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Journal articles on the topic 'Sleep clinic'

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Author: Grafiati

Published: 10 December 2022

Last updated: 28 January 2023

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1

Henry, Olivia, Alexandra Brito, Marguerite Cooper Lloyd, Robert Miller, Eleanor Weaver, and Raghu Upender. "A Model for Sleep Apnea Management in Underserved Patient Populations." Journal of Primary Care & Community Health 13 (January 2022): 215013192110689. http://dx.doi.org/10.1177/21501319211068969.

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Introduction: Obstructive sleep apnea (OSA) is a common condition in the United States that is strongly linked to metabolic disease, cardiovascular disease, and increased mortality. Uninsured populations experience sleep health disparities, including delayed recognition, diagnosis, and treatment of OSA due to barriers accessing and affording care. Partnerships between primary care clinics and sleep medicine specialists for sleep apnea management have the potential to increase screening, testing, and treatment among underserved populations. Here, we present an integrated and cost-effective model that is easier to navigate for patients while maintaining high quality care. Methods: We designed and implemented a specialty sleep clinic at Shade Tree Clinic, Vanderbilt’s student-run, free primary care clinic. Patients with signs and symptoms of OSA were identified at primary care appointments and screened using the STOP-BANG questionnaire. Clinic visits took place over telehealth with a medical student and sleep specialist. Patients were diagnosed using a home sleep test, and if indicated, were prescribed and given a CPAP device for treatment. CPAP adherence was monitored using a cloud-based remote monitoring system. Results: From December 2020 through August 2021, we hosted 6 telehealth Sleep Clinics, seeing a total of 28 patients across these visits. We have received a total of 37 referrals and have coordinated sleep evaluations and diagnostic testing for 18 of these patients so far. Prior to initiation of the sleep clinic, there were 17 patients on our primary care panel at Shade Tree with a diagnosis of OSA. These patients were using donated equipment and many had been lost to follow-up or had broken parts. We were able to replace 10 of these patient’s CPAP devices and plan to replace the remaining seven. Conclusions: We have created a model of integrated specialty care that is efficient and cost-effective. This paradigm can be replicated for the many specialties that are typically overlooked and undertreated when working with uninsured patients. As awareness of this sleep medicine program becomes more widespread at Shade Tree Clinic, we anticipate reaching more primary care patients with signs and symptoms of sleep apnea through student education, cost-effective diagnostics, and partnership with sleep specialists.

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Bennett, K. L. "0648 Impact of Positive Airway Pressure (PAP) Troubleshooting Clinic Visits on Patient Satisfaction, PAP Use, Mask Leak, and Prolonged Use." Sleep 43, Supplement_1 (April 2020): A247. http://dx.doi.org/10.1093/sleep/zsaa056.644.

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Abstract Introduction Patients with sleep apnea are often prescribed positive airway pressure (PAP) treatment. Some patients have difficulty consistently using a PAP machine due to problems such as air leak, mask discomfort, and dry mouth. The purpose of this project is to evaluate the satisfaction and efficacy of a PAP Troubleshooting Clinic lead by a RN and a respiratory technician (RT). This clinic seeks to improve PAP compliance, increase PAP tolerability and increase PAP treatment efficacy Methods The PAP Troubleshooting Clinic consists of a RN and RT with specialized knowledge about sleep apnea and PAP treatment. During a 30 or 60-minute clinic visit, these providers review the patient’s experience with PAP, assess mask fit, review PAP data and PAP settings, and recommend treatment adjustments for the primary Sleep Clinic provider’s consideration. Outcomes assessment includes satisfaction (a telephone survey one week after the visit) and efficacy (30-day data on overall use, mask leak, and days with ≥ 4 hours of use downloaded from PAP machines). Results To date, 58 patients have received care in the clinic and 56 (96.5%) patients reported they were satisfied/highly satisfied with the PAP Troubleshooting Clinic. From the sample, forty-three (74.1%) patients were compliant with mask use over 30 days. Twenty-four (55.81%) showed a greater than 10% reduction in mask leak after intervention. Ten patients (23.3%) achieved an improvement with a 10% increase in number of days with > than 4 hours of PAP use. Conclusion Patients and Sleep Clinic providers are very satisfied with the PAP Troubleshooting Clinic. Patients are referred to this clinic because they have significant issues with PAP usage and are at high risk of discontinuing use. Patients find the clinic helpful and encouraging, while sleep medicine physicians and APPs appreciate the assistance in helping patients succeed with PAP, especially during the 30-day time period where PAP compliance receives scrutiny from clinics and payers. Support A PAP Troubleshooting Clinic is an effective way to improve patient PAP Use, Mask Leak, Prolonged Use and Patient Satisfaction. Importantly, this new clinical model offers a valuable alternative to provide patients with the appropriate level of care.

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3

Robinson, Richard. "In the Clinic-Sleep Apnea." Neurology Today 18, no. 9 (May 2018): 19–20. http://dx.doi.org/10.1097/01.nt.0000533820.07878.7a.

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4

Reddy, K. R. Bharath Kumar. "Profile of paediatric sleep patients and polysomnography findings: Experience from an exclusive paediatric sleep clinic in India." Karnataka Pediatric Journal 36 (December 30, 2021): 119–22. http://dx.doi.org/10.25259/kpj_27_2021.

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Objectives: The objectives of the study were to describe the profile of patients attending an exclusive paediatric sleep clinic in India. Materials and Methods: Children aged 1 month–18 years, attending an exclusive paediatric sleep clinic, were assessed using standardized questionnaires. Children underwent sleep coaching, were treated medically, or underwent polysomnography based on the decision of the paediatric pulmonologist. Level 1 polysomnography was conducted by trained personnel. Results: Of 186 children, 36.5% were for infant sleep issues, 24.7% suspected obstructive sleep apnea (OSA), 18.2% neuromuscular diseases with sleep problems, 15.6% genetic disorders with sleep problems, 4.3% parasomnias, and 0.5% abnormal movements during sleep. Of the 85 paediatric polysomnographies conducted, 9.4% were normal studies, 87% had OSA, 1.1% restless leg syndrome, and 2.3% were inadequate studies. Conclusion: Sleep disorders in children are not uncommon and paediatricians need to be aware and identify them early. More number of exclusive paediatric sleep clinics need to be established in India.

