bluuebunny/crossref_metadata_2025_split huggingface dataset:
0504 Identifying Risk Factors for Developing Sleep Disorders
Authors: Johnson Amanda , Gonsalves Vanessa , Walker Brittany , Santos Amanda , Araujo Leana Goncalves , Santos Anael , Ajayi Akinyemi 
Published: May 2022

Abstract

Introduction
Sleep disorders in the pediatric clinical setting are often overlooked and under-screened. The study compared a set of clinical behavior questions and physiological risk factors with potential to increase the risk for sleep disorders within children.

Methods
A retrospective archive from electronic medical records was analyzed from 695 pediatric patients, 7-14 years old, that visited a pediatric clinic from March-November of 2019. Children or their parents reported on the presence of eight behavioral and physiological factors on the Kids Sleep Screener Questionnaire (KSSQ), which were used as potential risk factors for sleep disorders. The propensity of daytime sleepiness was measured using the Epworth Sleepiness Scale for Children and Adolescents (ESS-CHAD). Univariate analysis was performed to find frequencies to summarize the risk factors. Chi square test was used to test for associations between risk factors and ESS-CHAD. Multiple logistic regression (MLR) was used to predict different combinations of factors with ESS-CHAD. Odd ratios (ORs) and 95% CI were used to quantify the level of association. Receiver operating characteristic (ROC) with area under the curve analysis was used to compare three MLR models.

Results
The risk factors were positively (p&lt;0.05) associated with ESS-CHAD. Excessive daytime sleepiness and increased sleep duration were risk factors with greater potential to predict sleep disorder. They presented 3 times greater (p&lt;0.05) potential to predict sleep disorder than snoring, and 4 times than restless sleep and sleep onset latency. The two combined risk factors with greatest potential to predict sleep disorder are restless sleep with excessive daytime sleepiness, and sleep onset delay with excessive daytime sleepiness.Risk for potential sleep disorders is best assessed when considering the different risk factors with gender. Considering gender, the risk factors with greatest relationship to predict potential sleep disorders were sleep duration, excessive daytime sleepiness, night wakings and the previous discussed combinations (restless sleep with excessive daytime sleepiness, and sleep onset delay with excessive daytime sleepiness).

Conclusion
The Kids Sleep Screener Questionnaire is a potential tool to predict sleep disorder. Further studies are warranted to explore the behavior and physiological risk factors with potential to increase the risk for sleep disorders.

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0505 Maintenance of Wakefulness Test Characteristics In Pediatric Populations With Central Hypersomnia
Authors: Wisniewski Benjamin , Witt Rochelle , Cole Melissa , Gurbani Neepa , Huang Guixia , Hossain Md Monir , Simakajornboon Narong 
Published: May 2022

Abstract

Introduction
Children with central hypersomnia often have residual daytime sleepiness despite treatment with medical therapies. The Maintenance of Wakefulness Test (MWT) is an objective measure used to assess daytime alertness and responsiveness to treatment in patients with hypersomnia. There are limited data on MWT characteristics among pediatric populations. The purpose of this study was to: (1.) Compare MWT characteristics and subjective assessment between patients who passed and failed the MWT; (2.) Determine clinical management changes following MWT.

Methods
A retrospective review was conducted of all children who underwent MWT at Cincinnati Children’s Hospital Medical Center from September, 2008 to June, 2021. Pass and fail assessment designations were determined by the clinician as recorded in the medical record. Demographics, Epworth Sleepiness Scores (ESS), MWT characteristics, and pharmacological modifications were recorded. A majority of patients underwent MWT prior to driving. Descriptive statistics as well as Chi-square, Fisher’s exact, and Wilcoxon rank-sum testing were utilized. All variables were reported as medians with interquartile ranges.

Results
109 MWTs were performed on 79 children with a median age of 17.7 years [16.6, 18.6]. MWTs were indicated for 4 primary diagnoses: hypersomnia (n=5), idiopathic hypersomnia (n=11), narcolepsy type 1 (n=56), and narcolepsy type 2 (n=37). 55 (50.5%) were documented as pass (P) and 54 as fail (F). No differences in age (17.5 years) [16.2,18.5] (P) vs. (17.8) [16.9,18.9] (F) (p=NS) or other demographics existed between the two groups. As expected, mean sleep latency was significantly higher among those who passed (37.3 minutes) [31.2,40.0] (P) vs. (10.8) [7.9,16.6] (F) (p&lt;0.001). However, no significant differences were observed in ESS 12.0 [8.0,17.0] (P) vs. 11.0 (6.0,14.0) (F) (p=NS). Pharmacologic adjustments were made in 42/54 (77.8%) (F) vs. 17/54 (31.5%) (P). Medications were not modified in 12/54 (22.2%) (F) assessments.

