scholarly journals P029 Home video sleep recording as a screening tool for paediatric obstructive sleep apnoea

2021 ◽  
Vol 2 (Supplement_1) ◽  
pp. A30-A31
Author(s):  
C Daniels ◽  
N Kapur ◽  
L Gauld
Keyword(s):  
Scoring System ◽  
Screening Tool ◽  
Sleep Onset ◽  
Area Under The Curve ◽  
Healthy Children ◽  
Full Data ◽  
Neck Extension ◽  
Adenotonsillar Hypertrophy ◽  
Home Based ◽  
Obstructive Sleep

Abstract Introduction Polysomnography (PSG) remains gold standard for assessment of paediatric OSA, despite limitations. Home-based video sleep recordings offer a promising screening tool that would be relatively simple and inexpensive but have been minimally investigated. This study aims to assess the ability of short home-based video sleep recordings to predict PSG-diagnosed OSA in a population of healthy children. Methods Healthy children aged 1–18 years undergoing PSG to assess for OSA were recruited. Those with comorbidities likely to cause/exacerbate OSA, aside from adenotonsillar hypertrophy and obesity, were excluded. Thirty-minute video recordings of sleep shortly after sleep onset capturing the face and exposed torso were obtained. A previously validated scoring system was modified to include six parameters: snore, inspiratory noise, respiratory events, respiratory effort, mouth breathing and neck extension. Results We report interim results of this ongoing study. Of the 51 children meeting inclusion criteria, videos for 44 (28M, mean (SD) age 8.58 (2.96) years) were deemed satisfactory and analysed. Four (9%) children had OAHI >5 episodes/h on PSG and median Total Video Score (TVS) was 0 (IQR 0–1). TVS and OAHI >5 episodes/h on PSG showed a statistically significant association (OR 2.782, p=0.006) with area under the curve of 0.847. TVS ≥4 showed sensitivity of 75% and specificity of 100% for OAHI >5 episodes/h. Discussion This video scoring system, when applied to short home-based video sleep recordings, showed acceptable diagnostic accuracy for PSG-diagnosed OSA. Full data analysis will further clarify the role of this modality as a screening tool for paediatric OSA.

scholarly journals Cardiorespiratory Polygraphy for Detection of Obstructive Sleep Apnea in Patients With Atrial Fibrillation

2021 ◽  
Vol 8 ◽  
Author(s):  
Michiel Delesie ◽  
Lieselotte Knaepen ◽  
Johan Verbraecken ◽  
Karolien Weytjens ◽  
Paul Dendale ◽  
...  
Keyword(s):  
Atrial Fibrillation ◽  
Obstructive Sleep Apnea ◽  
Sleep Apnea ◽  
Screening Tool ◽  
Area Under The Curve ◽  
Screening Tools ◽  
Apnea Hypopnea Index ◽  
Automated Algorithm ◽  
Obstructive Sleep ◽  
At Home

Background: Obstructive sleep apnea (OSA) is a modifiable risk factor of atrial fibrillation (AF) but is underdiagnosed in these patients due to absence of good OSA screening pathways. Polysomnography (PSG) is the gold standard for diagnosing OSA but too resource-intensive as a screening tool. We explored whether cardiorespiratory polygraphy (PG) devices using an automated algorithm for Apnea-Hypopnea Index (AHI) determination can meet the requirements of a good screening tool in AF patients.Methods: This prospective study validated the performance of three PGs [ApneaLink Air (ALA), SOMNOtouch RESP (STR) and SpiderSAS (SpS)] in consecutive AF patients who were referred for PSG evaluation. Patients wore one of the three PGs simultaneously with PSG, and a different PG during each of three consecutive nights at home. Severity of OSA was classified according to the AHI during PSG (<5 = no OSA, 5–14 = mild, 15–30 = moderate, >30 = severe).Results: Of the 100 included AF patients, PSG diagnosed at least moderate in 69% and severe OSA in 33%. Successful PG execution at home was obtained in 79.1, 80.2 and 86.8% of patients with the ALA, STR and SpS, respectively. For the detection of clinically relevant OSA (AHI ≥ 15), an area under the curve of 0.802, 0.772 and 0.803 was calculated for the ALA, STR and SpS, respectively.Conclusions: This study indicates that home-worn PGs with an automated AHI algorithm can be used as OSA screening tools in AF patients. Based on an appropriate AHI cut-off value for each PG, the device can guide referral for definite PSG diagnosis.

