Independent Association Between Oxygen Desaturation Index and Cardiovascular Disease in Non-Sleepy Sleep-Disordered Breathing Subtype: A Chinese Community-Based Study

Abstract

Purpose Non-sleepy sleep-disordered breathing (SDB) is increasingly recognized as an important clinical subtype. The association between non-sleepy SDB and cardiovascular disease (CVD) is not well understood. Our objectives were to investigate the relationship between non-sleepy SDB and CVD and determine which nocturnal hypoxia parameter most strongly reflects this association in a large community population. Patients and Methods Cross-sectional data from 3626 randomly-selected Chinese community-dwelling participants who underwent overnight type IV sleep monitoring were analyzed. Parameters of nocturnal hypoxemia were extracted from sleep monitoring devices, including mean nocturnal oxygen saturation, lowest oxygen saturation, oxygen desaturation index (ODI), and time with oxygen saturation <90%. An ODI ≥7.0 events/h was considered to signify SDB. An Epworth Sleepiness Scale score of 10 or less indicated no sleepiness. Results The SDB rate was 30.7% (1114/3626), of which 96.5% (1075/1114) were considered the non-sleepy SDB subtype. ODI, typical nocturnal intermittent hypoxia indicator for SDB, was independently related to CVD, regardless of whether excessive daytime sleepiness was present. After adjusting for confounders, ODI most strongly reflected the association between non-sleepy SDB and CVD (OR:1.023; 95% CI:1.003–1.043). We observed a nonlinear association between ODI and the prevalence of CVD, where the likelihood of CVD increased with ODI≥10 events/h and a markedly increasing trend was observed with ODI ≥20 events/h (reference ODI = 7.0 events/h). Metabolic parameters, Pittsburgh Sleep Quality Index, and inflammatory marker did not mediate the association between ODI and CVD in the non-sleepy SDB subtype. Conclusion In the Chinese community-dwelling population, non-sleepy SDB was highly prevalent. ODI, an easily extracted indicator from a type IV sleep monitor, most strongly reflected the association between non-sleepy SDB and CVD.

Overall Obesity Not Abdominal Obesity Has a Causal Relationship with Obstructive Sleep Apnea in Individual Level Data

“…There were multiple studies showing that ODI was a more sensitive and valuable predictor to OSA 41,42 which was consistent with our results. Oxygen desaturation parameters were better markers for cardiovascular disease 43 and OSA associated morbidity and mortality compared to the AHI. 44,45 In turn, it was reported that BMI influences the accuracy of ODI for OSA diagnosis.…”

A Review of Novel Oximetry Parameters for the Prediction of Cardiovascular Disease in Obstructive Sleep Apnoea

“…Time below 90% saturation (T90) is recognised as an independent predictor of allcause CVD mortality and widely used in many studies [4,[23][24][25][26][27]. The calculation method of T90 varies among studies and can be divided into time-based and percentage-based parameters, as shown in Table 1 [4,14,18,22,27,28]. The time-based TST90 measures the time per night with oxygen saturation below 90%, and thus measures the cumulative hypoxemia insult.…”

“…Percentage-based parameter T90% [18] The percentage of sleep time with oxygen saturation level below 90%. The unit of this parameter is %.…”

“…Diagnostics 2023, 13, x FOR PEER REVIEW 3 of 18 a reliable predictor of CVD events too. Wang et al found that T90% outperformed TST90 in the prediction of incident CVD in patients with non-sleepy sleep-disordered breathing (SDB) [18]. However, other studies have not supported this conclusion.…”

“…Studies have shown that some oximetry parameters may provide good performance in the prediction of future CVD events. These parameters include T90, oxygen desaturation index (ODI), and area-based desaturation metrics [4,14,[18][19][20]. The T90 parameter measures the time below 90% oxygen saturation; ODI indicates the number of oxygen desaturation events per hour of sleep; and area-based desaturation metrics calculate the area of the desaturation [14,[19][20][21].…”