Pub Date : 2023-10-01DOI: 10.1093/sleepadvances/zpad035.081
C Rodriguez, B Bullock, S Buzwell
Abstract Introduction Narcolepsy and Idiopathic Hypersomnia (IH) are chronic sleep disorders that negatively impact sufferers’ Health-Related Quality of Life (HRQoL) across physical, emotional, and social functioning. Narcolepsy and IH may also impact the HRQoL of those close to the patient (i.e., partners, parents). This project explored the experiences of partners of people with Narcolepsy or IH, including how living with someone with the diagnoses had impacted their own HRQoL. Methods In this qualitative study, a semi-structured interview was used to collect data from 8 partners of people with Narcolepsy T1, Narcolepsy T2 and IH. The data were analyzed using Reflexive Thematic Analysis to find common themes emerging from the participants’ narratives. Results Five themes (and 2 sub-themes) were identified: 1) changes in dyadic identity; 2) negative impact on intimacy; 3) loneliness; 4) sacrifices to maintain the relationship, and 5) dissatisfaction at the lack of knowledge and information among (a) the general public, and (b) health professionals. Conclusions This novel, exploratory study identified several themes of social and emotional functioning most impacted by a partner’s sleep disorder diagnosis; themes which correspond with the areas shown to be negatively affected in patients. Psychosocial interventions for Narcolepsy and IH should include patients’ partners to reduce the impact of the diagnoses on the family system, and improve overall HRQoL.
{"title":"O081 “My partner just wants to sleep”: A qualitative study of the experience of living with a partner with Narcolepsy or Idiopathic Hypersomnia.","authors":"C Rodriguez, B Bullock, S Buzwell","doi":"10.1093/sleepadvances/zpad035.081","DOIUrl":"https://doi.org/10.1093/sleepadvances/zpad035.081","url":null,"abstract":"Abstract Introduction Narcolepsy and Idiopathic Hypersomnia (IH) are chronic sleep disorders that negatively impact sufferers’ Health-Related Quality of Life (HRQoL) across physical, emotional, and social functioning. Narcolepsy and IH may also impact the HRQoL of those close to the patient (i.e., partners, parents). This project explored the experiences of partners of people with Narcolepsy or IH, including how living with someone with the diagnoses had impacted their own HRQoL. Methods In this qualitative study, a semi-structured interview was used to collect data from 8 partners of people with Narcolepsy T1, Narcolepsy T2 and IH. The data were analyzed using Reflexive Thematic Analysis to find common themes emerging from the participants’ narratives. Results Five themes (and 2 sub-themes) were identified: 1) changes in dyadic identity; 2) negative impact on intimacy; 3) loneliness; 4) sacrifices to maintain the relationship, and 5) dissatisfaction at the lack of knowledge and information among (a) the general public, and (b) health professionals. Conclusions This novel, exploratory study identified several themes of social and emotional functioning most impacted by a partner’s sleep disorder diagnosis; themes which correspond with the areas shown to be negatively affected in patients. Psychosocial interventions for Narcolepsy and IH should include patients’ partners to reduce the impact of the diagnoses on the family system, and improve overall HRQoL.","PeriodicalId":21861,"journal":{"name":"SLEEP Advances","volume":"38 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":"136054626","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/zpad035.064
E Axelsson, A Metse, S Nanthakumar, A Robson, G Paeach, A Asis, K Purcell
Abstract Sleep is highly important for children’s behaviour (Touchette et al., 2007). However, screen time is associated with poorer sleep (Janssen et al., 2020), and greater behavioural difficulties (Hinkley et al., 2018), but they are rarely investigated together. Caregivers’ rules and perceptions about screen time are also associated with children’s engagement with screens. Caregivers of preschoolers completed online questionnaires about children’s screen time, sleep-related behaviours (Child Sleep-Wake Scale), behaviour (Child Behavior Checklist (CBCL, 1.5-5)), person-social development (Ages and Stages Questionnaire-3 (ASQ-3)), and questions about their rules and perceptions of screen time. Greater screen times predicted lower personal-social scores, and better sleep-related behaviours predicted lower internalising scores. Greater screen times were predicted by caregivers’ tendency to disagree about limits on screen time and a greater inclination to think limits cause conflict. Lower child personal-social scores predicted caregivers’ tendency to disagree about screen time limits. Greater child externalising behaviours predicted caregivers’ belief that screen time helps calm their child and that time limits cause conflicts. Poorer child sleep also predicted caregivers’ tendency to think screen time limits cause conflict. Therefore, caregivers’ rules and perceptions are associated with children’s screen times, but also children’s behaviours are associated with caregivers’ rules and perceptions about screen time. This is concerning as screen time predicted poorer personal-social behaviours in children. Providing caregivers with alternative ways to manage behaviours and conflicts surrounding time limits could also help in managing children’s screen times. This could have long-term implications for healthy sleep, social, and behavioural development in children.