scholarly journals Development of a Minimally Invasive Screening Tool to Identify Obese Pediatric Population at Risk of Obstructive Sleep Apnea/Hypopnea Syndrome

2020 ◽  
Vol 7 (4) ◽  
pp. 131
Author(s):  
José Miguel Calderón ◽  
Julio Álvarez-Pitti ◽  
Irene Cuenca ◽  
Francisco Ponce ◽  
Pau Redon
Keyword(s):  
Obstructive Sleep Apnea ◽  
Logistic Regression ◽  
Sleep Apnea ◽  
Screening Tool ◽  
Pediatric Population ◽  
Sleep Apnea Syndrome ◽  
Area Under The Curve ◽  
Support Vector ◽  
Obstructive Sleep ◽  
Logistic Regression Algorithm

Obstructive sleep apnea syndrome is a reduction of the airflow during sleep which not only produces a reduction in sleep quality but also has major health consequences. The prevalence in the obese pediatric population can surpass 50%, and polysomnography is the current gold standard method for its diagnosis. Unfortunately, it is expensive, disturbing and time-consuming for experienced professionals. The objective is to develop a patient-friendly screening tool for the obese pediatric population to identify those children at higher risk of suffering from this syndrome. Three supervised learning classifier algorithms (i.e., logistic regression, support vector machine and AdaBoost) common in the field of machine learning were trained and tested on two very different datasets where oxygen saturation raw signal was recorded. The first dataset was the Childhood Adenotonsillectomy Trial (CHAT) consisting of 453 individuals, with ages between 5 and 9 years old and one-third of the patients being obese. Cross-validation was performed on the second dataset from an obesity assessment consult at the Pediatric Department of the Hospital General Universitario of Valencia. A total of 27 patients were recruited between 5 and 17 years old; 42% were girls and 63% were obese. The performance of each algorithm was evaluated based on key performance indicators (e.g., area under the curve, accuracy, recall, specificity and positive predicted value). The logistic regression algorithm outperformed (accuracy = 0.79, specificity = 0.96, area under the curve = 0.9, recall = 0.62 and positive predictive value = 0.94) the support vector machine and the AdaBoost algorithm when trained with the CHAT datasets. Cross-validation tests, using the Hospital General de Valencia (HG) dataset, confirmed the higher performance of the logistic regression algorithm in comparison with the others. In addition, only a minor loss of performance (accuracy = 0.75, specificity = 0.88, area under the curve = 0.85, recall = 0.62 and positive predictive value = 0.83) was observed despite the differences between the datasets. The proposed minimally invasive screening tool has shown promising performance when it comes to identifying children at risk of suffering obstructive sleep apnea syndrome. Moreover, it is ideal to be implemented in an outpatient consult in primary and secondary care.

Physical and emotional disturbances in children with adenotonsillar hypertrophy

2007 ◽  
Vol 122 (9) ◽  
pp. 931-935 ◽  
Author(s):  
P Kurnatowski ◽  
L Putyński ◽  
M Łapienis ◽  
B Kowalska
Keyword(s):  
Trait Anxiety ◽  
Sleep Disordered Breathing ◽  
The State ◽  
Healthy Children ◽  
State Trait Anxiety Inventory ◽  
Emotional Instability ◽  
Adenotonsillar Hypertrophy ◽  
Obstructive Sleep ◽  
Obstructive Sleep Disordered Breathing ◽  
Disordered Breathing

