Authors : Moumita Chakraborty; Saujanya

Volume/Issue : Volume 11 - 2026, Issue 9 - September

Google Scholar : https://tinyurl.com/4n5pmkdt

DOI : https://doi.org/10.38124/ijisrt/26sep248

Note : A published paper may take 4-5 working days from the publication date to appear in PlumX Metrics, Semantic Scholar, and ResearchGate.

Abstract : Obstructive sleep apnea (OSA) is a highly prevalent sleep-related breathing disorder that drives substantial cardiovascular, metabolic, and cerebrovascular morbidity through recurrent cycles of intermittent hypoxia, sleep fragmentation, oxidative stress, and systemic inflammation. Globally, OSA affects close to one billion adults, with roughly 425 million living with moderate-to-severe disease; prevalence estimates in India range from 3.7% to 21%, with about 5% of adults affected at a moderate-to-severe level. Despite this burden, the apnea-hypopnea index (AHI) — the mechanical, frequency-based metric that anchors current diagnostic and severity classification — correlates poorly with individual comorbidity risk and symptom burden, as it disregards event duration, desaturation depth, sleep-stage distribution, and cumulative hypoxic load. Major sleep and cardiovascular society guidelines have not yet incorporated inflammatory or REM-specific biomarkers into diagnostic or prognostic frameworks, even though expert consensus repeatedly flags this as an unmet need. This review synthesizes the rationale for and evidence behind a set of low-cost, routinely available blood-derived biomarkers — serum uric acid, fibrinogen, neutrophil-to-lymphocyte ratio (NLR), platelet-to-lymphocyte ratio (PLR), and the systemic inflammatory response index (SIRI) — as candidate correlates of polysomnographic severity in OSA, with particular attention to REM-specific indices and to patients with OSA-associated comorbidities such as hypertension, diabetes, and chronic obstructive pulmonary disease. We map the evidentiary, conceptual, methodological, measurement, population, temporal, and translational gaps that currently limit clinical adoption of these markers, particularly in resource-constrained and under-represented settings such as India. Addressing these gaps through adequately powered, stage-specific, and longitudinal studies could establish affordable biomarker panels as scalable adjuncts to AHI for risk stratification and could inform decision-support pathways for respiratory therapists and clinicians managing OSA in low- and middle-income countries.

Keywords : Obstructive Sleep Apnea; Polysomnography; Biomarkers; Uric Acid; Fibrinogen; Neutrophil-To-Lymphocyte Ratio; Systemic Inflammatory Response Index; REM Sleep; Comorbidities.

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