Pilot Study to Investigate the Benefits of the InnoSpire Go Mesh Nebulizer Compared to Jet Nebulizers in the Treatment of Stable COPD

Background: Nebulizers are widely used for the delivery of aerosols to patients with chronic obstructive pulmonary disease (COPD). The InnoSpire Go mesh nebulizer has been designed to improve upon the ease of use and convenience of existing nebulizers for the treatment of COPD. Methods: This was a pilot, single-center, randomized, open-label crossover study conducted over 2 months to investigate the use of the InnoSpire Go mesh nebulizer compared to the patient's own compressor driven jet nebulizer in ambulatory patients with stable COPD. Patient preference was assessed at the end of the study; quality of life, symptom scores, treatment time, and satisfaction were assessed at multiple points during the study. Results: Data for 17 patients were eligible for analysis, patients had a mean age of 64.6 years, and 64.7% were graded 3 on the modified Medical Research Council dyspnea scale. All patients preferred the InnoSpire Go mesh nebulizer over their own compressor driven jet nebulizer (p < 0.001). Nebulization of study drugs using the InnoSpire Go mesh nebulizer was associated with statistically significant increases in health-related quality of life over baseline (Dyspnea p = 0.003, Emotion p = 0.043, Mastery p = 0.011). A mixed model analysis of Borg dyspnea scores before and after exercise showed significantly (p = 0.043) lower scores for the InnoSpire Go mesh nebulizer compared with the compressor driven nebulizers. Patient satisfaction was statistically significantly higher for each of 10 questions covering ease of use, confidence, burden of use, satisfaction, and how well the device fit into their lifestyle. Treatment time was significantly shorter with the InnoSpire Go mesh nebulizer (p = 0.003). Conclusions: Patients preferred and were more satisfied with the InnoSpire Go mesh nebulizer. Nebulization of study drugs using the InnoSpire Go mesh nebulizer resulted in improved quality of life compared with baseline, and treatments were delivered in a shorter period than the compressor driven jet nebulizers. Clinical Trial Registration number: ClinicalTrials.gov: NCT03933462.

Estimating sleep stages using cardiorespiratory signals: validation of a novel algorithm across a wide range of sleep-disordered breathing severity

STUDY OBJECTIVES

We have developed the CardioRespiratory Sleep Staging (CReSS) algorithm for estimating sleep stages using heart rate variability and respiration, allowing for estimation of sleep staging during home sleep apnea tests. Our objective was to undertake an epoch-by-epoch validation of algorithm performance against the gold standard of manual polysomnography sleep staging.

METHODS

Using 296 polysomnographs, we created a limited montage of airflow and heart rate and deployed CReSS to identify each 30-second epoch as wake, light sleep (N1 + N2), deep sleep (N3), or rapid eye movement (REM) sleep. We calculated Cohen's kappa and the percentage of accurately identified epochs. We repeated our analyses after stratification by sleep-disordered breathing (SDB) severity, and after adding thoracic respiratory effort as a backup signal for periods of invalid airflow.

RESULTS

CReSS discriminated wake/light sleep/deep sleep/REM sleep with 78% accuracy; the kappa value was 0.643 (95% confidence interval, 0.641-0.645). Discrimination of wake/sleep demonstrated a kappa value of 0.711 and accuracy of 89%, non-REM sleep/REM sleep demonstrated a kappa of 0.790 and accuracy of 94%, and light sleep/deep sleep demonstrated a kappa of 0.469 and accuracy of 87%. Kappa values did not vary by more than 0.07 across subgroups of no SDB, mild SDB, moderate SDB, and severe SDB. Accuracy increased to 80%, with a kappa value of 0.680 (95% confidence interval, 0.678-0.682), when CReSS additionally utilized the thoracic respiratory effort signal.

