Ana Isabel Soria Robles¹, Cristina Aguado Blanco¹, María Juárez España¹, Fernando Andrés², Pretel. María Llanos Massó Núñez³, María Sol Vizcaíno García³,Pedro Abizanda⁴, Ramón Coloma Navarro³

1. Geriatrics Department, Complejo Hospitalario Universitario de Albacete, Albacete, Spain

2. Statistics Department. Complejo Hospitalario Universitario de Albacete, Albacete, Spain

3. Sleep Unit, Neumology Department, Complejo Hospitalario Universitario de Albacete, Albacete, Spain

4. Head of the Geriatrics Department, Complejo Hospitalario Universitario de Albacete, Albacete, Spain. Facultad de Medicina de Albacete, Universidad de Castilla-La Mancha, Albacete, Spain. CIBER de Fragilidad y Envejecimiento Saludable (CIBERFES), Instituto de Salud Carlos III, Madrid, Spain

^*Corresponding author: :Dr. Ramón Coloma Navarro, Sleep Unit, Neumology Department, Complejo Hospitalario Universitario de Albacete, Spain.

Abstract

Obstructive sleep apnea (OSA) prevalence increases with age. Its severity is determined by apnea hypopnea index (AHI), but this categorization does not contemplate other oxymetric parameters that may have influence on the disease´s development in very old adults. The objective was to analyze differences in respiratory polygraphy/polysomnography parameters in OSA patients, depending on their age and sex. Methods: Retrospective Propensity Score matched study in a Sleep Unit of a University Hospital, including 11,747 participants, 210 with an age ≥ 80 years. A Propensity Score matching was held creating 4 groups of age using as a reference the 210 very old adults. Main result variables of the respiratory polygraphy/polysomnography were sleep time with arterial oxygen saturation (SaO2) < 90% (T90), medium SaO2, minimal SaO2, and AHI. Results: With similar AHI values, very old OSA patients had highest T90 and lower mean and minimum SaO2 values than those with younger ages. The proportion of severe OSA patients with T90 in the highest quartile were 12.5%, 14.8%, 21.7%, and 34% for the young adults, adults, old, and very old participants respectively (p<0.001). All these findings were more pronounced in very old women compared to men, addressing a different pattern of severity between sexes as they get older.Conclusions: Among patients with the same severity of OSA measured by AHI, the group of oldest adults had increased values of T90, and lower SaO2 values. This emphasizes the possible limitations that AHI has to define severe OSA in very old patients, mainly in women.

Key words: Obstructive sleep apnea, T90, apnea hypopnea index, older adults.

Introduction

Obstructive sleep apnea (OSA) is a highly prevalent respiratory disorder, and a major public health issue affecting almost one billion people all over the world [1-3]. The prevalence of OSA in population over 60 years old varies among the different studies, but it is estimated to be around 27-80% depending on the definition, population, and site analyzed [1]. This respiratory disorder has a great impact on individual´s health and it is responsible for multiple morbidities like hypertension, increased risk for cerebrovascular events, arrhythmias, heart failure, or diabetes mellitus [4]. OSA and aging have a strong bidirectional relationship. Age increases the severity of OSA [5], and is frequently underreported in this population [1]. Aging can lead to neurological and physical changes predisposing to OSA and OSA is responsible of other pathological processes that could accelerate aging. In the same way, other physiological changes seen in OSA, like accelerated atherosclerosis and changes in inflammatory and metabolic markers, correspond to conditions seen in the process of aging [1]. There are some studies that even find association between OSA and Alzheimer´s disease and emphasize that OSA treatment with continuous positive airway pressure (CPAP), may result in an improvement in patient´s cognitive condition [1-7].

