were used to identify predictors of driving impairment. Results Perceived sleepiness and driving impairment increased across the drives during wakefulness and within drives, regardless of grouping (p<0.001). The exception was the drive at 25-hours into wakefulness, where the vulnerable group showed higher perceived driving impairment within the drive (p=0.001). Pre-drive KSS, total sleep time, age and gender were not significant predictors of crashes at drives undertaken at 1-hour, 7-hours, 13-hours, or 25-hours, but were significant at 19-hours into wakefulness, together explaining 44% of the variance in crashes. Discussion Self-reports are sensitive to driving impairment but not differential vulnerability to performance decrements during extended wakefulness. However, the findings support that both groups can perceive their sleepiness and ideally employ appropriate countermeasures (e.g., stop driving, nap, caffeine). Future studies should target more objective predictors of vulnerable versus resistant groups.","PeriodicalId":21861,"journal":{"name":"SLEEP Advances","volume":"2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"136054766","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-10-01DOI: 10.1093/sleepadvances/zpad035.072
P Nguyen, C Dunbar, A Guyett, K Nguyen, K Bickley, A Reynolds, M Hughes, H Scott, R Adams, L Lack, P Catcheside, J Cori, M Howard, C Anderson, N Lovato, A Vakulin
Abstract Introduction Driver fatigue contributes to 2-16% of road crashes, highlighting the need for improved detection of at-risk drivers. We used a novel and brief test of vestibular ocular motor system (VOMS) assessed via virtual reality goggles to predict alertness state and driving simulator performance during 29hr extended wakefulness. Methods 49 individuals (Mean±SD Age, 32.6±12.9, 45% Males) undergone 9hr baseline sleep opportunity followed by ~29hrs extended wakefulness with five 60min driving assessments. Cluster analysis, combining steering deviation and number of crashes were used to split participants into groups of either poor vs good driving performance. VOMS assessment was conducted using virtual reality goggles approximately 10mins before and after each drive. Predictive importance of VOMs metrics were ranked using XGBoost machine learning model, which was then utilized to distinguish between poor vs good driving groups. Model performance was evaluated using a 5-fold cross-validation approach using ROC analysis. Results XGBoost machine learning ranked all 70 VOMS metrics on their importance in predicting driving performance group for each drive. Top 10 metrics from pre-drive VOMS test predicted both daytime driving (tests 1-3, AUC 0.8 [95%CI 0.64-0.93], p<0.001) and night-time driving (tests 4-5, AUC 0.78 [95%CI 0.6-0.95, p<0.001]). Post-driving VOMS assessments also predicted daytime (AUC 0.74 [95%CI 0.53-0.9, p<0.001] and night-time driving (AUC 0.76 [95%CI 0.52-0.94, p<0.001]). Conclusion VOMS assessment show promise as a short and effective assessment of sleepiness to predict driving failure. Future validation in independent samples, sleep disordered population and in-field on-road testing are needed to confirm these promising findings.
{"title":"O072 Simple Vestibular-Occular Motor Assessment as a Predictor of Alertness State and Driving Impairment during Extended Wakefulness","authors":"P Nguyen, C Dunbar, A Guyett, K Nguyen, K Bickley, A Reynolds, M Hughes, H Scott, R Adams, L Lack, P Catcheside, J Cori, M Howard, C Anderson, N Lovato, A Vakulin","doi":"10.1093/sleepadvances/zpad035.072","DOIUrl":"https://doi.org/10.1093/sleepadvances/zpad035.072","url":null,"abstract":"Abstract Introduction Driver fatigue contributes to 2-16% of road crashes, highlighting the need for improved detection of at-risk drivers. We used a novel and brief test of vestibular ocular motor system (VOMS) assessed via virtual reality goggles to predict alertness state and driving simulator performance during 29hr extended wakefulness. Methods 49 individuals (Mean±SD Age, 32.6±12.9, 45% Males) undergone 9hr baseline sleep opportunity followed by ~29hrs extended wakefulness with five 60min driving assessments. Cluster analysis, combining steering deviation and number of crashes were used to split participants into groups of either poor vs good driving performance. VOMS assessment was conducted using virtual reality goggles approximately 10mins before and after each drive. Predictive importance of VOMs metrics were ranked using XGBoost machine learning model, which was then utilized to distinguish between poor vs good driving groups. Model performance was evaluated using a 5-fold cross-validation approach using ROC analysis. Results XGBoost machine learning ranked all 70 VOMS metrics on their importance in predicting driving performance group for each drive. Top 10 metrics from pre-drive VOMS test predicted both daytime driving (tests 1-3, AUC 0.8 [95%CI 0.64-0.93], p&lt;0.001) and night-time driving (tests 4-5, AUC 0.78 [95%CI 0.6-0.95, p&lt;0.001]). Post-driving VOMS assessments also predicted daytime (AUC 0.74 [95%CI 0.53-0.9, p&lt;0.001] and night-time driving (AUC 0.76 [95%CI 0.52-0.94, p&lt;0.001]). Conclusion VOMS assessment show promise as a short and effective assessment of sleepiness to predict driving failure. Future validation in independent samples, sleep disordered population and in-field on-road testing are needed to confirm these promising findings.","PeriodicalId":21861,"journal":{"name":"SLEEP Advances","volume":"30 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"136055097","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-10-01DOI: 10.1093/sleepadvances/zpad035.173
