ObjectiveTo investigate the renal impairment and the risk factors of renal impairment in patients with OSA. MethodsData from patients who underwent polysomnography (PSG) in our department from July 2022 to January 2023 were collected, totaling 178 cases. Based on the results of the polysomnography, the patients were divided into an OSA group (145 cases) and a non-OSA group (33 cases). According to the severity of the condition, the OSA group was further divided into mild OSA (21 cases), moderate OSA (28 cases), and severe OSA (96 cases). The Pearson correlation analysis was further conducted to analyze the relationships between serum urea nitrogen (BUN), serum cystatin C (Cys-C) concentrations, and estimated Glomerular Filtration Rate (eGFR) with various risk factors that may influence renal impairment. Moreover, multiple linear regression analysis was used to identify the risk factors affecting BUN, Cys-C, and eGFR. ResultsWhen comparing the two groups, there were statistically significant differences in age, weight, BMI, neck circumference, waist circumference, eGFR、Cys-C、BUN, LSaO2, CT90% (all P<0.05). Univariate analysis of variance was used to compare differences in BUN, Serum creatinine (SCr), Cys-C, and eGFR among patients with mild, moderate, and severe OSA, indicating that differences in eGFR and Cys-C among OSA patients of varying severities were statistically significant. Further analysis with Pearson correlation was conducted to explore the associations between eGFR, BUN, and Cys-C with potential risk factors that may affect renal function. Subsequently, multiple linear regression was utilized, taking these three indices as dependent variables to evaluate risk factors potentially influencing renal dysfunction. The results demonstrated that eGFR was negatively correlated with age, BMI, and CT90% (β=−0.95, P<0.001; β=−1.36, P=0.01; β=−32.64, P<0.001); BUN was positively correlated with CT90% (β=0.22, P=0.01); Cys-C was positively correlated with CT90% (β=0.58, P<0.001. Conclusion Chronic intermittent hypoxia, age, and obesity are risk factors for renal dysfunction in patients with OSA.
Objective To investigate the possible association between serum level of hepatocyte growth factor( HGF) and obstructive sleep apnea hypopnea syndrome( OSAHS) with hypertension.Methods 58 cases of OSAHS without hypertension, 61 cases of OSAHS with hypertension, and 50 normal controls were enrolled. Serum level of HGF was measured by enzyme-linked immunosorbent assay( ELISA) , and the relationships between the serum HGF level and blood pressure( BP) , apnea hypopnea index( AHI) , lowest SaO2 ( LSaO2 ) were analyzed by linear correlation analysis. Results The serum HGF level ( pg/mL) was 761. 46 ±60. 18, 970. 87 ±60. 94, and 487. 34 ±45. 52 in the OSAHS patients without hypertention, OSAHS patients with hypertention, and normal subjects, respectively. Which was significantly higher in the OSAHSpatients than the normal subjects, and highest in the OSAHS patients with hypertension( P lt; 0. 05) . The serum HGF level was positively related to AHI( r = 0. 452, P lt;0. 05) and negatively related to LSaO2 ( r =- 0. 328, P lt;0. 05) in the OSAHS patients without hypertention, positively related to AHI, SBP, DBP( r =0. 670, P lt;0. 01; r =0. 535, P lt;0. 05; r =0. 424, P lt;0. 05) and negatively related to LSaO2 ( r = - 0. 572,P lt;0. 01) in the OSAHS patients with hypertension. Conclusions SerumHGF level increases significantly in patients with OSAHS especialy in OSAHS patients with hypertension, and positively correlates with the severity of OSAHS and hypertension.
Objective To study the correlation between smoking and obstructive sleep apnea (OSA). Methods A total of 454 patients from October 2015 to July 2021 were retrospectively collected for nocturnal polysomnography monitoring (no less than 7 hours). The patients were divided into an OSA group (n=405) and a control group (n=49, patients with primary snoring) according to the results of polysomnography monitoring. According to the apnea hypopnea index (AHI) and the lowest oxygen saturation during sleep, the severity of OSA was classified into a mild to moderate group (5 times/h ≤ AHI<30 times/h) and a severe group (AHI ≥30 times/h). The patients were inquired about their smoking history, then the patients diagnosed with OSA were further divided into a smoking group, a smoking cessation group, and a non-smoking group based on their smoking history. Results The smoking rate of the patients in the OSA group was higher than that in the control group (50.9% vs. 32.7%, P<0.05), while the smoking rate in the severe OSA group was higher than that in the mild to moderate group (55.7% vs. 39.8%, P<0.05). Smoking was positively correlated with AHI, cumulative percentages of time spent at oxygen saturation below 90% (Ts90%), and total apnea time (r value was 0.196, 0.197, 0.163, P<0.05), while negatively correlated with the lowest and average SpO2 during sleep (r value was –0.202, –0.214, P<0.05). The logistic regression analysis with severe OSA as the outcome variable showed that smoking (OR=1.781) and obesity (OR=1.930) were independent risk factors of severe OSA (P<0.05). The comparison between groups of the OSA patients with different smoking states showed that the proportion of severe OSA, AHI, Ts90%, and total apnea time (77.8%, 53.55 times/h, 18.35%, and 111.70 minutes, respectively) of the smoking group were higher than those of the non-smoking group (62.8%, 40.20 times/h, 8.40%, and 76.20 minutes, respectively, P<0.05). The lowest SpO2 and average SpO2 during sleep (69.50%, 93.00%, respectively) of the smoking group were lower than those of the non-smoking group (75.00%, 94.00%, respectively, both P<0.05). The average SpO2 of the smoking cessation group was higher than that of the smoking group (94.00% vs. 93.00%, P<0.05), and the Ts90% of the smoking cessation group was lower than that of the smoking group (6.75% vs. 18.35%, P<0.05). Conclusions Smoking significantly affects the degree of sleep-disordered breathing and may be an independent risk factor for severe OSA. Smoking can exacerbate the severity of OSA and the degree of hypoxia, while smoking cessation can improve the degree of hypoxia in OSA patients.