Conclusion
MWT provides useful objective assessment and often leads to management changes in adolescents with central hypersomnia. A subjective sleepiness assessment (ESS) does not correlate with objective MWT assessments. We speculate that an altered perception of sleepiness in children with hypersomnia may play a role in the inaccuracy of subjective assessments commonly utilized in clinical practice.

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Cincinnati Children’s Research Foundation.
0524 Polysomnographic Characteristics of Adolescent Patients with Class III Obesity and Severe OSA (AHI ≥30)
Authors: Strang Abigail , Crain Benjamin , Nguyen Linhda , Chidekel Aaron 
Published: May 2022

Abstract

Introduction
Adolescents with obesity are at increased risk for obstructive sleep apnea (OSA). Polysomnographic characteristics of pediatric patients with severe OSA (defined as AHI ≥30 events/hour) have not been frequently described. This study aims to describe clinical characteristics and polysomnographic data from a cohort of adolescents with both severe (class III, BMI ≥40 kg/m2) obesity and severe OSA.

Methods
This IRB-approved, retrospective review examines clinical and polysomnographic data from pediatric patients (ages 8-18) at Nemours Children’s Hospital, Wilmington, Delaware, who had initial baseline diagnostic polysomnogram performed from December 2012-September 2021. Subgroup analysis and descriptive statistics were performed in patients with severe OSA (AHI ≥30 events/hour).

Results
259 (mean age 15.2 years, range 8 – 18 years, 64.4% female, 40.2% white, 46.7% black, mean BMI 50.3 kg/m2) pediatric patients with severe obesity completed initial baseline diagnostic polysomnogram in the study period. Of these patients, 41/259 (15.8%) met criteria for severe OSA (mean age mean age 15.4 years, range 12 – 18 years, 43.9% female, 46.3% white, 43.9% black, mean BMI 53.7 kg/m2). Of these studies, the mean total AHI was 65.2 (range 31.4-159.4) events/hr, obstructive apnea index (OAI) of 11.4 (range 0 – 69.4) events/hr and hypopnea index of 47.8 (range 12.9 – 108.8) events/hour. Mean SpO2 nadir was 78.9 (range 52 – 98)% with peak ETCO2 of 53.2 (range 39 – 69) mmHg. 12/41 (29.2%) of patients met polysomnographic criteria for hypoventilation (EtCO2 &gt;50 mmHg for &gt;25% of TST). Sleep architecture was notable for decreased mean sleep efficiency at 62.8% and elevated arousal index (mean 62.4 arousals/hour).

Conclusion
Adolescents with both severe OSA and obesity demonstrated a high frequency of hypopneas compared to apneic events and disrupted sleep architecture with high arousal index and decreased sleep efficiency. Interestingly, even among those with severe OSA, ventilation was acceptable in a majority of the patients. Further analysis will be completed to correlate patient clinical characteristics, including co-morbidities and lung function measurements, to help identify which patients with severe obesity are at risk for the most severe OSA.

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None
0529 Average volume-assured pressure support as rescue therapy after CPAP failure in pediatric obstructive sleep apnea
Authors: Peng Victor , Hwig Nauras , Lasso-Pirot Anayansi , Isaiah Amal , Diaz-Abad Montserrat 
Published: May 2022

Abstract

Introduction
Average volume-assured pressure support with autotitrating EPAP (AVAPS-AE) is an automatically titrating mode of noninvasive ventilation (NIV) which provides a targeted tidal volume through adjustment of inspiratory pressures within a set range. In pediatric obstructive sleep apnea (OSA), adenotonsillectomy (AT) is often the first-line treatment and CPAP is often poorly tolerated as an alternative. We aimed to evaluate the efficacy of AVAPS as a potential option for children in whom CPAP titration is unsuccessful.

Methods
Retrospective review of records of children diagnosed with OSA with failed CPAP titration and in whom an in-laboratory AVAPS titration was performed.