睡眠对儿童的行为非常重要(Touchette et al.， 2007)。然而，屏幕时间与较差的睡眠(Janssen et al.， 2020)和更大的行为困难(Hinkley et al.， 2018)有关，但它们很少被一起调查。照顾者对屏幕时间的规则和看法也与儿童与屏幕的接触有关。学龄前儿童的照顾者完成了关于儿童屏幕时间、睡眠相关行为(儿童睡眠-觉醒量表)、行为(儿童行为清单(CBCL, 1.5-5))、个人-社会发展(年龄和阶段问卷-3 (ASQ-3))的在线问卷，以及关于他们对屏幕时间的规则和感知的问题。更长的屏幕时间预示着更低的个人社会得分，而更好的睡眠相关行为预示着更低的内化得分。看护人倾向于不同意对屏幕时间的限制，并且更倾向于认为限制会导致冲突，这预示着更长的屏幕时间。儿童的个人-社会得分越低，看护人对屏幕时间限制的看法就越不一致。更大的儿童外化行为预示着看护者相信屏幕时间有助于让孩子平静下来，而时间限制会导致冲突。儿童睡眠较差也预示着看护者倾向于认为屏幕时间限制会导致冲突。因此，照顾者的规则和感知与儿童的屏幕时间有关，但儿童的行为也与照顾者关于屏幕时间的规则和感知有关。这一点令人担忧，因为屏幕时间预示着儿童较差的个人社交行为。为照顾者提供其他方法来管理围绕时间限制的行为和冲突，也有助于管理儿童的屏幕时间。这可能会对儿童的健康睡眠、社交和行为发展产生长期影响。
{"title":"O064 Screen Time, Sleep, and Behavioural Development in Preschool Children: Relationships Caregiver Rules and Perceptions of Screen Time","authors":"E Axelsson, A Metse, S Nanthakumar, A Robson, G Paeach, A Asis, K Purcell","doi":"10.1093/sleepadvances/zpad035.064","DOIUrl":"https://doi.org/10.1093/sleepadvances/zpad035.064","url":null,"abstract":"Abstract Sleep is highly important for children’s behaviour (Touchette et al., 2007). However, screen time is associated with poorer sleep (Janssen et al., 2020), and greater behavioural difficulties (Hinkley et al., 2018), but they are rarely investigated together. Caregivers’ rules and perceptions about screen time are also associated with children’s engagement with screens. Caregivers of preschoolers completed online questionnaires about children’s screen time, sleep-related behaviours (Child Sleep-Wake Scale), behaviour (Child Behavior Checklist (CBCL, 1.5-5)), person-social development (Ages and Stages Questionnaire-3 (ASQ-3)), and questions about their rules and perceptions of screen time. Greater screen times predicted lower personal-social scores, and better sleep-related behaviours predicted lower internalising scores. Greater screen times were predicted by caregivers’ tendency to disagree about limits on screen time and a greater inclination to think limits cause conflict. Lower child personal-social scores predicted caregivers’ tendency to disagree about screen time limits. Greater child externalising behaviours predicted caregivers’ belief that screen time helps calm their child and that time limits cause conflicts. Poorer child sleep also predicted caregivers’ tendency to think screen time limits cause conflict. Therefore, caregivers’ rules and perceptions are associated with children’s screen times, but also children’s behaviours are associated with caregivers’ rules and perceptions about screen time. This is concerning as screen time predicted poorer personal-social behaviours in children. Providing caregivers with alternative ways to manage behaviours and conflicts surrounding time limits could also help in managing children’s screen times. This could have long-term implications for healthy sleep, social, and behavioural development in children.","PeriodicalId":21861,"journal":{"name":"SLEEP Advances","volume":"20 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":"136054762","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/zpad035.099
V Hill, A Rebar, S Ferguson, G Vincent
Abstract Introduction Bedtime procrastination is defined as the volitional delay of going to bed, without any external circumstances causing the delay, and is associated with inadequate sleep. Alleviating bedtime procrastination may be an important target for interventions promoting adequate sleep, yet the correlates of bedtime procrastination are poorly understood. This study examined (1) correlates of bedtime procrastination, and (2) strength and direction of the association between bedtime procrastination and sleep outcomes. Methods Six databases (CINAHL, EMBASE, PsychINFO, PubMed, Scopus, Web of Science) were searched from inception to September 2021 against pre-determined eligibility criteria. Results Forty-three studies were included (GRADE = low). Meta-analysis revealed that bedtime procrastination had a moderate negative association with self-control (z = -0.39; CI: -0.45, -0.29) and a moderate positive association with evening chronotype (z = 0.43; CI: 0.32, 0.48). Furthermore, bedtime procrastination was moderately negatively associated with sleep duration (z = -0.31; CI: -0.37, -0.24), sleep quality (z = -0.35; CI: -0.42, -0.27) and moderately positively associated with daytime fatigue (z = 0.32; CI: 0.25, 0.38). Conclusion Further high-quality studies are needed to identify causal relationships between bedtime procrastination and correlates, as well as bedtime procrastination and sleep. Future work will guide the development of interventions targeting bedtime procrastination for improved sleep outcomes.
