Determination of equation for estimating continuous positive airway pressure in patients with obstructive sleep apnea for the Indian population

BACKGROUND: Continuous positive airway pressure (CPAP) is the treatment of obstructive sleep apnea (OSA). The CPAP pressure is generally estimated by manual titration or an auto CPAP device. An alternative method involves the use of the predictive equation. AIM AND OBJECTIVE: There is no equation developed, taking into account the Indian population. The aim is to develop a predictive equation for optimal CPAP pressure in patients with OSA and to validate the equation by comparing it with manual titration pressure. MATERIALS AND METHODS: A total of 250 patients with OSAS who underwent successful manual titration for CPAP treatment in a tertiary care center were included in this study and divided randomly into two groups A and B with 150 and 100 patients, respectively. Stepwise multiple regression analysis was applied to anthropometric and polysomnographic variables of group A and the predictive equation for estimating CPAP was developed using SPSS. This equation was validated by comparing the estimated pressure with that of manual titration pressure in Group B. RESULTS: The mean age was 55.09 ± 11.43 and mean body mass index (BMI) was 33.69 ± 6.56. CPAP pressure in patients with OSA was 11.13 ± 1.83 cm H(2)O. The Apnea Hypopnea index (AHI) (r = 0.595, P < 0.001), minimal; SpO(2) (r = −0.502, P < 0.001), BMI (r = 0.494, P < 0.001) significantly correlated with optimal CPAP level. A predictive equation for optimal CPAP level in patients with OSA was developed using AHI, BMI, and minimal SpO(2), which can be easily measured during the diagnostic process. Optimal CPAP level (cm H(2)O) =8.401+ (0.053 × BMI) + (0.020 × AHI) − (0.031 × lowest oxygen). Twenty-six percent of the variance in the optimal CPAP level was explained by this equation (R(2) = 0.26, P < 0.001) and the equation showed 86% of optimal estimation. CONCLUSION: The results suggest that manual titration pressure correlates with the pressure derived from the predictive equation in our study.