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Lau, H., D. O’Brien, J. Hundloe, and D. Samaratunga. "P071 Listening to Beyoncé: factors associated with non-attendance at an outpatient sleep clinic." SLEEP Advances 2, Supplement_1 (October 1, 2021): A44. http://dx.doi.org/10.1093/sleepadvances/zpab014.115.

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Abstract Introduction Patient non-attendance at outpatient sleep clinics is common and costly. Little is known about the factors associated with sleep clinic non-attendance, especially in an Australian context. The goal of our audit was to identify the patient, referral, and appointment factors that may affect attendance at an outpatient sleep clinic. Methods A case-control study was performed in 171 patients (57 cases / non-attenders and 114 controls / attenders) who had a sleep clinic appointment between September 20th, 2020 and March 21st, 2021. Statistical analysis was performed using the two-sided chi-square test with a 5% significance level. Results The overall rate of non-attendance was 10.8%. The rates of non-attendance between new and review cases were similar. Being single (odds ratio [OR]: 2.49; p = 0.010), middle-aged (OR: 4.39; p < 0.001 vs. older-aged), or female (OR: 2.08; p = 0.026) was associated with a higher rate of non-attendance. English was the primary language for all non-attenders. A higher proportion of non-attenders than attenders were born in Australia. For new cases, the source of referral, reason for referral, and triage category did not affect attendance rates. Likewise, the patient’s primary sleep disorder and treatment status did not affect attendance for review cases. Conclusion Factors associated with non-attendance at an outpatient sleep clinic include being single, middle-aged, or female. By identifying patients at higher risk of clinic non-attendance, a more tailored approach can be developed to mitigate this issue.

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Reynor, A., N. McArdle, B. Shenoy, S. Dhaliwal, S. Rea, J. Walsh, P. Eastwood, et al. "P119 CPAP and adverse cardiovascular events in OSA: Are participants of randomized trials representative of sleep clinic patients?" SLEEP Advances 2, Supplement_1 (October 1, 2021): A60. http://dx.doi.org/10.1093/sleepadvances/zpab014.160.

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Abstract Introduction Randomized controlled trials (RCTs) have shown no reduction in adverse cardiovascular (CV) events in patients randomized to continuous positive airway pressure (CPAP) therapy for obstructive sleep apnea (OSA). This study examined whether randomized study populations were representative of OSA patients attending a sleep clinic. Methods Sleep clinic patients were 3,965 consecutive adults diagnosed with OSA by in-laboratory polysomnography from 2006–2010 at a tertiary hospital sleep clinic. Characteristics of these sleep clinic OSA patients were compared with participants of 5 well-known RCTs examining the effect of CPAP on adverse CV events in OSA. We determined the percentage of patients with severe (apnea hypopnea index, [AHI]≥30/h) or any OSA (AHI≥5/h) who met the selection criteria of each RCT, as well as identified those criteria that excluded the most patients. Results Compared to RCT participants, sleep clinic OSA patients were younger, sleepier, more likely to be female and less likely to have established CV disease. The percentage of patients with severe or any OSA who met the RCT selection criteria ranged from 1.2% to 20.2% and 0.8% to 21.1%, respectively. The selection criteria that excluded most patients were pre-existing CV disease, symptoms of excessive sleepiness, nocturnal hypoxemia and co-morbidities. Discussion A minority of sleep clinic patients diagnosed with OSA meet the selection criteria of RCTs of CPAP on adverse CV events in OSA. OSA populations in RCTs differ considerably from typical sleep clinic OSA patients. This suggests that the findings of RCTs may not be generalisable to most sleep clinic OSA patients.

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Dosman, James, John Gjevre, Chandima Karunanayake, Donna Rennie, Josh Lawson, Louise Hagel, Roland Dyck, John Gordon, and Punam Pahwa. "Predicting Sleep Apnea in the Clinic." Chest 145, no. 3 (March 2014): 595A. http://dx.doi.org/10.1378/chest.1825416.

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Pilowsky, I., I. Crettenden, and M. Townley. "Sleep disturbance in pain clinic patients." Pain 23, no. 1 (September 1985): 27–33. http://dx.doi.org/10.1016/0304-3959(85)90227-1.

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9

Stafford, Anne, and Philip Conn. "A COMMUNITY SERVICE-BASED SLEEP CLINIC." Clinical Psychology Forum 1, no. 7 (February 1987): 10–14. http://dx.doi.org/10.53841/bpscpf.1987.1.7.10.

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10

Ray, Christopher, Robert A. Strauss, and Ryan S. Nord. "Management of obstructive sleep apnea through a multidisciplinary sleep clinic." Oral Surgery, Oral Medicine, Oral Pathology and Oral Radiology 130, no. 1 (July 2020): e21-e22. http://dx.doi.org/10.1016/j.oooo.2019.12.023.

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11

Dealberto, Marie-José, Chantal Ferber, Lucile Garma, Patrick Lemoine, and Annick Alpérovitch. "Factors Related to Sleep Apnea Syndrome in Sleep Clinic Patients." Chest 105, no. 6 (June 1994): 1753–58. http://dx.doi.org/10.1378/chest.105.6.1753.

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12

Do, So Young, Sohyeon Kim, Keun Tae Kim, and Yong Won Cho. "Clinical Risk Factors for Sleep Apnea in a Korean Sleep Clinic." Journal of the Korean Neurological Association 37, no. 4 (November 1, 2019): 352–60. http://dx.doi.org/10.17340/jkna.2019.4.3.

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Siriwat, Rasintra, Neepa Gurbani, Yuanfang Xu, Md Monir Hossain, and Narong Simakajornboon. "Sleep manifestations, sleep architecture in children with Eosinophilic esophagitis presenting to a sleep clinic." Sleep Medicine 68 (April 2020): 160–66. http://dx.doi.org/10.1016/j.sleep.2019.08.018.

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Maclean, Joanna E., David Fitzsimons, Dominic Fitzgerald, and Karen Waters. "Comparison of Clinical Symptoms and Severity of Sleep Disordered Breathing in Children with and without Cleft Lip and/or Palate." Cleft Palate-Craniofacial Journal 54, no. 5 (September 2017): 523–29. http://dx.doi.org/10.1597/15-309.

