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Author: Grafiati

Published: 10 December 2022

Last updated: 29 January 2023

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1

Thomas, Simone, Kate Lycett, Nicole Papadopoulos, Emma Sciberras, and Nicole Rinehart. "Exploring Behavioral Sleep Problems in Children With ADHD and Comorbid Autism Spectrum Disorder." Journal of Attention Disorders 22, no. 10 (December 4, 2015): 947–58. http://dx.doi.org/10.1177/1087054715613439.

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Objective: This study (a) compared behavioral sleep problems in children with comorbid ADHD and autism spectrum disorder (ASD) with those with ADHD and (b) examined child/family factors associated with sleep problems. Method: Cross-sectional study comparison of 392 children with a confirmed ADHD diagnosis (ADHD+ASD, n=93, ADHD, n=299) recruited from 21 peadiatric practises in Victoria, Australia. Data were collected from parents. Key measures included the Child Sleep Habits Questionnaire (CSHQ). Results: Children with ADHD + ASD experienced similar levels and types of behavioral sleep problems compared with those with ADHD. In both groups, the presence of co-occurring internalizing and externalizing comorbidities was associated with sleep problems. Sleep problems were also associated with parent age in the ADHD + ASD group and poorer parent mental health in the ADHD group. Conclusion: Findings suggest comorbid ASD is not associated with increased behavioral sleep problems in children with ADHD and that co-occurring internalizing and externalizing comorbidities may flag children in these groups with sleep problems.

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Garrido-Cumbrera, M., V. Navarro-Compán, L. Christen, C. Bundy, R. Mahapatra, S. Makri, C. J. Delgado-Domínguez, J. Correa-Fernández, and D. Poddubnyy. "POS0961 PREVALENCE AND ASSOCIATED FACTORS OF SLEEP DISORDERS IN PATIENTS WITH AXIAL SPONDYLOARTHRITIS. RESULTS FROM THE EUROPEAN MAP OF AXIAL SPONDYLOARTHRITIS (EMAS)." Annals of the Rheumatic Diseases 80, Suppl 1 (May 19, 2021): 745. http://dx.doi.org/10.1136/annrheumdis-2021-eular.981.

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Background:Sleep is an essential health aspect that is often impacted in patients with axial spondyloarthritis (axSpA).Objectives:This analysis aims to assess the prevalence and associated factors of sleep disorders in a large sample of European axSpA patients.Methods:Data were analyzed from 2,846 unselected patients with self-reported clinician-given diagnosis of axSpA of the European Map of Axial Spondyloarthritis (EMAS) through an online survey (2017-2018) across 13 European countries. Socio-demographic data; BASDAI [0-10] scores; engagement in physical activity; axSpA influence on work choice (assessed with yes/no question “Was your current or past work choice in any way determined by axSpA?”); risk of psychological distress (12-item General Health Questionnaire [GHQ-12; 0-12]); functional limitation [0-54] and self-reported anxiety and depression were evaluated. Presence of sleep disorders was assessed by the question: “Please indicate whether you have been diagnosed with any of the following: sleep disorders”. A Mann-Whitney test was used to compare the means of numerical variables between dichotomous variables, the Chi-Square test was used to compare the distribution between the categorical variables. Simple and multivariable logistic regression models were used to identify associations between sleep disorders and disease characteristics, mental health and work-related variables.Results:Age of respondents was 43.9 years; 61.3% were female; 48.1% had a university degree; 67.9% were married and 71.3% were HLA-B27 positive. The prevalence of sleep disorders was 39.0%. In the bivariate analysis, presence of sleep disorders was associated with female gender (68.3% vs. 31.7%; p<0.001); overweight/obese (56.5% vs. 49.8%; p<0.001); increased BASDAI scores (6.1±1.8 vs. 5.0±2.1; p<0.001); fatigue (7.0±2.0 vs. 5.8±2.4; p<0.001); morning stiffness (5.8±2.4 vs. 4.8±2.4; p<0.001), work impact (56.5% vs. 38.2%; p< 0.001); anxiety (56.8% vs. 12.5%; p<0.001); depression (51.8% vs. 10.1%; p<0.001) and higher GHQ-12 scores (6.4±4.0 vs. 3.9±3.9; p<0.001). However, factors that remained independently associated with sleep disorders in the multivariable analysis were anxiety (OR=3.8 p<0.001) and depression (OR=3.1 p<0.001) and female gender (OR=1.4; p=0.002) [Table 1].Table 1.Regression analysis to predict presence of sleep disorders (N=2191)Simple logistic regressionMultivariable logistic regressionOR95% CIp-valueOR95% CIp-valueGender (female)1.591.36-1.87<0.0011.401.13-1.730.002Marital status (married)1.130.99-1.280.074NANANAOverweight/Obesity1.311.12-1.530.0011.391.14-1.710.001BASDAI (0-10)1.331.27-1.39<0.0011.070.95-1.210.246Fatigue/Tiredness (0-10)*1.281.23-1.33<0.0011.040.97-1.120.271Morning Stiffness intensity (0-10)*1.191.15-1.23<0.0011.050.98-1.130.188Reported Work impact (yes)2.101.78-2.48<0.0011.291.05-1.580.015Anxiety (yes)9.187.58-11.11<0.0013.842.99-4.94<0.001Depression (yes)9.537.78-11.66<0.0013.092.37-4.02<0.001GHQ-12 (0-12)**1.161.14-1.19<0.0011.031.00-1.060.029*As measured by the respective item of the BASDAI scale.**12-item General Health Questionnaire. A value of 3 or above indicates a risk of poor mental health.Conclusion:Sleep disorders were highly prevalent among axSpA European patients and strongly associated with female gender and reporting worse mental health, and spinal stiffness. Patients on permanent and temporary sick leave were more likely to report sleep disorders. The strong association between sleep disorders with both anxiety and depression should encourage rheumatologists to screen their patients with sleep disturbance in case they require additional specialist support.Acknowledgements:This study was supported by Novartis Pharma AG. The authors would like to thank all patients who participated in the study.Disclosure of Interests:Marco Garrido-Cumbrera: None declared, Victoria Navarro-Compán Grant/research support from: Abbvie, BMS, Lilly, MSD, Novartis, Pfizer, Roche, and UCB., Laura Christen Employee of: Novartis Pharma AG, Christine Bundy Speakers bureau: Abbvie, Celgene, Janssen, Lilly, Novartis, and Pfizer, Raj Mahapatra: None declared, Souzi Makri: None declared, Carlos Jesús Delgado-Domínguez: None declared, José Correa-Fernández: None declared, Denis Poddubnyy Speakers bureau: Abbvie, BMS, Celgene, Janssen, Lilly, MSD, Novartis, Pfizer, Roche, and UCB, Grant/research support from: Abbvie, MSD, Novartis, and Pfizer.

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Papadopoulos, Nicole, Emma Sciberras, Harriet Hiscock, Katrina Williams, Jane McGillivray, Cathrine Mihalopoulos, Lidia Engel, et al. "Sleeping sound with autism spectrum disorder (ASD): study protocol for an efficacy randomised controlled trial of a tailored brief behavioural sleep intervention for ASD." BMJ Open 9, no. 11 (November 2019): e029767. http://dx.doi.org/10.1136/bmjopen-2019-029767.

