Screening Tool For Sleep Disordered Breathing Research Articles

Translation and cross-cultural adaptation of the sleep-related breathing disorder scale of the Pediatric Sleep Questionnaire into Danish language

Objective/Background Sleep-disordered breathing (SDB) is common but often underestimated in children. The gold standard for assessing SDB is polysomnography, but it is expensive and time-consuming. The Paediatric Sleep Questionnaire (PSQ/SRDB) is a validated screening tool for SDB, which represents an efficient and alternative tool for screening SDB among children. However, a translated and validated Danish version of the PSQ/SRDB is not available yet. Our aim was to cross-culturally translate the PSQ/SRDB into Danish language for use in clinical and research settings. Patients/Methods The translation was carried out through forward-backward translation techniques performed by a panel of experts, and the cross-cultural adaptation was achieved by pretesting of the pre-final version. Internal consistency of the Danish PSQ/SRDB version was measured by Cronbach's alpha coefficients, while Cohen’s kappa was used to evaluate test-retest reliability. Construct validity was assessed by factor analysis of the principal components. Results The Danish PSQ/SRDB was administered to the caregivers of 348 children. An overall Cronbach’s alpha of 0.72 was found, confirming the survey’s consistency, with the results for the domains ranging 0.52–0.70. The Danish PSQ/SRDB showed moderate to perfect reliability for all items, except for one question (C14). Factor analysis performed on the Danish PSQ/SRDB showed that the predetermined four factors were similar with the original version of the PSQ/SRDB. Conclusions The Danish version of the PSQ/SRDB has been successfully translated and cross-culturally adapted, suggesting that it can be used as an appropriate paediatric screening tool for SDB in Denmark.

Utility of cyclic variation of heart rate score as a screening tool for sleep-disordered breathing in patients with heart failure.

Patients with sleep-disordered breathing have cyclic variation of heart rate (CVHR) in response to respiratory events. However, limited data are available regarding the utility of CVHR as a screening tool for sleep-disordered breathing in patients with mixed heart failure (HF) and those without HF. We enrolled consecutive patients with and without HF who underwent full polysomnographies with simultaneous Holter electrocardiogram monitoring. We determined the temporal position of the individual dips comprising the CVHR score using time-domain methods. The data of 101 patients, including 70 with and 31 without HF, were analyzed. The CVHR score was significantly correlated with the apnea-hypopnea index (r = .667, P < .001) and limits of agreement between the apnea-hypopnea index and CVHR score were -21.8 to 35.2. The receiver operating characteristic analysis demonstrated that the CVHR score (best cut-off of 23.5 events/h) identified severe sleep-disordered breathing with a sensitivity of 83.3%, specificity of 79.5%, and the area under the curve of 0.856. In addition, there was no interaction between the presence or absence of HF and the apnea-hypopnea index-CVHR score relationship (P = .323). The CVHR score, determined by Holter electrocardiogram monitoring, is a useful tool for evaluating sleep-disordered breathing even in patients with mixed HF and patients without HF. Yatsu S, Kasai T, Naito R, etal. Utility of cyclic variation of heart rate score as a screening tool for sleep-disordered breathing in patients with heart failure. J Clin Sleep Med. 2021;17(11):2187-2196.

Selection of Screening Tool for Sleep-Disordered Breathing or Obstructive Sleep Apnea in Pediatric Patients in the Perianesthesia Setting

PurposeThis study was undertaken to select an appropriate tool to predict risk of obstructive sleep apnea (OSA) among pediatric patients in the preoperative setting. Design/MethodsA retrospective chart review and a survey of nursing staff to compare two tools that were determined to be valid in assessing risk of OSA and postanesthesia complications in pediatric patients aged 6 months to 18 years was conducted. About 300 pediatric patients presenting for elective surgery were screened for OSA using STBUR (Snoring, Trouble Breathing during sleep, struggling to Breathe during Sleep, and waking UnRefreshed) and ST(1)OP-BANG (Snoring, Tonsillar hypertrophy, sleep Obstruction, BMI, Age, Neuromuscular disorders, and Genetic/congenital deformities) concurrently. Six preoperative nurses were then surveyed to compare ease of use and time to complete the screening tools. FindingsThe STBUR tool was found to predict complications in 37.5% patients versus 22.7% patients with the pediatric ST(1)OP-BANG. Nursing staff found that although both tools were quick and easy to use, the STBUR tool was easier for parents to answer. ConclusionsUse of a screening tool to help predict risk of OSA and postanesthetic complications also helps to dictate anesthesia technique, nursing staffing requirements, and plans of care for postoperative management of pediatric patients.