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Objective To determine whether the clinical presentation or severity of sleep disordered breathing differs between children with or without a history of cleft lip and/or palate (CL/P) presenting for sleep assessment. Design Retrospective chart review. Setting Tertiary care pediatric hospital cleft clinic, sleep clinic. Patients Children > 6 months of age presenting to the cleft clinic with sleep concerns and children without CL/P presenting to the sleep clinic in the same 2-year period. Main Outcomes Measures Clinical symptoms and overnight polysomnography (PSG) results. Results A total of 168 children (55 from cleft clinic, 113 from sleep clinic) were identified. Age at clinical review (6.6 ± 4.1 years versus 6.8 ± 4.0 years, P = ns), sex distribution (64.6% versus 58.4%, P = ns), and the presence of syndromes or significant medical conditions (12% versus 16%, P = ns) were similar between groups. Snoring was the reason for referral in 59% of children with CL/P and 69% of non-CL/P children ( P = ns). The only presenting feature that differentiated between the groups was a lower incidence of tonsillar enlargement in children with CL/P (33% versus 79%, chi-square 30.4, P < 0.001). Sleep study results showed similar apnea-hypopnea indices (6.2 ± 6.9 versus 7.9 ± 7.1 events/hr, P = ns) with more central apnea in children with CL/P (1.5 ± 1.5 versus 1.0 ± 1.0 events/hr, P = 0.017). Conclusions Snoring and obstructive sleep apnea are common in CL/P with less tonsillar enlargement than non-CL/P children. Children with CL/P have similar OSA severity compared to non-cleft children but more central apnea which may indicate differences in the control of breathing.

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Elphick, Heather, Claire Earley, Karen Tyas, Lowri Thomas, Lisa Artis, and Vicki Dawson. "The “Sleep Well, Lincolnshire” Project: Evaluation of an Online Sleep Practitioner Clinic." Journal of Sleep Medicine 18, no. 3 (December 31, 2021): 154–61. http://dx.doi.org/10.13078/jsm.210013.

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Objectives: Poor sleep is associated with adverse outcomes during childhood. Behavioral insomnia is the most common sleep difficulty experienced by children. The coronavirus disease 2019 (COVID-19) global pandemic in 2020 has profoundly affected children’s sleep patterns. This project aimed to evaluate a one-toone sleep service delivered via online clinics by community sleep practitioners in the UK.Methods: This was an observational pre- and post-evaluation study over a 12-month period. The intervention derived from aspects of cognitive-behavioral therapy for insomnia. The evaluation was questionnaire-based and assessed sleep parameters and well-being.Results: 104 parents returned completed questionnaires. The average time of sleep onset was 1 hour and 39 minutes pre-intervention and 20 minutes post-intervention. The average number of nights per week that children woke up was 3.9 pre-intervention and 0.9 post-intervention; the number of night awakenings fell from 1.9 to 0.5 and the time that children were awake after sleep onset fell from 66.8 minutes to 5.8 minutes. The average time that children were asleep was 8.0 hours per night pre-intervention and 10.2 hours post-intervention. The improvement in all sleep parameters was statistically significant (p<0.05). All parameters of parental and children’s well-being improved significantly (p<0.05), except for perceived ability to drive (p=0.07). All parents stated that they would recommend sleep support and 20% already had done so.Conclusions: The COVID-19 pandemic has accelerated the development of remote health care solutions, and in the case of children’s sleep clinics, the online mode of intervention delivery that is as effective, acceptable, and accessible as face-to-face delivery.

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Verbitsky, E. V. "Anxiety and sleep in experiment and clinic." Zhurnal nevrologii i psikhiatrii im. S.S. Korsakova 117, no. 4. Vyp. 2 (2017): 12. http://dx.doi.org/10.17116/jnevro20171174212-18.

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Camacho, Macario, Michael J. Ryhn, Christine S. Fukui, and Jennifer M. Bager. "Multidisciplinary sleep clinic: A patient-centered approach." CRANIO® 35, no. 2 (January 18, 2017): 129. http://dx.doi.org/10.1080/08869634.2017.1280246.

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Moran, Mark. "In the Clinic – REM Sleep Behavior Disorder." Neurology Today 17, no. 17 (September 2017): 22–23. http://dx.doi.org/10.1097/01.nt.0000524847.18215.22.

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Ali, Waleed, Guimin Gao, and George L. Bakris. "Improved Sleep Quality Improves Blood Pressure Control among Patients with Chronic Kidney Disease: A Pilot Study." American Journal of Nephrology 51, no. 3 (2020): 249–54. http://dx.doi.org/10.1159/000505895.

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Background: Despite the abundance of data documenting the consequences of poor sleep quality on blood pressure (BP), no previous study to our knowledge has addressed the impact of sleep improvement on resistant hypertension among patients with chronic kidney disease (CKD). Methods: The aim of this pilot study was to determine whether improved sleep quality and duration will improve BP control in patients with resistant hypertension and CKD. It was a prospective single-center cohort study that involved 30 hypertensive subjects with CKD presenting with primary resistant hypertension and poor sleep quality or duration <6 h/night. Sleep quality and duration were modified using either sleep hygiene education alone or adding sleep medication. The cohort’s BP was followed every 3 months for 6-month duration. The average home and clinic BPs were collected at each follow-up visit. The primary outcome baseline change in systolic BP (SBP) and diastolic BP (DBP; home and clinic) at 3 and 6 months after documented sleep improvement. Secondary outcomes included change from baseline in mean arterial pressure, and delta SBP after sleep improvement. Results: African American patients represented 50% of the cohort. All patients had evidence of CKD with GFR ≤60 mL/min and were obese with 40% having type 2 diabetes mellitus. The primary endpoint of change in clinic SBP and DBP was significantly reduced at 3 months, baseline 156 ± 15/88 ± 8 vs. 3 months 125 ± 14/73 ± 7 (p < 0.0001). This difference persisted at 6 months. However, there was no further reduction in-home or clinic BPs between the 3- and 6-month periods. Home and clinic average delta SBP change at 3 months from baseline was –34.4 ± 15 and –30.8 ± 19 mm Hg respectively. Delta SBP change was associated with sleep improvement of >6 h/night, that is, gaining an extra 3–4 h’ sleep duration, home; R2 = 0.66, p < 0.0001 and clinic; R2 = 0.49, p < 0.0001. Conclusion: Optimizing sleep quality and duration to >6 h/night improved BP control and was associated with a significant delta change in SBP within 3 months of follow-up. Physicians should obtain a sleep history in patients with CKD who present with resistant hypertension.