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IntroductionSleep problems are a characteristic feature of children with autism spectrum disorder (ASD) with 40% to 80% of children experiencing sleep difficulties. Sleep problems have been found to have a pervasive impact on a child’s socio-emotional functioning, as well as on parents’ psychological functioning. The Sleeping Sound ASD project aims to evaluate the efficacy of a brief behavioural sleep intervention in reducing ASD children’s sleep problems in a fully powered randomised controlled trial (RCT). Intervention impact on child and family functioning is also assessed.Methods and analysisThe RCT aims to recruit 234 children with a diagnosis of ASD, aged 5–13 years, who experience moderate to severe sleep problems. Participants are recruited from paediatrician clinics in Victoria, Australia, and via social media. Families interested in the study are screened for eligibility via phone, and then asked to complete a baseline survey online, assessing child sleep problems, and child and family functioning. Participants are then randomised to the intervention group or treatment as usual comparator group. Families in the intervention group attend two face-to-face sessions and a follow-up phone call with a trained clinician, where families are provided with individually tailored behavioural sleep strategies to help manage the child’s sleep problems. Teacher reports of sleep, behavioural and social functioning are collected, and cognitive ability assessed to provide measures blind to treatment group. The primary outcome is children’s sleep problems as measured by the Children’s Sleep Habits Questionnaire at 3 months post-randomisation. Secondary outcomes include parent and child quality of life; child social, emotional, behavioural and cognitive functioning; and parenting stress and parent mental health. Cost-effectiveness of the intervention is also evaluated.Ethics and disseminationFindings from this study will be published in peer-reviewed journals and disseminated at national and international conferences, local networks and online.Trial registration numberISRCTN14077107 (ISRCTN registry dated on 3 March 2017).

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Garrido-Cumbrera, M., V. Navarro-Compán, C. Bundy, L. Christen, R. Mahapatra, S. Makri, C. J. Delgado-Domínguez, J. Correa-Fernández, P. Plazuelo-Ramos, and D. Poddubnyy. "POS0988 FACTORS ASSOCIATED WITH PAIN INTENSITY IN AXIAL SPONDYLOARTHRITIS. RESULTS FROM THE EUROPEAN MAP OF AXIAL SPONDYLOARTHRITIS (EMAS)." Annals of the Rheumatic Diseases 80, Suppl 1 (May 19, 2021): 762.1–762. http://dx.doi.org/10.1136/annrheumdis-2021-eular.2439.

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Background:Pain is a hallmark of axial spondyloarthritis (axSpA) and can significantly deteriorate patients’ health status.Objectives:This analysis aims to investigate factors associated with pain intensity in a large sample of European axSpA patients.Methods:2,846 unselected patients participated in EMAS, a cross-sectional study (2017-2018) across 13 European countries. Data from 2,636 participants who reported pain were analysed. Pain was measured by the mean of two BASDAI questions (range 0 “no pain” to 10 “most severe pain”): “How would you describe the overall level of AS neck, back or hip pain you have had?” and “How would you describe the overall level of pain/swelling in joints other than neck, back, hips you have had?”. Linear regression analysis was applied to identify associations between pain intensity and sociodemographic factors, patient-reported outcomes [BASDAI (0-10), spinal stiffness (3-12), functional limitation (0-54), mental health using the 12-item General Health Questionnaire GHQ-12 (0-12)], work life, physical activity and comorbidities, for which 850 patients were included.Results:The mean age of the sample was 44 years, 61.4% were female, 49.4% had a university degree and 67.7% were married. The average reported pain intensity was 5.3 (±2.2); 76.2% reported pain intensity ≥4, with the greatest intensity reported by women (5.5 vs 4.9, p<0.001), those not university educated (5.6 vs 5.0, p<0.001), separated or divorced compared to singles (5.8 vs 5.2, p=0.004), and not physically active (5.7 vs 5.2, p<0.001). In addition, employed patients who experienced work-related issues reported greater pain (5.2 vs 3.9) as did those who experienced/ believed they would face difficulties finding work due to axSpA (5.9 vs 4.3), and those whose employment choice was determined by axSpA (5.7 vs 4.9; all p<0.001). Moreover, associations with anxiety (5.9 vs 5.0), depression (6.1 vs 5.0) and sleep disorders (5.9 vs 4.9; all p<0.001) were also found. The multiple linear regression model showed that those with higher pain intensity reported at least one work-related issue (B=0.65), difficulties finding work due to axSpA (B=0.48), not having attended university (B=0.38), greater spinal stiffness (B= 0.29), being female (B=0.26) and poorer mental health (GHQ-12) (B=0.10) (Table 1).Table 1.Regression analysis of the variables associated with pain intensity (0-10 NRS), n=850UnivariableMultivariableB95% CIB95% CIGender. Female10.6040.432, 0.7750.2600.003, 0.517Educational level. No University20.6710.504, 0.8380.3760.118,0.634Marital Status. Divorced/Separated30.4950.209, 0.780-0.044-0.468, 0.380Body Mass Index. Obese40.362-0.097, 0.821NANAGHQ-12 (0-12)0.1820.163, 0.2010.1000.064, 0.137Functional Limitation (0-54)0.0360.030, 0.0410.009-0.001, 0.018Spinal Stiffness (3-12)0.3570.326, 0.3880.2880.234, 0.342Diagnostic Delay, years0.0200.010, 0.030-0.015-0.032, 0.002Work-Related Issues. Yes1.3381.095, 1.5820.6540.338, 0.970Difficulty finding job due to axSpA. Yes1.5681.362, 1.7740.4760.176, 0.776Work choice determinate by axSpA. Yes0.8080.633, 0.9830.199-0.069, 0.467Physical activity. No0.4940.263, 0.725-0.128-0.497, 0.242Anxiety diagnosis. Yes0.9350.753, 1.117-0.047-0.416, 0.321Depression diagnosis. Yes1.1070.919, 1.2950.115-0.270, 0.500Sleep disorder diagnosis. Yes1.0420.871, 1.213-0.091-0.392, 0.2111Female vs Male; 2No university studies (no schooling, primary and high school) vs University studies; 3Divorced/separated vs single, married and widow; 4Obese vs not obese (underweight, normal and overweight).Conclusion:Pain was most strongly associated with working life impairment, as well as with spinal stiffness. Pain was also associated with suffering from depression, anxiety and sleep disorders. Understanding how pain affects individuals and shared-decision making between rheumatologists and patients are essential for long-term disease management and preserving quality of life of axSpA patients.Acknowledgements:This study was supported by Novartis Pharma AG. The authors would like to thank all patients who participated in the EMAS study.Disclosure of Interests:Marco Garrido-Cumbrera: None declared, Victoria Navarro-Compán Grant/research support from: Abbvie, BMS, Lilly, MSD, Novartis, Pfizer, Roche, and UCB, Christine Bundy Consultant of: Abbvie, Celgene, Janssen, Lilly, Novartis, and Pfizer, Laura Christen Employee of: Novartis Pharma AG, Raj Mahapatra: None declared, Souzi Makri: None declared, Carlos Jesús Delgado-Domínguez: None declared, José Correa-Fernández: None declared, Pedro Plazuelo-Ramos: None declared, Denis Poddubnyy Consultant of: Abbvie, BMS, Celgene, Janssen, Lilly, MSD, Novartis, Pfizer, Roche, and UCB, Grant/research support from: Abbvie, MSD, Novartis, and Pfizer.

