Is the time below 90% of SpO2 during sleep (T90%) a metric of good health? A longitudinal analysis of two cohorts.
Sleep Breath
; 28(1): 281-289, 2024 Mar.
Article
de En
| MEDLINE
| ID: mdl-37656346
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 1.10-1.26] (p value < 0.001) in SHHS and HR 1.34 [95% CI 1.04-1.71] (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.Mots clés
Texte intégral:
1
Collection:
01-internacional
Base de données:
MEDLINE
Sujet principal:
Sommeil
/
Syndrome d'apnées obstructives du sommeil
Type d'étude:
Prognostic_studies
/
Risk_factors_studies
Limites:
Female
/
Humans
/
Male
/
Middle aged
Langue:
En
Journal:
Sleep Breath
Sujet du journal:
NEUROLOGIA
/
OTORRINOLARINGOLOGIA
Année:
2024
Type de document:
Article
Pays d'affiliation:
Chili