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Rong, Yi, Shihan Wang, Hui Wang, Feng Wang, Jingjing Tang, Xiuhong Kang, Guangxi Li, and Zhiguo Liu. "Validation of the NoSAS Score for the Screening of Sleep-Disordered Breathing in a Sleep Clinic." Canadian Respiratory Journal 2020 (January 11, 2020): 1–6. http://dx.doi.org/10.1155/2020/4936423.

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Background. There is a growing number of patients with sleep-disordered breathing (SDB) referred to sleep clinics. Therefore, a simple but useful screening tool is urgent. The NoSAS score, containing only five items, has been developed and validated in population-based studies. Aim. To evaluate the performance of the NoSAS score for the screening of SDB patients from a sleep clinic in China, and to compare the predictive value of the NoSAS score with the STOP-Bang questionnaire. Methods. We enrolled consecutive patients from a sleep clinic who had undergone apnea-hypopnea index (AHI) testing by type III portable monitor device at the hospital and completed the STOP-Bang questionnaire. The NoSAS score was assessed by reviewing medical records. Sensitivity, specificity, positive predictive value, negative predictive value, and area under the receiver operating characteristic curve (AUC) of both screening tools were calculated at different AHI cutoffs to compare the performance of SDB screening. Results. Of the 596 eligible patients (397 males and 199 female), 514 were diagnosed with SDB. When predicting overall (AHI ≥ 5), moderate-to-severe (AHI ≥ 15), and severe (AHI ≥ 30) SDB, the sensitivity and specificity of the NoSAS score were 71.2, 80.4, and 83.1% and 62.4, 49.3, and 40.7%, respectively. At all AHI cutoffs, the AUC ranged from 0.688 to 0.715 for the NoSAS score and from 0.663 to 0.693 for the STOP-Bang questionnaire. The NoSAS score had the largest AUC (0.715, 95% CI: 0.655–0.775) of diagnosing SDB at AHI cutoff of ≥5 events/h. NoSAS performed better in discriminating moderate-to-severe SDB than STOP-Bang with a marginally significantly higher AUC (0.697 vs. 0.663, P=0.046). Conclusion. The NoSAS score had good performance on the discrimination of SDB patients in sleep clinic and can be utilized as an effective screening tool in clinical practice.

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Killgore, William D. S., Vincent F. Capaldi, and Melanie L. Guerrero. "Nocturnal Polysomnographic Correlates of Daytime Sleepiness." Psychological Reports 110, no. 1 (February 2012): 63–72. http://dx.doi.org/10.2466/17.22.pr0.110.1.63-72.

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The relations of nighttime Polysomnographic sleep variables with daytime sleepiness scores on the Epworth Sleepiness Scale were assessed in a retrospective chart review of 38 patients referred to a sleep clinic. Of the variables assessed, only slow wave sleep was statistically significantly correlated with daytime sleepiness, regardless of whether the analysis was based on absolute minutes of slow wave sleep or percentage of total sleep time spent in slow wave sleep. Stepwise linear regression suggested that other Polysomnographic variables did not provide additional predictive value beyond the two indices of slow wave sleep. Apparently, reduced quantity of slow wave sleep was weakly but significantly related to increased daytime sleepiness among these sleep-clinic patients.

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Hoffstein, Victor. "Relationship Between Smoking and Sleep Apnea in Clinic Population." Sleep 25, no. 5 (August 2002): 517–22. http://dx.doi.org/10.1093/sleep/25.5.517.

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Warhurst, S., F. Sethna, E. Georgousopoulou, and C. Huang. "P131 Factors associated with Referral to Sleep Clinic and Diagnosis of Obstructive Sleep Apnoea in Pregnant People with Class III Obesity." SLEEP Advances 3, Supplement_1 (October 1, 2022): A72. http://dx.doi.org/10.1093/sleepadvances/zpac029.199.

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Abstract Background Obstructive Sleep Apnoea (OSA) in pregnancy is associated with increased maternal and neonatal morbidity. Evidence supporting use of traditional screening tools (e.g. Epworth Sleepiness Scale and STOP-BANG) in pregnancy is inconsistent, especially for people with class III obesity. This study aims to determine factors associated with referral to sleep clinic and diagnosis of OSA in pregnant people with class III obesity. Method Retrospective audit of records for people with class III obesity seen in high-risk pregnancy clinic at Canberra Hospital between 1/7/20 and 30/6/21. It will a) describe patient factors associated with referral to sleep clinic and b) describe patient factors associated with diagnosis of OSA (apnoea-hypopnoea index ≥5). Progress to date Approval to proceed as quality improvement project by ACT Health Ethics Committee. Data collection will be completed in 4-8 weeks. Preliminary results will be available by September-October 2022. Intended outcome and impact Clinical parameters associated with sleep clinic referral will be presented and compared to existing evidence. Initial data screening suggests that referral rates to sleep clinic are low and reasons for this will be explored. Clinical features associated with a diagnosis of OSA in those who proceeded for polysomnography will also be presented. Our results will inform local practice to determine if pregnant people with class III obesity are being appropriately referred to sleep clinic and objectively assessed for OSA. Our research will add to the limited research in this area and inform further prospective studies on effective screening in this population.

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Nowakowski, Sara, Manasa Kokonda, Rizwana Sultana, Brittany B. Duong, Sarah E. Nagy, Mohammed F. Zaidan, Mirza M. Baig, Bryan V. Grigg, Justin Seashore, and Rachel R. Deer. "Association between Sleep Quality and Mental Health among Patients at a Post-COVID-19 Recovery Clinic." Brain Sciences 12, no. 5 (April 30, 2022): 586. http://dx.doi.org/10.3390/brainsci12050586.