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Garrido-Cumbrera, M., C. Bundy, V. Navarro-Compán, L. Christen, R. Mahapatra, S. Makri, C. J. Delgado-Domínguez, D. Gálvez-Ruiz, P. Plazuelo-Ramos, and D. Poddubnyy. "POS0989 FACTORS ASSOCIATED WITH INABILITY TO WORK AND DISABILITY IN PATIENTS WITH AXIAL SPONDYLOARTHRITIS. RESULTS FROM THE EUROPEAN MAP OF AXIAL SPONDYLOARTHRITIS (EMAS)." Annals of the Rheumatic Diseases 80, Suppl 1 (May 19, 2021): 762.2–763. http://dx.doi.org/10.1136/annrheumdis-2021-eular.2450.

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Background:Axial spondyloarthritis (axSpA) is associated with a high burden of disease, which may lead to inability to work and disability.Objectives:This analysis aims to identify factors associated with inability to work and disability among European axSpA patients.Methods:Data from 2,846 unselected patients participating in EMAS, a cross-sectional study (2017-2018) across 13 European countries were analysed. The sample was divided into those on permanent sick leave or with a recognised disability (Group 1) and those with neither permanent sick leave nor a recognized disability (Group 2). Mann-Whitney and Pearson’s χ2 tests were used to analyse possible differences between groups regarding sociodemographic characteristics, patient-reported outcomes [BASDAI (0-10), GHQ-12 (0-12), functional limitation (0-54) and spinal stiffness (3-12)], lifestyle habits, working life, and comorbidities). Univariable and multivariable binary logistic regression were used to analyse variables possibly explaining being on permanent sick leave and disability, for which 1,657 patients were included.Results:Mean age was 43.9 years, 61.3% were female, 48.1% had a university degree, and 67.9% were married. Patients in Group 1 (34.4%; n=978) were more likely to be women (54.3%), married (71.1%), with higher disease activity (BASDAI 5.9 vs. 5.3), functional limitation (25.1 vs. 18.0), spinal stiffness (8.6 vs. 7.3; all p<0.001), and longer diagnostic delay (8.1 vs 7.1 years; p = 0.01) than those in Group 2 (65.6%; n=1,868). In addition, 88.0% of Group 1 (n=728) had difficulties in finding a job due to axSpA throughout life; and more than 30.0% reported a diagnosis of anxiety, depression, or sleep disorders. Moreover, being in Group 1 was associated with higher functional limitation in all daily activities. In the multivariable binary logistic regression, the qualitative variables associated with permanent sick leave or disability were: difficulties finding work (OR= 2.52), belonging to a patient organisation (OR= 1.54) and work choice determined by axSpA (OR= 1.38). The quantitative variables associated with permanent sick leave or disability were: higher spinal stiffness (OR= 1.09), older age (OR= 1.03), longer disease duration (OR= 1.03), shorter diagnostic delay (OR= 0.98), and higher functional limitation (OR= 1.01) (Table 1).Table 1.Regression analysis for variables explaining being on permanent sick leave or disability (n=1,657)Univariable logistic analysisMultivariable logistic analysisQualitative variablesOR95% CI3OR95% CI3Gender11.571.34, 1.831.240.97, 1.57Educational level21.711.46, 2.001.080.86, 1.35Member of a patient organisation. Yes1.961.67, 2.291.541.23, 1.94Smoking. Yes1.281.08, 1.511.220.96, 1.55Difficulty finding job due to axSpA. Yes3.712.89, 4.772.521.83, 3.47Work choice determined by axSpA. Yes1.691.43, 1.991.381.09, 1.75Anxiety diagnosis. Yes1.271.07, 1.510.980.72, 1.34Depression diagnosis. Yes1.581.33, 1.891.250.92, 1.69Sleep disorder diagnosis. Yes1.331.13, 1.560.950.73, 1.23Quantitative variablesOR95% CI3OR95% CI3Age. Years1.041.03, 1.041.031.01, 1.04BASDAI (0-10)1.181.13, 1.241.060.98, 1.13Functional limitation (0-54)1.031.02, 1.031.011.00, 1.02Spinal stiffness (3-12)1.251.20, 1.291.091.03, 1.15Diagnostic delay1.011.01, 1.020.980.96, 0.99Disease duration1.041.03, 1.051.031.01, 1.041Male vs Female; 2No university studies vs university studies. 395% CI for test H0: OR=1Conclusion:One third of patients reported being on permanent sick leave or having a recognised disability. They were more likely to have higher spinal stiffness scores, were older in age, experiencing difficulty finding a job, and belonged to a patient organisation. Increased efforts in relation to early access to effective treatments and the creation of flexible working environments are essential for axSpA patients to continue working and remain active, which benefits their quality of life.Acknowledgements:This study was supported by Novartis Pharma AG.The authors would like to thank all patients who participated in this study.Disclosure of Interests:Marco Garrido-Cumbrera: None declared, Christine Bundy Consultant of: Abbvie, Celgene, Janssen, Lilly, Novartis, and Pfizer, Victoria Navarro-Compán Grant/research support from: Abbvie, BMS, Lilly, MSD, Novartis, Pfizer, Roche, and UCB, Laura Christen Employee of: Novartis Pharma AG, Raj Mahapatra: None declared, Souzi Makri: None declared, Carlos Jesús Delgado-Domínguez: None declared, David Gálvez-Ruiz: None declared, Pedro Plazuelo-Ramos: None declared, Denis Poddubnyy Consultant of: Abbvie, BMS, Celgene, Janssen, Lilly, MSD, Novartis, Pfizer, Roche, and UCB, Grant/research support from: Abbvie, MSD, Novartis, and Pfizer.

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CARTWRIGHT, ROSALIND D. "Sleep Disorders: Diagnosis and Treatment." American Journal of Psychiatry 156, no. 3 (March 1, 1999): 493. http://dx.doi.org/10.1176/ajp.156.3.493.

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Liebman, Albert. "Sleep Disorders: Diagnosis and Treatment." Annals of Internal Medicine 129, no. 9 (November 1, 1998): 759. http://dx.doi.org/10.7326/0003-4819-129-9-199811010-00046.

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STORES, G. "Sleep Disorders: Diagnosis and Treatment." Archives of Disease in Childhood 79, no. 4 (October 1, 1998): 380. http://dx.doi.org/10.1136/adc.79.4.380b.

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SHNEERSON, J. "Sleep Disorders: Diagnosis and Treatment." Journal of Neurology, Neurosurgery & Psychiatry 66, no. 1 (January 1, 1999): 123–24. http://dx.doi.org/10.1136/jnnp.66.1.123.