Results
A total of 9 patients with OSA (8 male, age (95% CI) = 6.7 ± 2.6, BMI percentile (95% CI) = 81.0 ± 18.9) were identified. Of these patients, 6 had prior AT. All 9 patients had failed CPAP titration prior to AVAPS titration: 3 failed due to inability to control the apnea-hypopnea index (AHI, events/hour), 2 due to persistent hypercapnia, 2 due to treatment-emergent central sleep apneas, and 2 due to pressure intolerance. All 9 patients showed improvement in AHI following AVAPS titration (mean change = -17.9, 95% CI = 17.9 ± 9.5) as well as improvement in AHI from initial PSG to AVAPS titration (mean change = -42.5, 95% CI = 42.5 ±24.6). 7 patients had reduction in total sleep time with oximetry recording below 90% (T&lt;90) from CPAP to AVAPS titration (mean change = -4.7 minutes, 95% CI = 4.7 ± 14.7), while 8 patients had reduction in T&lt;90 from initial PSG to AVAPS titration (mean change = -14.0 minutes, 95% CI = 14.0 ±24.5). 7 patients had increase in REM sleep from CPAP to AVAPS titration (mean change = +15.9 minutes, 95% CI = 15.9 ±18.3), while 6 patients had increase in REM sleep from initial PSG to AVAPS titration (mean change = +7.7 minutes, 95% CI = 7.7 ±26.6).

Conclusion
In this case series of children with OSA and with failed CPAP titration, AVAPS is an effective treatment modality.

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0534 Dysphagia Severity is Associated with Worse Sleep Disordered Breathing in Infants with Trisomy 21
Authors: Cho Yeilim , DelRosso Lourdes , Sobremonte-King Michelle 
Published: May 2022

Abstract

Introduction
Hypotonia is common in infants with Trisomy 21. This can cause masticatory and oropharyngeal muscle weakness increasing the risk for dysphagia and sleep disordered breathing. Data describing the occurrence of dysphagia and sleep disordered breathing in infants with Trisomy 21 is limited. This study aims to determine the frequency and severity of dysphagia and its relationship to polysomnogram parameters in infants with Trisomy 21.

Methods
Retrospective chart review of patients with Trisomy 21 &lt;12 months old that underwent polysomnography at Seattle Children’s Hospital between October 1, 2015-August 23, 2021. Data collected included: sex, age, presence of dysphagia, recommended thickener type and polysomnographic data.

Results
A total of 526 polysomnograms in patients with Trisomy 21 were performed. Forty-one studies were identified in &lt;12 months old. Results in mean ± SD showed: age 6.5 months + 3, 66% were male and 73% were diagnosed with dysphagia through a video fluoroscopic swallow study. In those with dysphagia, 16% can tolerate thin liquids, 20% prescribed nectar-thick, 7% prescribed honey-thick and 57% were G-tube dependent. In patients with dysphagia compared to those without dysphagia: there was higher total AHI of 43.3 +/- 35.3 vs. 22.6 +/- 10.6 (p=0.006), oAHI of 39.7 +/- 35.5 vs. 17.2 +/- 11.6 (p=0.004), CAI of 3.4 +/- 3.4 vs. 3.4 +/- 1.8 (p=0.11), oxygen saturation nadir of 78.6 +/- 10.6 vs. 83.1 +/- 6.6 (p=0.11) and percentage total sleep time TcCO2 &gt;50 mmHg of 44.6 +/- 42.6 vs. 31 +/- 40.3 (p=0.44). Worse dysphagia was positively correlated with a higher oAHI (r=0.38, p=0.03).

Conclusion
There is a high incidence of dysphagia and sleep disordered breathing in infants with Trisomy 21. Dysphagia severity correlated with oAHI severity. Dysphagia in OSA can be due to the sensory and motor changes of the pharynx with impaired swallow-breathing mechanism. Chronic microaspiration can also result in decreased pulmonary reserve from lower airway inflammation or lung parenchymal disease, which may lead to worse sleep disordered breathing. Current guidelines suggest screening at school age or when there are clinical symptoms of OSA in Trisomy 21. However, results suggest the need to evaluate and intervene earlier especially in infants with dysphagia.

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0548 Behavioral Validation of the University of Michigan REM Behavior Disorder Questionnaire in the Synucleinopathies
Authors: Dworetz Alex , Trotti Lynn Marie , Bliwise Donald 
Published: May 2022

Abstract

Introduction
Questionnaires that inquire about REM sleep behavior disorder are typically validated by reference to polysomnographic findings of REM sleep without atonia. We sought validation for such a questionnaire by examining observed REM-based dream enactment over two nights in a sleep laboratory.