M Gale, E Axelsson, A Eidels, A Robson, J Mace
Abstract An increasingly prevalent factor in the preschool years is screen time, with possible implications for sleep and development. Few studies have simultaneously assessed screen time, sleep, and development. I aim to investigate preschoolers’ screen time, sleep, and language development, alongside predictors of screen time, social behaviours, and how sleep supports long-term memory for new words. Screen time durations for educational, entertaining, and relaxing content types, will be recorded over three days. This is to assess whether content types have differing relationships with sleep. If sleep quality and duration are impeded, this may create a cyclical pattern between sedentary behaviour, sleep, and screen time. I will also measure screen times at differing times of the day, and the percentage of time spent interacting with another person or the screen content. Children will be exposed to new words at the beginning of the study and their memory will be tested after three nights. Importantly, assessing the interaction between screen time and sleep, in relation to children’s memory for the new words. Sleep will be measured using actigraphy watches and a sleep diary. Standardised measures of vocabulary and communication will be used to assess children’s language development. As language development is a multifaceted process, assessing predictors, social behaviours, and memory for new words, allows assessment of factors that may benefit or hinder sleep and language development. This comprehensive study will contribute to the understanding of the relationships between screen time, sleep, and language development, and the nuanced factors that relate to its success.
{"title":"P088 The Relationship between Screen time, Sleep, and Language Development in Pre-school Aged Children","authors":"M Gale, E Axelsson, A Eidels, A Robson, J Mace","doi":"10.1093/sleepadvances/zpad035.173","DOIUrl":"https://doi.org/10.1093/sleepadvances/zpad035.173","url":null,"abstract":"Abstract An increasingly prevalent factor in the preschool years is screen time, with possible implications for sleep and development. Few studies have simultaneously assessed screen time, sleep, and development. I aim to investigate preschoolers’ screen time, sleep, and language development, alongside predictors of screen time, social behaviours, and how sleep supports long-term memory for new words. Screen time durations for educational, entertaining, and relaxing content types, will be recorded over three days. This is to assess whether content types have differing relationships with sleep. If sleep quality and duration are impeded, this may create a cyclical pattern between sedentary behaviour, sleep, and screen time. I will also measure screen times at differing times of the day, and the percentage of time spent interacting with another person or the screen content. Children will be exposed to new words at the beginning of the study and their memory will be tested after three nights. Importantly, assessing the interaction between screen time and sleep, in relation to children’s memory for the new words. Sleep will be measured using actigraphy watches and a sleep diary. Standardised measures of vocabulary and communication will be used to assess children’s language development. As language development is a multifaceted process, assessing predictors, social behaviours, and memory for new words, allows assessment of factors that may benefit or hinder sleep and language development. This comprehensive study will contribute to the understanding of the relationships between screen time, sleep, and language development, and the nuanced factors that relate to its success.","PeriodicalId":21861,"journal":{"name":"SLEEP Advances","volume":"42 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"136053884","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-10-01DOI: 10.1093/sleepadvances/zpad035.184
J McKenzie, C Pattinson, K Rossa, S Edmed, A Loeffler, S Smith
Abstract Introduction The Child Bedtime Routines Study (CBRT) sets out to examine patterns and attitudes towards sleep in daily life in a novel and detailed way, by constructing personal timelines of 5–8-year-old children’s sleep routines in their homes, their digital technology use, and parental attitudes and behaviours surrounding sleep and digital technology use. Methods This project involved individual semi-structured interviews with 30 parents of 5–8-year-old children via zoom. During the interview parents completed a novel visualisation of their home environment and the visual diagramming tasks for afternoon and evening, sleep and wake routines at home via the online interactive platform Mural. Results Thirty parents (Female = 86.7%) of 30 children (66.7% boys) aged between 5 and 8 years participated in the study. The most common description of their child using technology was watching shows or videos via tv or tablet. Over 76% of parents identified having rules or regulations regarding digital technology use. There was little technology use reported around bed-time routines, however, the use of apps to listen to bedtime stories was reported by some. Discussion The interviews allowed for greater description and nuance regarding the parenting decisions around technology use in the home. Household rules around the use of digital technology by children were not specifically oriented around bedtime or the potential impact of technology on sleep quality, duration, or timing. The use of technology-based sleep aids may increase, and a better understanding of the potential benefits and costs of those technologies needs to be understood.
