Is the time below 90% of SpO2 during sleep (T90%) a metric of good health? A longitudinal analysis of two cohorts
Keywords: Mortality; Nocturnal hypoxemia; Obstructive sleep apnea; Sleep apnea
Abstract
Background: Novel wireless-based technologies can easily record pulse oximetry at home. One of the main parameters that are recorded in sleep studies is the time under 90% of SpO2 (T90%) and the oxygen desaturation index 3% (ODI-3%). We assessed the association of T90% and/or ODI-3% in two different scenarios (a community-based study and a clinical setting) with all-cause mortality (primary outcome). Methods: We included all individuals from the Sleep Heart Health Study (SHHS, community-based cohort) and Santiago Obstructive Sleep Apnea (SantOSA, clinical cohort) with complete data at baseline and follow-up. Two measures of hypoxemia (T90% and ODI-3%) were our primary exposures. The adjusted hazard ratios (HRs) per standard deviation (pSD) between T90% and incident all-cause mortality (primary outcome) were determined by adjusted Cox regression models. In the secondary analysis, to assess whether T90% varies across clinical factors, anthropometrics, abdominal obesity, metabolic rate, and SpO2, we conducted linear regression models. Incremental changes in R2 were conducted to test the hypothesis. Results: A total of 4323 (56% male, median 64 years old, follow-up: 12 years, 23% events) and 1345 (77% male, median 55 years old, follow-up: 6 years, 11.6% events) patients were included in SHHS and SantOSA, respectively. Every 1 SD increase in T90% was associated with an adjusted HR of 1.18 [95% CI: 1.10â1.26] (p value < 0.001) in SHHS and HR 1.34 [95% CI: 1.04â1.71] (p value = 0.021) for all-cause mortality in SantOSA. Conversely, ODI-3% was not associated with worse outcomes. R2 explains 62% of the variability in T90%. The main contributors were baseline-mean change in SpO2, baseline SpO2, respiratory events, and age. Conclusion: The findings suggest that T90% may be an important marker of wellness in clinical and community-based scenarios. Although this nonspecific metric varies across the populations, ventilatory changes during sleep rather than other physiological or comorbidity variables explain their variability.
Más información
| Título según WOS: | Is the time below 90% of SpO2 during sleep (T90%) a metric of good health? A longitudinal analysis of two cohorts |
| Título según SCOPUS: | Is the time below 90% of SpO2 during sleep (T90%) a metric of good health? A longitudinal analysis of two cohorts |
| Título de la Revista: | Sleep and Breathing |
| Volumen: | 28 |
| Número: | 1 |
| Editorial: | Springer Science and Business Media Deutschland GmbH |
| Fecha de publicación: | 2024 |
| Página de inicio: | 281 |
| Página final: | 289 |
| Idioma: | English |
| DOI: |
10.1007/s11325-023-02909-x |
| Notas: | ISI, SCOPUS |