Clinical utility of a type 4 portable device for in-home screening of sleep disordered breathing.

Portable monitoring devices have been developed for in-home screening and to aid in the diagnosis of sleep disordered breathing (SDB) while increasing accessibility and reducing costs. Although there are many different devices available in the market, most have not undergone rigorous validation. Therefore, although such devices are promising, more research on their clinical utility is necessary. The purpose of this study was to assess the clinical utility of a type 4 home sleep apnea test (HSAT) as an in-home screening for SDB. We investigated consecutive subjects who underwent in-laboratory overnight polysomnography following in-home screening using HSAT. We evaluated the correlation between apnea-hypopnea index (AHI) by in-laboratory overnight polysomnography and by HSAT and evaluated the sensitivity and specificity for AHI ≥5 and AHI ≥30 by the receiver operating characteristic (ROC) analysis. Finally, data of 387 participants (86.8% men, mean age 55.3±13.3 years and body mass index 25.1±4.1 kg/m2) were assessed. In all patients, AHI by HSAT correlated significantly with AHI by polysomnography (r=0.670, P<0.001). The area under curves of ROC for AHI ≥5 and AHI ≥30 were 0.854±0.029 and 0.841±0.022, respectively. The best cut-off of AHI by HSAT for detecting AHI by polysomnography ≥5 was 10.3 events/h (sensitivity, 82.8%; and specificity, 76.0%), and AHI by HSAT for detecting AHI by polysomnography ≥30 was 24.5 events/h (sensitivity, 75.8%; and specificity, 80.4%). This type 4 HSAT may have potential as a screening tool for SDB and thus have sufficient clinical utility.

0877 Impact of Sleep-Disordered Breathing on Quality of Life in Pediatric Cystic Fibrosis

Abstract Introduction The frequency of sleep-disordered breathing (SDB) may be high among children with cystic fibrosis (CF), a life-shortening, genetic disease that affects 1/3400 Caucasian live-births. Yet, the potential impact of SDB on their quality of life has not been well-studied. Methods The Pediatric Sleep Questionnaire Sleep-Related Breathing Disorders (PSQ-SRBD) Scale, a well-validated SDB screening tool, and two validated quality-of-life questionnaires, the Pediatric Quality of Life Inventory (PedsQL™) and the Cystic Fibrosis Questionnaire-Revised (CFQ-R), were administered to children 6-17 years of age with CF consecutively during a 2-week period during routine pulmonary clinic visits. Results Twenty-two children with CF and their parents completed the questionnaires. Mean age of the participants was 11.6±3.8(sd) years. Mean body mass index (BMI) percentile was 54.8±27.1%. Mean forced expiratory volume in 1 second percent predicted (FEV1 PPD) was 86.6±22.5%. Five subjects (23%) showed high risk for SDB (PSQ-SRBD Scores &amp;gt; 0.33). Seven additional subjects had PSQ-SRBD Scores of 0.3. Mean BMI percentile was higher among subjects with vs. without positive PSQ-SRBD Scores (66% vs. 42% respectively, p=0.03). The groups did not differ with regards to FEV1. Pearson/Spearman correlation identified negative associations between PSQ-SRBD Scores and functioning in multiple parent PedsQL domains: physical (R=-0.45, p=0.03), social (R=-0.53, p=0.01), school (R=-0.56, p=0.008); two child PedsQL domains: physical (R=-0.41, p=0.06), school (R=-0.41, p=0.06); multiple parent CFQ-R domains: physical (R=-0.44, p=0.08), respiratory (R=-0.45, p=0.07), emotional (R=-0.54, p=0.02), school (R=-0.70, p=0.002); and one child CFQ-R domain: physical (R=-0.51, p=0.01). None of these domains were associated with FEV1. Conclusion Children with CF may have SDB symptoms independent of the extent of lung dysfunction. Although the current cross-sectional data cannot prove a causal effect, they raise the possibility that the SDB itself may have adverse impact on physical, emotional, social, and school functioning. Support NIH Training Grant (F32HL145915)

A Novel Artificial Neural Network Based Sleep-Disordered Breathing Screening Tool.

