Aim of work

1. Primary aim: Asses correlation between FeNO level, OSA severity
2. Secondary aim: Clarifying FeNO's role as a biomarker to assess airway inflammation, Cut off value prediction to moderate and severe OSA and its potential significance to improve clinical management strategies for OSA patients.

Obstructive Sleep Apnea is a highly prevalent sleep-related breathing disorder characterized by recurrent episodes of upper airway obstruction during sleep, resulting in intermittent hypoxia, sleep fragmentation, and significant cardiometabolic consequences. The severity of OSA is traditionally assessed using overnight polysomnography (PSG), with the apnea-hypopnea index (AHI) serving as the gold standard metric. However, PSG is resource-intensive, time-consuming, and not readily accessible in many healthcare settings, particularly in resource-limited environments. This has driven increasing interest in identifying reliable, non-invasive biomarkers that could aid in the assessment of disease severity and reduce dependence on PSG.(1) Airway and systemic inflammation play a central role in the pathophysiology of OSA. Recurrent hypoxia-reoxygenation cycles induce oxidative stress and activate inflammatory pathways, leading to endothelial dysfunction and tissue injury.(1) Fractional exhaled nitric oxide (FeNO) is a well-established non-invasive biomarker of airway inflammation, widely used in the assessment of eosinophilic airway diseases such as asthma. Given its ability to reflect inflammatory processes within the respiratory tract, FeNO has been proposed as a potential marker in OSA.(2) Several studies have explored the relationship between FeNO levels and OSA. Some have demonstrated elevated FeNO levels in patients with OSA compared to healthy controls, along with positive correlations between FeNO and indices of disease severity such as AHI and oxygen desaturation index (ODI).(3) In contrast, other studies have reported inconsistent or weak associations, suggesting that the inflammatory profile in OSA (often predominantly neutrophilic rather than eosinophilic) may limit the specificity of FeNO as a biomarker in this context.

Importantly, the current literature is characterized by several limitations. Many studies have small sample sizes, heterogeneous populations, and inadequate control for confounding factors such as smoking, obesity, and coexisting airway diseases. Furthermore, most studies focus primarily on simple correlations with AHI, without evaluating the diagnostic performance of FeNO or its ability to discriminate between different severity categories of OSA. The absence of robust predictive models integrating FeNO with clinical parameters further limits its applicability in routine clinical practice.(4) Therefore, a significant gap remains regarding whether FeNO can serve as a clinically meaningful, non-invasive biomarker for stratifying OSA severity. In particular, there is a need for well-designed studies that not only assess the association between FeNO and polysomnographic parameters, but also evaluate its diagnostic accuracy and potential role within predictive models.

Accordingly, the present study aims to investigate the role of FeNO in assessing the severity of OSA, to determine its relationship with key polysomnographic indices, and to evaluate its potential utility as a non-invasive tool for disease stratification.

Inclusion Criteria:

• Ages Eligible for study: 18 years till 70 years old.
• Newly suspected OSA patients with Epworth Sleepiness Scale (ESS) ≥ 10.

Exclusion Criteria:

• Current smokers.
• Any chronic Respiratory disorders other than OSA (asthma, COPD, allergic rhinitis, and atopic diseases).
• Younger age than 18 years.
• Recent inhaled or systemic corticosteroids within the pasr 4 weeks.
• Recent respiratory infection less than 4 weeks.
• Uncontrolled diabetes & any chronic debilitating diseases (liver, renal, collagen diseases) Informed Consent will be taken from the participants before clinical examination.

Study Type: prospective observational cross sectional study. Sample Size: This study will be carried out on 200 patients' suspected for obstructive sleep apnea, following approval of medical research ethical committee of Tanta University, Faculty of Medicine.

Sample size was calculated using this formula 2SD ^2 × (1.96 + 0.84)^2 /d^2 SD of FeNO 50 at moderate OSA 17.25 d is the difference between both means 21, 13.57 So at power of study 80% CI 95% Least Sample size will be 85 in each group