# The Role of Neutrophil-Lymphocyte Ratio in Identifying the Severity of Obstructive Sleep Apnea: A Retrospective Study

## TL;DR

This study shows that the neutrophil-to-lymphocyte ratio (NLR) can help identify severe obstructive sleep apnea, offering a low-cost alternative to more complex tests.

## Contribution

The study introduces NLR as a novel, accessible biomarker for assessing the severity of obstructive sleep apnea.

## Key findings

- NLR significantly predicted severe OSA with an AUC of 0.760.
- An NLR cut-off of 3.6 achieved high sensitivity and specificity for severe OSA.
- Severe OSA patients had higher BMI compared to other groups.

## Abstract

Background: Obstructive sleep apnea (OSA) is a prevalent disorder characterized by recurrent episodes of upper airway blockage during sleep, leading to intermittent hypoxia and disturbed sleep patterns. It is often associated with systemic inflammation as well as metabolic and cardiovascular disorders. The neutrophil-to-lymphocyte ratio (NLR) has emerged as a promising predictor of systemic inflammation. This study aimed to evaluate the role of NLR in assessing the severity of OSA.

Patients and methods: This retrospective cross-sectional study included 100 adult patients diagnosed with OSA through overnight polysomnography at a sleep center in Baghdad, Iraq, from April 6 to October 3, 2025. Patients with active infections, chronic inflammatory or autoimmune diseases, malignancy, or hematologic disorders were excluded. The severity of OSA was classified based on the apnea-hypopnea index (AHI). Statistical analysis was performed using SPSS software (IBM Corp., Armonk, NY), with t-tests and Fisher’s exact tests applied and receiver operating characteristic (ROC) analysis used to determine the diagnostic efficiency of NLR.

Results: Among the 100 patients, 42% had mild OSA, 25% moderate OSA, and 33% severe OSA. Body mass index (BMI) was significantly higher among patients with severe OSA (p = 0.025). ROC analysis revealed that NLR significantly predicted severe OSA (area under the curve (AUC)= 0.760, p < 0.001). An optimal cut-off point of NLR = 3.6 achieved 78.7% sensitivity, 74.6% specificity, 94.1% negative predictive value (NPV), and 87.7% positive predictive value (PPV).

Conclusion: The NLR shows promise as an accessible and cost-effective biomarker for identifying severe OSA. Elevated NLR values reflect the systemic inflammatory processes associated with intermittent hypoxia and may aid clinicians in assessing OSA severity, particularly when polysomnography is not readily available.