Pub Date : 2023-12-27DOI: 10.1093/sleepadvances/zpad055
Johanna E. Elumn, Patrick Li, Malcolm S Lytell, Marisol Garcia, Emily A. Wang, H. Yaggi
Sleep is an underexplored factor in the health of people involved in the criminal legal system. This study addresses the paucity of research on how individual, social, and physical environmental factors impact sleep health during and after incarceration by highlighting the voices of people involved in the criminal legal system through a community-engaged qualitative research approach. We conducted 20 semi-structured interviews with men recently released from prison for a study on trauma and healthcare during incarceration and after release. Interviews were coded and analyzed using reflexive thematic analysis and a critical realist framework. Our research team included people with a history of incarceration who performed central roles in the research process. Three themes emerged from participants’ descriptions of sleep during and after incarceration: (1) concerns about health contributing to sleep problems, (2) lack of access to treatment for sleep disorders leading to ongoing sleep problems, and (3) issues of safety contributing to sleep problems during incarceration and after release. This study identifies factors and domains influencing sleep during and after incarceration. By identifying which interpersonal, environmental, and structural factors impact sleep quality, medical and carceral staff are better equipped to ameliorate sleep health disparities within populations with a history of incarceration and those actively bound by the criminal legal system. Future research should examine other factors impacting sleep in incarcerated and recently released populations and develop multi-level interventions to improve sleep health.
{"title":"“What if that’s your last sleep?”: A qualitative exploration of the trauma of incarceration and sleep","authors":"Johanna E. Elumn, Patrick Li, Malcolm S Lytell, Marisol Garcia, Emily A. Wang, H. Yaggi","doi":"10.1093/sleepadvances/zpad055","DOIUrl":"https://doi.org/10.1093/sleepadvances/zpad055","url":null,"abstract":"Sleep is an underexplored factor in the health of people involved in the criminal legal system. This study addresses the paucity of research on how individual, social, and physical environmental factors impact sleep health during and after incarceration by highlighting the voices of people involved in the criminal legal system through a community-engaged qualitative research approach. We conducted 20 semi-structured interviews with men recently released from prison for a study on trauma and healthcare during incarceration and after release. Interviews were coded and analyzed using reflexive thematic analysis and a critical realist framework. Our research team included people with a history of incarceration who performed central roles in the research process. Three themes emerged from participants’ descriptions of sleep during and after incarceration: (1) concerns about health contributing to sleep problems, (2) lack of access to treatment for sleep disorders leading to ongoing sleep problems, and (3) issues of safety contributing to sleep problems during incarceration and after release. This study identifies factors and domains influencing sleep during and after incarceration. By identifying which interpersonal, environmental, and structural factors impact sleep quality, medical and carceral staff are better equipped to ameliorate sleep health disparities within populations with a history of incarceration and those actively bound by the criminal legal system. Future research should examine other factors impacting sleep in incarcerated and recently released populations and develop multi-level interventions to improve sleep health.","PeriodicalId":21861,"journal":{"name":"SLEEP Advances","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-12-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139153692","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 : 2023-12-22DOI: 10.1093/sleepadvances/zpad054
M. Pitkänen, R. K. Nath, H. Korkalainen, Sami Nikkonen, Alaa Mahamid, A. Oksenberg, B. Duce, Juha Töyräs, S. Kainulainen, T. Leppänen
Polygraphy (PG) is often used to diagnose obstructive sleep apnea (OSA). However, it does not use electroencephalography (EEG), and therefore cannot estimate sleep time or score arousals and related hypopneas. Consequently, the PG-derived respiratory event index (REI) differs from the polysomnography (PSG) derived apnea-hypopnea index (AHI). In this study, we comprehensively analyzed the differences between AHI and REI. Conventional AHI and REI were calculated based on total sleep time (TST) and total analyzed time (TAT), respectively, from two different PSG datasets (N=1561). Moreover, TAT-based AHI (AHITAT) and TST-based REI (REITST) were calculated. These indices were compared keeping AHI as the gold standard. The REI, AHITAT, and REITST were significantly lower than AHI (p<0.0001, p≤0.002, p≤0.01, respectively). The total classification accuracy of OSA severity based on REI was 42.1% and 72.8% for two datasets. Based on AHITAT the accuracies were 68.4% and 85.9%, and based on REITST they were 65.9% and 88.5% compared to AHI. AHI was most correlated with REITST (r=0.98 and r=0.99 for the datasets) and least with REI (r=0.92 and r=0.97). Compared to AHI, REI had the largest mean absolute error (13.9 and 6.7) and REITST the lowest (5.9 and 1.9). REI had the lowest sensitivity (42.1% and 72.8%) and specificity (80.7% and 90.9%) in both datasets. Based on these present results, REI underestimates AHI. Furthermore, these results indicate that arousal-related hypopneas are an important measure for accurately classifying OSA.