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A growing body of research documents the persistence of physical and neuropsychiatric symptoms following the resolution of acute COVID-19 infection. To the best of our knowledge, no published study has examined the interaction between insomnia and mental health. Accordingly, we proposed to examine new diagnoses of insomnia, and referrals to pulmonary and sleep medicine clinics for treatment of sleep disorders, in patients presenting to one post-acute COVID-19 recovery clinic. Additionally, we aimed to examine the relationship between poor sleep quality, depression, anxiety, and post-traumatic stress. Patients presented to the clinic on average 2 months following COVID-19 infection; 51.9% (n = 41) were hospitalized, 11.4% (n = 9) were in the intensive care unit, 2.5% (n = 2) were on a mechanical ventilator, and 38.0% (n = 30) were discharged on oxygen. The most commonly reported symptom was fatigue (88%, n = 70), with worse sleep following a COVID-19 infection reported in 50.6% (n = 40). The mean PSQI score was 9.7 (82.3%, n = 65 with poor sleep quality). The mean GAD-7 score was 8.3 (22.8%, n = 14 with severe depression). The mean PHQ-9 was 10.1 (17.8%, n = 18 with severe anxiety). The mean IES-6 was 2.1 (54.4%, n = 43 with post-traumatic stress). Poor sleep quality was significantly associated with increased severity of depression, anxiety, and post-traumatic stress. Future work should follow patients longitudinally to examine if sleep, fatigue, and mental health symptoms improve over time.

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Carpenter, Mary Katherine, Linda Sue Hammonds, and Carlie Frederick. "A Quality Improvement Project: Improving Sleep Quality and Duration Among Pediatric Mental Health Patients." Creative Nursing 27, no. 3 (August 1, 2021): 216–19. http://dx.doi.org/10.1891/crnr-d-19-00071.

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This article is a report of a project to improve the quality and duration of sleep among patients ages 3–17 years in an outpatient mental health clinic. The Pediatric Insomnia Severity Index (PISI) (now the Behavioral Sleep Medicine Clinic Sleep Questionnaire) was administered at baseline. Patients and parents were provided with education about the American Academy of Pediatrics sleep tips. Compliance with the sleep tips was tracked using an electronic health record (EHR) checklist. The PISI was administered again after the interventions and showed overall improvement in sleep quality and duration. Some patients experienced no change or a decline in sleep quality or duration and some had an increase in daytime somnolence.

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Jeon, J. Y., H. J. Moon, K. T. Kim, and Y. W. Cho. "Clinical risk factors for obstructive sleep apnea in a Korean sleep clinic." Sleep Medicine 64 (December 2019): S175. http://dx.doi.org/10.1016/j.sleep.2019.11.483.

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Arentson-Lantz, Emily, Ahmad Debian, Manasa Kokanda, Fidaa Shaib, and Sara Nowakowski. "707 Association of Self-Reported Anxiety, Informational Support, and Sleep in Sleep Medicine Patients during the COVID-19 Pandemic." Sleep 44, Supplement_2 (May 1, 2021): A276. http://dx.doi.org/10.1093/sleep/zsab072.705.

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Abstract Introduction Stressful events, such as the COVID-19 pandemic, can have a detrimental effect on sleep. It is important for practitioners to understand how their patients are affected by events to optimize their care. In this study we evaluated associations of anxiety and daily habits with self-reported sleep disturbance among sleep medicine clinic patients. Methods Between June-November 2020, 81 sleep medicine clinic patients (54.8±15.9 y, 44% male, 69% Caucasian) completed an online survey that included PROMIS measures (Sleep Disturbance, Sleep-Related Impairments, Informational Support, Emotional Distress-Anxiety) and Insomnia Severity Index (ISI). Patients were asked about changes in their daily habits (sunlight exposure, caffeine consumption). During the 5-month survey completion time window, the weekly average of positive COVID-19 cases in the Houston area was 2,914. Stepwise linear regression was performed using SAS to determine if self-reported anxiety and informational support predicted PROMIS Sleep Disturbance, PROMIS Sleep-Related Impairments and ISI. Results Anxiety had a significant effect on Sleep Disturbance (0.43 ± 0.11, p=0.0001), Sleep-Related Impairments (0.53 ± 0.12, p=0.0001) and ISI (0.28 ± 0.08, p=0.0004). Informational support had a significant inverse effect on Sleep Disturbance (-0.29 ± 0.10, p=0.0063), Sleep-Related Impairments (-0.26 ± 0.11, p=0.01) and ISI (-0.31 ± 0.08, p<0.0001) measures. Decreased sunlight exposure during the pandemic contributed to a significant increase in Sleep Disturbance scores (0.06 ± 0.03, p=0.045). Increased caffeine consumption during the pandemic had significant increase in ISI scores (16.3 ± 7.59, p=0.035). Conclusion Higher levels of anxiety and lower levels of informational support predicted greater insomnia severity, sleep disturbance, and sleep-related impairments in sleep medicine clinic patients during the COVID-19 pandemic. Decreased sunlight exposure and increased caffeine consumption also predicted greater sleep disturbance and insomnia severity, respectively. Addressing anxiety symptoms and access to accurate information during the pandemic is advised when treating sleep medicine clinic patients. Support (if any) This work is supported by National Institutes of Health (NIH) Grant # R01NR018342 (PI: Nowakowski) and by the Department of Veteran Affairs, Veterans Health Administration, Office of Research and Development, and the Center for Innovations in Quality, Effectiveness and Safety (CIN 13–413).

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Rosenberg, C., and K. Strohl. "0610 The Reverse Stroop Test applied in the Sleep Clinic." Sleep 41, suppl_1 (April 2018): A226. http://dx.doi.org/10.1093/sleep/zsy061.609.

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Rezayat, T., S. Vassar, S. Hakopian, and J. Wallace. "0715 Long-term CPAP Adherence In A Public Sleep Clinic." Sleep 43, Supplement_1 (April 2020): A272. http://dx.doi.org/10.1093/sleep/zsaa056.711.