{"title":"P014 Go to bed! A Systematic Review and Meta-analysis of Bedtime Procrastination Correlates and Sleep Outcomes","authors":"V Hill, A Rebar, S Ferguson, G Vincent","doi":"10.1093/sleepadvances/zpad035.099","DOIUrl":"https://doi.org/10.1093/sleepadvances/zpad035.099","url":null,"abstract":"Abstract Introduction Bedtime procrastination is defined as the volitional delay of going to bed, without any external circumstances causing the delay, and is associated with inadequate sleep. Alleviating bedtime procrastination may be an important target for interventions promoting adequate sleep, yet the correlates of bedtime procrastination are poorly understood. This study examined (1) correlates of bedtime procrastination, and (2) strength and direction of the association between bedtime procrastination and sleep outcomes. Methods Six databases (CINAHL, EMBASE, PsychINFO, PubMed, Scopus, Web of Science) were searched from inception to September 2021 against pre-determined eligibility criteria. Results Forty-three studies were included (GRADE = low). Meta-analysis revealed that bedtime procrastination had a moderate negative association with self-control (z = -0.39; CI: -0.45, -0.29) and a moderate positive association with evening chronotype (z = 0.43; CI: 0.32, 0.48). Furthermore, bedtime procrastination was moderately negatively associated with sleep duration (z = -0.31; CI: -0.37, -0.24), sleep quality (z = -0.35; CI: -0.42, -0.27) and moderately positively associated with daytime fatigue (z = 0.32; CI: 0.25, 0.38). Conclusion Further high-quality studies are needed to identify causal relationships between bedtime procrastination and correlates, as well as bedtime procrastination and sleep. Future work will guide the development of interventions targeting bedtime procrastination for improved sleep outcomes.","PeriodicalId":21861,"journal":{"name":"SLEEP Advances","volume":"23 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":"136054765","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/zpad035.121
N Malagutti, L Chen, S Miller
Abstract Background Limitations in scale, population diversity, technical quality, data curation methods and accessibility of existing data resources have been recognised as limiting factors for the advancement of sleep clinical research through big data approaches. To bridge this gap, this study introduces a new sleep dataset which seeks to capture a data-rich, longitudinal snapshot of a representative Australian clinical sleep cohort. Methods Retrospective collation of de-identified sleep clinical records from adult patients who underwent at least one in-lab Type-1 polysomnography between 2012 and 2018 at Canberra Sleep Clinic. We extracted polysomnography raw signals and annotations, as well as medical record information including basic demographics, comorbidities, medications, examination findings, diagnoses, therapy settings and follow-up observations throughout subjects’ time in the Clinic’s care. Records were organised according to a graph database structure, embedding SNOMED terminology encodings wherever possible. Results N=6,777 subjects were included. Gender split (M/F: 62%/38%) and age (51.7±15.3 years) distribution were consistent with typical clinical sleep cohorts. Polysomnography recordings included diagnostic (n=6,635) and non-invasive ventilation titration/therapy (n=2,834), as well as MSLT (n=270) and MWT (n=25) studies. Clinical subgroups featured healthy, Obstructive Sleep Apnea (OSA) and non-OSA dyssomnia patients, as well as small cohort of parasomnia cases. Follow-up duration varied among cases (<3 months to >5 years). Discussion Despite limitations associated with retrospective data extraction, the data-richness and scale of Big Sleep ACT compare favourably with world-leading sleep datasets. Careful data organisation makes this dataset well placed to support innovative data-driven research into precise diagnoses, personalised interventions, and automation in sleep medicine.