多导睡眠图（PG）通常用于诊断阻塞性睡眠呼吸暂停（OSA）。但是，它不使用脑电图 (EEG)，因此无法估计睡眠时间或对觉醒和相关的低通气进行评分。因此，PG 得出的呼吸事件指数（REI）不同于多导睡眠图（PSG）得出的呼吸暂停-低通气指数（AHI）。本研究全面分析了 AHI 和 REI 之间的差异。 传统的 AHI 和 REI 分别根据两个不同 PSG 数据集（N=1561）中的总睡眠时间（TST）和总分析时间（TAT）计算得出。此外，还计算了基于 TAT 的 AHI（AHITAT）和基于 TST 的 REI（REITST）。将 AHI 作为金标准对这些指数进行了比较。 REI、AHITAT和REITST明显低于AHI（分别为p<0.0001、p≤0.002和p≤0.01）。在两个数据集中，基于 REI 的 OSA 严重程度总分类准确率分别为 42.1%和 72.8%。与 AHI 相比，基于 AHITAT 的准确率分别为 68.4% 和 85.9%，基于 REITST 的准确率分别为 65.9% 和 88.5%。AHI 与 REITST 的相关性最高（数据集的 r=0.98 和 r=0.99），与 REI 的相关性最低（r=0.92 和 r=0.97）。与 AHI 相比，REI 的平均绝对误差最大（13.9 和 6.7），REITST 的平均绝对误差最小（5.9 和 1.9）。在两个数据集中，REI 的灵敏度（42.1% 和 72.8%）和特异性（80.7% 和 90.9%）都最低。 根据这些结果，REI 低估了 AHI。此外，这些结果表明，唤醒相关低通气是对 OSA 进行准确分类的重要指标。
{"title":"Respiratory event index underestimates severity of sleep apnea compared to apnea-hypopnea index","authors":"M. Pitkänen, R. K. Nath, H. Korkalainen, Sami Nikkonen, Alaa Mahamid, A. Oksenberg, B. Duce, Juha Töyräs, S. Kainulainen, T. Leppänen","doi":"10.1093/sleepadvances/zpad054","DOIUrl":"https://doi.org/10.1093/sleepadvances/zpad054","url":null,"abstract":"Polygraphy (PG) is often used to diagnose obstructive sleep apnea (OSA). However, it does not use electroencephalography (EEG), and therefore cannot estimate sleep time or score arousals and related hypopneas. Consequently, the PG-derived respiratory event index (REI) differs from the polysomnography (PSG) derived apnea-hypopnea index (AHI). In this study, we comprehensively analyzed the differences between AHI and REI. Conventional AHI and REI were calculated based on total sleep time (TST) and total analyzed time (TAT), respectively, from two different PSG datasets (N=1561). Moreover, TAT-based AHI (AHITAT) and TST-based REI (REITST) were calculated. These indices were compared keeping AHI as the gold standard. The REI, AHITAT, and REITST were significantly lower than AHI (p<0.0001, p≤0.002, p≤0.01, respectively). The total classification accuracy of OSA severity based on REI was 42.1% and 72.8% for two datasets. Based on AHITAT the accuracies were 68.4% and 85.9%, and based on REITST they were 65.9% and 88.5% compared to AHI. AHI was most correlated with REITST (r=0.98 and r=0.99 for the datasets) and least with REI (r=0.92 and r=0.97). Compared to AHI, REI had the largest mean absolute error (13.9 and 6.7) and REITST the lowest (5.9 and 1.9). REI had the lowest sensitivity (42.1% and 72.8%) and specificity (80.7% and 90.9%) in both datasets. Based on these present results, REI underestimates AHI. Furthermore, these results indicate that arousal-related hypopneas are an important measure for accurately classifying OSA.","PeriodicalId":21861,"journal":{"name":"SLEEP Advances","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-12-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139164431","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 : 2023-12-01DOI: 10.1093/sleepadvances/zpad053
A. Reffi, D. Kalmbach, Philip Cheng, Peter C Tappenden, Jennifer Valentine, Christopher L. Drake, W. Pigeon, Scott M. Pickett, Michelle M Lilly
Fear of sleep contributes to insomnia in some individuals with posttraumatic stress disorder (PTSD) but remains uncharacterized in first responders, a population with high rates of insomnia and PTSD. We evaluated the clinical relevance of fear of sleep in first responders by (1) examining its relationship with trauma types and clinical symptoms and (2) assessing differences in fear of sleep severity between those reporting provisional PTSD, insomnia, or both. A cross-sectional study of 242 first responders across the US (59.2% male, 86.4% White, 56.2% law enforcement officers, 98.7% active duty, Myears of service = 17). Participants completed the Fear of Sleep Inventory – Short Form and measures of trauma history, psychopathology (e.g., PTSD), and sleep disturbances (insomnia and trauma-related nightmares). Fear of sleep was associated with trauma types characterized by interpersonal violence and victimization, as well as symptoms of PTSD, depression, anxiety, stress, alcohol use problems, insomnia, and trauma-related nightmares. Fear of sleep was most pronounced among first responders reporting provisional PTSD comorbid with insomnia compared to those with PTSD or insomnia only. Post hoc analyses revealed PTSD hyperarousal symptoms and trauma-related nightmares were independently associated with fear of sleep, even after adjusting for the remaining PTSD clusters, insomnia, sex, and years of service. Fear of sleep is a clinically relevant construct in first responders that is associated with a broad range of psychopathology symptoms and is most severe among those with co-occurring PTSD and insomnia. Fear of sleep may merit targeted treatment in first responders.