{"title":"P099 Use of Digital Technology During Child Bedtime Routines: A qualitative investigation","authors":"J McKenzie, C Pattinson, K Rossa, S Edmed, A Loeffler, S Smith","doi":"10.1093/sleepadvances/zpad035.184","DOIUrl":"https://doi.org/10.1093/sleepadvances/zpad035.184","url":null,"abstract":"Abstract Introduction The Child Bedtime Routines Study (CBRT) sets out to examine patterns and attitudes towards sleep in daily life in a novel and detailed way, by constructing personal timelines of 5–8-year-old children’s sleep routines in their homes, their digital technology use, and parental attitudes and behaviours surrounding sleep and digital technology use. Methods This project involved individual semi-structured interviews with 30 parents of 5–8-year-old children via zoom. During the interview parents completed a novel visualisation of their home environment and the visual diagramming tasks for afternoon and evening, sleep and wake routines at home via the online interactive platform Mural. Results Thirty parents (Female = 86.7%) of 30 children (66.7% boys) aged between 5 and 8 years participated in the study. The most common description of their child using technology was watching shows or videos via tv or tablet. Over 76% of parents identified having rules or regulations regarding digital technology use. There was little technology use reported around bed-time routines, however, the use of apps to listen to bedtime stories was reported by some. Discussion The interviews allowed for greater description and nuance regarding the parenting decisions around technology use in the home. Household rules around the use of digital technology by children were not specifically oriented around bedtime or the potential impact of technology on sleep quality, duration, or timing. The use of technology-based sleep aids may increase, and a better understanding of the potential benefits and costs of those technologies needs to be understood.","PeriodicalId":21861,"journal":{"name":"SLEEP Advances","volume":"240 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"136053892","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-10-01DOI: 10.1093/sleepadvances/zpad035.015
M Lu, D Fitzgerald, C Sullivan, K Waters
Abstract Background Restless sleep is common in children, and video polysomnography (vPSG) has been used to score body movements during sleep. The Sonomat provides a contactless, portable alternative for home sleep studies over several nights. This study aimed to compare body movements measured by the Sonomat with those scored using vPSG. Methods Twenty-nine children (13 females, 16 males) with a median age of 5.4 years underwent concurrent Sonomat and vPSG studies. Movement indices per hour of sleep period and movement duration (%) were blindly scored on separate days. Statistical analysis included the Wilcoxon rank test and Pearson's correlations. Results Movement indices were higher on the Sonomat than vPSG (median 38.6/hr vs. 22.7/hr, p < 0.001), but movement duration did not differ (median 10.8% vs. 10.5%, p = 0.092). Comparing movements above 5 seconds, the indices became more comparable (15.9/hr vs. 19.2/hr, p = 0.05). The correlation between devices was weak for movement indices (r = 0.37, p = 0.051) but strong for movement duration (r = 0.81, p < 0.001). The Sonomat identified 82.5% of movements seen on vPSG, while vPSG identified only 43.6% of those on the Sonomat. Conclusion The Sonomat offers a contactless and portable alternative to vPSG for assessing body movements during sleep in children. It exhibited higher sensitivity in detecting shorter movements and was comparable to vPSG in movement duration. These findings suggest that the Sonomat holds promise for evaluating restless sleep in children.