AbstractObjective:Enlarged tonsils and adenoids (part of Waldeyer's ring) are responsible for obstructive sleep disordered breathing. Obstructive sleep disordered breathing episodes lead to hypoxaemia, hypercapnia and a state of arousal, all of which affect normal development of the nervous system. In this study, two hypotheses were tested: (1) obstructive sleep disordered breathing is caused by adenotonsillar hypertrophy and is associated with hypoxia and brain dysfunction; and (2) children with obstructive sleep disordered breathing more commonly display emotional lability, depressive behaviour and anxiety.Material and methods:A total of 225 children were examined. The study group consisted of 121 children with adenotonsillar hypertrophy (87 aged six to nine years and 34 aged 10 to 13 years) and with obstructive sleep apnoeas and hypopnoeas confirmed by polysomnography. Patients were compared with 104 children with no obstructive sleep disordered breathing and no adenotonsillar hypertrophy (74 aged six to nine years and 30 aged 10 to 13 years). The following tests were used to measure the children's emotional disorders: the children's depression inventory; the state-trait anxiety inventory for children; and the emotional instability scale. The average values and standard deviations were calculated for all results. Student's t-test was used to compare differences in all groups of children. The minimum level of p < 0.05 was set as statistically significant.Results:Children with adenotonsillar hypertrophy are more likely to experience poor brain development and sleep problems. They also have emotional disturbances. In the sick and healthy children aged six to nine years, mean results for the emotional instability scale were statistically significantly different in the two groups, being higher in children with adenotonsillar hypertrophy than in healthy children. Mean values for the children's depression inventory test were higher in children with adenotonsillar hypertrophy, but the differences were not statistically significant. In the state-trait anxiety inventory for children test, the mean T score was T = 1.760 and the level of significance was p = 0.08 for both groups. Since the standard level of significance was p < 0.05, the differences in mean values for the state-trait anxiety inventory for children test bordered on statistical significance. There were no differences between tests results in the older children (10 to 13 years).Conclusions:Recent studies have confirmed the negative emotional effect of adenotonsillar hypertrophy induced obstructive sleep disordered breathing in children aged six to nine years. The main problems are emotional lability, and anxiety and depressive disturbances. Such emotional problems subside in older children (aged 10 to 13 years).

scholarly journals Development of a practical prediction score for acute renal injury after surgery for Stanford type A aortic dissection

2020 ◽  
Vol 30 (5) ◽  
pp. 746-753
Author(s):  
Ning Dong ◽  
Hulin Piao ◽  
Yu Du ◽  
Bo Li ◽  
Jian Xu ◽  
...  
Keyword(s):  
Aortic Dissection ◽  
Risk Score ◽  
Scoring System ◽  
Characteristic Curve ◽  
Area Under The Curve ◽  
Kidney Injury ◽  
Type A ◽  
Postoperative Management ◽  
Prediction Score ◽  
Improve Patient

Abstract OBJECTIVES Acute kidney injury (AKI) is a common complication of cardiovascular surgery that is associated with increased mortality, especially after surgeries involving the aorta. Early detection and prevention of AKI in patients with aortic dissection may help improve outcomes. The objective of this study was to develop a practical prediction score for AKI after surgery for Stanford type A acute aortic dissection (TAAAD). METHODS This was a retrospective cohort study that included 2 independent hospitals. A larger cohort of 326 patients from The Second Hospital of Jilin University was used to identify the risk factors for AKI and to develop a risk score. The derived risk score was externally validated in a separate cohort of 102 patients from the other hospital. RESULTS The scoring system included the following variables: (i) age &gt;45 years; (ii) body mass index &gt;25 kg/m2; (iii) white blood cell count &gt;13.5 × 109/l; and (iv) lowest perioperative haemoglobin &lt;100 g/l, cardiopulmonary bypass duration &gt;150 min and renal malperfusion. On receiver operating characteristic curve analysis, the score predicted AKI with fair accuracy in both the derivation [area under the curve 0.778, 95% confidence interval (CI) 0.726–0.83] and the validation (area under the curve 0.747, 95% CI 0.657–0.838) cohorts. CONCLUSIONS We developed a convenient scoring system to identify patients at high risk of developing AKI after surgery for TAAAD. This scoring system may help identify patients who require more intensive postoperative management and facilitate appropriate interventions to prevent AKI and improve patient outcomes.

