Night-to-Night Variability of Polysomnography-Derived Physiologic Endotypic Traits in Patients With Moderate to Severe OSA

Abstract

Background: Emerging data suggest that determination of physiologic endotypic traits (eg, loop gain) may enable precision medicine in OSA.

Research question: Does a single-night assessment of polysomnography-derived endotypic traits provide reliable estimates in moderate to severe OSA?

Study design and methods: Two consecutive in-lab polysomnography tests from a clinical trial (n = 67; male, 69%; mean ± SD age, 61 ± 10 years; apnea-hypopnea index [AHI] 53 ± 22 events/h) were used for the reliability analysis. Endotypic traits, reflecting upper airway collapsibility (ventilation at eupneic drive [V_passive]), upper airway dilator muscle tone (ventilation at the arousal threshold [V_active]), loop gain (stability of ventilatory control, LG1), and arousal threshold (ArTh) were determined. Reliability was expressed as an intraclass correlation coefficient (ICC). Minimal detectable differences (MDDs) were computed to provide an estimate of maximum spontaneous variability. Further assessment across four repeated polysomnography tests was performed in a subcohort (n = 22).

Results: Reliability of endotypic traits between the two consecutive nights was moderate to good (ICC: V_passive = 0.82, V_active = 0.76, LG1 = 0.72, ArTh = 0.83). Variability in AHI, but not in body position or in sleep stages, was associated with fluctuations in V_passive and V_active (r = -0.49 and r = -0.41, respectively; P < .001 for both). MDDs for single-night assessments were: V_passive = 22, V_active = 34, LG1 = 0.17, and ArTh = 21. Multiple assessments (mean of two nights, n = 22) further reduced MDDs by approximately 20% to 30%.

Interpretation: Endotypic trait analysis using a single standard polysomnography shows acceptable reliability and reproducibility in patients with moderate to severe OSA. The reported MDDs of endotypic traits may facilitate the quantification of relevant changes and may guide future evaluation of interventions in OSA.

Keywords: arousal threshold; collapsibility; endotypes; loop gain; muscle compensation; phenotypes; polysomnography; precision medicine; reliability; sleep-disordered breathing.

Figure 1

Study flow chart of the presented analysis. Main analysis was performed on 67 participants with two consecutive polysomnography tests for evaluation of night-to-night variability. A subgroup analysis was performed of 22 participants with a total of four repeated polysomnography tests available over the course of 4 weeks.

Figure 2

Conceptual visualization of the computation of endotypic traits. A, The ventilatory control system is evaluated by a breath-by-breath analysis of individual 7-min sequences of disturbed breathing. Parameters are derived based on the estimated ventilatory drive. B, Upper airway characteristics are evaluated based on a combination of all evaluated 7-min sequences. Parameters are derived based on the observed ventilation at different levels of ventilatory drive as a surrogate of upper airway muscle activity.

Figure 2

Conceptual visualization of the computation of endotypic traits. A, The ventilatory control system is evaluated by a breath-by-breath analysis of individual 7-min sequences of disturbed breathing. Parameters are derived based on the estimated ventilatory drive. B, Upper airway characteristics are evaluated based on a combination of all evaluated 7-min sequences. Parameters are derived based on the observed ventilation at different levels of ventilatory drive as a surrogate of upper airway muscle activity.

Figure 3

A-D, Bland-Altmann plots (A, B) and distribution of differences (C, D) for AHI and LG1 during nonrapid eye movement sleep. Shown data are taken from the main analysis cohort (n = 67), addressing the differences between two consecutive polysomnographic assessments. Distribution patterns show a normally distributed spread of differences, indicating no systematic bias in the tested parameters and justifying the use of mean results from consecutive recordings to reduce variability. AHI = apnea-hypopnea index; LG1 = loop gain at 1 cycle/min.