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. 2021 Dec 1;17(12):2355-2362.
doi: 10.5664/jcsm.9430.

Characterizing respiratory parameters, settings, and adherence in real-world patients using adaptive servo ventilation therapy: big data analysis

Atul Malhotra  1 , Adam V Benjafield  2 , Peter A Cistulli  3 , Jingjing Li  4 , Holger Woehrle  5 , Jeff Armitstead  2 , Kimberly L Sterling  6 , Carlos M Nunez  6 , Jean-Louis Pépin  7 ; medXcloud group
Affiliations

Characterizing respiratory parameters, settings, and adherence in real-world patients using adaptive servo ventilation therapy: big data analysis

Atul Malhotra et al. J Clin Sleep Med. .

Abstract

Study objectives: There is minimal guidance around how to optimize inspiratory positive airway pressure (IPAP) levels during use of adaptive servo ventilation (ASV) in clinical practice. This real-world data analysis investigated the effects of IPAP and minimum pressure support settings on respiratory parameters and adherence in ASV-treated patients.

Methods: A United States-based telemonitoring database was queried for patients starting ASV between August 1, 2014 and November 30, 2019. Patients meeting the following criteria were included: United States-based patients aged ≥ 18 years; AirCurve 10 device (ResMed); and ≥ 1 session with usage of ≥ 1 hour in the first 90 days. Key outcomes were mask leak and residual apnea-hypopnea index at different IPAP settings, adherence and therapy termination rates, and respiratory parameters at different minimum pressure support settings.

Results: There were 63,996 patients included. Higher IPAP was associated with increased residual apnea-hypopnea index and mask leak but did not impact device usage per session (average > 6 h/day at all IPAP settings; 6.7 h/day at 95th percentile IPAP 25 cm H2O). There were no clinically relevant differences in respiratory rate, minute ventilation, leak, and residual apnea-hypopnea index across all possible minimum pressure support settings. Patients with a higher 95th percentile IPAP or with minimum pressure support of 3 cm H2O were most likely to remain on ASV therapy at 1 year.

Conclusions: Our findings showed robust levels of longer-term adherence to ASV therapy in a large group of real-world patients. There were no clinically important differences in respiratory parameters across a range of pressure and pressure support settings. Future work should focus on the different phenotypes of patients using ASV therapy.

Citation: Malhotra A, Benjafield AV, Cistulli PA, et al. Characterizing respiratory parameters, settings, and adherence in real-world patients using adaptive servo ventilation therapy: big data analysis. J Clin Sleep Med. 2021;17(12):2355-2362.

Keywords: adaptive servo ventilation; big data analysis; minute ventilation; pressure support; treatment adherence.

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Conflict of interest statement

All authors have seen and approved this manuscript. This study was funded by ResMed. Dr. Malhotra is funded by the NIH. Dr. Malhotra received funding from Equillium, Corvus, and Livanova related to medical education. ResMed, Inc. provided a philanthropic donation to the UC San Diego in support of a sleep center. Drs. Benjafield, Armitstead, Sterling, and Nunez, and Mr. Li are employees of ResMed. Dr. Cistulli has an appointment to an endowed academic chair at the University of Sydney that was established from ResMed funding; has received research support from ResMed, SomnoMed, and Zephyr Sleep Technologies; is a consultant to Zephyr Sleep Technologies, SomnoMed, Narval, and Signifier Medical Technologies; and has a pecuniary interest in SomnoMed related to a 2004 role in research and development (2004). Dr. Woehrle has received consulting and speaker’s fees from ResMed and Inspire Medical. Dr. Pépin is supported by the French National Research Agency in the framework of the “Investissements d’avenir” program (ANR-15-IDEX-02) and supported by MIAI @ Grenoble Alpes, (ANR-19-P3IA-0003), and his department has received research support from ResMed, Philips Respironics, and Fisher and Paykel.

Figures

Figure 1
Figure 1. Flowcharts for patient inclusion in the study.
ASV = adaptive servo ventilation.
Figure 2
Figure 2. Kaplan-Meier plot of probability of remaining on ASV therapy in patient subgroups based on PSmin setting.
ASV = adaptive servo ventilation, PSmin = minimum pressure support.
Figure 3
Figure 3. Forest plot showing predictors of adherence to ASV therapy.
Data show hazard ratio (squares) with 95% confidence interval (lines). AHI = apnea-hypopnea index, ASV = adaptive servo ventilation, EPAP = expiratory positive airway pressure, IPAP = inspiratory positive airway pressure, lpm = liters per minute, PSmax = maximum pressure support, PSmin = minimum pressure support.
See this image and copyright information in PMC

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