儿童睡眠不安是很常见的，视频多导睡眠描记(vPSG)已被用于记录睡眠期间的身体运动。Sonomat为几个晚上的家庭睡眠研究提供了一种非接触式、便携的选择。这项研究旨在比较由索诺玛测量的身体运动和用vPSG评分的身体运动。方法29例儿童(女13例，男16例)，中位年龄5.4岁，同时进行索诺玛和vPSG研究。每小时睡眠时间的运动指数和运动持续时间(%)分别在不同的天进行盲法评分。统计分析包括Wilcoxon秩检验和Pearson相关性。结果sononomat组的运动指数高于vPSG组(中位38.6/hr vs. 22.7/hr, p <0.001)，但运动持续时间没有差异(中位数10.8% vs. 10.5%， p = 0.092)。对比5秒以上的运动，各项指标更具可比性(15.9/hr vs. 19.2/hr, p = 0.05)。器械与运动指标的相关性较弱(r = 0.37, p = 0.051)，与运动持续时间的相关性较强(r = 0.81, p <0.001)。Sonomat识别出vPSG上82.5%的动作，而vPSG仅识别出Sonomat上43.6%的动作。结论:Sonomat为评估儿童睡眠时的身体运动提供了一种非接触式、便携的vPSG替代方案。它在检测较短的运动中表现出更高的灵敏度，在运动持续时间上与vPSG相当。这些发现表明，索诺马特有望评估儿童的不安性睡眠。
{"title":"O015 Measuring Body Movements during Sleep. Sonomat Vs Video Polysomnography","authors":"M Lu, D Fitzgerald, C Sullivan, K Waters","doi":"10.1093/sleepadvances/zpad035.015","DOIUrl":"https://doi.org/10.1093/sleepadvances/zpad035.015","url":null,"abstract":"Abstract Background Restless sleep is common in children, and video polysomnography (vPSG) has been used to score body movements during sleep. The Sonomat provides a contactless, portable alternative for home sleep studies over several nights. This study aimed to compare body movements measured by the Sonomat with those scored using vPSG. Methods Twenty-nine children (13 females, 16 males) with a median age of 5.4 years underwent concurrent Sonomat and vPSG studies. Movement indices per hour of sleep period and movement duration (%) were blindly scored on separate days. Statistical analysis included the Wilcoxon rank test and Pearson's correlations. Results Movement indices were higher on the Sonomat than vPSG (median 38.6/hr vs. 22.7/hr, p &lt; 0.001), but movement duration did not differ (median 10.8% vs. 10.5%, p = 0.092). Comparing movements above 5 seconds, the indices became more comparable (15.9/hr vs. 19.2/hr, p = 0.05). The correlation between devices was weak for movement indices (r = 0.37, p = 0.051) but strong for movement duration (r = 0.81, p &lt; 0.001). The Sonomat identified 82.5% of movements seen on vPSG, while vPSG identified only 43.6% of those on the Sonomat. Conclusion The Sonomat offers a contactless and portable alternative to vPSG for assessing body movements during sleep in children. It exhibited higher sensitivity in detecting shorter movements and was comparable to vPSG in movement duration. These findings suggest that the Sonomat holds promise for evaluating restless sleep in children.","PeriodicalId":21861,"journal":{"name":"SLEEP Advances","volume":"134 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"136054286","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-10-01DOI: 10.1093/sleepadvances/zpad035.148
R Broadhead, S Mukherjee, V Aiyappan, C Chai-Coetzer, S Ullah, A Walker
Abstract Introduction Domiciliary long-term non-invasive ventilation (LT-NIV) is an accepted therapy for patients with severe chronic obstructive pulmonary disease (COPD) and chronic hypercapnia. This study aimed to characterise patients with COPD who were commenced on LT-NIV. Methods A retrospective analysis was performed of all patients prescribed LT-NIV with a primary physician-diagnosis of COPD, between June 2016 and March 2022 at an Australian tertiary hospital. Results 333 patients were commenced on LT-NIV, of whom 67 (20%) had COPD. Inpatient LT-NIV Initiation: 53/67 (79%) were commenced on LT-NIV during an inpatient admission with acute exacerbation of COPD. Patients were elderly (age, mean 69± SD 9.5 years), predominantly female (60%) with moderate-severe COPD (FEV1 37±18%) and mild-moderate comorbidity burden (Charlson Comorbidity Index Score 2.1±1.4). Prior to LT-NIV, 64% patients had a sleep study with 15% having severe OSA (AHI≥30 or ODI≥30). 30% previously required acute NIV. Pre-admission non-exacerbated PaCO2 was 58±7.3mmHg During admission, all inpatients demonstrated hypercapnia (PaCO2≥45mmHg). Peak inpatient PaCO2 was 87±20mmHg, with persistent hypercapnia on discharge 58±9.0mmHg. On discharge, IPAP and EPAP settings were 17±3.8 and 7.7cm±2.7cmH2O respectively. There was a non-significant reduction in respiratory-related and all-cause hospitalizations in the 12-months following LT-NIV initiation (p=0.66 and 0.53 respectively). Outpatient LT-NIV Initiation: [Further data collection in progress] Discussion This study illustrates the real-world prescription of LT-NIV for COPD at our centre, with the majority being initiated in the inpatient setting, rather than early outpatient reassessment. A prospective multi-centre analysis is required to better understand the nuances of LT-NIV prescription in patients with COPD.
