A predictive model for optimal continuous positive airway pressure in the treatment of pure moderate to severe obstructive sleep apnea in China.

BACKGROUND: Numerous predictive formulas based on different ethnics have been developed to determine continuous positive airway pressure (CPAP) for patients with obstructive sleep apnea (OSA) without laboratory-based manual titrations. However, few studies have focused on patients with OSA in China. Therefore, this study aimed to develop a predictive equation for determining the optimal value of CPAP for patients with OSA in China. METHODS: 526 pure moderate to severe OSA patients with attended CPAP titrations during overnight polysomnogram were spited into either formula derivation (419 patients) or validation (107 patients) group according to the treatment time. Predictive model was created in the derivation group, and the accuracy of the model was tested in the validation group. RESULTS: Apnea hypopnea index (AHI), body mass index (BMI), longest apnea time (LAT), and minimum percutaneous oxygen saturation (minSpO2) were considered as independent predictors of optimal CPAP through correlation analysis and multiple stepwise regression analysis. The best equation to predict the optimal value of CPAP was: CPAPpred = 7.581 + 0.020*AHI + 0.101*BMI + 0.015*LAT-0.028*minSpO2 (R2 = 27.2%, p < 0.05).The correlation between predictive CPAP and laboratory-determined manual optimal CPAP was significant in the validation group (r = 0.706, p = 0.000). And the pressure determined by the predictive formula did not significantly differ from the manually titrated pressure in the validation cohort (10 ± 1 cmH2O vs. 11 ± 3 cmH2O, p = 0.766). CONCLUSIONS: The predictive formula based on AHI, BMI, LAT, and minSpO2 is useful in calculating the effective CPAP for patients with pure moderate to severe OSA in China to some extent.

Cigarette smoke extract stimulates human pulmonary artery smooth muscle cell proliferation: Role of inflammation and oxidative stress.

Objectives: Cigarette smoke may play a direct role in proliferation of human pulmonary artery smooth muscle cells (HPASMCs). However, the mechanism involved and the effect of interventions remain unclear. We aimed to evaluate the effect of cigarette smoke extract (CSE) on HPASMCs, explore the role of inflammation and oxidative stress, and the effects of Tempol and PDTC in this process. Materials and Methods: HPASMCs were subjected to normal control (NC), CSE, CSE+Tempol (CSE+T), and CSE+PDTC (CSE+P) groups. Proliferation of HPASMCs was measured by CCK-8 and Western blot. TNF-α, IL-6, MDA, and SOD levels were determined by ELISA and commercial kits. Nuclear translocation of NF-κB p65 was evaluated by western blot. Results: 1%, 2.5%, and 5% CSE all promoted proliferation of HPASMCs, and effect of 1% CSE was the most significant, however, 7.5% and 10% CSE inhibited viability of cells (all P<0.05). Compared with the NC group, TNF-α, IL-6, and MDA levels increased, SOD activity decreased (all P<0.05), and NF-κB p65 expression in nuclei increased (P=0.04) in the CSE group. Tempol and PDTC inhibited the proliferation of HPASMCs induced by CSE (all P<0.05). And compared with the CSE group, TNF-α, IL-6, and MDA levels in CSE+T and CSE+P groups decreased, while SOD activity increased (all P<0.05). Tempol reduced the expression of NF-κB p65 in nuclei but did not achieve a significant difference (P=0.08). PDTC inhibited the nuclear translocation of NF-κB p65 (P=0.03). Conclusion: CSE stimulates HPASMCs proliferation in a certain concentration range. The CSE-induced proliferation of HPASMCs involved excessive inflammatory response and oxidative stress. Tempol and PDTC attenuate these effects of CSE on HPASMCs.