scholarly journals Initiation of therapy for obstructive sleep apnea syndrome: a randomized comparison of outcomes of telemetry-supported home-based vs. sleep lab-based therapy initiation

2021 ◽  
Author(s):  
Ingo Fietze ◽  
Sebastian Herberger ◽  
Gina Wewer ◽  
Holger Woehrle ◽  
Katharina Lederer ◽  
...  
Keyword(s):  
Obstructive Sleep Apnea ◽  
Sleep Apnea ◽  
Control Group ◽  
Sleep Laboratory ◽  
Home Therapy ◽  
Home Management ◽  
Therapy Initiation ◽  
Home Based ◽  
Obstructive Sleep ◽  
At Home

Abstract Purpose Diagnosis and treatment of obstructive sleep apnea are traditionally performed in sleep laboratories with polysomnography (PSG) and are associated with significant waiting times for patients and high cost. We investigated if initiation of auto-titrating CPAP (APAP) treatment at home in patients with obstructive sleep apnea (OSA) and subsequent telemonitoring by a homecare provider would be non-inferior to in-lab management with diagnostic PSG, subsequent in-lab APAP initiation, and standard follow-up regarding compliance and disease-specific quality of life. Methods This randomized, open-label, single-center study was conducted in Germany. Screening occurred between December 2013 and November 2015. Eligible patients with moderate-to-severe OSA documented by polygraphy (PG) were randomized to home management or standard care. All patients were managed by certified sleep physicians. The home management group received APAP therapy at home, followed by telemonitoring. The control group received a diagnostic PSG, followed by therapy initiation in the sleep laboratory. The primary endpoint was therapy compliance, measured as average APAP usage after 6 months. Results The intention-to-treat population (ITT) included 224 patients (110 home therapy, 114 controls); the per-protocol population (PP) included 182 patients with 6-month device usage data (89 home therapy, 93 controls). In the PP analysis, mean APAP usage at 6 months was not different in the home therapy and control groups (4.38 ± 2.04 vs. 4.32 ± 2.28, p = 0.845). The pre-specified non-inferiority margin (NIM) of 0.3 h/day was not achieved (p = 0.130); statistical significance was achieved in a post hoc analysis when NIM was set at 0.5 h/day (p < 0.05). Time to APAP initiation was significantly shorter in the home therapy group (7.6 ± 7.2 vs. 46.1 ± 23.8 days; p < 0.0001). Conclusion Use of a home-based telemonitoring strategy for initiation of APAP in selected patients with OSA managed by sleep physicians is feasible, appears to be non-inferior to standard sleep laboratory procedures, and facilitates faster access to therapy.

The effect of 4-h versus 6-h time restricted feeding on sleep quality, duration, insomnia severity and obstructive sleep apnea in adults with obesity

2021 ◽  
pp. 026010602110023
Author(s):  
Sofia Cienfuegos ◽  
Kelsey Gabel ◽  
Faiza Kalam ◽  
Mark Ezpeleta ◽  
Vicky Pavlou ◽  
...  
Keyword(s):  
Obstructive Sleep Apnea ◽  
Sleep Apnea ◽  
Sleep Quality ◽  
Sleep Onset ◽  
Control Group ◽  
Sleep Onset Latency ◽  
Restricted Feeding ◽  
Wake Time ◽  
Obstructive Sleep ◽  
Insomnia Severity