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Abstract Introduction CPAP adherence may drop substantially over a long time frame. Since minorities including Hispanics and low socioeconomic groups have lower short-term acceptance and adherence, long-term adherence may also be reduced. We adapted a brief motivational enhancement education program (BMEEP) (Lai, CHEST 2014) in a Los Angeles County safety-net sleep clinic and found improved CPAP adherence at 3 months. We now report longitudinal long-term adherence over >=2 years. Our hypothesis: Many patients would meet CMS adherence criteria over >= 2 years. Methods During 3/1/2016 - 4/1/17, 118 patients completed BMEEP during CPAP initiation and were scheduled for a reinforcement session and routine clinic visits at 1 and 3 months and every 6 months thereafter. Electronic adherence and efficacy data were accessed each visit. Multivariate regression analyses explored association of adherence variables with demographic, clinical and workflow features. Results Baseline characteristics (mean (SD) or percent): Age 57.2 (17.8); Women 44.9%; Hispanic 69.5%, Non-Hispanic-White 22.9%, Other 5%, Black 3%; BMI 37; Epworth score 10.4 (6.05). Home sleep testing (69 patients) respiratory event indices were >=15/hr in 67% and >=30/hr in 57%. Polysomnography (81 patients) apnea hypopnea indices were (AHI) >= 15 in 78% and >=30/hr in 43%. By 7/1/2019, 23 (19%) patients were lost with unknown CPAP use status, while 76 (70.5%) of remaining patients continued to use CPAP. At 2 years, CPAP adherence parameters included: Average nightly use, 75% (27.7); Average hours/night, 4.74 (2.5); Average nightly use >=4 hours, 65.2% (31.6); >=70% nightly use >= 4 hours, 35 (51.5%). Average residual AHI was 2.05 (1.69). Adherence parameters in individual patients remained similar throughout 2 years. Long-term adherence was not associated with the demographic, clinical or workflow variables tested. Conclusion Programs that educate, motivate and provide regular follow-up for predominantly Hispanic low income populations can achieve acceptable long-term CPAP adherence rates. Support None

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Faber, Jasmin, Indra Steinbrecher-Hocke, Peter Bommersbach, and Angelika A. Schlarb. "Does media use before bedtime affect the sleep of psychosomatic rehabilitation patients?" Somnologie 24, no. 4 (November 10, 2020): 253–58. http://dx.doi.org/10.1007/s11818-020-00282-5.

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Abstract Objective Media use can affect sleep. However, research regarding various populations is sparse. The objective of this study was to examine the relationship between media use directly before bedtime and various sleep parameters in patients of a psychosomatic rehabilitation clinic. Methods Patients from a German psychosomatic rehabilitation clinic were tested regarding subjective sleep quality and insomnia symptoms based on questionnaires such as the Pittsburgh Sleep Quality Index (PSQI). Eligible patients also completed an additional sleep log over a period of 1 week. A total of 347 insomnia patients were enrolled, with a mean age of 49.77 years (range 22–64 years; median = 52 years). 57.5% of the patients were 50 years or older. Results Analysis showed that media use and various sleep diary parameters such as total sleep time (r = −0.386, p = 0.042; rTST2 = 0.149) and sleep efficiency (r = −0.507, p = 0.006; rSE2 = 0.257) were significantly associated. In detail, more media consumption was associated with less total sleep time and a lower sleep efficiency. The same result was found for media use and sleep efficiency on weekdays (r = −0.544, p = 0.002; rSE2 = 0.296), but not for other sleep parameters. However, media use time and subjective sleep quality were not significantly correlated, r = −0.055, p = 0.768. Conclusion This study, which is the first to examine the relation between media use and sleep in patients of a psychosomatic rehabilitation clinic, suggests a significant association between media use and sleep duration as well as sleep efficiency. However, more research is needed to investigate the relationship between media use and sleep in more detail, to increase patients’ quality of life and to incorporate these findings into the daily life of clinicians and therapists as well as into sleep hygiene education and sleep trainings.

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Takashima, M. "Practice of Sleep Medicine in the ENT Clinic." Nihon Kikan Shokudoka Gakkai Kaiho 71, no. 2 (April 10, 2020): 176–77. http://dx.doi.org/10.2468/jbes.71.176.

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Nolan, B. "Sleep-Disordered Breathing in Fatigued Postpoliomyelitis Clinic Patients." Yearbook of Neurology and Neurosurgery 2008 (January 2008): 185–86. http://dx.doi.org/10.1016/s0513-5117(08)79026-4.

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Yamamoto, H., H. Kawashima, and H. Tanaka. "Utility of somnolyzer G3 in Japanese sleep clinic." Sleep Medicine 64 (December 2019): S428—S429. http://dx.doi.org/10.1016/j.sleep.2019.11.1201.

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Andersen, Monica Levy, and Sergio Tufik. "Is thyroid screening of sleep clinic patients essential?" Sleep Medicine 13, no. 10 (December 2012): 1215–16. http://dx.doi.org/10.1016/j.sleep.2012.09.015.

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Dahan, Valerie, R. John Kimoff, Basil J. Petrof, Andrea Benedetti, Diane Diorio, and Daria A. Trojan. "Sleep-Disordered Breathing in Fatigued Postpoliomyelitis Clinic Patients." Archives of Physical Medicine and Rehabilitation 87, no. 10 (October 2006): 1352–56. http://dx.doi.org/10.1016/j.apmr.2006.07.256.

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Westerlund, Anna, Lena Brandt, Richard Harlid, Torbjörn Åkerstedt, and Ylva Trolle Lagerros. "Using the Karolinska Sleep Questionnaire to identify obstructive sleep apnea syndrome in a sleep clinic population." Clinical Respiratory Journal 8, no. 4 (January 20, 2014): 444–54. http://dx.doi.org/10.1111/crj.12095.

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Netzer, Nikolaus C. "Concomitant sleep disorders—a reason for in-clinic sleep studies in patients with obstructive sleep apnea?" Sleep and Breathing 9, no. 2 (May 20, 2005): 49. http://dx.doi.org/10.1007/s11325-005-0019-9.

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Brink, A., S. Munns, G. Nolan, and N. Pyne. "P025 Using questionnaires to predict OSA in patients presenting to sleep clinics." SLEEP Advances 3, Supplement_1 (October 1, 2022): A39—A40. http://dx.doi.org/10.1093/sleepadvances/zpac029.098.

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Abstract Purpose In sleep clinics, the Epworth Sleepiness Scale (ESS) and STOP-Bang (SB) questionnaire are widely used to determine the probability that a patient has obstructive sleep apnoea (OSA), though neither were designed as a triaging tool specifically for patients with suspected OSA. Previously we found that ESS had poor correlation with OSA presence and severity as determined by the apnoea-hypopnoea index (AHI) >15. In this paired clinical chart audit, we determined if the SB has improved predictive ability and thus better suitability for triaging sleep clinic patients suspected of OSA compared to ESS. Method 101 sleep clinic patients (56 male, 45 female) completed both ESS and SB questionnaires and underwent overnight polysomnography (OPSG) to determine AHI. Correlation of ESS and SB to AHI was determined using Spearman’s rho, and predictive ability of each questionnaire was determined using ROC curves and logistic regression. Results ESS was not significantly correlated to AHI in men (p=0.208) or women (p=0.533) and had poor sensitivity (60.2%) and specificity (47.8%). In contrast, SB was correlated to AHI in both men (p=<.001) and women (p=0.045), and had improved sensitivity (94.1%). An ESS>8 was not predictive of clinically significant OSA (AHI>15, p=0.244), whereas SB>3 was associated with 4.4 times higher odds of clinically significant OSA (p=.007). Discussion In our cohort, SB is more suitable than ESS for triaging patients presenting to sleep clinics due to its higher predictive ability for OSA. This finding has important implications for OPSG rebates and patient access to publicly funded treatment schemes.