Methods
Participants with alpha-synucleinopathic disease underwent two consecutive nights of polysomnography attended by a single sleep technologist who was instructed to observe for and document any abnormal behaviors occurring out of sleep. We evaluated University of Michigan REM Behavior Disorder Questionnaire responses completed by either the participant or bed-partner prior to polysomnographic recording and analyzed associations between questionnaire responses and observational data in the sleep laboratory. We subsequently cross-validated the technologist’s observations with hypnogram tracings from nights when dream enactment was observed to determine whether the timing of observed behavior aligned with the timing of REM sleep.

Results
We studied 92 participants [idiopathic Parkinson’s disease, n = 67; Dementia with Lewy bodies, n = 14; Multiple Systems Atrophy, n = 3; Idiopathic REM sleep behavior disorder, n = 8]. Of 92 participants studied, 30 (32.61%) exhibited dream enactment during REM sleep observed on either night of polysomnographic recording (11 on both nights, 19 on one night). There was a statistically significant difference (p = 0.041 by 2-tailed test) in mean questionnaire scores between participants with observed dream enactment during REM sleep (mean score 0.43; [95% CI mean 0.34-0.52]) and those without dream enactment on either night (mean score 0.32; [95% CI mean 0.26-0.38]). When limiting the sample to participants whose questionnaire responses were derived from the bed-partner (n = 74), the difference approached, but did not reach, statistical significance (p = 0.066).

Conclusion
These data provide further validation of the University of Michigan REM Behavior Disorder Questionnaire as a useful tool in evaluating REM-based dream enactment behavior in patients with alpha-synucleinopathic disease.

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0559 Prevalence of Cannabis Use in Patients with Restless Leg Syndrome for Symptomatic Relief
Authors: Kachechian Talar , Jamil Saad Bin , Armache Maria , Fleet Benjamin , Grewal Ritu 
Published: May 2022

Abstract

Introduction
Restless leg syndrome (RLS) can be debilitating and have a significant negative impact on sleep. Most patients respond well to dopamine agonists, alpha 2 delta ligands, iron supplementation, and opioids. Some patients report persistent symptoms despite using recommended therapies.

Methods
We investigated the prevalence of cannabis use and its potential therapeutic effects in patients with RLS through a retrospective chart review over a three-year period. All patients with diagnosis of RLS and cannabis/marijuana use listed in the electronic health record were included. Data was collected from each patient's chart pertaining to the prevalence of cannabis use including method of use and frequency, patient demographics, use of certain medications, and whether they found symptom relief when using cannabis.

Results
41 patients were identified who has a diagnosis of RLS and cannabis use. 25 of 41 (61%) were using medical marijuana and 8 of 41 (20%) were using marijuana recreationally. 12 of 41 (29.3%) patients found overall relief in their sleep while 4 (9.7%) patients did not and 25 (61%) patients we were unable to determine through chart review.Among the patients who were using medial marijuana, 5 patients were using it for pain and insomnia, 4 patients were using it for RLS, and 4 patients were using it for anxiety. 3 out of 4 (75%) patients who were using medical marijuana for RLS reported regular use. 3 of the patients inhaled cannabis while the remaining patient used an ointment containing cannabis. 2 of the 4 (50%) found symptom relief of RLS when using medical marijuana. 1 patient did not find relief with marjiuana but found relief when using Methadone instead. The remaining 3 patients also used Gabapentin and 2 of the 3 (67%) patients found symptom relief with the addition of a dopamine agonist.

Conclusion
Patients with RLS may use Cannabis for symptomatic relief. We believe this association should be recognized by sleep physicians and documented when conducting their patient's history.

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0567 When Loud Sleep Aids a Silent Killer: A Prevalence Study on Obstructive Sleep Apnoea in Type-2 Diabetics from a Tertiary Care Hospital in Western India
Authors: Desai Khushi , Ghanchi Firoj , Rami Kinjal 
Published: May 2022

Abstract

Introduction
Type-2 diabetes mellitus is a highly prevalent multisystemic disorder having bidirectional association with Obstructive sleep apnoea. These disorders, when present as co-morbidities, can lead to life-threatening cardiovascular complications. The current prevalence of Obstructive sleep apnoea in Type-2 diabetics is largely unknown, especially in developing nations like India. This study was aimed at determining its prevalence and other risk factors in Type-2 diabetics visiting a tertiary-care hospital in Western India.