{"title":"P037 The Big Sleep ACT Project: Developing a Modern Dataset to Support Sleep Research","authors":"N Malagutti, L Chen, S Miller","doi":"10.1093/sleepadvances/zpad035.121","DOIUrl":"https://doi.org/10.1093/sleepadvances/zpad035.121","url":null,"abstract":"Abstract Background Limitations in scale, population diversity, technical quality, data curation methods and accessibility of existing data resources have been recognised as limiting factors for the advancement of sleep clinical research through big data approaches. To bridge this gap, this study introduces a new sleep dataset which seeks to capture a data-rich, longitudinal snapshot of a representative Australian clinical sleep cohort. Methods Retrospective collation of de-identified sleep clinical records from adult patients who underwent at least one in-lab Type-1 polysomnography between 2012 and 2018 at Canberra Sleep Clinic. We extracted polysomnography raw signals and annotations, as well as medical record information including basic demographics, comorbidities, medications, examination findings, diagnoses, therapy settings and follow-up observations throughout subjects’ time in the Clinic’s care. Records were organised according to a graph database structure, embedding SNOMED terminology encodings wherever possible. Results N=6,777 subjects were included. Gender split (M/F: 62%/38%) and age (51.7±15.3 years) distribution were consistent with typical clinical sleep cohorts. Polysomnography recordings included diagnostic (n=6,635) and non-invasive ventilation titration/therapy (n=2,834), as well as MSLT (n=270) and MWT (n=25) studies. Clinical subgroups featured healthy, Obstructive Sleep Apnea (OSA) and non-OSA dyssomnia patients, as well as small cohort of parasomnia cases. Follow-up duration varied among cases (&lt;3 months to &gt;5 years). Discussion Despite limitations associated with retrospective data extraction, the data-richness and scale of Big Sleep ACT compare favourably with world-leading sleep datasets. Careful data organisation makes this dataset well placed to support innovative data-driven research into precise diagnoses, personalised interventions, and automation in sleep medicine.","PeriodicalId":21861,"journal":{"name":"SLEEP Advances","volume":"30 26 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":"136054774","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/zpad035.130
N Eriksson, A Carballo, C Roberts
Abstract Introduction AASM recommends the use of nasal pressure (NP), oronasal thermal flow (TF), and respiratory inductance plethysmography (RIP) for detecting and characterising respiratory events in polysomnography. The use of both NP and TF sensors is reported to be more accurate in respiratory event identification than either alone. However, these sensors can be unreliable if dislodged and cause discomfort. Noxturnal calibrated RIP flow (cRIPflow), derived from RIP, may provide a non-invasive alternative method for flow measurement in identification of respiratory events. Method Respiratory scoring was performed manually by a single experienced scorer on 10 diagnostic sleep studies under AASM standards. Scoring was repeated using three different measurements for each study: cRIPflow only, Thermistor (Th) only and both Th+NP (AASM recommendation). Apnoea hypopnoea index (AHI), central apnoea index (CAI), obstructive apnoea index (OAI), mixed apnoea index (MAI) and hypopnoea index (HI) were calculated and paired t-test analysis utilised for comparison between measurements. Results No statistical differences were identified in comparison of cRIPflow with Th or Th+NP in respiratory event identification: CAI (cRIPflow 3.2/hr±7.1, Th 3.9/hr±8.9, Th+NP 3.1/hr±7.5), OAI (cRIPflow 6.1/hr±6.8, Th 5.3/hr±8.2, Th+NP 6.7/hr±8.9), MAI (cRIPflow 5.2/hr±9.7, Th 4.3/hr±8.7, Th+NP 4.7/hr±9.2), or HI (cRIPflow 12.5/hr±13.9, Th 11.1/hr±10.5, Th+NP 10.4/hr±10.7). There was a statistical difference for AHI (cRIPflow 26.9/hr±26.6, Th 24.5/hr±26.4, Th+NP 25.0/hr±26.5). Discussion This study suggests cRIPflow may provide an alternative measurement in the detection and characterisation of respiratory events, however further analysis with larger sample size would provide more insight into sensitivity and specificity of this method.
{"title":"P045 Noxturnal cRIP: A Comparative Analysis of Sensors for the Identification of Respiratory Events in Polysomnography","authors":"N Eriksson, A Carballo, C Roberts","doi":"10.1093/sleepadvances/zpad035.130","DOIUrl":"https://doi.org/10.1093/sleepadvances/zpad035.130","url":null,"abstract":"Abstract Introduction AASM recommends the use of nasal pressure (NP), oronasal thermal flow (TF), and respiratory inductance plethysmography (RIP) for detecting and characterising respiratory events in polysomnography. The use of both NP and TF sensors is reported to be more accurate in respiratory event identification than either alone. However, these sensors can be unreliable if dislodged and cause discomfort. Noxturnal calibrated RIP flow (cRIPflow), derived from RIP, may provide a non-invasive alternative method for flow measurement in identification of respiratory events. Method Respiratory scoring was performed manually by a single experienced scorer on 10 diagnostic sleep studies under AASM standards. Scoring was repeated using three different measurements for each study: cRIPflow only, Thermistor (Th) only and both Th+NP (AASM recommendation). Apnoea hypopnoea index (AHI), central apnoea index (CAI), obstructive apnoea index (OAI), mixed apnoea index (MAI) and hypopnoea index (HI) were calculated and paired t-test analysis utilised for comparison between measurements. Results No statistical differences were identified in comparison of cRIPflow with Th or Th+NP in respiratory event identification: CAI (cRIPflow 3.2/hr±7.1, Th 3.9/hr±8.9, Th+NP 3.1/hr±7.5), OAI (cRIPflow 6.1/hr±6.8, Th 5.3/hr±8.2, Th+NP 6.7/hr±8.9), MAI (cRIPflow 5.2/hr±9.7, Th 4.3/hr±8.7, Th+NP 4.7/hr±9.2), or HI (cRIPflow 12.5/hr±13.9, Th 11.1/hr±10.5, Th+NP 10.4/hr±10.7). There was a statistical difference for AHI (cRIPflow 26.9/hr±26.6, Th 24.5/hr±26.4, Th+NP 25.0/hr±26.5). Discussion This study suggests cRIPflow may provide an alternative measurement in the detection and characterisation of respiratory events, however further analysis with larger sample size would provide more insight into sensitivity and specificity of this method.","PeriodicalId":21861,"journal":{"name":"SLEEP Advances","volume":"206 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":"136054788","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/zpad035.006