This study evaluated a novel artificial neural network (ANN) based sleep-disordered breathing (SDB) screening tool incorporating nocturnal pulse oximetry with demographic, anatomic, and clinical data. The tool was compatible with 6 categories of apnea-hypopnea index (AHI) with 4% oxyhemoglobin desaturation threshold, ≥ 5, 10, 15, 20, 25, and 30 events/h. Using a general population dataset, the training set included 2,280 subjects, whereas the test set included 470 subjects. The input of this tool was a set of 22 variables. The tool had six neural network models for each AHI threshold. Several metrics were explored to evaluate the performance of the tool: area under the receiver operating characteristic curve (AUC), sensitivity, specificity, positive predictive value, negative predictive value, and 95% confidence interval (CI). The AUC was 0.904, 0.912, 0.913, 0.926, 0.930, and 0.954, respectively, with models of AHI ≥ 5, 10, 15, 20, 25, and 30 events/h thresholds. The sensitivities of all neural network models were higher than 95%. The AHI ≥ 30 events/h model had the maximum sensitivity: 98.31% (95% CI: 95.01%-100%). The results of this study suggested that the ANN based SDB screening tool can be used to identify the presence or absence of SDB. Future validation should be performed in other populations to determine the practicability of this screening tool in sleep clinics and other at-risk populations.

Sleep Overnight Monitoring for Apnea in Patients Hospitalized with Heart Failure (SOMA-HF Study).

Sleep-disordered breathing (SDB) is highly prevalent in hospitalized patients with congestive heart failure (CHF) and the condition is diagnosed and treated in only a minority of these patients. Portable monitoring (PM) is a screening option, but due to costs and the expertise required, many hospitals may find it impractical to implement. We sought to test the utility of an alternative approach for screening hospitalized CHF patients for SDB, high-resolution pulse oximetry (HRPO). We conducted a prospective controlled trial of 125 consecutive patients admitted to the hospital with CHF. Simultaneous PM and HRPO for a single night was performed. All but one patient were monitored on breathing room air. The HRPO-derived ODI (oxygen desaturation index) was compared with PM-derived respiratory event index (REI) using both receiver operator characteristic (ROC) curve analysis and a Bland-Altman plot. Of 105 consecutive CHF patients with analyzable data, 61 (58%) were males with mean age of 64.9 ± 15.1 years and mean body mass index of 30.3 ± 8.3 kg/m2. Of the 105 patients, 10 (9.5%) had predominantly central sleep apnea (central events > 50% of the total events), although central events were noted in 42 (40%) of the patients. The ROC analysis showed an area under the curve of 0.89 for REI > 5 events/h. The Bland-Altman plot showed acceptable agreement with 95% limits of agreement between -28.5 to 33.7 events/h and little bias. We conclude that high-resolution pulse oximetry is a simple and cost-effective screening tool for SDB in CHF patients admitted to the hospital. Such screening approaches may be valuable for large-scale implementation and for the optimal design of interventional trials.

The efficacy of the OSA-18 as a waiting list triage tool for OSA in children.

Sleep disordered breathing (SDB) is common in children, resulting in extensive waiting lists for specialist clinics. There is an urgent need for a valid method of triaging patients and the OSA-18, a disease-specific tool, is an attractive candidate for this role. We aimed to examine the OSA-18 as a measurement tool in detail and to determine whether the score or aspects of it could be used as a screening tool for SDB in children. Retrospective analysis of 582 children (6months to 16.4years)-216 underwent overnight PSG and 366 overnight oximetry. Confirmatory factor analysis (CFA) and exploratory factor analysis (EFA) were conducted. Receiver operating characteristic curve analysis assessed the diagnostic accuracy of the factors for the presence of OSA. Rasch analysis was used to assess the structure of the items (1-18) and categories of response (Likert scale). The CFA with a forced five-factor structure, revealed three factors with Eigenvalues >1, and explained 73.7% of the variance. EFA resulted in a two-factor structure, explaining 60.3% of the variance. Assessment of sensitivity and specificity showed a high false-positive rate, irrespective of the factor structure tested. Rasch analysis showed poor discrimination between adjacent categories on the Likert scale. This study confirmed that the predictive value of the OSA-18 for SDB severity is weak. Some questions perform better than others statistically, and the seven categories of response introduce significant statistical noise, raising the possibility that modification of the OSA-18 may improve its performance in the prediction of OSA severity.