Background: Time restricted feeding (TRF) involves deliberately restricting the times during which energy is ingested. Preliminary findings suggest that 8–10-h TRF improves sleep. However, the effects of shorter TRF windows (4–6 h) on sleep, remain unknown. Aims: This study compared the effects of 4-h versus 6-h TRF on sleep quality, duration, insomnia severity and the risk of obstructive sleep apnea. Methods: Adults with obesity ( n = 49) were randomized into one of three groups: 4-h TRF (eating only between 3 and 7 p.m.), 6-h TRF (eating only between 1 and 7 p.m.), or a control group (no meal timing restrictions) for 8 weeks. Results: After 8 weeks, body weight decreased ( p < 0.001) similarly by 4-h TRF (–3.9 ± 0.4 kg) and 6-h TRF (–3.4 ± 0.4 kg), versus controls. Sleep quality, measured by the Pittsburgh Sleep Quality Index (PSQI), did not change by 4-h TRF (baseline: 5.9 ± 0.7; week 8: 4.8 ± 0.6) or 6-h TRF (baseline: 6.4 ± 0.8; week 8: 5.3 ± 0.9), versus controls. Wake time, bedtime, sleep duration and sleep onset latency also remained unchanged. Insomnia severity did not change by 4-h TRF (baseline: 4.4 ± 1.0; week 8: 4.7 ± 0.9) or 6-h TRF (baseline: 8.3 ± 1.2; week 8: 5.5 ± 1.1), versus controls. Percent of participants reporting obstructive sleep apnea symptoms did not change by 4-h TRF (baseline: 44%; week 8: 25%) or 6-h TRF (baseline: 47%; week 8: 20%), versus controls. Conclusion: These findings suggest that 4- and 6-h TRF have no effect on sleep quality, duration, insomnia severity, or the risk of obstructive sleep apnea.

scholarly journals Snoring: a source of noise pollution and sleep apnea predictor

SLEEP ◽  
2019 ◽  
Vol 43 (6) ◽  
Author(s):  
Mudiaga Sowho ◽  
Francis Sgambati ◽  
Michelle Guzman ◽  
Hartmut Schneider ◽  
Alan Schwartz
Keyword(s):  
Sleep Apnea ◽  
Operating Characteristic ◽  
Area Under The Curve ◽  
Noise Pollution ◽  
Apnea Hypopnea Index ◽  
Sleep Study ◽  
Sound Levels ◽  
Obstructive Sleep ◽  
Single Night ◽  
The Relationship

Abstract Snoring is a highly prevalent condition associated with obstructive sleep apnea (OSA) and sleep disturbance in bed partners. Objective measurements of snoring in the community, however, are limited. The present study was designed to measure sound levels produced by self-reported habitual snorers in a single night. Snorers were excluded if they reported nocturnal gasping or had severe obesity (BMI &gt; 35 kg/m2). Sound was measured by a monitor mounted 65 cm over the head of the bed on an overnight sleep study. Snoring was defined as sound ≥40 dB(A) during flow limited inspirations. The apnea hypopnea index (AHI) and breath-by-breath peak decibel levels were measured. Snore breaths were tallied to determine the frequency and intensity of snoring. Regression models were used to determine the relationship between objective measures of snoring and OSA (AHI ≥ 5 events/h). The area under the curve (AUC) for the receiver operating characteristic (ROC) was used to predict OSA. Snoring intensity exceeded 45 dB(A) in 66% of the 162 participants studied, with 14% surpassing the 53 dB(A) threshold for noise pollution. Snoring intensity and frequency were independent predictors of OSA. AUCs for snoring intensity and frequency were 77% and 81%, respectively, and increased to 87% and 89%, respectively, with the addition of age and sex as predictors. Snoring represents a source of noise pollution in the bedroom and constitutes an important target for mitigating sound and its adverse effects on bed partners. Precise breath-by-breath identification and quantification of snoring also offers a way to risk stratify otherwise healthy snorers for OSA.