Methods
Adult patients with Type 2 diabetes mellitus visiting the Departments of Pulmonary medicine and Non-communicable diseases on an out-patient basis at a tertiary-care hospital were recruited for the study. Those with unstable medical illnesses or other forms of diabetes were excluded. Participants were interviewed and examined based on a case-study form, including Epworth Sleepiness Scale, STOP-BANG and OSA-50 questionnaires, followed by a Home Sleep Apnoea Test. Apnoea-Hypopnoea Index(AHI) was used to evaluate for Obstructive sleep apnoea.

Results
A sample of 62 diabetics (median age: 61(16) years; 34 males; 28 females) was analysed. Obstructive sleep apnoea(Apnea-Hypopnea Index [AHI] ≥ 5.0/h) was diagnosed in 55 subjects(88.7%, median AHI – 20.95/h). 62.9% had moderate-to severe Obstructive sleep apnoea(OSA)(AHI ≥ 15/h), 21% had positional OSA and 48.4% had OSA syndrome(OSAS). AHI had significant positive correlation with waist circumference(rho- 0.318, p- 0.012), neck circumference(rho-0.363, p-0.004), Modified Mallampati score(rho-0.372, p-0.003) and Epworth Sleepiness Scale(rho-0.403, p-0.001). No significant association of glycaemic control, duration of Type-2 diabetes and Random Blood Sugar level with AHI was identified. Sensitivity and specificity of STOP-BANG questionnaire for diagnosing OSA was 69.1% and 71.4% and that of OSA-50 questionnaire was 94.5% and 14.3%, respectively.

Conclusion
Obstructive sleep apnoea(OSA) is more prevalent in adult population with Type-2 diabetes mellitus(T2DM) than in the general population. A high index of suspicion for OSA in patients with T2DM is warranted, because they may not have overt daytime sleepiness or presence of high-risk predictors. Waist and neck circumferences are better predictors of OSA syndrome than body mass index(BMI). Home Sleep Apnoea Test is a more reliable test for OSA detection compared to screening questionnaires and hence can be a useful tool for diagnosis and management planning of OSA in high-burden, low-resource settings.

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0569 COVID-19 and Fatigue: Does Fatigue Persist Beyond Diagnosis?
Authors: Muench Alexandria , Boyle Julia , Reddy Varudhini , Thompson Michelle , Perlis Michael , Vargas Ivan 
Published: May 2022

Abstract

Introduction
While it is not surprising that COVID is associated with increased fatigue, there is emerging data that COVID-19 symptoms extend well beyond the acute illness period. This phenomenon, known as “Long COVID”, may include fatigue (persistent fatigue post viral infection). The present analysis was undertaken to evaluate fatigue in subjects with and without COVID-19 virus at two time points separated by ~ one year’s time.

Methods
The parent study was a large online study of subjects during the COVID lockdown which was designed to evaluate the effects of social distancing on mood and sleep (n=4052; 3,184 women; X̅age= 46.0 years). The proband subsample of interest was the subjects that reported having COVID as compared to matched controls (whole sample n=242; 195 women [80.6% female]; 206 identified primarily as white [85.1%]; X̅age=42.0 years). Subjects who reported testing positive for COVID-19 provided additional information on COVID-19 symptoms (e.g., severity and duration per symptom). The PROMIS Fatigue scale was administered at time one (T1: April-June 2020) and one year later (T2: January-March 2021). Control subjects were matched based on age, sex, and race to reduce potential confounding or effect modification by these variables.

Results
The mean PROMIS Fatigue scores for the COVID-19 group and Control groups at baseline (T1) were X̅=52.9 + 8.2 (n=121) and X̅=50.7 + 10.4, (n=121), p&lt;0.06, respectively. The mean PROMIS scores for the COVID-19 group and Control groups at follow-up (T2) were X̅=55.3 + 8.7 (n=121) and X̅=52.6 + 8.4, (n=121), p&lt;0.017, respectively. Overall, the groups were found to significantly differ at both time points, p&lt;0.001. No group-by-time interaction was observed. Both groups exhibited a small increase in fatigue from T1 to T2, p&lt;0.716.

Conclusion
As expected, there were significant differences in patient reported fatigue between the COVID-19 and the control group. The between group differences were modest. Significant and large scale group differences were not evident for T2 (during follow-up). This suggests that COVID is associated with increased fatigue but we did not detect “Long COVID” effects. This may be due to methodologic considerations. In order to observe “Long COVID” the data will need to be anchored to illness onset and offset.

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