759: A validated screening tool for sleep-disordered breathing in pregnancy and risk of preeclampsia in a large cohort of gravidae

759: A validated screening tool for sleep-disordered breathing in pregnancy and risk of preeclampsia in a large cohort of gravidae

Cyclic variation in heart rate score by holter electrocardiogram as screening for sleep-disordered breathing in subjects with heart failure.

Sleep-disordered breathing (SDB) is critically associated with cardiovascular mortality and morbidity, especially in patients with heart failure (HF). However, the majority of SDB patients remain undiagnosed. In contrast, abnormality in heart rate variability has been reported in patients with SDB. To explore an efficient electrocardiogram (ECG)-based screening tool for SDB, we examined the usefulness of cyclic variation in heart rate score (CVHRS) by Holter ECG in subjects with HF. In this study, 102 subjects with HF were enrolled. We simultaneously performed Holter ECG with overnight portable sleep monitoring, and we measured the respiratory disturbance index (RDI) and CVHRS. We determined the temporal position of the individual dips comprising the CVHRS using time-domain methods. CVHRS was measured as cyclic and autocorrelated dips in smoothed interbeat interval time series. There were 25 subjects with severe SDB (RDI ≥ 30 events/h) and 77 subjects with none-to-moderate SDB (0 ≤ RDI < 30 events/h). There was a significant positive correlation between CVHRS and RDI (r = 0.60, P < .001). In receiver operating characteristic analysis, CVHRS (cutoff of 30 events/h) identified severe SDB with a sensitivity of 82%, a specificity of 77%, and an area under the curve of 0.83. CVHRS determined by Holter ECG is a useful screening index for severe SDB in subjects with HF.

Abstract 9391: Cyclic Variation of Heart Rate Score by Holter ECG for screening Sleep Disordered Breathing in Heart Failure Patients

Background: Sleep disordered breathing (SDB) has a critical association with cardiovascular mortality and morbidity, especially in patients with heart failure (HF). However, because of the complexity to refer the polysomnography, the majority of SDB patients remain undiagnosed. On the other hand, the abnormality of heart rate variability has been reported in patients with SDB. To explore an efficient ECG-based screening tool for SDB, we examined the usefulness of cyclic variation of heart rate score (CVHRS) by Holter ECG in HF patients. Methods and Results: In this study, 110 patients with HF (mean age 58.6 years, body mass index 23.6, left ventricular ejection fraction 45.5%) were enrolled. The exclusion criteria were the presence of atrial fibrillation and receiving implantable pacemaker device therapy. We simultaneously performed Holter ECG and polysomnography in night time, and measured apnea-hypopnea index (AHI) and CVHRS. We determined the temporal position of the individual dips comprising the CVHRS, using time-domain methods. CVHRS was measured as cyclic and auto correlated dips in smoothed interbeat interval time series. There were 77 patients with mild to moderate SDB (5≤AHI&lt;30/h) and 26 patients with severe SDB (AHI ≥30/h). There was a significant positive correlation between CVHRS and AHI (R=0.60, P&lt;0.001). From the ROC analysis, CVHRS (a cut off value of 30) identified severe SDB with sensitivity 82%, specificity 77%, positive predictive value (PPV) 78%, negative predictive value (NPV) 81% and area under the curve (AUC) 0.83. Conclusions: CVHRS determined by Holter ECG is a useful screening index for severe SDB in HF patients.

Utility of Cyclic Variation of Heart Rate Score by Holter ECG for Screening Sleep Disordered Breathing in Heart Failure Patients

Sleep disordered breathing (SDB) has a critical association with cardiovascular mortality and morbidity, especially in patients with heart failure (HF). However, because of the complexity to refer the polysomnography, the majority of SDB patients remain undiagnosed. On the other hand, the abnormality of heart rate variability has been reported in patients with SDB. To explore an efficient ECG-based screening tool for SDB, we examined the usefulness of cyclic variation of heart rate score (CVHRS) by Holter ECG in HF patients.