{"title":"Fear of sleep in first responders: Associations with trauma types, psychopathology, and sleep disturbances","authors":"A. Reffi, D. Kalmbach, Philip Cheng, Peter C Tappenden, Jennifer Valentine, Christopher L. Drake, W. Pigeon, Scott M. Pickett, Michelle M Lilly","doi":"10.1093/sleepadvances/zpad053","DOIUrl":"https://doi.org/10.1093/sleepadvances/zpad053","url":null,"abstract":"\u0000 \u0000 \u0000 Fear of sleep contributes to insomnia in some individuals with posttraumatic stress disorder (PTSD) but remains uncharacterized in first responders, a population with high rates of insomnia and PTSD. We evaluated the clinical relevance of fear of sleep in first responders by (1) examining its relationship with trauma types and clinical symptoms and (2) assessing differences in fear of sleep severity between those reporting provisional PTSD, insomnia, or both.\u0000 \u0000 \u0000 \u0000 A cross-sectional study of 242 first responders across the US (59.2% male, 86.4% White, 56.2% law enforcement officers, 98.7% active duty, Myears of service = 17). Participants completed the Fear of Sleep Inventory – Short Form and measures of trauma history, psychopathology (e.g., PTSD), and sleep disturbances (insomnia and trauma-related nightmares).\u0000 \u0000 \u0000 \u0000 Fear of sleep was associated with trauma types characterized by interpersonal violence and victimization, as well as symptoms of PTSD, depression, anxiety, stress, alcohol use problems, insomnia, and trauma-related nightmares. Fear of sleep was most pronounced among first responders reporting provisional PTSD comorbid with insomnia compared to those with PTSD or insomnia only. Post hoc analyses revealed PTSD hyperarousal symptoms and trauma-related nightmares were independently associated with fear of sleep, even after adjusting for the remaining PTSD clusters, insomnia, sex, and years of service.\u0000 \u0000 \u0000 \u0000 Fear of sleep is a clinically relevant construct in first responders that is associated with a broad range of psychopathology symptoms and is most severe among those with co-occurring PTSD and insomnia. Fear of sleep may merit targeted treatment in first responders.\u0000","PeriodicalId":21861,"journal":{"name":"SLEEP Advances","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138618978","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 : 2023-11-14DOI: 10.1093/sleepadvances/zpad047
Ana Vaquer-Alicea, Jinsheng Yu, Haiyan Liu, Brendan P Lucey
Abstract Study objectives Acute sleep deprivation affects both central and peripheral biological processes. Prior research has mainly focused on specific proteins or biological pathways that are dysregulated in the setting of sustained wakefulness. This exploratory study aimed to provide a comprehensive view of the biological processes and proteins impacted by acute sleep deprivation in both plasma and cerebrospinal fluid (CSF). Methods We collected plasma and CSF from human participants during one night of sleep deprivation and control normal sleep conditions. 1300 proteins were measured at hour 0 and hour 24 using a high-scale aptamer-based proteomics platform (SOMAscan) and a systematic biological database tool (Metascape) was used to reveal altered biological pathways. Results Acute sleep deprivation decreased the number of upregulated and downregulated biological pathways and proteins in plasma but increased upregulated and downregulated biological pathways and proteins in CSF. Predominantly affected proteins and pathways were associated with immune response, inflammation, phosphorylation, membrane signaling, cell-cell adhesion, and extracellular matrix organization. Conclusions The identified modifications across biofluids adds to evidence that acute sleep deprivation has important impacts on biological pathways and proteins that can negatively affect human health. As a hypothesis-driving study, these findings may help with the exploration of novel mechanisms that mediate sleep loss and associated conditions, drive the discovery of new sleep loss biomarkers, and ultimately aid in the identification of new targets for intervention to human diseases.
