Clinical profile of responders to adaptive servo-ventilation: a cluster analysis from the READ-ASV European cohort.

BACKGROUND

Adaptive servo-ventilation (ASV) effectively treats central sleep apnea (CSA), with or without coexisting obstructive sleep apnea (CSA-OSA). However, this is a diverse patient group, and the characteristics of patients who are most likely to benefit from ASV therapy, outside of traditional etiology-based subgroups, are unknown.

OBJECTIVES

To identify clusters of ASV-treated patients based on anthropometric data and comorbidities, and to evaluate the differential response to ASV in these patient clusters.

METHODS

This analysis used data from the READ-ASV registry, which enrolled adults with CSA prescribed ASV from September 2017-March 2021. Evaluations included the Epworth Sleepiness Scale, Functional Outcomes of Sleep Questionnaire, Pittsburg Sleep Quality Index, EuroQol-5-dimension, and sleep study data. Latent class analysis was used to identify patient clusters based on baseline anthropometric data and comorbidities.

RESULTS

Of 812 patients, 421 (52%) were in Cluster (C) 1 (older, high rate of cardiovascular comorbidities [including stroke], high body mass index [BMI]), 239 (29%) were in C2 (elderly/middle-aged, average-low cardiovascular comorbidity rate, high stroke rate, lower BMI, low diabetes rate), and 152 (19%) were in Cluster 3 (younger, low cardiovascular comorbidity rate, higher BMI, high depression rate). Patients from C3 versus C1/C2 had the highest apnea-hypopnea index at baseline (55 vs. 48/39.5 events/h), were the most symptomatic, had the worst quality of life (QoL), and had the greatest symptomatic and QoL improvement on ASV. They remained the most symptomatic cluster after treatment.

CONCLUSIONS

The identification of subgroups of ASV users with differing responses to therapy and residual symptom burden could facilitate a more personalized approach to ASV prescription and therapy management.

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CLINICALTRIALS: gov; NCT03032029.