Electrocardiogram-derived respiration in screening of sleep-disordered breathing

Methods for assessment of sleep-disordered breathing (SDB), including sleep apnea, range from a simple questionnaire to complex multichannel polysomnography. Inexpensive and efficient electrocardiogram (ECG)–based solutions could potentially fill the gap and provide a new SDB screening tool. In addition to the heart rate variability (HRV)–based SDB screening method that we reported a year ago, we have developed a novel method based on ECG-derived respiration (EDR). This method derives the respiratory waveform by (a) measuring peak-to-trough QRS amplitude in a single-channel ECG, (b) removing outlier introduced by noise and artifacts, (c) interpolating the derived values, and (d) filtering values within the respiration rates of 5 and 25 cycles per minute. Each 30 seconds of the respiratory waveform is then classified as normal, SDB, or indeterminate epoch. The previously reported HRV-based method, applied at the same time, is based on power spectrum of heart rate over a sliding 6-minute time window to classify the middle 30-second epoch. We then combined the EDR- and HRV-based techniques to optimize the classification of each epoch. The combined method further improved the accuracy of SDB screening in an independent test database with annotated SDB epochs. The development database was from PhysioNet (n = 25 polysomnograms). The test database was from Sleep Health Centers in Boston (n = 1907 polysomnogram) where the SDB epochs (n = 1 538 222 epochs) were scored using American Academy of Sleep Medicine criteria. The first test was to classify every epoch in the evaluation data set. The combined EDR and HRV method classified 78% of the epochs as either normal or SDB and 22% as indeterminate, with a total accuracy of 88% for scored epochs (not indeterminate). The second test was to evaluate the SDB status for each patient. The algorithm correctly classified 71% of patients with either moderate-to-severe SDB or mild-to-no SDB. We believe that the ECG-based methods provide an efficient and inexpensive tool for SDB screening in both home and hospital settings and make SDB screening feasible in large populations.

Heart rate increment analysis is not effective for sleep-disordered breathing screening in patients with chronic heart failure

Frequency domain analysis of heart rate variation has been suggested as an effective screening tool for sleep-disordered breathing (SDB) in the general population. The aim of this study was to assess this method in patients with chronic congestive heart failure (CHF). We included prospectively 84 patients with stable CHF, left ventricular ejection fraction (LVEF) <45% and sinus rhythm. The patients underwent polygraphy to measure the apnoea/hypopnoea index (AHI) and simultaneous Holter electrocardiogram monitoring to measure the power spectral density of the very low frequency component of the heart rate increment, expressed as the percentage of total power spectral density [% very low frequency increment (%VLFI)]. %VLFI could be determined in 54 patients (mean age, 52.8 +/- 12.3 years; LVEF, 33.5 +/- 9.8%). SDB defined as AHI > or =15 h(-1) was diagnosed in 57.4% of patients. Percent VLFI was not correlated with AHI (r = 0.12). Receiver-operating characteristic curves constructed using various AHI cut-offs (5-30 h(-1)) failed to identify a %VLFI cut-off associated with SDB. The 2.4% VLFI cut-off recommended for the general population of patients with suspected SDB had low specificity (35%) and low positive and negative predictive values (35% and 54%, respectively). Heart rate increment analysis has several limitations in CHF patients and cannot be recommended as an SDB screening tool in the CHF population.

Electrocardiogram Recording as a Screening Tool for Sleep Disordered Breathing

Transient changes in heart rate associated with obstructive apneas have been suggested for screening of sleep disordered breathing (SDB). This study prospectively compares the outcomes of an automated ECG-based SDB screening tool with simultaneous polysomnography. The previously-developed automated algorithm was applied to a single channel ECG obtained during standard overnight polysomnography (92 subjects) to obtain an apnea-hypopnea index (AHI) estimate. Using AHI thresholds of < 5 and > or =15 to define absence and presence of SDB, respectively, we determined the likelihood ratios of the proposed technique. The automated algorithm achieved positive and negative likelihood ratios of 2.16 and 0.08. Estimated and reference AHI were highly correlated (r = 0.88). Pathologically insignificant arrhythmia in some subjects had no discernible impact on the algorithm. ECG-based assessment provides a simple but limited means of recognizing subjects with obstructive sleep apnea.