{"title":"Plasma and CSF Proteomic Signatures of Acutely Sleep-Deprived Humans: An Exploratory Study","authors":"Ana Vaquer-Alicea, Jinsheng Yu, Haiyan Liu, Brendan P Lucey","doi":"10.1093/sleepadvances/zpad047","DOIUrl":"https://doi.org/10.1093/sleepadvances/zpad047","url":null,"abstract":"Abstract Study objectives Acute sleep deprivation affects both central and peripheral biological processes. Prior research has mainly focused on specific proteins or biological pathways that are dysregulated in the setting of sustained wakefulness. This exploratory study aimed to provide a comprehensive view of the biological processes and proteins impacted by acute sleep deprivation in both plasma and cerebrospinal fluid (CSF). Methods We collected plasma and CSF from human participants during one night of sleep deprivation and control normal sleep conditions. 1300 proteins were measured at hour 0 and hour 24 using a high-scale aptamer-based proteomics platform (SOMAscan) and a systematic biological database tool (Metascape) was used to reveal altered biological pathways. Results Acute sleep deprivation decreased the number of upregulated and downregulated biological pathways and proteins in plasma but increased upregulated and downregulated biological pathways and proteins in CSF. Predominantly affected proteins and pathways were associated with immune response, inflammation, phosphorylation, membrane signaling, cell-cell adhesion, and extracellular matrix organization. Conclusions The identified modifications across biofluids adds to evidence that acute sleep deprivation has important impacts on biological pathways and proteins that can negatively affect human health. As a hypothesis-driving study, these findings may help with the exploration of novel mechanisms that mediate sleep loss and associated conditions, drive the discovery of new sleep loss biomarkers, and ultimately aid in the identification of new targets for intervention to human diseases.","PeriodicalId":21861,"journal":{"name":"SLEEP Advances","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-11-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134991479","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 : 2023-11-13DOI: 10.1093/sleepadvances/zpad046
Ashley Redding, Sara Santarossa, Chaewon Sagong, David A Kalmbach, Christopher L Drake, Melynda D Casement, Philip Cheng
Abstract Study Objectives To utilize qualitative data analysis to enrich our understanding of the impact of COVID-19 on those with a pre-pandemic history of insomnia. Methods The sample included 208 participants who completed the Coronavirus Impact Scale in April and May 2020. A content analysis was used to analyze responses to a free response item “Please tell us about any other ways the coronavirus has impacted your life” (n = 175), using a combination of inductive and deductive coding. Results Both negative and positive themes emerged, including altered access to health care, negative financial impacts, and various emotions surrounding COVID-19. Some shared “silver linings” such as having more time for physical activity and deepening familial connections. Conclusions This analysis provides novel insight into the shared concerns and lived experiences of those with a history of insomnia. Understanding these unique stressors can enable healthcare professionals to better anticipate the needs of this population, as well as learn to navigate future stressful events.
{"title":"“Life Will Never Be the Same”: A Qualitative Analysis of the Impact of COVID-19 on Adults with a History of Insomnia","authors":"Ashley Redding, Sara Santarossa, Chaewon Sagong, David A Kalmbach, Christopher L Drake, Melynda D Casement, Philip Cheng","doi":"10.1093/sleepadvances/zpad046","DOIUrl":"https://doi.org/10.1093/sleepadvances/zpad046","url":null,"abstract":"Abstract Study Objectives To utilize qualitative data analysis to enrich our understanding of the impact of COVID-19 on those with a pre-pandemic history of insomnia. Methods The sample included 208 participants who completed the Coronavirus Impact Scale in April and May 2020. A content analysis was used to analyze responses to a free response item “Please tell us about any other ways the coronavirus has impacted your life” (n = 175), using a combination of inductive and deductive coding. Results Both negative and positive themes emerged, including altered access to health care, negative financial impacts, and various emotions surrounding COVID-19. Some shared “silver linings” such as having more time for physical activity and deepening familial connections. Conclusions This analysis provides novel insight into the shared concerns and lived experiences of those with a history of insomnia. Understanding these unique stressors can enable healthcare professionals to better anticipate the needs of this population, as well as learn to navigate future stressful events.","PeriodicalId":21861,"journal":{"name":"SLEEP Advances","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-11-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"136281922","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 : 2023-11-11DOI: 10.1093/sleepadvances/zpad045
Nicholas R Gessner, Morteza Peiravi, Fan Zhang, Shemsiya Yimam, Danielle Springer, Susan T Harbison
Abstract Previous studies of natural variants in Drosophila melanogaster implicated the Wnt signaling receptor frizzled in sleep. Given that the Wnt signaling pathway is highly conserved across species, we hypothesized that frizzled class receptor 1 (Fzd1), the murine homolog of frizzled, would also have a role in sleep. Using a CRISPR transgenic approach, we removed most of the Fzd1 coding region from C57BL/6N mice. We used a video assay to measure sleep characteristics in Fzd1-deficient mice. As Wnt signaling is known to affect visuospatial memory, we also examined the impact of the deletion on learning and memory using the Novel Object Recognition (NOR) paradigm. Fzd1-deficient mice had altered sleep compared to littermate controls. The mice did not respond differently to the NOR paradigm compared to controls but did display anxiety-like behavior. Our strategy demonstrates that the study of natural variation in Drosophila sleep translates into candidate genes for sleep in vertebrate species such as the mouse.