Actually, the severity of OSA is determined exclusively by the apnea-hypopnea index (AHI). This categorization has limitations because it does not contemplate other parameters that have influence on the disease course and future consequences. According to the International Consensus Document on Obstructive Sleep Apnea, OSA severity classification should take into a count the following items: AHI, total sleep time spent with arterial oxygen saturation (SaO2) < 90% (T90), excessive daytime sleepiness assessed by the Epworth Sleepiness Scale, obesity measured with the body mass index (BMI), and other comorbidities related with OSA like cardiovascular disease risk factors, coronary artery disease, previous cerebrovascular disease, heart failure and atrial fibrillation [4].

According to some studies, at least 50% of older adults have an AHI ≥ 5, the cut-point for OSA diagnosis. However, excessive daytime sleepiness is less frequent in this group of age. This could imply that the impact of OSA in older adults may have differences and particularities when compared to that in younger populations, even with the same AHI [1]. Some authors even suggest that AHI does not have a significant correlation with excessive daytime sleepiness, cardiovascular morbidity and mortality [8,9]. In that sense, other sleep parameters that relate with hypoxia, like T90, appear to be better predictors of cardiometabolic effects in the long term [8]. The severity of apneas and desaturations is also related with clinical and cardiovascular consequences [9]. In that context, there could be an association between T90 >20% and minimum SaO2 < 75% with an increased risk of hypertension, diabetes mellitus and 5-year mortality [10]. This oxygen parameters may define different groups of OSA, and also identify patients with high risk phenotypes, even if they have the same AHI [10,11]. For these reasons, the main objective of this study was to analyze the differences in respiratory polygraphy (RP) or polysomnography (RPS) parameters between very old patients with OSA, and younger matched patients.

Methods

Participants were selected from a cohort of patients belonging to a Clinical Sleep Unit of a University Hospital. The collected data from this cohort was obtained by RP/RPS between 24th April 1989 and 5th July 2021. Of the 11,747 patients included in this cohort, 11,331 patients with confirmed OSA diagnosis were included in the present research, considering OSA diagnosis an AHI equal or higher than five. First, from these 11,331 OSA patients, all those with an age equal or older than 80 years (n=225) were considered the initial reference group for the Propensity Score matching process. Second, patients younger than 80 years were divided into three groups: younger than 45 years (n=2,696), between 45 and 65 years (n=6,010) and between 65 and lower than 80 years old (n=2,400). We labeled our four groups of age as very old (≥ 80 years), old (≥ 65 to <80 years), adults (≥ 45 to < 65 years), and young adults (< 45 years). In order to minimize Propensity Score selection bias, the sample was adjusted by sex, AHI, BMI, and hypertension (defined by systolic blood pressure higher or equal to 140 mmHg or diastolic blood pressure higher or equal to 90 mmHg). Consequently, 2,591, 5,756, 2,307, and 210 patients had valid data for the Propensity Score matching process for the four age groups respectively (young adults, adults, old, and very old). Patients belonging to the oldest group (n=210), were matched 1:1 with patients from the rest of the three age groups. Supplementary Figure 1 shows the flowchart of the Propensity Score process. The result variables were the total sleep time spent with SaO2 < 90% (T90), baseline SaO2 (measured with an oxymeter previously to RP/RPS), mean SaO2 (measured with RP/RPS), and minimum SaO2 (measured with RP/RPS). Other considered variables of the study were AHI (measured with RP/RPS), baseline Epworth Sleep Scale score, baseline BMI, and the previous diagnosis of hypertension, diabetes mellitus, dyslipidemia, ischemic heart disease and stroke, as reflected in the electronic Health Records of the participants. OSA was classified as mild (AHI ≥ 5 to < 15), moderate (AHI ≥ 15 to < 30), and severe (AHI ≥ 30) following the International Consensus Document on Obstructive Sleep Apnea [4]. Finally, the T90 was classified in quartiles for further analyses.