Rural Barriers to Surgical Care for Children With Sleep-Disordered Breathing

2021 ◽  
pp. 019459982199338
Author(s):  
Flora Yan ◽  
Dylan A. Levy ◽  
Chun-Che Wen ◽  
Cathy L. Melvin ◽  
Marvella E. Ford ◽  
...  
Keyword(s):  
Logistic Regression ◽  
Regression Analysis ◽  
Sleep Disordered Breathing ◽  
Healthy Children ◽  
Loss To Follow Up ◽  
Cox Regression Analysis ◽  
Obstructive Sleep ◽  
The Impact ◽  
Disordered Breathing

Objective To assess the impact of rural-urban residence on children with obstructive sleep-disordered breathing (SDB) who were candidates for tonsillectomy with or without adenoidectomy (TA). Study Design Retrospective cohort study. Setting Tertiary children’s hospital. Methods A cohort of otherwise healthy children aged 2 to 18 years with a diagnosis of obstructive SDB between April 2016 and December 2018 who were recommended TA were included. Rural-urban designation was defined by ZIP code approximation of rural-urban commuting area codes. The main outcome was association of rurality with time to TA and loss to follow-up using Cox and logistic regression analyses. Results In total, 213 patients were included (mean age 6 ± 2.9 years, 117 [55%] male, 69 [32%] rural dwelling). Rural-dwelling children were more often insured by Medicaid than private insurance ( P < .001) and had a median driving distance of 74.8 vs 16.8 miles ( P < .001) compared to urban-dwelling patients. The majority (94.9%) eventually underwent recommended TA once evaluated by an otolaryngologist. Multivariable logistic regression analysis did not reveal any significant predictors for loss to follow-up in receiving TA. Cox regression analysis that adjusted for age, sex, insurance, and race showed that rural-dwelling patients had a 30% reduction in receipt of TA over time as compared to urban-dwelling patients (hazard ratio, 0.7; 95% CI, 0.50-0.99). Conclusion Rural-dwelling patients experienced longer wait times and driving distance to TA. This study suggests that rurality should be considered a potential barrier to surgical intervention and highlights the need to further investigate geographic access as an important determinant of care in pediatric SDB.

scholarly journals 1253 Multiple sleep onset REM episodes in middle age woman with excessive daytime sleepiness – Is this automatically assumed narcolepsy?

SLEEP ◽  
2020 ◽  
Vol 43 (Supplement_1) ◽  
pp. A477-A477
Author(s):  
Kamal Patel ◽  
Bianca J Lang
Keyword(s):  
Daytime Sleepiness ◽  
Sleep Latency ◽  
Sleep Onset ◽  
Sleep Time ◽  
Multiple Sleep Latency Test ◽  
Sleep Onset Latency ◽  
Onset Latency ◽  
Obstructive Sleep ◽  
Falling Asleep ◽  
Multiple Sleep Latency

Abstract Introduction Presence of sleep onset REM episodes often raises concerns of narcolepsy. However other conditions have shown to have presence of sleep on REM episodes which include but not limited to obstructive sleep apnea, sleep wake schedule disturbance, alcoholism, neurodegenerative disorders, depression and anxiety Report of Case Here we present a case of 30 year old female with history of asthma, patent foraman ovale, migraine headache, and anxiety who presented with daytime sleepiness, falling asleep while at work, occasional scheduled naps, non-restorative sleep, sleep paralysis, and hypnopompic hallucination. Pertinent physical exam included; mallampati score of 4/4, retrognathia, high arched hard palate, crowded posterior oropharynx. She had a score of 16 on Epworth sleepiness scale. Patient previously had multiple sleep latency test at outside facility which revealed 4/5 SOREM, with mean sleep onset latency of 11.5 minutes. She however was diagnosed with narcolepsy and tried on modafinil which she failed to tolerate. She was tried on sertraline as well which was discontinued due to lack of benefit. She had repeat multiple sleep latency test work up which revealed 2/5 SOREM, with mean sleep onset latency was 13.1 minutes. Her overnight polysomnogram prior to repeat MSLT showed SOREM with sleep onset latency of 10 minutes. Actigraphy showed consistent sleep pattern overall with sufficient sleep time but was taking hydroxyzine and herbal medication. Patient did not meet criteria for hypersomnolence disorder and sleep disordered breathing. Conclusion There is possibility her medication may have played pivotal role with her daytime symptoms. We also emphasize SOREMs can be present in other disorders such as anxiety in this case and not solely in narcolepsy

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