Prediction of Optimal Positive Airway Pressure in Chinese Patients With Obstructive Sleep Apnea

Feng Pang; Wenmin Deng; Jingyan Huang; Yu Guo; Minmin Lin; Xiangmin Zhang; Jie Liu

doi:10.1111/crj.70047

Prediction of Optimal Positive Airway Pressure in Chinese Patients With Obstructive Sleep Apnea

Clin Respir J. 2024 Dec;18(12):e70047. doi: 10.1111/crj.70047.

Authors

Feng Pang^{1

2

3}, Wenmin Deng^{1

2

3}, Jingyan Huang⁴, Yu Guo^{2

3}, Minmin Lin^{1

2

3}, Xiangmin Zhang^{1

4}, Jie Liu^{1

2

3}

Affiliations

¹ Department of Sleep Medicine, The Sixth Affiliated Hospital, Sun Yat-sen University, Guangzhou, Guangdong, China.
² Department of Otolaryngology-Head and Neck Surgery, The Sixth Affiliated Hospital, Sun Yat-sen University, Guangzhou, Guangdong, China.
³ Biomedical Innovation Center, The Sixth Affiliated Hospital, Sun Yat-sen University, Guangzhou, China.
⁴ Department of Otolaryngology-Head and Neck Surgery, Foresea Life Insurance Guangzhou General Hospital, Guangzhou, Guangdong, China.

Abstract

Purpose: Positive airway pressure (PAP) is the primary treatment for obstructive sleep apnea (OSA). This study aims to predict the optimal PAP pressure in Chinese OSA patients by their polysomnography (PSG) variables and demographic characteristics.

Methods: Patients with an apnea-hypopnea index (AHI) ≥ 15 times/h who received PAP therapy (residual AHI < 5 times/h) and underwent PSG were included in this study. Sex, age, body mass index (BMI), Epworth Sleepiness Scale (ESS), AHI, supine AHI, lowest oxygen saturation (LSaO₂), percentage of total sleep time spent with SaO₂ < 90% (CT90), and PAP pressure were recorded. PAP pressure and other variables were analyzed using univariate correlation and multivariate linear stepwise regression analysis.

Results: A total of 167 patients were enrolled, with 122 in the study group and 45 in the validation group. Univariate correlation analysis revealed a significant correlation between PAP pressure and age, BMI, ESS, AHI, supine AHI, LSaO₂, and CT90. The multivariate linear regression analysis showed that PAP pressure was correlated with gender (b = 1.142, p = 0.032), age (b = -0.039, p = 0.005), AHI (b = 0.047, p = 0.000), and CT90 (b = 0.037, p = 0.000). The final PAP pressure prediction equation was PAPpre (cmH₂O) = 8.548 + 1.142 × sex -0.039 × age + 0.047 × AHI + 0.037 × CT90 (R² = 0.553) (male is defined as 0 and female as 1). This model accounts for 55.3% of the optimal pressure variance, and the area under the ROC curve of PAP prediction pressure is 0.7419.

Conclusion: PSG variables can be used to predict PAP pressure in Chinese OSA patients, but for some individuals, the prediction model is not very good. PAP is correlated with age, BMI, ESS, AHI, supine AHI, LSaO₂, and percentage of total sleep time spent with SaO₂ < 90% (CT90), which can be used to predict the optimal PAP pressure.

Keywords: China; obstructive sleep apnea (OSA); optimal pressure; positive airway pressure (PAP); prediction.

MeSH terms

Adult
Aged
Body Mass Index*
China / epidemiology
Continuous Positive Airway Pressure* / methods
East Asian People
Female
Humans
Male
Middle Aged
Oxygen Saturation / physiology
Polysomnography* / methods
Retrospective Studies
Sleep Apnea, Obstructive* / diagnosis
Sleep Apnea, Obstructive* / physiopathology
Sleep Apnea, Obstructive* / therapy
Treatment Outcome

Grants and funding

National Key Clinical Discipline