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Herman, J. H. "Sleep Disorders: Diagnosis and Treatment." Archives of Neurology 56, no. 1 (January 1, 1999): 121–22. http://dx.doi.org/10.1001/archneur.56.1.121.

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Rosen, Dennis. "Sleep Disorders: Diagnosis and Therapeutics." JAMA 303, no. 15 (April 21, 2010): 1541. http://dx.doi.org/10.1001/jama.2010.467.

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Labar, Douglas. "Sleep Disorders and Epilepsy: Differential Diagnosis." Seminars in Neurology 11, no. 02 (June 1991): 128–34. http://dx.doi.org/10.1055/s-2008-1041214.

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Martins-Da-Silva, A., J. Ramalheira, L. Silva, D. Cunha, S. Brás, and C. Carvalho. "Sleep disorders diagnosis by genetic assessment." Sleep Medicine 14 (December 2013): e268. http://dx.doi.org/10.1016/j.sleep.2013.11.652.

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YAMAKAWA, Koji. "Diagnosis of Obstructive Sleep Respiratory Disorders." Practica Oto-Rhino-Laryngologica 89, no. 5 (1996): 637–44. http://dx.doi.org/10.5631/jibirin.89.637.

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Garrido-Cumbrera, M., J. Gratacos-Masmitja, E. Collantes-Estevez, P. Zarco-Montejo, C. Sastré, S. Sanz-Gómez, P. Plazuelo-Ramos, and V. Navarro-Compán. "POS0991 THE IMPACT OF AXIAL SPONDYLOARTHRITIS ON PATIENTS’ SEXUAL LIFE: RESULTS FROM THE SPANISH ATLAS." Annals of the Rheumatic Diseases 80, Suppl 1 (May 19, 2021): 763.2–764. http://dx.doi.org/10.1136/annrheumdis-2021-eular.2491.

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Background:Axial Spondyloarthritis (axSpA) can impact patients’ sexual life.Objectives:The aim is to assess the prevalence of functional limitation in sexual activity in axSpA patients in Spain and its associated factors.Methods:Data from an online survey of 680 unselected axSpA patients pertaining to the Atlas of Axial Spondyloarthritis in Spain were collected. Functional limitation in intimate relations was assessed through a 3-point Likert scale (low, medium, and high) and the sample was divided into 1) low-medium and 2) high. Mann-Whitney and χ2 tests were used to analyse relations between sociodemographic, employment, lifestyle, patient-reported outcomes, and comorbidities with respect to functional limitation in intimate relations. Univariate and multivariate binary logistic regression was used to analyse its associated factors.Results:605 axSpA patients were included: the mean age was 45.5 years, 51.4% were female, 38.3% had a university degree, and 70.7% were married. A total of 57.7%, 28.9%, and 13.4% participants presented high, medium, and low limitation in intimate relations, respectively. Patient with high functional limitation in intimate relations were younger (44.6 vs 46.7, p=0.032), female (67.2% vs 47.6% of male, p<0.001), did not belong to a patient organisation (62.7% vs 51.5% of members, p=0.006), were on sick leave (73.3% vs 51.9% of employed, p<0.001) and smoked more (67.3% vs 52.6%, p<0.001). The high limitation group presented higher disease activity (6.3 vs 4.9), functional limitation (48.2 vs 34.4) and spinal stiffness (7.9 vs 6.9, all p<0.001), worse mental health (7.0 vs 4.1, p<0.001), longer diagnostic delay (9.2 vs 7.6, p=0.019), and more comorbidities such as anxiety (73.3% vs 53.2%), depression (80.0% vs 53.3%) and sleep disorders (70.9% vs 53.9%, all p<0.001). In addition, 80.3% of patients with decreased frequency of intimate relations presented high functional limitation in intimate relations (vs 10.0% with more frequency) and 81.4% had experienced a worsening relationship with their spouse (vs 55.6% with better relation, all p<0.001). In the multivariate binary logistic regression, the qualitative factors associated with high functional limitation in intimate relations were a reduction in the frequency of intimate relations (OR= 18.66) and smoking (OR= 2.89), while the quantitative factor associated with high functional limitation in the intimate relation was higher overall functional limitation (B= 0.292; Table 1).Table 1.Logistic regression to analyse factor associated with high functional limitation in intimate relation (N= 302)Univariate logistic analysisMultivariate logistic analysisORp-value1ORp-value1Qualitative factorsGender. Female2.254<0.0011.3110.569Patient Organization. Member0.6320.0060.5150.171Employment. Sick leave2.354<0.0011.0600.910Smoking. Yes1.8520.0012.8850.020Anxiety diagnosis. Yes2.420<0.0010.5690.306Depression diagnosis. Yes3.509<0.0011.6650.408Sleep disorder diagnosis. Yes2.0810.0010.6250.381Frequency of intimate relation. Less than before vs same or more than before12.605<0.00118.655<0.001Relation with spouse. Worse than before5.480<0.0011.2560.636Quantitative factorsBp-value2Bp-value2Age-0.0180.0210.0100.718BASDAI (0-10)0.398<0.001-0.1550.284GHQ-12 (0-12)0.154<0.0010.0030.952Functional Limitation (0-54)0.237<0.0010.292<0.001Spinal Stiffness (3-12)0.131<0.001-0.1160.226Diagnostic Delay0.0300.0130.0200.4741p-value for test H0: OR = 1 2p-value for test H0: B = 0Conclusion:More than half of patients with axSpA in Spain presented high functional limitation in intimate relations, who more likely presented decreased frequency of relations. This may indicate that avoidance of sexual encounters is a common coping mechanism for the functional limitation accompanying this disease. Healthcare providers can play a key role in the sexual health of axSpA patients by improving patient-physician communication and raising awareness about the benefits of counselling on a healthy sexual life.Acknowledgements:This study was supported by Novartis Spain. The authors would like to thank all patients who participated in this study.Disclosure of Interests:Marco Garrido-Cumbrera: None declared, Jordi Gratacos-Masmitja Grant/research support from: Abbvie, BMS, Lilly, MSD, Novartis, Pfizer, Roche, and UCB, Eduardo Collantes-Estevez Grant/research support from: Abbvie, BMS, Lilly, MSD, Novartis, Pfizer, Roche, and UCB, Pedro Zarco-Montejo: None declared, Carlos Sastré Employee of: Novartis Farmacéutica Spain, Sergio Sanz-Gómez: None declared, Pedro Plazuelo-Ramos: None declared, Victoria Navarro-Compán Grant/research support from: Abbvie, BMS, Lilly, MSD, Novartis, Pfizer, Roche, and UCB.

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Douglass, Alan B., and Peter Hays. "Three Simultaneous Major Sleep Disorders." Canadian Journal of Psychiatry 32, no. 1 (February 1987): 57–60. http://dx.doi.org/10.1177/070674378703200111.

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Yamakawa, Koji, Kiyoshi Togawa, Soichiro Miyazaki, and Hiroyuki Tada. "Diagnosis and Therapy: Obstructive Sleep Respiratory Disorders." Nihon Kikan Shokudoka Gakkai Kaiho 45, no. 3 (1994): 211–18. http://dx.doi.org/10.2468/jbes.45.211.

