Dataset Information

Tracheal sounds for the scoring of sleep respiratory events in children.

ABSTRACT:

Study objectives

Oronasal thermistor and nasal cannula are recommended for the scoring of respiratory events (RE) but these sensors are poorly tolerated in children. The aim of the study was to evaluate tracheal sounds (TS) and suprasternal pressure (SSP) for the scoring of RE during sleep in children.

Methods

We compared the detection and characterization of RE by AASM-recommended sensors ("AASM" scoring), with the detection and characterization of RE by the combination of TS and SSP with respiratory inductance plethysmography-sum (TS-RIP scoring), and TS and SSP only (TS scoring).

Results

The recordings of 17 patients were analyzed. The TS, SSP, and RIP flow signals were present during 95%, 95%, and 99% of the validated recording time, respectively, as compared to 79% and 86% for nasal cannula and oronasal thermistor. A total of 1,456 RE were scored with the "AASM" scoring, 1,335 with the TS-RIP scoring, and 1,311 with the TS scoring. Sensitivity for apnea and hypopnea detection was 88% and 84% for the TS-RIP scoring, and 86% and 77% for the TS scoring. For apnea characterization, the TS-RIP scoring sensitivities and specificities were 97% and 100%, 76% and 98%, and 95% and 97%, for obstructive, mixed, and central apnea, respectively. For the TS scoring, they were 95% and 100%, 95% and 97%, and 91% and 97%, respectively.

Conclusions

TS and SSP + RIP-sum has a good sensitivity and specificity for the detection and characterization of apnea and hypopnea in children. TS and SSP alone have good sensitivity and specificity for apnea detection and characterization but lower sensitivity for hypopnea detection.

SUBMITTER: Amaddeo A

PROVIDER: S-EPMC7075091 | biostudies-literature | 2020 Mar

REPOSITORIES: biostudies-literature

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Publications

Tracheal sounds for the scoring of sleep respiratory events in children.

Amaddeo Alessandro A Sabil Abdelkebir A Arroyo Jorge Olmo JO De Sanctis Livio L Griffon Lucie L Baffet Guillaume G Khirani Sonia S Fauroux Brigitte B

Journal of clinical sleep medicine : JCSM : official publication of the American Academy of Sleep Medicine 20200114 3

<h4>Study objectives</h4>Oronasal thermistor and nasal cannula are recommended for the scoring of respiratory events (RE) but these sensors are poorly tolerated in children. The aim of the study was to evaluate tracheal sounds (TS) and suprasternal pressure (SSP) for the scoring of RE during sleep in children.<h4>Methods</h4>We compared the detection and characterization of RE by AASM-recommended sensors ("AASM" scoring), with the detection and characterization of RE by the combination of TS and ...[more]

PMID: 31992398

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Project description:Studies ascribe different functions to rapid eye movement (REM) and non-rapid eye movement (NREM) sleep, such that their disruption could result in discrepant clinical outcomes. Although sleep architecture is globally preserved in children with obstructive sleep apnoea (OSA), it is considered to be an REM sleep REMS disorder. Furthermore, body position during sleep affects the occurrence of respiratory events, while the presence of obesity has been claimed to affect sleep-state distribution of respiratory disturbance.To explore the distribution of respiratory events during REMS and NREM sleep NREMS and its potential predictors, a cross-sectional analysis of 335 overnight sleep studies in snoring children from the community was conducted. The ratio of REMS to NREMS respiratory events was compared, and potential associations were assessed using general linear modelling (GLM).Children were 7.3±1.2 years old and had a body mass index (BMI) z-score of 1.0±1.3. The obstructive apnoea-hypopnea index (OAHI) was 1.7±3 and 45.8% of children had an apnoea-hypopnea index (AHI) >1h(-1) total sleep time (TST). Obstructive respiratory events were 3.8 times more likely in REMS (2.0 h(-1)) than NREMS (0.5h(-1)), and the GLM revealed distinctive predictive associations for the apnoeic and hypopneic indices separately, and for body position, the latter indicating that the REMS/NREMS distribution of respiratory events depends on body position.Obstructive respiratory events are predominantly, albeit not exclusively, present in REMS in school-aged children. NREMS respiratory events are more likely in the presence of lower oxyhaemoglobin saturations during event, side body position and in African-American children. However, REMS dominance is not affected by either BMI z-score or obesity. Our findings suggest that incorporating comprehensive respiratory event profiles of children may enhance our understanding of the pathophysiology and adverse outcomes in the context of paediatric OSA.

