Introduction

Sleep apnea is a prevalent sleep disorder that can impact individuals of all ages, although it is more frequently observed in older adults [1]. This condition is defined by repeated interruptions in breathing during sleep, potentially resulting in various complications. These complications may include daytime fatigue, excessive drowsiness, a heightened risk of cardiovascular disease, sudden drops in blood oxygen levels, challenges with specific medications like sedatives and painkillers, and an elevated likelihood of post-surgical complications due to the relaxing effects of general anesthetics on the upper airway [2].

Sleep apnea is a complex condition with various risk factors such as obesity, family history, allergies, and enlarged tonsils. Healthcare professionals typically conduct an overnight sleep study to diagnose this condition. During this study, they closely monitored for more than five episodes per hour, classified as “apneas” when there is a complete or near-complete cessation of breathing and “hypopneas” when there is a partial reduction in breathing [3].

Obstructive Sleep Apnea (OSA) occurs when the upper airway is partially or completely blocked during sleep, causing irregular or interrupted breathing patterns, it can lead to decreased oxygen levels and increased carbon dioxide levels in the bloodstream, which can trigger various physiological responses such as heightened oxidative stress, adrenergic activation, endothelial dysfunction, metabolic dysregulation, endocrine system activation, increased clotting tendencies, and chronic systemic inflammation [4, 5]. Additionally, chemoreceptors in the bloodstream detect elevated carbon dioxide levels, signaling the brain to awaken the person. This arousal clears the airway, resuming normal breathing and restoring oxygen levels. Afterward, the person typically falls back asleep [4].

Obstructive sleep apnea (OSA) severity and treatment outcomes are commonly assessed using AHI [6]. AHI calculates the average number of apneas and hypopneas per hour of sleep. The American Academy of Sleep Medicine (AASM) defines three severity categories based on AHI scores [7]: mild (5–15 events/h), moderate (15–30 events/h), and severe (> 30 events/h).

Chronic inflammation is pooled in various diseases, including metabolic disorders, neurodegenerative disorders, cancer, and cardiovascular diseases [8]. The inflammatory response involves a complex sequence of events, including cellular and vascular changes and the release of specific humoral secretions [9]. Immune cells release mediators such as histamine, prostaglandins, leukotrienes, free radicals, and serotonin as part of this process [10].

Chronic inflammation is characterized by the infiltration of mononuclear cells, such as monocytes and lymphocytes, fibroblast proliferation, and collagen formation [8]. In chronic inflammation, tissue damage is often caused by nitrogen and oxygen-reactive species from infiltrated inflammatory cells [11].

Systemic inflammatory markers like the platelet/lymphocyte ratio (PLR), neutrophil/lymphocyte ratio (NLR), monocyte/lymphocyte ratio (MLR), and the systemic inflammation response index (SIRI) have emerged as valuable independent prognostic indicators in various diseases [12,13,14,15]. SIRI, introduced in 2016, is calculated using routine blood samples and effectively reflects cancer-related inflammatory responses, making it a noninvasive, cost-effective, and readily accessible tool [16].

Initially developed for predicting survival in advanced pancreatic cancer patients following chemotherapy, SIRI's utility has expanded to assess systemic inflammation in multiple cancer types [16, 17]. By 2019, eleven studies and a systematic review had collectively established that pretreatment SIRI is a useful predictive marker for adverse prognosis in cancer patients [18].

Recent research discovered the connection between obstructive sleep apnea (OSA) and specific inflammatory biomarkers. Two noteworthy biomarkers, C-reactive protein (CRP) and fibrinogen, which play crucial roles in inflammation and coagulation [19,20,21], have shown a direct relationship with the severity of OSA as measured by the apnea-hypopnea index (AHI) and arousal index (AI). Conversely, these biomarkers exhibit an inverse association with mean and lowest oxygen saturation levels during sleep [22]. Another biomarker under investigation is erythrocyte sedimentation rate (ESR), which gauges the tendency of red blood cells to clump together [23, 24]. Fleming et al. have postulated that various combinations of these biomarkers may offer more robust insights into OSA, potentially serving as physiological signatures of the disorder that could benefit initial OSA screening and subsequent monitoring [25].