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Romaker, Ann M., and Sonia Ancoli-Israel. "The Diagnosis of Sleep-Related Breathing Disorders." Clinics in Chest Medicine 8, no. 1 (March 1987): 105–17. http://dx.doi.org/10.1016/s0272-5231(21)00470-6.

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Lamberg, Lynne. "New Manual Aids Diagnosis Of Sleep Disorders." Psychiatric News 41, no. 3 (February 3, 2006): 6. http://dx.doi.org/10.1176/pn.41.3.0006.

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Penzel, T., and J. H. Peter. "Ambulatory Diagnosis of Sleep-Related Breathing Disorders." Sleep 15, suppl_6 (December 1992): S9—S12. http://dx.doi.org/10.1093/sleep/15.suppl_6.s9.

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Kales, Anthony, and Joyce Kales. "Evaluation and Diagnosis of Sleep Disorders Patients." Seminars in Neurology 7, no. 03 (September 1987): 243–49. http://dx.doi.org/10.1055/s-2008-1041424.

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Stores, G. "Clinical diagnosis and misdiagnosis of sleep disorders." Journal of Neurology, Neurosurgery & Psychiatry 78, no. 12 (December 1, 2007): 1293–97. http://dx.doi.org/10.1136/jnnp.2006.111179.

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Korchuganova, Elena N., Elena V. Katamanova, Irina V. Kudaeva, and Natalya V. Slivnitsyna. "Diagnosis of insomnia disorders in chronic mercury intoxication." Hygiene and sanitation 101, no. 11 (November 30, 2022): 1419–23. http://dx.doi.org/10.47470/0016-9900-2022-101-11-1419-1423.

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Introduction. It is now known that insomnia has a high comorbidity with various somatic and neurological diseases. In patients with chronic mercury intoxication, sleep disturbances are significantly more common than in the general population. The purpose of the study is to identify the most significant diagnostic criteria for insomnia disorders in patients with occupational chronic mercury intoxication. Materials and methods. The study involved thirty patients with occupational chronic mercury intoxication (CMI), who worked at Usolekhimprom LLC, whose mean age was 56±0.71 years, and 30 patients in the comparison group, whose mean age was 54±0.66 years, who complained of disorders sleep without contact with toxic production factors. A neurophysiological (polysnography), psychological (anxiety and depression level) study was carried out, as well as a quantitative determination of some neurotransmitters in the blood. Results. Polygraphic registration of biopotentials in CMI patients revealed an increase in the time to fall asleep (35.0 (30.5-47.0) min; a decrease in the duration of sleep (total sleep time, 339.5 (305.0-374.0) min); increase in the number of activations (2.9 (1.9-3.6)% of RVO) and total wakefulness during sleep (18.7 (11.3-23.5)%); decrease in the number of sleep cycles (3.0 (2.0-4.0)); decreased sleep efficiency index (70.95 (60.7-78.2)%) and integrative sleep quality index - IISQ (17.8 (13.4-27 ,5)), in the control group, an increase in total wakefulness within sleep (12.2 (8.4-18.6)%); an increase in the latent period of the REM stage (93.0 (72.0-117.0) min); decrease in the number of sleep cycles (3.0 (3.0-4.0)); decrease in the sleep efficiency index (78.4 (73.9-81.5)%) and the integrative sleep quality index - IISQ ( 14.1 (10.9-20.6)). dopamine levels in the blood, compared with the control group. Limitations of the obtained results. The results cannot be generalized to workers as the group included only men. Conclusion. A certain set of diagnostic criteria can be used for the differential diagnosis of insomnia in occupational CMI.

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Walker, Matthew C., and Sofia H. Eriksson. "Epilepsy and Sleep Disorders." US Neurology 07, no. 01 (2011): 60. http://dx.doi.org/10.17925/usn.2011.07.01.60.

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There is a close association between sleep and epilepsy. In some epilepsy syndromes, seizures occur predominantly (or even exclusively) during sleep or on awakening. Excessive daytime sleepiness is common in patients with epilepsy and may be due not only to medication but also to nocturnal seizures or concomitant sleep disorders. Sleep disorders such as obstructive sleep apnea can worsen epilepsy, with improvement of seizure control following appropriate treatment of the sleep disorder. Conversely, epilepsy and antiepileptic medication can worsen sleep disorders. Nocturnal epileptic seizures may be difficult to differentiate from parasomnias, in particular non-rapid eye movement parasomnias such as night terrors, sleepwalking and confusional arousals, on history alone since there are semiologic similarities between the two disorders. Schemes have been developed to facilitate differential diagnosis, although this remains a challenge even using the gold standard, video-electroencephalography telemetry.

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Walker, Matthew C., and Sofia H. Eriksson. "Epilepsy and Sleep Disorders." European Neurological Review 6, no. 1 (2011): 60. http://dx.doi.org/10.17925/enr.2011.06.01.60.

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There is a close association between sleep and epilepsy. In some epilepsy syndromes, seizures occur predominantly (or even exclusively) during sleep or on awakening. Excessive daytime sleepiness is common in patients with epilepsy and may be due not only to medication but also to nocturnal seizures or concomitant sleep disorders. Sleep disorders such as obstructive sleep apnoea can worsen epilepsy, with improvement of seizure control following appropriate treatment of the sleep disorder. Conversely, epilepsy and antiepileptic medication can worsen sleep disorders. Nocturnal epileptic seizures may be difficult to differentiate from parasomnias, in particular non-rapid eye movement parasomnias such as night terrors, sleepwalking and confusional arousals, on history alone since there are semiological similarities between the two disorders. Schemes have been developed to facilitate differential diagnosis, although this remains a challenge even using the gold standard, video-electroencephalography telemetry.

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Uchiyama, Makoto. "LC2. Clinical and neurophysiological diagnosis of sleep disorders." Clinical Neurophysiology 130, no. 10 (October 2019): e181-e182. http://dx.doi.org/10.1016/j.clinph.2019.06.048.

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Staufenberg, E. F. "Sleep disorders. Epilepsy a differential diagnosis in children." BMJ 306, no. 6890 (May 29, 1993): 1476. http://dx.doi.org/10.1136/bmj.306.6890.1476-b.

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Suzuki, Keisuke, Masayuki Miyamoto, and Koichi Hirata. "Sleep disorders in the elderly: Diagnosis and management." Journal of General and Family Medicine 18, no. 2 (March 30, 2017): 61–71. http://dx.doi.org/10.1002/jgf2.27.

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Khritinin, Dmitry Fedorovich, M. A. Sumarokova, and E. P. Schukina. "Features of modern approaches to the diagnosis and treatment of insomnia." Vestnik nevrologii, psihiatrii i nejrohirurgii (Bulletin of Neurology, Psychiatry and Neurosurgery), no. 10 (October 1, 2020): 56–66. http://dx.doi.org/10.33920/med-01-2010-07.