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Eissa, Mohamed, Shikha Bansal, Rachael Bosma, Sarah Sheffe, Yen Shuang Law, Mary Mcloone, Tania Di Renna, and Mandeep Singh. "693 Sleep Health in the Young Adult Clinic: A retrospective observational cohort study." Sleep 44, Supplement_2 (May 1, 2021): A271. http://dx.doi.org/10.1093/sleep/zsab072.691.

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Abstract Introduction The Toronto Academic Pain Medicine Institute (TAPMI) Young Adult Clinic (YAC) was developed to offer transition services for clients aged 17–25 with persistent pain. It was noticed that YAC patients had significant problems with their sleep and the program was expanded in January 2019 by including a sleep medicine specialist for systematic evaluation of sleep health. Long-term sleep disruption has been associated with increase sensitivity to pain, prolonged pain duration, and predicts chronic pain. The degree of pain relief can directly impact the quality and disruption of sleep. Methods After approval from institutional review board, we reviewed YAC medical charts from March 2018 to April 2019 and extracted information pertaining to demographics, chronic pain and sleep. We present here the preliminary data of our multidisciplinary clinic Results 55 medical charts were reviewed which included 40 females, 13 males, 2 nonbinary individuals, with a mean age of 20.3±2.4 years. 53% of the patients had chronic widespread pain. Symptoms of or disorder of sleep were reported in 72.7% of the patients. The various nighttime disorders of sleep were trouble falling asleep, insomnia, problems with sleep initiation, difficulty in maintaining sleep, poor sleep continuity, frequent night awakenings due to pain, restless leg syndrome (RLS), obstructive sleep apnea, parasomnic behavior, circadian rhythm disorder such as delayed sleep phase disorder. As assessed by Epworth Sleepiness scale, 7% of the patients had mild, 7% had moderate and 2% had severe daytime sleepiness. 42% of the youths demonstrated a low self-efficacy score as per Pain Self Efficacy Questionnaire (PSEQ). Patient Health Questionnaire (PHQ-9) was used to measure the severity of depression which showed that 5.5%, 27%, 18%, 14.5%, 22% of the YAC patients suffered from minimal, mild, moderate, moderately-severe and severe depression respectively. The information collected on Pain Catastrophizing scale (PCS) suggested that 24%, 29% and 31% were at low, moderate, and high risk respectively in having catastrophizing thoughts and feelings related to pain. There was no statistical difference in the means PSEQ, PHQ-9 and PCS scores of young adults. Conclusion Sleep disturbances may be an important modifiable risk factor for alleviating distress in young adults with chronic pain. Support (if any):

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Garven, Alex, Shauna Brady, Susan Wood, Melinda Hatfield, Jennifer Bestard, Lawrence Korngut, and Cory Toth. "The Impact of Enrollment in a Specialized Interdisciplinary Neuropathic Pain Clinic." Pain Research and Management 16, no. 3 (2011): 159–68. http://dx.doi.org/10.1155/2011/518710.

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BACKGROUND: Chronic pain clinics have been created because of the increasing recognition of chronic pain as a very common, debilitating condition that requires specialized care. Neuropathic pain (NeP) is a multifaceted, specialized form of chronic pain that often requires input from multiple disciplines for assessment and management.OBJECTIVE: To determine the impact of an interdisciplinary clinic for evaluation and treatment of patients with NeP.METHODS: Patients with heterogeneous etiologies for NeP were prospectively evaluated using an interdisciplinary approach every six months. Diagnostic evaluation, comorbidity evaluation, education, and pharmacological and/or nonpharmacological management were completed. Severity (visual analogue scale) and features of pain (Modified Brief Pain Inventory), sleep difficulties (Medical Outcomes Study – Sleep Scale), mood/anxiety disruption (Hospital Anxiety and Depression Scale), quality of life (European Quality-of-Life Five-Domain index), health care resources use, patient satisfaction (Pain Treatment Satisfaction Scale and Neuropathic Pain Symptom Inventory) and self-perceived change in well-being (Patient Global Impression of Change scale) were examined at each visit.RESULTS: Pain severity only decreased after one year of follow-up, while anxiety and quality-of-life indexes improved after six months. Moderate improvements of sleep disturbance, less frequent medication use and reduced health care resource use were observed during enrollment at the NeP clinic.DISCUSSION: Despite the limitations of performing a real-world, uncontrolled study, patients with NeP benefit from enrollment in a small interdisciplinary clinic. Education and a complete diagnostic evaluation are hypothesized to lead to improvements in anxiety and, subsequently, pain severity. Questions remain regarding the long-term maintenance of these improvements and the optimal structure of specialized pain clinics.

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Jacobson, Natalie, Kathleen Antony, and Mihaela Bazalakova. "0577 Sleep Apnea in Pregnancy: What We Have Learned From the Sleep Pregnancy Clinic." Sleep 42, Supplement_1 (April 2019): A229—A230. http://dx.doi.org/10.1093/sleep/zsz067.575.

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Pagel, J. F., Steve Snyder, and Dawn Dawson. "Obstructive Sleep Apnea in Sleepy Pediatric Psychiatry Clinic Patients: Polysomnographic and Clinical Correlates." Sleep And Breathing 8, no. 3 (August 2004): 125–31. http://dx.doi.org/10.1055/s-2004-834482.

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Shenoy, B., B. Singh, G. Cadby, B. McQuillan, J. Hung, S. Rea, J. Walsh, et al. "O022 Long-term cardiovascular risk in obstructive sleep apnoea: a sleep clinic cohort study." SLEEP Advances 2, Supplement_1 (October 1, 2021): A10. http://dx.doi.org/10.1093/sleepadvances/zpab014.021.