B Shenoy, N McArdle, J Walsh, G Cadby, A Reynor, S Dhaliwal, B McQuillan, D Hillman, J Hung, P Eastwood, S Mukherjee, L Palmer, B Singh
Abstract Background Obstructive sleep apnoea (OSA) is a heterogeneous disorder with certain phenotypes at increased risk of major adverse cardiovascular events (MACE). We investigated whether symptom subtypes and/or symptom burden are useful predictors of MACE risk in severe OSA. Method In a longitudinal sleep clinic cohort with apnoea-hypopnoea index ≥30 events/hour (n=1767), we investigated 19 OSA-related symptoms across four symptom domains (upper airway [UA], insomnia and disturbed sleep, morning, and daytime sleepiness) and the Epworth Sleepiness Scale score. Latent class analysis identified five symptom subtypes. A symptom burden score (0–8) was developed by selecting the two symptoms from each domain most strongly associated with MACE. Multivariable-adjusted associations of subtypes and symptom burden with future MACE were investigated using Cox regressions. Results Over a median follow-up of 7 years, 18.7% developed MACE. Relative to the moderately sleepy subtype, the disturbed sleep (adjusted hazard ratio [HR], 1.65; 95%CI, 1.15–2.37) and UA symptoms predominant (HR, 1.57; 95%CI, 1.05–2.34) subtypes showed increased MACE risk. There was a graded increase in MACE risk with increasing symptom burden score (adjusted p for linear trend = 0.003). Compared to patients that reported ≤2 of 8 symptoms, those with ≥7 symptoms showed an independent risk for MACE (HR, 1.77; 95%CI, 1.12–2.77). Discussion Both symptom subtypes and symptom burden may help identify severe OSA patients at increased risk of MACE. However, our novel symptom burden score may have more clinical utility as it is an easily calculated summative measure of OSA-related symptoms that allows objective comparisons across diverse patient populations.
{"title":"O006 Major adverse cardiovascular events in severe Obstructive Sleep Apnoea: Associations with symptom subtypes and symptom burden","authors":"B Shenoy, N McArdle, J Walsh, G Cadby, A Reynor, S Dhaliwal, B McQuillan, D Hillman, J Hung, P Eastwood, S Mukherjee, L Palmer, B Singh","doi":"10.1093/sleepadvances/zpad035.006","DOIUrl":"https://doi.org/10.1093/sleepadvances/zpad035.006","url":null,"abstract":"Abstract Background Obstructive sleep apnoea (OSA) is a heterogeneous disorder with certain phenotypes at increased risk of major adverse cardiovascular events (MACE). We investigated whether symptom subtypes and/or symptom burden are useful predictors of MACE risk in severe OSA. Method In a longitudinal sleep clinic cohort with apnoea-hypopnoea index ≥30 events/hour (n=1767), we investigated 19 OSA-related symptoms across four symptom domains (upper airway [UA], insomnia and disturbed sleep, morning, and daytime sleepiness) and the Epworth Sleepiness Scale score. Latent class analysis identified five symptom subtypes. A symptom burden score (0–8) was developed by selecting the two symptoms from each domain most strongly associated with MACE. Multivariable-adjusted associations of subtypes and symptom burden with future MACE were investigated using Cox regressions. Results Over a median follow-up of 7 years, 18.7% developed MACE. Relative to the moderately sleepy subtype, the disturbed sleep (adjusted hazard ratio [HR], 1.65; 95%CI, 1.15–2.37) and UA symptoms predominant (HR, 1.57; 95%CI, 1.05–2.34) subtypes showed increased MACE risk. There was a graded increase in MACE risk with increasing symptom burden score (adjusted p for linear trend = 0.003). Compared to patients that reported ≤2 of 8 symptoms, those with ≥7 symptoms showed an independent risk for MACE (HR, 1.77; 95%CI, 1.12–2.77). Discussion Both symptom subtypes and symptom burden may help identify severe OSA patients at increased risk of MACE. However, our novel symptom burden score may have more clinical utility as it is an easily calculated summative measure of OSA-related symptoms that allows objective comparisons across diverse patient populations.","PeriodicalId":21861,"journal":{"name":"SLEEP Advances","volume":"51 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":"136054999","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/zpad035.101
S Ittinirundorn, N Chirakalwasan, C Kline, W Tongtako
Abstract Introduction There is some evidence indicating that exercise, such as aerobic training (AT) and inspiratory muscle training (IMT), improves Obstructive Sleep Apnea (OSA) symptoms. Nonetheless, no study compares the types of exercise in OSA patients. Objective To compare the effects of type of exercise on Apnea-Hypopnea Index (AHI) and respiratory muscle strength in OSA patients Methods Twenty-nine non-obese OSA patients aged 20-50 years with mild to moderate severity (Apnea-hypopnea index 5-30 events/hour) were randomized to the AT group (n=9), the IMT group (n=10) or the control (CON) group (n=10). Participants in the AT group received 60 minutes per day, 3 times per week, for 12 weeks. For the IMT group, participants received the Powerbreathe ® device for practicing 8 cycles of 30 breaths per day, 5 times per week, for 12 weeks. Participants in the CON group did not receive any intervention. Their AHI and respiratory muscle strength were analyzed during the pre- and post-tests. Dependent variables were compared between pre- and post-tests via paired t-test, and independent variables were compared between the groups using one-way analysis of variance (ANOVA). Differences were considered significant at p<0.05. Results AHI, maximal inspiratory pressure (MIP), and maximal expiratory pressure (MEP) changed significantly in the AT group and IMT group after 12 weeks of training. Therefore, AHI, MIP, and MEP in the AT group and the IMT group improved significantly compared to the CON group. Conclusions Aerobic training and inspiratory muscle training improve the apnea-hypopnea index and respiratory muscle strength in OSA patients.