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Currently, insomnia is not only a medical, but also a social as well as an economic problem. Sleep disorders increase the risk of somatic, neurological and mental illnesses. The shift schedule has a significant impact on the employee’s health, increasing the risk of developing such disorders as metabolic syndrome, arterial hypertension and other. As a result of sleep disturbances, lipid peroxidation processes may intensify, which can lead to the disorders described above. Therefore, the prevention and treatment of sleep disorders is an important aspect of chronic diseases diagnostics. In our opinion, it is crucial to study possible sleep disorders for their timely correction. The article discusses the features of drug and non-drug treatment of sleep disorders, as well as approaches to the primary and secondary prevention of insomnia. It is recommended to begin the treatment of sleep disorders with cognitive-behavioral therapy. Cognitive-behavioral therapy for insomnia typically includes psycho-education, training in relaxation techniques, stimulation limitation method, sleep limitation therapy, and cognitive therapy. When developing recreational activities for employees with a shift work schedule, attention should be paid to work and rest regimes, prevention of fatigue and obesity, and the sleep disorders treatment. Training in sleep hygiene and improving its compliance in the target groups is regarded as a method of non-pharmacological treatment of sleep disorders and a means of primary and secondary prevention of insomnia. In our opinion, further research on the features of the prevention and treatment of insomnia in various population groups is needed. Effective primary and secondary prevention of sleep disorders will reduce the risks of developing neurological, somatic and mental diseases and significantly improve the quality of life.

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Stores, Gregory. "Sleep disorders in children and adolescents†." BJPsych Advances 21, no. 2 (March 2015): 124–31. http://dx.doi.org/10.1192/apt.bp.114.014050.

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SummaryDisordered sleep has long been recognised as both a consequence of psychiatric illness and a contributory factor to its development. Significant sleep disturbance occurs in about 25% of children and adolescents and 80% or more of children in high-risk groups; it often continues into adulthood. All psychiatrists should therefore be familiar with the principles of sleep medicine and the impact of sleep and its disorders. In this article, the relationship between sleep disorders and the breadth of child and adolescent psychiatry in particular is explored. The classification, aetiology and implications of sleep disorders are discussed, as well as the practicalities of screening, diagnosis and management, with a view to informing readers how accurate diagnosis, prevention and successful treatment of sleep disorders can benefit patients and their families.

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Ohlmann, Brigitte, Moritz Waldecker, Michael Leckel, Wolfgang Bömicke, Rouven Behnisch, Peter Rammelsberg, and Marc Schmitter. "Correlations between Sleep Bruxism and Temporomandibular Disorders." Journal of Clinical Medicine 9, no. 2 (February 24, 2020): 611. http://dx.doi.org/10.3390/jcm9020611.

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The aim of this study was to identify correlations between sleep bruxism (SB) and temporomandibular disorders (TMD) as diagnosed by means of the research diagnostic criteria for temporomandibular disorders (RDC/TMD). Sleep bruxism was diagnosed on the basis of I) validated questionnaires, II) clinical symptoms, and III) electromyographic/electrocardiographic data. A total of 110 subjects were included in the study. Fifty-eight patients were identified as bruxers and 52 as nonbruxers. A psychosocial assessment was also performed. An RDC/TMD group-I diagnosis (myofascial pain) was made for 10 out of 58 bruxers, whereas none of the nonbruxers received a diagnosis of this type. No significant differences were found between bruxers and nonbruxers with regard to RDC/TMD group-II (disc displacement) and group-III (arthralgia, arthritis, arthrosis) diagnoses. Somatization was significantly more common among bruxers than nonbruxers. Multivariate logistic regression analysis revealed that somatization was the only factor significantly correlated with the diagnosis of myofascial pain. The results of this study indicate a correlation between myofascial pain, as diagnosed using the RDC/TMD, and somatization. It seems that somatization is a stronger predictor of an RDC/TMD diagnosis of myofascial pain than sleep bruxism is.

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Kay-Stacey, Margaret, and Hrayr P. Attarian. "Managing Sleep Disorders during Pregnancy." Gender and the Genome 1, no. 1 (March 2017): 34–45. http://dx.doi.org/10.1089/gg.2016.0006.

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Sleep disturbances and disorders are common during pregnancy, and they can be risk factors for a number of serious pregnancy-related sleep disorders. These include postpartum depression, pregnancy-induced hypertension, gestational diabetes, and intrauterine growth retardation. In addition, certain chronic sleep disorders, such as narcolepsy, are quite challenging to manage in the context of pregnancy and during lactation, particularly with medications that can be teratogenic. This review discusses 4 common sleep disorders and their impacts on pregnancy, and suggests ways to deal with these disorders that improves maternal and fetal outcomes safely. The review discusses diagnosis and treatment of obstructive sleep apnea, restless legs syndrome, insomnia, and narcolepsy in pregnancy.

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Yuryeva, Liudmyla, and Yuliia Liashchenko. "Diagnosis and treatment of dyssomnic impairment in patients with anxiety-depressive disorders (literature review)." Ukrains'kyi Visnyk Psykhonevrolohii, Volume 28, issue 3 (104) (October 14, 2020): 70–76. http://dx.doi.org/10.36927/2079-0325-v28-is3-2020-11.

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Sleep disorders are one of the most common complaints in patients seeking medical attention. In turn, dyssomnic disorders are often associated with other somatic and mental illnesses. The greatest comorbidity of sleep disorders is seen with anxiety and depressive disorders. The relationship, which is defined as bi-directional and can aggravate the course of each other, as well as affect the results of treatment and the occurrence of relapse in the future. The purpose of this article was to conduct a systematic literature review of a number of studies related to the study of the relationship between anxiety-depressive disorders and sleep disorders, assessment features and existing therapeutic approaches. As a result of a systematic literature search, 25 studies were selected for further analysis. The inclusion criteria were the availability of information on the mutual influence of sleep disorders on the course of states of the anxiety-depressive spectrum, methods of monitoring and self-monitoring sleep disorders in patients, as well as approaches of pharmacological and psychotherapeutic influence. Most studies reported the successful use of psychoeducational work, cognitive-behavioral therapy (individual, group), and person-centered psychotherapy to correct sleep in patients, and it was noted that sleep recovery led to a significant improvement in comorbidity. It was also found that the most studied sleep disorders were in depressive disorder, while the relationship and methods of correcting dyssomnias in anxiety disorders have not been studied enough. Thus, further research aimed at expanding the methods of sleep correction in anxiety states and the creation of appropriate differentiated rehabilitation programs for the treatment of patients with anxiety-depressive disorders with sleep disorders would make a significant contribution to the development of clinical medical, psychological and psychiatric practice. Key words: depression, dyssomnia treatment, psychopharmacotherapy, psychotherapy, sleep disorders, anxiety

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Kim, Seog Ju. "Recent Advances in Diagnosis and Treatment of Sleep Disorders." Journal of Korean Neuropsychiatric Association 59, no. 1 (2020): 1. http://dx.doi.org/10.4306/jknpa.2020.59.1.1.

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Shatkin, Jess Parker, and Michelina Pando. "Diagnosis and Treatment of Common Sleep Disorders in Adolescence." Adolescent Psychiatry 5, no. 3 (December 4, 2015): 146–63. http://dx.doi.org/10.2174/2210676605666150521232247.