Descriptive results are presented as medians with the interquartile range (IQR) or number of participants with the respective percentages. Differences between groups were analyzed using chi-square tests and Kruskal-Wallis tests. Subsequently, density plots using Rieman sum were constructed representing the individual probability of being among a value range of the T90 and AHI for each age group. The value range represents the percentage of time in which the participant has a SaO2 less than 90%, and the number of apneas-hypopneas. We constructed linear regression models to analyze the relationship between T90 and AHI for the four age groups, and finally we determined the percentages of T90 quartiles per OSA severity and age/sex groups. Logistic regression analyses were conducted to analyze the relevance of age groups in OSA severity. All analyses were done in R (v4.0.0).

Results

Supplementary Table 1 shows the characteristics of the complete sample population and of the four age groups. The median age of the complete sample was 65 years (IQR 44-80), and 373 (44.4 %) were female. The median age of the very old group was 82 years (IQR 80-83), and 93 were female (44%). Considering the 840 subjects included in the match, 503 (59.9%) had hypertension, 138 diabetes mellitus (16.4%) and 240 dyslipidemia (28.6%). Diabetes and dyslipidemia were more common in the old and very old age groups. Ischemic heart disease and stroke were also more common in the very old and old groups. Supplementary Table 1 also provides information about other parameters related to the severity of OSA. As the very old group had a median AHI of 43 (IQR 27-60), the other three matched groups also had a median AHI > 30 corresponding to severe OSA, due to the matching process. However, we could not find differences between age groups in the Epworth Sleepiness Scale, which was 12 points (IQR 8-15) in the complete sample. There were significant differences between age groups in all the SaO2 parameters, more pronounced in the T90. The T90 quartiles for the complete sample were 3.3%, 22%, and 66%, and the T90 median T90 was 5%, 15%, 34%, and 44% in the young adults, adults, old, and very old groups respectively (p<0.001). OSA was considered mild, moderate or severe in 120 (14.3%), 175 (20.8%), and 545 (64.9%) of the participants, following AHI values.

Supplementary Figure 2 shows the AHI (panel A) and T90 (panel B) density curves according to each group of age, and by sex categories (panels C and D). Notwithstanding the matching process, AHI density curves show that old and very old participants had more frequently higher AHI values. In addition, younger patients (especially those < 45 years old) were more probable to have lower T90, while very old participants had a greater dispersion of the T90 values and a greater probability of higher percentages of T90. Regarding sex, panel C shows that contrary to men that present similar AHI across all age ranges, women present higher AHI as they get older. In addition, panel D depicts a different T90 distribution in men and women as age increases, with young women usually presenting with very low T90 values, and very old women with higher T90 figures. Supplementary Figure 3 illustrates the relationship between AHI and T90 for the four age groups with the correspondent 95% confidence interval, using linear regression models. Greater AHI correlated positively with higher percentages of T90 in all age groups, although the lines were up-shifted with older ages, reflecting that with similar AHI, T90 increases as the population gets older.

Finally, Supplementary figure 4A shows a stacked bar chart formed by OSA severity groups classified by AHI, and T90 divided into quartiles. At a first view, old and very old subjects presented more frequently moderate or severe OSA. In addition, it can be observed that highest T90 (third and fourth quartiles) were less common among mild or moderate OSA (blue and yellow bars), and more common in patients with severe OSA (red bars). This Supplementary figure also shows that, even though all patients with severe OSA had higher T90, very old patients had the highest T90 in this category (severe OSA - T90 fourth quartile). In the complete sample, 173 patients (20.6%) presented severe OSA with T90 in the highest quartile (T90>66%), but in the four age groups the Supplementary figures were 26 (12.5%), 31 (14.8%), 45 (21.7%), and 71 (34%) for the young adults, adults, old, and very old participants respectively (p<0.001). These findings are mainly observed in women than in men ( Supplementary figure 4B), addressing a different pattern of severity between men and women as they get older.