{"title":"P016 Effects of Aerobic Exercise versus Inspiratory Muscle training on Apnea-Hypopnea Index in patients with Obstructive Sleep Apnea","authors":"S Ittinirundorn, N Chirakalwasan, C Kline, W Tongtako","doi":"10.1093/sleepadvances/zpad035.101","DOIUrl":"https://doi.org/10.1093/sleepadvances/zpad035.101","url":null,"abstract":"Abstract Introduction There is some evidence indicating that exercise, such as aerobic training (AT) and inspiratory muscle training (IMT), improves Obstructive Sleep Apnea (OSA) symptoms. Nonetheless, no study compares the types of exercise in OSA patients. Objective To compare the effects of type of exercise on Apnea-Hypopnea Index (AHI) and respiratory muscle strength in OSA patients Methods Twenty-nine non-obese OSA patients aged 20-50 years with mild to moderate severity (Apnea-hypopnea index 5-30 events/hour) were randomized to the AT group (n=9), the IMT group (n=10) or the control (CON) group (n=10). Participants in the AT group received 60 minutes per day, 3 times per week, for 12 weeks. For the IMT group, participants received the Powerbreathe ® device for practicing 8 cycles of 30 breaths per day, 5 times per week, for 12 weeks. Participants in the CON group did not receive any intervention. Their AHI and respiratory muscle strength were analyzed during the pre- and post-tests. Dependent variables were compared between pre- and post-tests via paired t-test, and independent variables were compared between the groups using one-way analysis of variance (ANOVA). Differences were considered significant at p&lt;0.05. Results AHI, maximal inspiratory pressure (MIP), and maximal expiratory pressure (MEP) changed significantly in the AT group and IMT group after 12 weeks of training. Therefore, AHI, MIP, and MEP in the AT group and the IMT group improved significantly compared to the CON group. Conclusions Aerobic training and inspiratory muscle training improve the apnea-hypopnea index and respiratory muscle strength in OSA patients.","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":"136055002","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/zpad035.110
D Levendowski, T Neylan, J Lee-Iannotti, D Tsuang, C Walsh, C Berka, G Mazeika, B Boeve, E St. Louis
Abstract Introduction Atypical N3 sleep (AN3=delta waves with limited theta and sigma) has been associated with ICU delirium and sepsis and averaged 25% of sleep time in Japanese ICU patients. We were interested in exploring whether AN3 might be a marker of cerebral dysfunction in ambulatory patients across a range of neurodegenerative disorders, including those with a dementia diagnosis. Methods After ethics review and with informed consent, patients with Lewy body disease (DLB/PDD: n=20,male=90%,age=70 + 6.2), Alzheimers disease dementia (AD: n=29,male=79%,age=75 + 6.7), Parkinson disease (PD: n=16,male=69%,age=67 + 8.7), mild cognitive impairment (MCI: n=41,male=63%,age=70 + 8.5), isolated REM sleep behavior disorder (iRBD: n=19,male=74%,age=64 + 9.6) and a control group (CG: n=61,male=47%,age=65 + 8.3) were studied with the Sleep Profiler and auto-detected AN3 computed. Between-group comparisons were assessed with Mann-Whitney U and Chi-square tests. Results The mean percentages of sleep time with AN3 were significantly greater in DLB/PDD (8 + 12.3) vs. PD (4 + 10.8), AD (2 + 3.7), MCI (2 + 2.3), iRBD (1 + 1.6), and CG (1 + 2.4)(all p<0.02). The proportions of records with abnormal AN3 (>5% of sleep time) were significantly greater in those with DLB/PDD=35% vs. MCI=10%, iRBD=5% and CG=5% (all p<0.05), but not AD=17% and PD=13%. Conclusions Further investigations are needed to determine if abnormal AN3 may be a biomarker that distinguishes patients with Lewy body spectrum diseases from alternative pathologies and/or could be helpful in monitoring the side effects of CNS-acting medications