{"title":"P063 Long-term Non-invasive Ventilation in Patients with COPD: A Retrospective Cohort Study.","authors":"R Broadhead, S Mukherjee, V Aiyappan, C Chai-Coetzer, S Ullah, A Walker","doi":"10.1093/sleepadvances/zpad035.148","DOIUrl":"https://doi.org/10.1093/sleepadvances/zpad035.148","url":null,"abstract":"Abstract Introduction Domiciliary long-term non-invasive ventilation (LT-NIV) is an accepted therapy for patients with severe chronic obstructive pulmonary disease (COPD) and chronic hypercapnia. This study aimed to characterise patients with COPD who were commenced on LT-NIV. Methods A retrospective analysis was performed of all patients prescribed LT-NIV with a primary physician-diagnosis of COPD, between June 2016 and March 2022 at an Australian tertiary hospital. Results 333 patients were commenced on LT-NIV, of whom 67 (20%) had COPD. Inpatient LT-NIV Initiation: 53/67 (79%) were commenced on LT-NIV during an inpatient admission with acute exacerbation of COPD. Patients were elderly (age, mean 69± SD 9.5 years), predominantly female (60%) with moderate-severe COPD (FEV1 37±18%) and mild-moderate comorbidity burden (Charlson Comorbidity Index Score 2.1±1.4). Prior to LT-NIV, 64% patients had a sleep study with 15% having severe OSA (AHI≥30 or ODI≥30). 30% previously required acute NIV. Pre-admission non-exacerbated PaCO2 was 58±7.3mmHg During admission, all inpatients demonstrated hypercapnia (PaCO2≥45mmHg). Peak inpatient PaCO2 was 87±20mmHg, with persistent hypercapnia on discharge 58±9.0mmHg. On discharge, IPAP and EPAP settings were 17±3.8 and 7.7cm±2.7cmH2O respectively. There was a non-significant reduction in respiratory-related and all-cause hospitalizations in the 12-months following LT-NIV initiation (p=0.66 and 0.53 respectively). Outpatient LT-NIV Initiation: [Further data collection in progress] Discussion This study illustrates the real-world prescription of LT-NIV for COPD at our centre, with the majority being initiated in the inpatient setting, rather than early outpatient reassessment. A prospective multi-centre analysis is required to better understand the nuances of LT-NIV prescription in patients with COPD.","PeriodicalId":21861,"journal":{"name":"SLEEP Advances","volume":"131 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"136054290","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-10-01DOI: 10.1093/sleepadvances/zpad035.116
I Ling, J Christoforou, G Chin, P Currie
Abstract Introduction Oral Appliance Therapy (OAT) is an effective second line treatment for OSA. However, OAT devices do not have active efficacy monitoring, hence little is known about methods to best identify the optimal degree of mandibular advancement. Methods Consecutive OSA patients undergoing OAT at a sleep disorders service were recruited to participate in a novel titration protocol using nightly monitoring via a portable device (NightOwl®, Ectosense, Belgium). Demographic & sleep study (PSG) data, and key NightOwl® metrics were collected. A treatment PSG was conducted at conclusion of OAT implementation using identified optimal point of mandibular advancement. Results 80 subjects were recruited (52 male, 65%) with mean (±SD) age 49±12 years, BMI 28±4.4 kg/m2, Epworth score (ESS) 9.1±4.9. Baseline PSG showed mean AHI 28±20 events/hr, nadir SpO2 84±21%, time SpO2<90% 8.3±30 minutes. Blood pressure monitoring at baseline showed mean day BP 123/70mmHg and night BP 106/57mmHg. The mean mandibular advancement implemented was 2.9±1.7mm. Post treatment mean ESS was 5.1±3.5 (p<0.001). 62/68 (91%) subjects reported perceived benefit on OAT, 49/53 (92%) reduced snoring, 51/62 (82%) improved sleep, 49/62 (79%) increased energy. Treatment PSG on completion of the protocol showed AHI 14±10 events/hr (p<0.001), nadir SpO2 82±33% (p>0.05), time SpO2<90% 1.2±21 minutes (p=0.04). 48/63 (76%) met the AHI definition of OAT success. Discussion This study demonstrates a novel OAT protocol which led to minimal degree of mandibular advancement, resulting in high rates of symptom benefit and effective treatment of OSA.