Project description:Current scoring criteria of non-apneic events (ie, hypopnea) require the presence of oxyhemoglobin desaturation and/or arousal. However, other sleep study parameters may help to identify abnormal respiratory events (REs) and assist in making more accurate diagnosis. To investigate whether non-apneic REs without desaturation or cortical arousal are associated with respiratory and cardiac consequences. Thirteen participants with sleep disturbances (snoring and/or excessive day time sleepiness), were screened using attended in laboratory polysomnography (PSG) while monitoring pressure and airflow via a nasal mask with an attached pneumotach. To separate the contribution of the upper airway resistance (RUA) and total pulmonary resistance (RL), supraglottic and esophageal pressures were measured using Millar pressure catheters. RL and RUA were calculated during baseline and hypopneas. RL was defined as the resistive pressure divided by the maximal flow during inspiration and expiration. Hypopnea was defined 30% decrease in flow with 3% desaturation and/or cortical arousal. REs was defined as 30% decrease in the flow without desaturation and/or cortical arousal. In eight subjects continuous positive airway pressure (CPAP) was titrated to optimal pressure. R-R interval (RRI) was defined as consecutive beat-to-beat intervals on single lead electrocardiograph (ECG) during baseline, RE/hypopnea and on optimal CPAP. REs associated with increased expiratory RUA (14.6 ± 11.3 vs. 7.5 ± 4.5 cmH2O L-1 s-1; p < .05), and increased expiratory RL relative to baseline (29.2 ± 14.6 vs. 20.9 ± 11.0 and 23.7 ± 12.1 vs. 14.3 ± 5.6 cmH2O L-1 s-1 during inspiration and expiration, respectively; p < .05). RRI decreased significantly following RE and hypopnea relative to baseline (804.8 ± 33.1 vs. 806.4 ± 36.3 vs. 934.3 ± 45.8 ms; p < .05). Optimal CPAP decreased expiratory RUA (4.0 ± 2.5 vs. 7.5 ± 4.5 cmH2O L-1 s-1; p < .05), decreased inspiratory RL (12.6 ± 14.1 vs. 7.5 ± 4.5 cmH2O L-1 s-1; p < .05), and allowed RRI to return to baseline (p < .05). RRI dips index was an independent predictor of sleep-disordered breathing (SDB) when non-apneic REs were accounted for in symptomatic patients (p < .05). Non-apneic REs without cortical arousal or desaturation are associated with significant respiratory and heart rate changes. Optimal CPAP and the reduction of resistive load are associated with the normalization of heart rate indicating potential clinical benefit.

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Project description:Objective:Tracheal sounds were used to detect apnea on various occasions. However, ambient noises can contaminate tracheal sounds which result in poor performance of apnea detection. The objective of this paper was to apply the adaptive filtering (AF) algorithm to improve the quality of tracheal sounds and examine the accuracy of the apnea detection algorithm using tracheal sounds after AF. Method:Tracheal sounds were acquired using a primary microphone encased in a plastic bell, and the ambient noises were collected using a reference microphone resting outside the plastic bell in quiet and noisy environments, respectively. Simultaneously, the flow pressure signals and thoracic and abdominal movement were obtained as the standard signals to determine apnea events. Then, the normalized least mean square (NLMS) AF algorithm was applied to the tracheal sounds mixed with noises. Finally, the algorithm of apnea detection was used to the tracheal sounds with AF and the tracheal sounds without AF. Sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), accuracy, and Cohen's kappa coefficient of apnea detection were calculated. Results:Forty-six healthy subjects, aged 18-35 years and with BMI < 21.4, were included in the study. The apnea detection performance using tracheal sounds was as follows: in the quiet environment, the tracheal sounds without AF detected apnea with 97.2% sensitivity, 99.9% specificity, 99.8% PPV, 99.4% NPV, 99.5% accuracy, and 0.982 kappa coefficient. The tracheal sounds with AF detected apnea with 98.2% sensitivity, 99.9% specificity, 99.4% PPV, 99.6% NPV, 99.6% accuracy, and 0.985 kappa coefficient. While in the noisy environment, the tracheal sounds without AF detected apnea with 81.1% sensitivity, 96.9% specificity, 85.1% PPV, 96% NPV, 94.2% accuracy, and 0.795 kappa coefficient and the tracheal sounds with AF detected apnea with 91.5% sensitivity, 97.4% specificity, 88.4% PPV, 98.2% NPV, 96.4% accuracy, and 0.877 kappa coefficient. Conclusion:The performance of apnea detection using tracheal sounds with the NLMS AF algorithm in the noisy environment proved to be accurate and reliable. The AF technology could be applied to the respiratory monitoring using tracheal sounds.

Dataset Information

Tracheal sounds for the scoring of sleep respiratory events in children.

Study objectives

Methods

Results

Conclusions

Publications

Tracheal sounds for the scoring of sleep respiratory events in children.

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