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Abstract The relationship between obstructive sleep apnoea (OSA) and the development of long-term cardiovascular disease (CVD) is incompletely understood. We therefore investigated the impact of OSA severity, assessed by polysomnographic (PSG) metrics, on the development of long-term CVD in a sleep clinic cohort. Participants in the Western Australian Sleep Health Study, who attended a sleep clinic at a tertiary hospital between 2006 and 2010, were linked to state health administrative data from 1969 to 2016. Cox regression was used to investigate associations between standard PSG metrics of OSA severity (including the apnoea-hypopnoea index [AHI], time with oxygen saturation <90% [T90], and arousal index) and a CVD composite outcome (hospitalisation due to coronary heart disease, heart failure, stroke, or atrial fibrillation), controlling for baseline CVD risk factors such as age, sex, and body mass index (BMI). A total of 4067 participants were included: mean (SD) age of 50.6 (14.0) years, with 60.8% men. The mean BMI was 32.7 (7.7) kg/m². Over a median follow-up of 7.3 years, 584 (14.4%) participants developed the composite CVD outcome. Following adjustment for risk factors, independent predictors of incident CVD were an AHI ≥30 events/hour (hazard ratio [HR], 1.21; 95% CI, 1.02–1.45), log (T90 + 1) (HR, 1.16; 95% CI, 1.03–1.31), and the periodic limb movements of sleep index (PLMSI) (HR, 1.01; 95% CI, 1.00–1.01). We demonstrated independent effects of AHI, hypoxaemia, and PLMSI on incident CVD in this large sleep clinic cohort, suggesting multi-faceted aspects of disrupted sleep influence cardiovascular risk in OSA.

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Yu, C., J. Stonehouse, A. R. Turton, S. A. Joosten, and Garun S. Hamilton. "Prevalence and predictors of REM sleep without atonia in a sleep clinic population." Sleep and Biological Rhythms 19, no. 4 (June 18, 2021): 423–31. http://dx.doi.org/10.1007/s41105-021-00332-x.

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GURUBHAGAVATULA, INDIRA, GREG MAISLIN, and ALLAN I PACK. "An Algorithm to Stratify Sleep Apnea Risk in a Sleep Disorders Clinic Population." American Journal of Respiratory and Critical Care Medicine 164, no. 10 (November 15, 2001): 1904–9. http://dx.doi.org/10.1164/ajrccm.164.10.2103039.

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Ballou, Sarah, Eaman Alhassan, Elise Hon, Cara Lembo, Vikram Rangan, Prashant Singh, William Hirsch, Thomas Sommers, Judy Nee, and Anthony J. Lembo. "Tu1632 - Sleep Disturbance and Sleep Quality Among Patients Presenting to a Gastroenterology Clinic." Gastroenterology 154, no. 6 (May 2018): S—975. http://dx.doi.org/10.1016/s0016-5085(18)33276-1.

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Alemohammad, Z., and K. Sadeghniiat-Haghighi. "Comparing a portable sleep apnea screener with standard polysomnography in sleep clinic patients." Sleep Medicine 16 (December 2015): S75. http://dx.doi.org/10.1016/j.sleep.2015.02.191.

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Ju, Gawon, In-Young Yoon, Sang Don Lee, and Nayoung Kim. "Relationships between sleep disturbances and gastroesophageal reflux disease in Asian sleep clinic referrals." Journal of Psychosomatic Research 75, no. 6 (December 2013): 551–55. http://dx.doi.org/10.1016/j.jpsychores.2013.10.004.

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Sahrmann, Julie, David Cheung, Alvan Omeni, and Joseph Espiritu. "0965 No-show Rates To A Sleep Clinic: Drivers And Determinants." Sleep 42, Supplement_1 (April 2019): A388. http://dx.doi.org/10.1093/sleep/zsz067.962.

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Nurkowski, Joshua, Habiba Elshorbagy, Katelyn Halpape, Karen Jensen, Darcy Lamb, Eric Landry, Alfred Remillard, and Derek Jorgenson. "Impact of Pharmacist-Led Cognitive Behavioural Therapy for Chronic Insomnia." INNOVATIONS in pharmacy 11, no. 3 (August 3, 2020): 2. http://dx.doi.org/10.24926/iip.v11i3.3378.

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Background: Chronic insomnia is a common medical condition that negatively impacts quality of life and daytime function. Access to the first-line treatment for insomnia, cognitive behavioural therapy (CBT-i), is limited. Pharmacists are well positioned to provide this service, but evidence regarding pharmacist delivered CBT-i is sparse. The aim of this study was to evaluate the effectiveness of CBT-i delivered by pharmacists practicing in an outpatient clinic setting. Methods: This study was a retrospective chart audit of adult patients with chronic insomnia who received CBT-i from a pharmacist at one of two outpatient clinics in Canada. The primary endpoints were the differences between patient self-reported sleep diary parameters and utilization of hypnotic medications before and after CBT-i was delivered. The differences in patient reported sleep parameters were compared using Wilcoxon Signed Rank test and paired samples t-test and changes in hypnotic utilization was compared using McNemar Chi-square test. Results: 183 patients were referred for CBT-i and attended an initial appointment with a pharmacist. Of these, 105 did not receive the CBT-i. This resulted in 78 patients who met the inclusion criteria. Changes in sleep diary parameters were all statistically significantly improved after patients received CBT-i, except for total sleep time. Hypnotic medication use was also reduced. At baseline, 71.8% (n=56/78) of patients were taking one or more hypnotic medications compared to 52.6% (n=41/78) after CBT-i (p=0.0003). Discussion: The results of this study provide preliminary evidence that pharmacists working in an outpatient clinic setting may be able to effectively deliver CBT-i for patients with chronic insomnia. The external validity of these results is limited by the observational study design and the inclusion of pharmacists practicing in outpatient clinics, which is not the setting where most pharmacists currently practice. Conclusion: This observational study found improvements in sleep quality and efficiency, as well as, a reduction in hypnotic medication use, in patients who received CBT-i from pharmacists practicing in an outpatient clinic setting. Future randomized, controlled trials should evaluate the impact of CBT-i in a larger sample of patients, provided by pharmacists practicing in both outpatient clinics and community pharmacies. Original Research

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