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KumarGarg, Vijay, and R. K. Bansal. "Knowledge based System for the Diagnosis of Sleep Disorders." International Journal of Computer Applications 110, no. 1 (January 16, 2015): 47–51. http://dx.doi.org/10.5120/19284-0702.

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Ancoli-Israel, Sonia, and Liat Ayalon. "Diagnosis and Treatment of Sleep Disorders in Older Adults." American Journal of Geriatric Psychiatry 14, no. 2 (February 2006): 95–103. http://dx.doi.org/10.1097/01.jgp.0000196627.12010.d1.

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Ancoli-Israel, Sonia, and Liat Ayalon. "Diagnosis and Treatment of Sleep Disorders in Older Adults." FOCUS 7, no. 1 (January 2009): 98–105. http://dx.doi.org/10.1176/foc.7.1.foc98.

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BUYSSE, DANIEL J. "Diagnosis and Assessment of Sleep and Circadian Rhythm Disorders." Journal of Psychiatric Practice 11, no. 2 (March 2005): 102–15. http://dx.doi.org/10.1097/00131746-200503000-00005.

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Stores, Gregory. "Errors in the recognition and diagnosis of sleep disorders." Progress in Neurology and Psychiatry 13, no. 6 (November 2009): 24–33. http://dx.doi.org/10.1002/pnp.146.

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Louter, Maartje, Willemijn C. C. A. Aarden, Joy Lion, Bastiaan R. Bloem, and Sebastiaan Overeem. "Recognition and diagnosis of sleep disorders in Parkinson’s disease." Journal of Neurology 259, no. 10 (April 26, 2012): 2031–40. http://dx.doi.org/10.1007/s00415-012-6505-7.

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Kim, Keun Tae, and Yong Won Cho. "Hospital Selection Factors of Sleep Disorder: Sleep Apnea Versus Other Sleep Disorders." Journal of Sleep Medicine 18, no. 2 (August 31, 2021): 100–105. http://dx.doi.org/10.13078/jsm.210008.

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Objectives: The hospital selection factor is the criterion based on the judgment of the patients’ decision process. We investigated the hospital selection factors of patients with sleep disorders and compared that for patients with sleep apnea and other sleep disorders. Methods: This is a questionnaire-based cross-sectional study that evaluated patients with a sleep disorder at the sleep unit of a tertiary referral center. We investigated the patients’ demographic information, occupational status, diagnosis of sleep disorders, and hospital-related and patient-related factors associated with hospital selection. Results: A total of 138 patients with a sleep disorder were analyzed. Internet information was the primary data source for sleep apnea patients to select a hospital, while it was acquaintances for patients with other sleep disorders. None with sleep apnea gathered information from broadcast or print media. Patients gave the highest score for the least waiting time and recency of the hospital’s facility. Unlike patients with other sleep disorders, those with sleep apnea valued the hospital’s popularity, accessibility, availability of appointments at desired dates, and medical expense benefits. Conclusions: This is the first study to analyze the hospital selection factors of patients with sleep disorders in South Korea. This study might improve the sleep medication as well as the medical system by revealing the medical use behavior of patients with sleep disorders.

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Burchakov, Denis I. "Sleep disturbances in pregnancy: features of diagnosis and therapy: A review." Gynecology 24, no. 6 (January 20, 2023): 471–77. http://dx.doi.org/10.26442/20795696.2022.6.202028.

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Physiological changes during pregnancy often disrupt women's sleep. If these changes are combined with other factors (obesity, iron or magnesium deficiency, anxiety, etc.), the pregnant woman may develop sleep disorders: obstructive sleep apnoea syndrome, restless legs syndrome, leg cramps, and insomnia. These disorders increase the risk of pregnancy complications, reduce the quality of a woman's life, and form the basis for somatic and mental disorders in the postpartum period. Therefore, the obstetrician has to be familiar with the phenomenology, diagnosis, and treatment of sleep disorders in pregnant women to treat them promptly or to refer a woman to a neurologist or psychiatrist. This review briefly describes the common sleep disorders occurring in pregnant women, especially the various types of insomnia. The main groups of sedative agents are characterized, of which only doxylamine is acceptable for use in routine practice because of its proven efficacy and safety during pregnancy.

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44

Klingman, K. J., A. Morse, N. Williams, M. Grandner, and M. L. Perlis. "1175 Sleep Disorders Screening in Primary Care: Prevalence of Diagnosis and Treatment in the EMR." Sleep 43, Supplement_1 (April 2020): A448—A449. http://dx.doi.org/10.1093/sleep/zsaa056.1169.

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Abstract Introduction Undetected and untreated sleep disorders likely precipitate or exacerbate medical and/or psychiatric illnesses. Given this, primary care is an ideal point for managing sleep disorders, yet prior research shows that PCPs diagnose and/or treat sleep disorders at rates far below population prevalences. The purpose of this study was to determine the current rate of detection and treatment of sleep disorders within primary care settings. Methods EMR data from two health care systems was analyzed. The proportion of PCPs diagnosing and treating one or more sleep disorders was calculated (per year) for 5 years (2014-2018). Also calculated was the percent of PCP caseload diagnosed and/or treated for sleep disorders. Results The two systems comprised n=1021 PCPs. From 2014-2018, the proportion of PCPs diagnosing patients with sleep disorders fluctuated between 58-89%. The proportion treating sleep disorders fluctuated between 50-91%. Non-parametric one-sample run tests (SPSS) indicate these are random distributions (p>0.05). PCPs’ use of medications to treat sleep disorders is trending downward over time within one system (per linear regression, p=0.03, R-squared=0.8). Other temporal trends were not evidenced. The average percentage of diagnosed and treated patients per PCP was around 2.5% of their caseloads. Between-system differences were observed. Conclusion There is a profound mismatch between percentage of PCPs identifying patients with sleep disorders (60-90%) and the percentage of patient caseload diagnosed and/or treated for sleep disorders (2.5%). This suggests that the majority of PCPs are willing to assess for sleep health but do so in only a small minority of patients. These data, along with our survey data (elsewhere in this volume) suggest that the intention-action gap could be closed if PCPs were appropriately resourced. Support There was no funding for this study.

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Wang, Yujie, and Rachel Marie E. Salas. "Approach to Common Sleep Disorders." Seminars in Neurology 41, no. 06 (November 26, 2021): 781–94. http://dx.doi.org/10.1055/s-0041-1726364.

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AbstractSleep disorders are highly relevant in clinical practice given their prevalence as well as their impact on health outcomes and quality of life. The most common concerns are excessive daytime sleepiness, insomnia, disordered breathing, and abnormal movements or behaviors during sleep. A detailed but targeted history is vital, particularly from the sleep partner/witness. In-laboratory sleep testing (polysomnography and multiple sleep latency test) remains vital in the diagnosis of certain sleep disorders (such as sleep-disordered breathing and central hypersomnia) and in specific populations (such as in children and individuals with comorbid medical disorders). Advances in technology have allowed for a variety of methods in assessing a patient's sleep, from compact devices to evaluate for sleep apnea, wrist actigraphy, and mobile device-based applications. As the pathophysiology of various sleep disorders becomes better elucidated, disease-specific medications have been developed for these conditions. Nonetheless, a multidisciplinary approach to management is necessary, including improving sleep hygiene and cognitive behavioral therapy.