Age was the main independent risk factor for presenting OSA in the highest severity category (severe OSA - T90 fourth quartile), adjusted for sex, diabetes, dyslipidemia, stroke, ischemic heart disease, BMI, and Epworth scale. Those with an age between 65 and < 80, and ≥ 80 years, presented a higher association with this category, OR 2.57 (95% CI 1.42-4.65), and OR 5.52 (95% CI 3.06-9.97) respectively, than those younger than 45 years old.

Discussion

The aim of this research was to analyze the relationship between AHI and SaO2 parameters, mainly T90, in very old adults with OSA. In our main study group, OSA patients with an age equal or older than 80 years, we included 210 participants after adjusting for relevant variables, and three propensity score matched age groups were constructed for comparisons. The main results of our study are that severe OSA seems to be more frequent in older populations than in younger ones, that with similar OSA severities, SaO2 parameters show worse results in aged groups, increasing hypoxia risks, and that the patterns of severity change between men and women as they get older.

The prevalence of OSA in older adults and its impact on health justifies the importance of redefining its distinctive features in this group of age. Despite the clearly demonstrated increased prevalence of OSA with aging [1-15], there is still scarce research concerning this pathology in older populations, including diagnosis, specific phenotypes, management, and consequences [3-16]. As we mentioned before, severity of OSA is based upon AHI, although there are many studies that advocate against focusing exclusively in this parameter [8-11]. AHI is an imperfect measure of OSA severity and treatment response [17], and hypoxic burden (the area under the curve of desaturation resulting from an apnea or hypopnea) [18], heart rate response (change in heart rate after a respiratory event) [19,20], or neurocognitive measures [6] may be better biomarkers for risk stratification, especially in older adults.

A recent retrospective propensity score matched study in 110 Chinese adults older than 65 years, showed that the presence of OSA in this population is associated with significant abnormalities of sleep architecture, aggravated nocturnal hypoxia and increased risks of hypertension, coronary artery disease, and stroke, suggesting that it may represent a unique clinical phenotype [21]. Moreover, it has been described that in patients with more severe OSA, longer sleep apneas and hypopneas, and marked intermittent/global nocturnal hypoxemia may be more likely to develop cardiometabolic comorbidities [22]. OSA is the manifestation of a multifactorial syndrome, resulting from repetitive partial or complete obstruction of the airway that leads to sympathetic activation and vagally-mediated bradycardia, intrathoracic pressure swings, intermittent hypoxia, oxidative stress, systemic inflammation, and sleep fragmentation [23]. In the pathogenesis, several factors like compromised upper airway anatomy, edentulous condition, poor pharyngeal muscle responsiveness, respiratory control instability, and low arousal threshold have been described [1-4]. All these factors have also been related with the aging process [1].

Regarding OSA severity and hypoxia surrogates, variables related with hypoxemia like T90 are not considered at the present in the classification, although nocturnal hypoxemia may be associated with clinical differences and worse prognoses [10,11]. Some studies have reported results of individuals with equal AHI but different hypoxemic burden (T90 and minimum SaO2), showing that patients with hypoxemia have greater expressions of proinflammatory markers, higher platelet count and endothelial stiffness [10-25]. These two studies from Labarca et al. showed that T90 > 20% was associated with an increased severity of OSA, and a higher risk of hypertension, dyslipemia, type 2 diabetes mellitus and even 5-year mortality. Another research carried out in old men [26], emphasized that the prognostic value of T90 did not depend on the AHI value, and that even in patients with a low AHI, an increased hypoxemic burden could be associated with an increased cardiovascular mortality. This new approach to the severity of T90 may also have therapeutic implications, because in this case, the use of CPAP guided by AHI may not translate into an improved survival [26]. Our sample had no differences in values of AHI, but the differences shown in oximetric parameters could define a new population at increased risk of comorbidities and mortality.