{"title":"A conserved role for <i>frizzled</i> in sleep architecture","authors":"Nicholas R Gessner, Morteza Peiravi, Fan Zhang, Shemsiya Yimam, Danielle Springer, Susan T Harbison","doi":"10.1093/sleepadvances/zpad045","DOIUrl":"https://doi.org/10.1093/sleepadvances/zpad045","url":null,"abstract":"Abstract Previous studies of natural variants in Drosophila melanogaster implicated the Wnt signaling receptor frizzled in sleep. Given that the Wnt signaling pathway is highly conserved across species, we hypothesized that frizzled class receptor 1 (Fzd1), the murine homolog of frizzled, would also have a role in sleep. Using a CRISPR transgenic approach, we removed most of the Fzd1 coding region from C57BL/6N mice. We used a video assay to measure sleep characteristics in Fzd1-deficient mice. As Wnt signaling is known to affect visuospatial memory, we also examined the impact of the deletion on learning and memory using the Novel Object Recognition (NOR) paradigm. Fzd1-deficient mice had altered sleep compared to littermate controls. The mice did not respond differently to the NOR paradigm compared to controls but did display anxiety-like behavior. Our strategy demonstrates that the study of natural variation in Drosophila sleep translates into candidate genes for sleep in vertebrate species such as the mouse.","PeriodicalId":21861,"journal":{"name":"SLEEP Advances","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-11-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135086521","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 : 2023-10-31DOI: 10.1093/sleepadvances/zpad042
Karen A Wong, Ankita Paul, Paige Fuentes, Diane C Lim, Anup Das, Miranda Tan
Abstract Background Obstructive sleep apnea (OSA) is a highly prevalent sleep disorder associated with daytime sleepiness, fatigue, and increased all-cause mortality risk in cancer patients. Existing screening tools for OSA do not account for the interaction of cancer-related features that may increase OSA risk. Study Design and Methods This is a retrospective study of cancer patients at a single tertiary cancer institution who underwent home sleep apnea test (HSAT) to evaluate for OSA. Unsupervised machine learning (ML) was used to reduce the dimensions and extract significant features associated with OSA. ML classifiers were applied to principal components and model hyperparameters were optimized using k-fold cross validation. Training models for OSA were subsequently tested and compared with the STOP-Bang questionnaire on a prospective unseen test set of patients who underwent an HSAT. Results From a training dataset of 249 patients, kernel principal component analysis extracted 8 components through dimension reduction to explain the maximum variance with OSA at 98%. Predictors of OSA were smoking, asthma, chronic kidney disease, STOP-Bang score, race, diabetes, radiation to head/neck/thorax (RT-HNT), type of cancer, and cancer metastases. Of the ML models, PCA+RF had the highest sensitivity (96.8%), specificity (92.3%), negative predictive value (92%), F1 score (0.93), and ROC-AUC score (0.88). The PCA+RF screening algorithm also performed better than the STOP-Bang questionnaire alone when tested on a prospective unseen test set. Conclusion The PCA+RF ML model had the highest accuracy in screening for OSA in cancer patients. History of RT-HNT, cancer metastases, and type of cancer were identified as cancer-related risk factors for OSA.