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Wutzl, Betty, Stefan M. Golaszewski, Kenji Leibnitz, Patrick B. Langthaler, Alexander B. Kunz, Stefan Leis, Kerstin Schwenker, Aljoscha Thomschewski, Jürgen Bergmann, and Eugen Trinka. "Narrative Review: Quantitative EEG in Disorders of Consciousness." Brain Sciences 11, no. 6 (May 25, 2021): 697. http://dx.doi.org/10.3390/brainsci11060697.

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In this narrative review, we focus on the role of quantitative EEG technology in the diagnosis and prognosis of patients with unresponsive wakefulness syndrome and minimally conscious state. This paper is divided into two main parts, i.e., diagnosis and prognosis, each consisting of three subsections, namely, (i) resting-state EEG, including spectral power, functional connectivity, dynamic functional connectivity, graph theory, microstates and nonlinear measurements, (ii) sleep patterns, including rapid eye movement (REM) sleep, slow-wave sleep and sleep spindles and (iii) evoked potentials, including the P300, mismatch negativity, the N100, the N400 late positive component and others. Finally, we summarize our findings and conclude that QEEG is a useful tool when it comes to defining the diagnosis and prognosis of DOC patients.

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Khachatryan, Marine, Jenna Kay, and Sejal Jain. "704 The Association of Sleep Disorders in Patients with Chronic Pain Disorders." Sleep 44, Supplement_2 (May 1, 2021): A275. http://dx.doi.org/10.1093/sleep/zsab072.702.

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Abstract Introduction Sleep and pain are interrelated and have a bidirectional relationship. The study was performed to identify the impact of sleep disorders on pain perception. Methods The institutional review board approved the study. Patients evaluated in the Pain Clinic between 1/1/2014 and 12/31/2017 who had polysomnography done were identified by database search. Chart review identified demographics, initial pain score, pain treatments, sleep disorder diagnosis, treatments of sleep disorder and pain scores after sleep treatments. Numerical pain score (NPS) and insomnia severity index (ISI) were used as a measure of pain and sleep quality, respectively. The descriptive statistics were presented by percentages, mean and standard deviations. Regression analysis was performed between initial NPS and ISI. T-test compared change in NPS for compliant and non-compliant subjects, before and after sleep treatments. Linear regression model identified factors associated with changes in pain perception after sleep treatments. Results Of the 320 participants identified, complete data was available for 180 subjects. The average age was 55.9±13.9; 51.41% were female; 60.2% were Caucasian and 26.64% were Hispanic. Initial NPS was 8.8±1.7, average ISI was 15.00±6.41, average BMI was 35.4±10.2. Ninety-five percent had a diagnosis of obstructive sleep apnea (OSA), 27.81% had restless leg syndrome, and 7.19% had complex sleep apnea. Since most patients had OSA, details of positive airway pressure (PAP) treatments were also investigated. Of 84% of subjects treated with PAP, compliance data were available for 53%, which showed 69% (n=55) being complaint with PAP. Initial NPS correlated positively with ISI (R2: 0.064±0.024, p<0.01). No difference in NPS was found in groups based on compliance, before and after PAP treatments. Regression model identified that BMI was the most significant factor in the change in NPS following sleep treatment (R2: 0.083±0.034, p = 0.03). Conclusion The study identified that the severity of pain is associated with poor quality of sleep. While this study failed to identify improvement in pain perception after successful OSA treatment, limited number of subjects in our study were compliant with PAP treatment which may have impacted the results. Future prospective studies are needed to understand the complex association between improvement in sleep quality and pain perception. Support (if any):

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48

Lebedev, Vladislav V., Olga V. Kozhevnikova, Andrey A. Gazaryan, Victoriya A. Aysina, Eka A. Abashidze, Lyudmila M. Kuzenkova, Lale A. Pak, and Irina K. Filimonova. "Algorithm for the diagnosis of breathing disorders during sleep in children with neurological pathology." L.O. Badalyan Neurological Journal 2, no. 2 (June 30, 2021): 73–82. http://dx.doi.org/10.46563/2686-8997-2021-2-2-73-82.

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Introduction. Sleep disorders in children with nervous system pathology are more pronounced than in the general population. One of the most common causes of sleep disorders in children is sleep-disordered breathing. The aim of our study was to create an algorithm for the diagnosis of sleep breathing disorders in children with neurological pathology. Materials and methods. The results of night studies (160 polysomnographies, 98 cardiorespiratory monitorings) carried out in the department of instrumental diagnostics at the National Medical Research Center for Children’s Health in 258 children (154 boys and 104 girls, aged one month to 17 years) with neurological pathology were analyzed. Questionnaires were used to assess the quality of sleep. An essential criterion for dividing children into groups was the presence of maxillofacial anomalies (MFA). The results were compared with complaints according to questionnaires, age, BMI and ENT-status of patients. Results. In the general sample, a significant (p < 0.001) relationship between respiratory disorders and complaints and the presence of ENT pathology was obtained. The most severe breathing disorders were recorded in children with MFA (p < 0.001). The result was the creation of an algorithm for examining children with neurological pathology. Conclusion. Children with neurological pathology in sleep-breathing disorders require a personalized approach to correcting the causes of these disturbances, depending on the nosology. Chronic pathology of the ENT organs aggravates respiratory disorders during sleep. Regular monitoring of sleep disorders using questionnaires should be included in the algorithm for managing children with neurological diseases of all ages for early detection of these disorders.

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Penzel, Thomas, Christoph Schöbel, and Ingo Fietze. "New technology to assess sleep apnea: wearables, smartphones, and accessories." F1000Research 7 (March 29, 2018): 413. http://dx.doi.org/10.12688/f1000research.13010.1.

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Sleep medicine has been an expanding discipline during the last few decades. The prevalence of sleep disorders is increasing, and sleep centers are expanding in hospitals and in the private care environment to meet the demands. Sleep medicine has evidence-based guidelines for the diagnosis and treatment of sleep disorders. However, the number of sleep centers and caregivers in this area is not sufficient. Many new methods for recording sleep and diagnosing sleep disorders have been developed. Many sleep disorders are chronic conditions and require continuous treatment and monitoring of therapy success. Cost-efficient technologies for the initial diagnosis and for follow-up monitoring of treatment are important. It is precisely here that telemedicine technologies can meet the demands of diagnosis and therapy follow-up studies. Wireless recording of sleep and related biosignals allows diagnostic tools and therapy follow-up to be widely and remotely available. Moreover, sleep research requires new technologies to investigate underlying mechanisms in the regulation of sleep in order to better understand the pathophysiology of sleep disorders. Home recording and non-obtrusive recording over extended periods of time with telemedicine methods support this research. Telemedicine allows recording with little subject interference under normal and experimental life conditions.

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Murata, Akira. "Diagnosis and Treatment of Sleep Apnea Syndrome: Sleep Apnea Syndrome Triggers Life-Threatening Disorders During Sleep." Nihon Ika Daigaku Igakkai Zasshi 3, no. 2 (2007): 96–101. http://dx.doi.org/10.1272/manms.3.96.

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