The present study highlighted the inflammatory aspects of patients with severe OSA and tried to find some independent predictors of disease severity.

Methods

Patients and study design

A retrospective cohort study was conducted at the sleep lab of King Fahad Specialist Hospital in Buraidah, Qasim, Saudi Arabia, between June 2022 and 2023. The study included OSA-confirmed cases (27), via PSG (Alice 6 LDx Machine connected with Sleepware G3 program from Philips company), excluding those under 18 years and with autoimmune disease, hepatic and renal dysfunction, malignancy, and other sleep-related disorders.

Measurement and endpoint

The endpoint of the study was detecting severe OSA group; the severity of OSA was classified according to the AHI index [7].

The basic demographic data of the recruited patients were collected in an Excel sheet. Additionally, the full and differential blood count at the time of diagnosis was collected from the patient’s file as well as the CRP and ESR. The inflammatory ratios were measured automatically via the specialized formula in an Excel sheet. Hence, NLR was equal to (Neutrophil/Lymphocyte) number, PLR was equal to (Platelets/Lymphocyte) number, and SIRI was equal to (Neutrophil × Monocytes)/lymphocytes.

Ethics approval, IRB number, and consent to participate

Ethical approval has been obtained from the ethical committee office, King Fahad Specialist Hospital, Buraidah, Qasim, Saudi Arabia, (No: 607-45-3465) in accordance with the Helsinki Declaration protocol. Informed consent has been obtained from all participants involved in the study, as well as their legal guardians, to ensure that they are fully aware of the nature and purpose of the research, and have given their voluntary and informed consent to participate.

Statistical analysis

The data was collected in an Excel sheet and analyzed using Sigma Plot for Windows version 12.5.0.38 (Systat Software, Inc, UK, 2011). The normality of the data was measured using the Shapiro-Wilk test. A one-way ANOVA test or Kruskal Wallis test was used to compare means, while a Chi-square test was used to compare frequencies. The Pearson correlation coefficient was used to find the correlation between AHI and other inflammatory cells and markers. General linear model and Logistic regression analysis with backward elimination technique were used to evaluate the impact of inflammatory cells and markers on AHI and detecting severe OSA. All tests were two-sided, and a p value < 0.05 was considered significant.

Results

Characteristics of patients with OSA

Table 1 showed that patients with moderate and severe OSA were significantly older and had associated comorbidities such as diabetes mellitus (DM) and hypertension (HTN) compared to those with mild OSA. The p values were 0.02 and 0.001 for age, and 0.03 and 0.001 for DM and HTN, respectively. However, there was no significant difference between males and females (p = 0.76).

Table 1 Characters of patients with OSA
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Inflammatory aspect of OSA in correlation with disease severity

Table 2 revealed that across the different severity groups of OSA, lymphocyte count, platelet count, and PLR showed a significant difference between the groups, p = 0.01 for all; however, considering their linear relationship with AHI, only PLT has a significant negative correlation, r = − 0.23, p = 0.03 (Fig. 1) (Supplementary Table 1). On the other hand, neither neutrophils nor NLR revealed any significant difference across the groups of OSA, yet, in Fig. 2, both neutrophils and NLR showed a significant positive linear relationship, r = 0.31 and 0.37, respectively, p = 0.001 for both. Moreover, despite an insignificant difference in SIRI between the OSA groups, it showed a significant positive correlation with AHI; r = 0.39, p = 0.001 (Fig. 3). Furthermore, the inflammatory markers CRP and ESR, which are first-phase reactants, significantly increased in moderate and severe OSA compared to mild OSA (Table 2, p < 0.05). Both markers demonstrated a significant positive linear relationship with AHI (Fig. 4), with r = 0.61 and 0.54 and p < 0.001 for both, respectively.