{"title":"Screening for Obstructive Sleep Apnea in Patients with Cancer – a Machine Learning Approach","authors":"Karen A Wong, Ankita Paul, Paige Fuentes, Diane C Lim, Anup Das, Miranda Tan","doi":"10.1093/sleepadvances/zpad042","DOIUrl":"https://doi.org/10.1093/sleepadvances/zpad042","url":null,"abstract":"Abstract Background Obstructive sleep apnea (OSA) is a highly prevalent sleep disorder associated with daytime sleepiness, fatigue, and increased all-cause mortality risk in cancer patients. Existing screening tools for OSA do not account for the interaction of cancer-related features that may increase OSA risk. Study Design and Methods This is a retrospective study of cancer patients at a single tertiary cancer institution who underwent home sleep apnea test (HSAT) to evaluate for OSA. Unsupervised machine learning (ML) was used to reduce the dimensions and extract significant features associated with OSA. ML classifiers were applied to principal components and model hyperparameters were optimized using k-fold cross validation. Training models for OSA were subsequently tested and compared with the STOP-Bang questionnaire on a prospective unseen test set of patients who underwent an HSAT. Results From a training dataset of 249 patients, kernel principal component analysis extracted 8 components through dimension reduction to explain the maximum variance with OSA at 98%. Predictors of OSA were smoking, asthma, chronic kidney disease, STOP-Bang score, race, diabetes, radiation to head/neck/thorax (RT-HNT), type of cancer, and cancer metastases. Of the ML models, PCA+RF had the highest sensitivity (96.8%), specificity (92.3%), negative predictive value (92%), F1 score (0.93), and ROC-AUC score (0.88). The PCA+RF screening algorithm also performed better than the STOP-Bang questionnaire alone when tested on a prospective unseen test set. Conclusion The PCA+RF ML model had the highest accuracy in screening for OSA in cancer patients. History of RT-HNT, cancer metastases, and type of cancer were identified as cancer-related risk factors for OSA.","PeriodicalId":21861,"journal":{"name":"SLEEP Advances","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-10-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135927973","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/zpad035.175
C Gupta, M Duncan, S Ferguson, A Rebar, C Vandelanotte, M Sprajcer, S Khalesi, L Booker, C Rampling, G Rigney, G Vincent
Abstract Background Increasing engagement with sleep, diet, and physical activity (PA) is critical for populations who are at higher risk of poor health, such as shiftworkers. To increase engagement in sleep, diet and PA, it is critical to first understand which of these behaviours Australians currently prioritise and whether this prioritisation relates to actual behaviour. Therefore, this study aimed to investigate how Australians prioritise sleep, diet and PA. Methods A cohort of 1151 Australian adults (54% female, aged 18-65 years) completed a phone interview, and a cohort of 588 Australian shiftwork-only adults (76% female, 18-72 years) completed an online survey. All participants were asked which health behaviour (sleep, diet or PA) they prioritised. Behavioural correlates of sleep, diet, and PA, and questions on shiftwork experience were also collected. Results Diet was prioritised by the adults (49%), whereas sleep was prioritised by the shiftwork-only sample (68%). Multinomial logistic regressions revealed that adults who prioritised diet were significantly more likely to report less fast-food consumption (p<0.002) and more fruit consumption (p<0.002) compared to those that prioritised sleep. For the shiftwork-only sample, those with 16-30 years of shiftwork experience were significantly more likely to prioritise sleep compared to diet (p<0.05). Conclusions While prioritising diet was associated with healthier diet behaviour in Australian adults, overall, across both cohorts, behaviour prioritisation did not relate to actual behaviour. This suggests that there are factors other than behaviour prioritisation that influence engagement in healthy behaviours. These factors, such as workplace barriers, should be the focus of future research.