{"title":"P025 Atypical N3 Sleep: A Biomarker for Altered Mental Status in Lewy Body Disease?","authors":"D Levendowski, T Neylan, J Lee-Iannotti, D Tsuang, C Walsh, C Berka, G Mazeika, B Boeve, E St. Louis","doi":"10.1093/sleepadvances/zpad035.110","DOIUrl":"https://doi.org/10.1093/sleepadvances/zpad035.110","url":null,"abstract":"Abstract Introduction Atypical N3 sleep (AN3=delta waves with limited theta and sigma) has been associated with ICU delirium and sepsis and averaged 25% of sleep time in Japanese ICU patients. We were interested in exploring whether AN3 might be a marker of cerebral dysfunction in ambulatory patients across a range of neurodegenerative disorders, including those with a dementia diagnosis. Methods After ethics review and with informed consent, patients with Lewy body disease (DLB/PDD: n=20,male=90%,age=70 + 6.2), Alzheimers disease dementia (AD: n=29,male=79%,age=75 + 6.7), Parkinson disease (PD: n=16,male=69%,age=67 + 8.7), mild cognitive impairment (MCI: n=41,male=63%,age=70 + 8.5), isolated REM sleep behavior disorder (iRBD: n=19,male=74%,age=64 + 9.6) and a control group (CG: n=61,male=47%,age=65 + 8.3) were studied with the Sleep Profiler and auto-detected AN3 computed. Between-group comparisons were assessed with Mann-Whitney U and Chi-square tests. Results The mean percentages of sleep time with AN3 were significantly greater in DLB/PDD (8 + 12.3) vs. PD (4 + 10.8), AD (2 + 3.7), MCI (2 + 2.3), iRBD (1 + 1.6), and CG (1 + 2.4)(all p&lt;0.02). The proportions of records with abnormal AN3 (&gt;5% of sleep time) were significantly greater in those with DLB/PDD=35% vs. MCI=10%, iRBD=5% and CG=5% (all p&lt;0.05), but not AD=17% and PD=13%. Conclusions Further investigations are needed to determine if abnormal AN3 may be a biomarker that distinguishes patients with Lewy body spectrum diseases from alternative pathologies and/or could be helpful in monitoring the side effects of CNS-acting medications","PeriodicalId":21861,"journal":{"name":"SLEEP Advances","volume":"1 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":"136055005","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/zpad035.076
M Crowther, S Ferguson, R Adams, A Reynolds
Abstract Shift work is associated with increased chronic disease risk and suboptimal health behaviours. However, our understanding of the impact of shift work on health behaviours is impacted by a lack of longitudinal studies that examine health behaviours in shift workers relative to behaviours prior to shift work commencement. To address this limitation, we examined sleep changes and perceived health risk (i.e., individual’s perception of risk to their health) in intern paramedics during the first 12 months of shift work. The current study examined self-report sleep quality and duration in 21 interns (15 Female, 6 Male, aged 23.0 [20.0, 36.0]) from one Australian Ambulance service. Data were collected quarterly for a year (pre-shift work, and then 3, 6, 9 and 12 months post recruitment training). Linear mixed models, controlling for chronotype and baseline perceived health risk, showed that the first 12 months of shift work were associated with a significant decline in sleep quality (p=0.021) but no change in sleep duration (p=0.76). Linear mixed models also showed that perceived health risk significantly increased (p=0.036). Substantial between-subjects differences were observed, highlighting individual differences in response to shift work onset on sleep and perceived health risk. This study demonstrates that commencement of shift work is associated with a decline in sleep quality and increase in perceived health risk in early career paramedics. The considerable individual differences observed in this study highlight a need for larger studies with more participants, and a focus on personalised strategies for workers commencing shift work.