It is not clear which is the cut off value for T90 that could show and increased risk for the patients. Quan et al. established a cutoff of T90 ≥ 9.5% to categorize patients with high risk of cardiovascular events [27]. Labarca et al. identified different cut-off points of T90 depending on the comorbidity; T90 ≥ 10% was associated with an increased risk of hypertension, T90 ≥ 15% with higher risk of coronary heart disease, and T90 ≥ 20% was the cut-off value for an increased risk of type 2 diabetes mellitus and for cardiovascular mortality [11]. In our study, very old patients had the highest T90 values, and more than one third (34%) presented AHI > 30 and T90 > 66% (fourth quartile), otherwise implying higher risk of these events.

Sex is a relevant aspect in OSA, with several studies finding differences in the presentation of the disease between men and women [28]. A German study reported that female OSA patients were significantly older than males. Men presented higher AHI, although women showed a higher AHI in REM sleep. Finally, men were desaturated more often than women [29]. Another Chinese study described that the AHI during total sleep time and non-rapid eye movement sleep was higher in OSA men compared with women, whereas AHI during rapid eye movement sleep was higher in women. No significant differences in the lowest SaO2 were observed between men and women [30]. The findings of these two studies do not match with our results, but could be perfectly explained by differences in the age of the participants, 60.9 ± 12.3 for women and 56.9 ± 12.5 years for men in the German study, and 58.2 ± 8.9 for women and 57.3 ± 9.2 years for men in the Chinese study, both of them not really including very old adults. Our data support the idea that OSA in very old adults, mainly in women, may be either a different disease or a disease with differential characteristics, needing better physiopathological, management, and outcomes considerations.

Regarding the hypoxic burden, in severely OSA older adults, it has been described a decreased relative regional cerebral blood flow (rCBF) in the left parietal lobe, the left precentral gyrus, the bilateral postcentral gyri and the right precuneus, a hypoperfusion geographic pattern similar to that seen in early Alzheimer's disease [31]. In addition, untreated OSA older adults presented a worsening in rCBF in specific brain areas over time, mainly left hippocampus and the right parahippocampal gyrus, while treated OSA showed the opposite [32]. This could explain the relationship between OSA and cognitive impairment, and other geriatric syndromes like frailty, instability, depression, or deconditioning in older adults [33-36]. CPAP treatment has yielded promising results in dementia prevention, although results are not definitive [37,38].

Many issues related to aging and OSA have no clear answers actually. First, there is a need to define the disease and its impact on the different age and gender groups. Second, we need to know how the different comorbidities like heart failure or dementia modulate the impact of OSA on major outcomes. Third, not all respiratory events during sleep have an obstructive nature, because there are also central events which have important but not well known consequences. Fourth, we need to determine the cut-off points of respiratory parameters (like AHI or T90) that put this population at higher risk of adverse events, not only mortality, but also frailty, disability, cognitive decline or other geriatric syndroms. Fifth, the best treatment modality for each circumstance and for each older adult is not well defined. Not all symptomatic patients should be treated with continuous CPAP, alone or in combination with other treatments. Sixth, the results of most published studies in young populations should not be extrapolated to older adult populations. Large clinical trials with international participation and powerful methodologies are thus necessary to answer these black hole aspects of OSA in older adult populations [3].

Funding

This work was supported by CIBERFES (CB16/10/00408), Instituto de Salud Carlos III, Ministerio de Economía y Competitividad, España. Ayuda cofinanciada por el Fondo Europeo de Desarrollo Regional FEDER Una Manera de hacer Europa.

Conflicts of interest

All authors declare that there are no conflicts of interest.

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Received: May 2, 2024;
Accepted: May 28, 2024;
Published: May 31, 2024.

To cite this article : Ana Isabel Soria Robles, Cristina Aguado Blanco, María Juárez España, Fernando Andrés, Pretel. María Llanos Massó Núñez, María Sol Vizcaíno García, et al. Obstructive Sleep Apnea and Oxygenation in Very Old Adults: A Propensity-Score Match Study. European Journal of Respiratory Medicine. 2024; 6(2): 429 - 433. doi: 10.31488/EJRM.148.

© The Author(s) 2024