{"title":"P031 A Novel Oral Appliance Implementation Protocol Using Nightly Portable Monitoring for OSA Patients Failing CPAP therapy","authors":"I Ling, J Christoforou, G Chin, P Currie","doi":"10.1093/sleepadvances/zpad035.116","DOIUrl":"https://doi.org/10.1093/sleepadvances/zpad035.116","url":null,"abstract":"Abstract Introduction Oral Appliance Therapy (OAT) is an effective second line treatment for OSA. However, OAT devices do not have active efficacy monitoring, hence little is known about methods to best identify the optimal degree of mandibular advancement. Methods Consecutive OSA patients undergoing OAT at a sleep disorders service were recruited to participate in a novel titration protocol using nightly monitoring via a portable device (NightOwl®, Ectosense, Belgium). Demographic & sleep study (PSG) data, and key NightOwl® metrics were collected. A treatment PSG was conducted at conclusion of OAT implementation using identified optimal point of mandibular advancement. Results 80 subjects were recruited (52 male, 65%) with mean (±SD) age 49±12 years, BMI 28±4.4 kg/m2, Epworth score (ESS) 9.1±4.9. Baseline PSG showed mean AHI 28±20 events/hr, nadir SpO2 84±21%, time SpO2&lt;90% 8.3±30 minutes. Blood pressure monitoring at baseline showed mean day BP 123/70mmHg and night BP 106/57mmHg. The mean mandibular advancement implemented was 2.9±1.7mm. Post treatment mean ESS was 5.1±3.5 (p&lt;0.001). 62/68 (91%) subjects reported perceived benefit on OAT, 49/53 (92%) reduced snoring, 51/62 (82%) improved sleep, 49/62 (79%) increased energy. Treatment PSG on completion of the protocol showed AHI 14±10 events/hr (p&lt;0.001), nadir SpO2 82±33% (p&gt;0.05), time SpO2&lt;90% 1.2±21 minutes (p=0.04). 48/63 (76%) met the AHI definition of OAT success. Discussion This study demonstrates a novel OAT protocol which led to minimal degree of mandibular advancement, resulting in high rates of symptom benefit and effective treatment of OSA.","PeriodicalId":21861,"journal":{"name":"SLEEP Advances","volume":"41 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"136054498","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-10-01DOI: 10.1093/sleepadvances/zpad035.185
N Rather, R Shankumar, A Nizamuddin, D Mansfield
Abstract Background Obstructive Sleep Apnoea (OSA) represents an established risk factor for several medical conditions. The evidence demonstrates that OSA can be effectively treated by an oral appliance. However, there less information about the role of an oral appliance in a clinical care model in terms of uptake and efficacy. This study aimed at examining the efficacy of an intervention in dental public health settings in Melbourne, Australia. Methods Data were collected from the 2018-2021. Participants who fitted inclusions criteria completed two instruments. The Epworth Sleepiness Score (ESS) was used to assess the Subjective daytime sleepiness, and the Apnoea Hypopnea Index (AHI) objectively evaluated the severity of OSA. Participants were further asked to self-report felt improvements post intervention. Paired t-tests were used to compare pre-test and the post-test results. Results 34 participants had complete before and after data recorded. The mean age of the final samples of 66.4 (s.d., 14.2), the majority were female (67.7%). Participants unanimously acknowledged improvements after the intervention. Findings also indicated that after the intervention, participants had significantly lower EES scores compared to their baseline scores (6.9 vs 12.7; p<0.001). Regarding the AHI, at post-test, participants had significantly lower AHI scores compared to their baseline scores (13.8 vs. 19.2; p<0.001). Conclusions Present results indicate the use of oral appliance will ultimately benefit public patients who suffer from OSA. After the intervention, there were both objective and subjective improvements in OSA. Thus, findings provide valuable inputs and guidance for the design and implementation for larger efficacy trial.