{"title":"P090 How do Australian Shiftworkers and Non-Shiftworkers Prioritise Sleep, Diet, and Physical activity?","authors":"C Gupta, M Duncan, S Ferguson, A Rebar, C Vandelanotte, M Sprajcer, S Khalesi, L Booker, C Rampling, G Rigney, G Vincent","doi":"10.1093/sleepadvances/zpad035.175","DOIUrl":"https://doi.org/10.1093/sleepadvances/zpad035.175","url":null,"abstract":"Abstract Background Increasing engagement with sleep, diet, and physical activity (PA) is critical for populations who are at higher risk of poor health, such as shiftworkers. To increase engagement in sleep, diet and PA, it is critical to first understand which of these behaviours Australians currently prioritise and whether this prioritisation relates to actual behaviour. Therefore, this study aimed to investigate how Australians prioritise sleep, diet and PA. Methods A cohort of 1151 Australian adults (54% female, aged 18-65 years) completed a phone interview, and a cohort of 588 Australian shiftwork-only adults (76% female, 18-72 years) completed an online survey. All participants were asked which health behaviour (sleep, diet or PA) they prioritised. Behavioural correlates of sleep, diet, and PA, and questions on shiftwork experience were also collected. Results Diet was prioritised by the adults (49%), whereas sleep was prioritised by the shiftwork-only sample (68%). Multinomial logistic regressions revealed that adults who prioritised diet were significantly more likely to report less fast-food consumption (p&lt;0.002) and more fruit consumption (p&lt;0.002) compared to those that prioritised sleep. For the shiftwork-only sample, those with 16-30 years of shiftwork experience were significantly more likely to prioritise sleep compared to diet (p&lt;0.05). Conclusions While prioritising diet was associated with healthier diet behaviour in Australian adults, overall, across both cohorts, behaviour prioritisation did not relate to actual behaviour. This suggests that there are factors other than behaviour prioritisation that influence engagement in healthy behaviours. These factors, such as workplace barriers, should be the focus of future research.","PeriodicalId":21861,"journal":{"name":"SLEEP Advances","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"136052641","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/zpad035.019
M Shetty, B Tan, M Davey, G Nixon, L Walter, R Horne
Abstract Background Children with Down syndrome (DS) are at increased risk of sleep disordered breathing (SDB), which is associated with sleep disruption affecting daytime functioning. There is growing evidence that sleep spindles may serve as a sensitive marker of sleep quality. We investigated sleep spindle activity and its relationship with daytime functioning in children with DS compared to typically developing (TD) children matched for SDB severity. Methods Children with DS and SDB (n=44) and TD children matched for age, sex and SDB severity underwent overnight polysomnography. Fast or Slow sleep spindles were identified manually during N2 and N3 sleep. Spindle activity was characterised as spindle number, density (number of spindles/h) and intensity (density x average duration) on central (C) and frontal (F) electrodes. Parents completed the Child Behavior Checklist (CBCL) and OSA-18 questionnaires. Results Spindle number, density, and intensity were lower in the children with DS compared to TD children for F Slow and F Slow&Fast spindles combined (p<0.001 for all). In children with DS, there were no correlations between the density of any spindle type and subscales of the CBCL, however, spindle number, density and intensity for C Fast and C Slow&Fast were negatively correlated with OSA-18 emotional symptoms and caregiver concerns and C Fast number, density and intensity were also negatively correlated with daytime function and total problems. Conclusions The reduced spindle activity in the children with DS, indicates sleep micro-architecture is disrupted and this disruption may underpin the negative effects of SDB on quality of life and behaviour.
{"title":"O019 Sleep spindles are reduced in children with Down syndrome and sleep disordered breathing","authors":"M Shetty, B Tan, M Davey, G Nixon, L Walter, R Horne","doi":"10.1093/sleepadvances/zpad035.019","DOIUrl":"https://doi.org/10.1093/sleepadvances/zpad035.019","url":null,"abstract":"Abstract Background Children with Down syndrome (DS) are at increased risk of sleep disordered breathing (SDB), which is associated with sleep disruption affecting daytime functioning. There is growing evidence that sleep spindles may serve as a sensitive marker of sleep quality. We investigated sleep spindle activity and its relationship with daytime functioning in children with DS compared to typically developing (TD) children matched for SDB severity. Methods Children with DS and SDB (n=44) and TD children matched for age, sex and SDB severity underwent overnight polysomnography. Fast or Slow sleep spindles were identified manually during N2 and N3 sleep. Spindle activity was characterised as spindle number, density (number of spindles/h) and intensity (density x average duration) on central (C) and frontal (F) electrodes. Parents completed the Child Behavior Checklist (CBCL) and OSA-18 questionnaires. Results Spindle number, density, and intensity were lower in the children with DS compared to TD children for F Slow and F Slow&Fast spindles combined (p&lt;0.001 for all). In children with DS, there were no correlations between the density of any spindle type and subscales of the CBCL, however, spindle number, density and intensity for C Fast and C Slow&Fast were negatively correlated with OSA-18 emotional symptoms and caregiver concerns and C Fast number, density and intensity were also negatively correlated with daytime function and total problems. Conclusions The reduced spindle activity in the children with DS, indicates sleep micro-architecture is disrupted and this disruption may underpin the negative effects of SDB on quality of life and behaviour.","PeriodicalId":21861,"journal":{"name":"SLEEP Advances","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"136053885","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/zpad035.170
G Desalegn, G Rawson, Y Melaku, Z Abitew, P Eastwood, A Reynolds
Abstract Background By middle-age, 43% of Australian adults live with a clinical sleep disorder. Sleep disorders are linked to chronic illnesses which are a leading cause of premature mortality. The aim of this review was to identify, appraise and synthesise evidence from longitudinal observational studies to clarify childhood and adolescence risk factors associated with sleep disorders in adulthood. Method Four databases (Web of Science, Medline, SCOPUS, and PSYCINFO) were searched using predefined inclusion and exclusion criteria for studies which were longitudinal, including at least one risk factor measured before 18 years of age, and an assessment of sleep problems or disorders in adulthood. This study was registered with PROSPERO (CRD42022301342). Result A total of 13,712 studies were screened, with 51 studies meeting criteria for data extraction. Sleep problems in childhood (n=9), childhood mental health (n=7), family environment (n= 2), adverse childhood experience (n=5), and lifestyle factors (n=9) were reported to be associated with sleep problems in adulthood. However most studies (n=30) only considered one or two measurements time points in childhood or adolescence as a predictor of adult sleep problems, and the age of sleep problem measurement in adulthood varied considerably (18 – 42 years). Further, heterogeneous sleep outcomes were reported across the studies, making quantitative synthesis of the data extremely challenging. Discussion Sleep problems in adulthood may be a result of cumulative risk factors in early childhood and adolescence. Consideration of childhood and adolescent trajectories are needed to better understand the biopsychosocial predictors of sleep problems in adulthood.