Table 2 Inflammatory aspect of patients with different severity groups of OSA
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Fig. 1
figure 1

PLT in correlation with AHI. *The test of significance: Pearson correlation coefficient, the direction before "r" denoting the direction of relationship, p < 0.05 considered significant

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Fig. 2
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Neutrophils and NLR in correlation with AHI. *The test of significance: Pearson correlation coefficient, the direction before “r” denoting the direction of relationship, p < 0.05 considered significant

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Fig. 3
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SIRI in correlation with AHI. *The test of significance: Pearson correlation coefficient, the direction before “r” denoting the direction of relationship, p < 0.05 considered significant

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Fig. 4
figure 4

Inflammatory markers in correlation with AHI. *The test of significance: Pearson correlation coefficient, the direction before “r” denoting the direction of relationship, p < 0.05 considered significant

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Factors influencing the degree of AHI and predict moderate to severe OSA

The results presented in Table 3 indicate that a general linear model with a backward elimination technique found that being hypertensive and having higher SIRI, CRP, and ESR levels all independently affected AHI, with p values less than 0.05 for all. However, an increase in monocyte levels had a significant negative impact. Furthermore, Table 4 revealed that for every one-unit increase in SIRI, CRP, and ESR levels, the likelihood of moderate and severe OSA doubled with p-values less than 0.05 for all. On the other hand, being hypertensive increased the likelihood of moderate and severe OSA by sixteen times, with a p value of 0.01.

Table 3 Factors influencing the degree of AHI
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Table 4 Predictors of moderate/severe OSA
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Discussion

The exact role of chronic inflammation in the development of obstructive sleep apnea has yet to be fully understood. However, it is believed that multiple factors cause the pathogenesis of OSA. Precisely, it is thought that activation of certain inflammatory pathways occurs in response to the activity of the sympathetic nervous system and oxidative stress. These pathways can lead to vascular endothelial dysfunction and metabolic dysregulation, contributing to the development and progression of OSA [26].

The present study revealed that patients with moderate to severe OSA were generally older and had associated conditions like DM and HTN. Additionally, being hypertensive positively influences the degree of AHI, and the likelihood of moderate to severe OSA increases by 16 times in hypertensive patients. A supportive study found that older patients with OSA were more prone to severe disease and could benefit from positional therapy [27]. Moreover, moderate to severe OSA was significantly linked to DM or its complications, and could also be related to co-association with hypertension [28, 29].

The frequent drops in oxygen levels and brief awakenings during sleep in patients with OSA, potentially affect a patient’s overall health. It has been linked to cardiovascular complications, including high blood pressure, pulmonary hypertension, heart failure, irregular heartbeats, heart attacks, and strokes [30]. In contrary, many clinical studies involving OSA patients have been hindered by inadequate control for co-morbid conditions, such as obesity, pre-existing cardiovascular disease, or medication use. This limitation can make it difficult to isolate the specific impact of OSA on cardiovascular health. Moreover, study results related to OSA and its impact on cardiovascular health often showed substantial variability, making it challenging to establish transparent cause-and-effect relationships and identify consistent mechanisms [31]; therefore, the most acceptable explanation for this variability is related to variations in the morphology and duration of nocturnal airflow cessations and oxygen desaturation, which may be not fully captured by the traditional AHI.

Obesity is a common risk factor for OSA and DM. However, if patients have an array of clusters of metabolic syndrome such as obesity, HTN, and DM, the condition may be further exacerbated. Metabolic syndrome is higher in OSA patients due to commonly shared risks, and studies indicate that metabolic syndrome is significantly associated with severe OSA [32].