{"title":"O076 Changes in Sleep and Perceived Health risk in early Career Paramedics","authors":"M Crowther, S Ferguson, R Adams, A Reynolds","doi":"10.1093/sleepadvances/zpad035.076","DOIUrl":"https://doi.org/10.1093/sleepadvances/zpad035.076","url":null,"abstract":"Abstract Shift work is associated with increased chronic disease risk and suboptimal health behaviours. However, our understanding of the impact of shift work on health behaviours is impacted by a lack of longitudinal studies that examine health behaviours in shift workers relative to behaviours prior to shift work commencement. To address this limitation, we examined sleep changes and perceived health risk (i.e., individual’s perception of risk to their health) in intern paramedics during the first 12 months of shift work. The current study examined self-report sleep quality and duration in 21 interns (15 Female, 6 Male, aged 23.0 [20.0, 36.0]) from one Australian Ambulance service. Data were collected quarterly for a year (pre-shift work, and then 3, 6, 9 and 12 months post recruitment training). Linear mixed models, controlling for chronotype and baseline perceived health risk, showed that the first 12 months of shift work were associated with a significant decline in sleep quality (p=0.021) but no change in sleep duration (p=0.76). Linear mixed models also showed that perceived health risk significantly increased (p=0.036). Substantial between-subjects differences were observed, highlighting individual differences in response to shift work onset on sleep and perceived health risk. This study demonstrates that commencement of shift work is associated with a decline in sleep quality and increase in perceived health risk in early career paramedics. The considerable individual differences observed in this study highlight a need for larger studies with more participants, and a focus on personalised strategies for workers commencing shift work.","PeriodicalId":21861,"journal":{"name":"SLEEP Advances","volume":"24 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":"136055102","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/zpad035.122
B Tong, S McClintock, S He, P De Chazal, B Yee, P Cistulli
Abstract Pulse wave amplitude derived from photoplethysmography signals is a surrogate measure of autonomic function and vascular response. Recent studies have demonstrated low pulse wave amplitude drop(PWAD) index to be associated with increased cardiovascular risk in obstructive sleep apnoea(OSA). The nature of PWAD in patients with cardiovascular disease remains unknown. We aimed to characterize PWAD in patients with acute coronary syndrome(ACS) diagnosed with OSA in terms of cardiovascular measures. We studied 70 patients with ACS (age:58[52,63]years, BMI:27[24,30]kg/m2). A level 2 polysomnogram was conducted to confirm OSA diagnosis within 6 months after discharge. Cardiovascular measures of heart rate variability(HRV), baroreflex sensitivity, pulse wave velocity (PWV) and endothelial function(FMD) were measured. PWAD was analysed using a validated algorithm. PWAD with an amplitude reduction of >30% from baseline and a duration >4 heartbeats were identified. PWAD frequency, duration, amplitude, area under the curve(AUC), descending and ascending slopes were calculated. There was no relationship between PWAD frequency and AHI (r=0.057, p=0.642). PWAD amplitude (rs= 0.308, p=0.031) and duration (rs= -0.319, p= 0.025) correlated with baroreflex effectiveness index. After controlling for age, gender and BMI, baroreflex effectiveness index was associated with PWAD duration (β±SE: -0.009±0.003, p=0.009). Aortic augmentation index correlated with PWAD duration (rs= 0.3565, p=0.0041). HRV parameters, FMD and PWV did not correlate with PWAD parameters (data not shown). These preliminary findings suggest PWAD duration and amplitude are not associated with OSA severity in patients with ACS. However PWAD may be appropriate markers of vascular and autonomic nervous system response in patients with cardiovascular disease.
{"title":"P038 Characterising Pulse Wave Amplitude Drops in Patients with Acute Coronary Syndrome","authors":"B Tong, S McClintock, S He, P De Chazal, B Yee, P Cistulli","doi":"10.1093/sleepadvances/zpad035.122","DOIUrl":"https://doi.org/10.1093/sleepadvances/zpad035.122","url":null,"abstract":"Abstract Pulse wave amplitude derived from photoplethysmography signals is a surrogate measure of autonomic function and vascular response. Recent studies have demonstrated low pulse wave amplitude drop(PWAD) index to be associated with increased cardiovascular risk in obstructive sleep apnoea(OSA). The nature of PWAD in patients with cardiovascular disease remains unknown. We aimed to characterize PWAD in patients with acute coronary syndrome(ACS) diagnosed with OSA in terms of cardiovascular measures. We studied 70 patients with ACS (age:58[52,63]years, BMI:27[24,30]kg/m2). A level 2 polysomnogram was conducted to confirm OSA diagnosis within 6 months after discharge. Cardiovascular measures of heart rate variability(HRV), baroreflex sensitivity, pulse wave velocity (PWV) and endothelial function(FMD) were measured. PWAD was analysed using a validated algorithm. PWAD with an amplitude reduction of &gt;30% from baseline and a duration &gt;4 heartbeats were identified. PWAD frequency, duration, amplitude, area under the curve(AUC), descending and ascending slopes were calculated. There was no relationship between PWAD frequency and AHI (r=0.057, p=0.642). PWAD amplitude (rs= 0.308, p=0.031) and duration (rs= -0.319, p= 0.025) correlated with baroreflex effectiveness index. After controlling for age, gender and BMI, baroreflex effectiveness index was associated with PWAD duration (β±SE: -0.009±0.003, p=0.009). Aortic augmentation index correlated with PWAD duration (rs= 0.3565, p=0.0041). HRV parameters, FMD and PWV did not correlate with PWAD parameters (data not shown). These preliminary findings suggest PWAD duration and amplitude are not associated with OSA severity in patients with ACS. However PWAD may be appropriate markers of vascular and autonomic nervous system response in patients with cardiovascular disease.","PeriodicalId":21861,"journal":{"name":"SLEEP Advances","volume":"45 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":"136055103","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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