到中年时，43%的澳大利亚成年人患有临床睡眠障碍。睡眠障碍与慢性疾病有关，而慢性疾病是导致过早死亡的主要原因。本综述的目的是识别、评估和综合来自纵向观察研究的证据，以澄清儿童期和青春期与成年期睡眠障碍相关的风险因素。方法对Web of Science、Medline、SCOPUS和PSYCINFO四个数据库进行检索，采用预先确定的纵向研究纳入和排除标准，包括18岁之前测量的至少一个风险因素，以及成年期睡眠问题或障碍的评估。本研究已在PROSPERO注册(CRD42022301342)。结果共筛选13712项研究，其中51项研究符合资料提取标准。据报道，儿童时期的睡眠问题(n=9)、儿童时期的心理健康(n=7)、家庭环境(n= 2)、不良的童年经历(n=5)和生活方式因素(n=9)与成年期睡眠问题有关。然而，大多数研究(n=30)只考虑童年或青春期的一两个测量时间点作为成年睡眠问题的预测因素，并且成年期睡眠问题测量的年龄差异很大(18 - 42岁)。此外，这些研究报告的睡眠结果各不相同，这使得数据的定量合成极具挑战性。成年期的睡眠问题可能是儿童早期和青春期累积风险因素的结果。需要考虑童年和青少年的轨迹，以更好地理解成年期睡眠问题的生物心理社会预测因素。
{"title":"P085 Early Childhood and Adolescent Predictors of Sleep Problems and Sleep Disorders in Adulthood: A Systematic Review of Longitudinal Observational Studies","authors":"G Desalegn, G Rawson, Y Melaku, Z Abitew, P Eastwood, A Reynolds","doi":"10.1093/sleepadvances/zpad035.170","DOIUrl":"https://doi.org/10.1093/sleepadvances/zpad035.170","url":null,"abstract":"Abstract Background By middle-age, 43% of Australian adults live with a clinical sleep disorder. Sleep disorders are linked to chronic illnesses which are a leading cause of premature mortality. The aim of this review was to identify, appraise and synthesise evidence from longitudinal observational studies to clarify childhood and adolescence risk factors associated with sleep disorders in adulthood. Method Four databases (Web of Science, Medline, SCOPUS, and PSYCINFO) were searched using predefined inclusion and exclusion criteria for studies which were longitudinal, including at least one risk factor measured before 18 years of age, and an assessment of sleep problems or disorders in adulthood. This study was registered with PROSPERO (CRD42022301342). Result A total of 13,712 studies were screened, with 51 studies meeting criteria for data extraction. Sleep problems in childhood (n=9), childhood mental health (n=7), family environment (n= 2), adverse childhood experience (n=5), and lifestyle factors (n=9) were reported to be associated with sleep problems in adulthood. However most studies (n=30) only considered one or two measurements time points in childhood or adolescence as a predictor of adult sleep problems, and the age of sleep problem measurement in adulthood varied considerably (18 – 42 years). Further, heterogeneous sleep outcomes were reported across the studies, making quantitative synthesis of the data extremely challenging. Discussion Sleep problems in adulthood may be a result of cumulative risk factors in early childhood and adolescence. Consideration of childhood and adolescent trajectories are needed to better understand the biopsychosocial predictors of sleep problems in adulthood.","PeriodicalId":21861,"journal":{"name":"SLEEP Advances","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"136054062","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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