Many literatures have discussed the coexistence of a chronic inflammatory state in patients with OSA. The mechanism of developing this chronic inflammatory state is still controversial [26, 33]; one of these mechanisms is the effect of intermittent hypoxia in association with oxidative stress, which may increase the sympathetic response [34, 35]. The other alternative pathway may be due to the release of many inflammatory cells and mediators from the upper airways into the systemic circulation by the effect of endothelial injury [36].

In this study, it was shown that OSA has an inflammatory aspect. The results indicated a positive correlation between AHI and neutrophilis. However, as the severity of the disease increased, lymphocyte count decreased, which could be explained by the significant positive correlation between NLR and AHI. Additionally, NLR independently predicts moderate to severe OSA.

Neutrophils are innate inflammatory cells that serve as a first-line immune response during acute inflammation. However, research has found that neutrophils also play a crucial role in chronic inflammation [37]. They contribute to the development of coronary atherosclerosis by activating macrophages [37, 38]. Additionally, the average level of neutrophils in the blood does not necessarily indicate the absence of underlying immune system activation, as seen in acute myocardial infarction and heart failure [39]. Studies have shown a significant correlation between NLR and AHI, which supports our findings [40, 41]. This link may be due to subclinical inflammation in the respiratory tract system and the chronic inflammatory state of associated comorbidities such as diabetes and hypertension.

Our study found that blood monocytes have an inverse correlation with AHI. Monocyte cells are mainly synthesized in the bone marrow, and their circulation period in the blood does not exceed 3 days before they immigrate to different tissues, where they are transformed into activated macrophages [42]. When exposed to hypoxia, these macrophages release a pro-inflammatory cytokine called macrophage migration inhibitory factor (MIF). This cytokine has a dual action on the hypothalamic-pituitary-adrenal axis [43], significantly regulating inflammation.

In recent studies, the Systemic Inflammatory Response Index (SIRI) has been used to predict the poor prognosis of cancer [15,16,17,18], and cardiovascular disease patients [44, 45]. Our study found a positive correlation between SIRI and AHI, indicating that the likelihood of moderate to severe OSA doubled with every unit increase in SIRI. SIRI comprises three essential blood cells: neutrophils, monocytes, and lymphocytes, contributing to its effectiveness. These findings are consistent with a recent study [46].

As a part of systemic inflammation response, CRP and ESR, a first-phase inflammatory marker, were easy to measure as a routine workup. In our work, CRP and ESR correlated positively with AHI and particulate a high prediction power for moderate to severe OSA.

A supportive study found that individuals with sleep apnea and those with a high risk of heart problems had similar levels of CRP. The study matched patients and controls carefully and suggested a possible causal link between sleep apnea and elevated CRP [47], which was recently supported by another study [48]; the authors referred the possible causality to the constant inflammatory state of upper airway mucosa due to repeated closure and opening. Additionally, intermittent hypoxia leads to the generation of reactive oxygen species that trigger inflammatory pathways like TNF-α [49]. Moreover, OSA has a notable impact on the composition of the protein component in CRP, which could play a role in OSA-related damage [50]. Moreover, a recent meta-analysis considered CRP as a predictive marker of OSA [21]. In the same line of CRP, ESR was closely related to moderate to severe OSA in different studies [24, 51, 52, 53].

This study has a noteworthy limitation: the relatively small sample size. However, the single-center nature of the study might account for the limited sample. Additionally, retrospective data provided valuable insights into the association between various factors and the study’s outcomes. Nevertheless, it is essential to acknowledge that the small sample size remains a limitation, and further prospective research is advisable to enhance the depth of prognosis reporting.

Conclusion

This study highlights several key findings. Patients with moderate and severe OSA were older and had comorbidities like diabetes and hypertension. CRP and ESR were significantly elevated in these severe OSA cases and positively correlated with AHI. Additionally, higher SIRI levels were associated with higher AHI. Being hypertensive and having elevated SIRI, CRP, and ESR levels were independently linked to increased OSA severity, while increased monocyte levels had a negative impact. These findings underscore the intricate relationship between inflammation, comorbidities, and the severity of OSA.