背景阻塞性睡眠呼吸暂停(OSA)是几种医学条件下的既定危险因素。有证据表明，使用口腔器械可以有效地治疗阻塞性睡眠呼吸暂停。然而，关于口腔矫治器在临床护理模式中的作用，在吸收和疗效方面的信息较少。本研究旨在检查干预在澳大利亚墨尔本牙科公共卫生设置的效果。方法收集2018-2021年的数据。符合纳入标准的参与者完成了两个工具。采用Epworth嗜睡评分(ESS)评价白天主观嗜睡，采用呼吸暂停低通气指数(AHI)客观评价OSA的严重程度。参与者进一步被要求自我报告干预后的感觉改善。配对t检验用于比较前测和后测结果。结果34例受试者完成了前后数据记录。最终样本的平均年龄为66.4岁(标准差14.2)，以女性居多(67.7%)。参与者一致承认干预后情况有所改善。研究结果还表明，干预后，参与者的EES得分显著低于基线得分(6.9 vs 12.7;p&肝移植;0.001)。关于AHI，在测试后，参与者的AHI得分明显低于基线得分(13.8比19.2;p&肝移植;0.001)。结论使用口腔矫治器对阻塞性睡眠呼吸暂停(OSA)患者最终是有益的。干预后，OSA客观和主观均有改善。因此，研究结果为更大规模疗效试验的设计和实施提供了有价值的输入和指导。
{"title":"P100 Acceptance, Compliance and Efficacy of Oral Appliance Therapy by Patients Suffering from Sleep Apnoea.","authors":"N Rather, R Shankumar, A Nizamuddin, D Mansfield","doi":"10.1093/sleepadvances/zpad035.185","DOIUrl":"https://doi.org/10.1093/sleepadvances/zpad035.185","url":null,"abstract":"Abstract Background Obstructive Sleep Apnoea (OSA) represents an established risk factor for several medical conditions. The evidence demonstrates that OSA can be effectively treated by an oral appliance. However, there less information about the role of an oral appliance in a clinical care model in terms of uptake and efficacy. This study aimed at examining the efficacy of an intervention in dental public health settings in Melbourne, Australia. Methods Data were collected from the 2018-2021. Participants who fitted inclusions criteria completed two instruments. The Epworth Sleepiness Score (ESS) was used to assess the Subjective daytime sleepiness, and the Apnoea Hypopnea Index (AHI) objectively evaluated the severity of OSA. Participants were further asked to self-report felt improvements post intervention. Paired t-tests were used to compare pre-test and the post-test results. Results 34 participants had complete before and after data recorded. The mean age of the final samples of 66.4 (s.d., 14.2), the majority were female (67.7%). Participants unanimously acknowledged improvements after the intervention. Findings also indicated that after the intervention, participants had significantly lower EES scores compared to their baseline scores (6.9 vs 12.7; p&lt;0.001). Regarding the AHI, at post-test, participants had significantly lower AHI scores compared to their baseline scores (13.8 vs. 19.2; p&lt;0.001). Conclusions Present results indicate the use of oral appliance will ultimately benefit public patients who suffer from OSA. After the intervention, there were both objective and subjective improvements in OSA. Thus, findings provide valuable inputs and guidance for the design and implementation for larger efficacy trial.","PeriodicalId":21861,"journal":{"name":"SLEEP Advances","volume":"34 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"136052639","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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