CONCLUSIONS

We observed substantial agreement between CReSS and the gold-standard comparator of manual sleep staging of polysomnographic signals, which was consistent across the full range of SDB severity. Future research should focus on the extent to which CReSS reduces the discrepancy between the apnea-hypopnea index and the respiratory event index, and the ability of CReSS to identify REM sleep-related obstructive sleep apnea.

0689 Use Of An Automated Scanning System To Select A Patient Interface

Introduction

There is no universal process for selecting mask style, size, and fit, and there is considerable variance in clinician and patient mask preference and patient anatomy. Poor mask fit may negatively affect adherence. A three-dimensional (3D) facial scanner and proprietary analytical software were developed to bring efficiencies to mask selection. This study explored the impact of that system on initial mask success compared to standard practice.

Methods

This was an open-label, randomized-controlled study. Participants provided written informed consent. 3D Scanner Arm (3DA): Participants answered questions about sleeping habits then had 3D facial images taken. Proprietary software recommended a hierarchy of up to four Philips Respironics masks and sizes. Traditional Fitting Arm (TFA): A designated clinician selected and fit masks using their standard methods. Mask selection was assessed by applying therapy and soliciting patient and clinician feedback. Mask refits and adherence were tracked through 90 days. Five sleep centers recruited 115 participants into the 3DA (61 males, 51.1±13.4 years, BMI 35.2±7.0, diagnostic AHI 26.2±21.9) and 123 into the TFA (79 males, 51.1±11.9 years, BMI 35±7.9, diagnostic AHI 26.9±22.6).

Results

A significantly higher percentage of 3DA patients required only one mask fitting (with no refits) compared to TFA during the initial setup (89.6% vs. 54.5%, p&lt;0.001) and through 90 days (62.6% vs 37.4%, p&lt;0.001). 3DA subjectively rated confidence in and satisfaction with the scanner-selected mask significantly higher than TFA. Mask leak was lower in the 3DA compared to TFA (29.4±10.6 vs 32.3±11.4 L/M, p= 0.043). The CMS adherence rate tended to favor 3DA vs. TFA (66.7% vs. 55.3, p=0.083). There were no significant differences in AHI or other adherence metrics.

Conclusion

The 3D scanner system was successful in mask selection with lower mask leak and greater patient satisfaction and confidence. This tool may bring about operational efficiencies to the mask selection process.

Support

This study was sponsored by Philips Respironics

Closed-loop system to enhance slow-wave activity

OBJECTIVE

Recent evidence reports cognitive, metabolic, and sleep restoration benefits resulting from the enhancement of sleep slow-waves using auditory stimulation. Our objective is to make this concept practical for consumer use by developing and validating an electroencephalogram (EEG) closed-loop system to deliver auditory stimulation during sleep to enhance slow-waves.

APPROACH

The system automatically detects slow-wave sleep with 74% sensitivity and 97% specificity and optimally delivers stimulation in the form of 50 ms-long tones separated by a constant one-second inter-tone interval at a volume that is dynamically modulated such that louder tones are delivered when sleep is deeper. The system was tested in a study involving 28 participants (18F, 10M; 36.9  ±  7.3 years old; median age: 40 years old) who used the system for ten nights (five nights in a sham condition and five in a stimulation condition). Four nights in each condition were recorded at-home and the fifth one in-lab.

MAIN RESULTS

The analysis in two age groups defined by the median age of participants in the study shows significant slow wave activity enhancement (+16.1%, p  <  0.01) for the younger group and absence of effect on the older group. However, the older group received only a fraction (57%) of the stimulation compared to the younger group. Changes in sleep architecture and EEG properties due to aging have influenced the amount of stimulation. The analysis of the stimulation timing suggests an entrainment-like phenomenon where slow-waves align to the stimulation periodicity. In addition, enhancement of spindle power in the stimulation condition was found.

SIGNIFICANCE

We show evidence of the viability of delivering auditory stimulation during sleep, at home, to enhance slow wave activity. The system ensures the stimulation delivery to be at the right time during sleep without causing disturbance.