| Objective: to analyze the data of sleep monitoring and coronary angiography in patients with coronary heart disease complicated with different degrees of obstructive sleep apnea hypopnea syndrome,and then to analyze the relationship between the two diseases.to provide basis for clinical treatment and prognosis of these patients.Method: through the electronic case system of our hospital,we collected the patients who were diagnosed as coronary heart disease by coronary angiography((CAG))in the Department of Cardiology of Landa first Hospital from January 2017 to November 2019,and the patients who were hospitalized with sleep monitoring(PSG)were observed.The past medical history,laboratory tests and sleep monitoring reports of these patients were recorded.Coronary angiography was performed by experienced interventional cardiologists,and the Gensini score was obtained according to the results of coronary angiography.According to the inclusion and exclusion criteria,81 cases were included in this study,aged between 31 and 78 years old,with an average age of(55.9 ±10.4)years,including 70 males and 11 females.According to the apnea hypopnea index((AHI)),the patients were divided into control group and experimental group.The control group was negative,while the experimental group included mild OSAHS group,moderate OSAHS group and severe OSAHS group.The history,laboratory parameters,PSG parameters and coronary angiography results of the patients in the two groups were analyzed,and the differences between the two groups and the correlation between the two diseases were compared.Results:1.There was no significant difference in the admission status of the four groups,including sex,age,smoking history,drinking history,hypertension history,diabetes history and other risk factors of coronary heart disease(P > 0.05).2.There was no significant difference in blood routine and biochemical items among the four groups(P > 0.05).3.There were significant differences in AHI,LaSO2,average SO2 and BMI among the four groups of patients with coronary heart disease(P < 0.01).4.In the correlation analysis,there was a positive correlation between AHI and BMI(r = 0.52,P < 0.01);There was a negative correlation between AHI and LaSO2(correlation coefficient r = 0.657);There was a negative correlation between AHI and average SO2(r = 0.499,P < 0.05).5.The more severe the OSAHS,the higher the proportion of diseased coronary arteries and Gensini score,and the difference was statistically significant(P <0.05).6.In the Spearman correlation analysis between Gensini score and related factors,Gensini score was positively correlated with AHI(r = 0.679,P < 0.01);There was a positive correlation between Gensini score and BMI(r = 0.448,P < 0.01);There was a negative correlation between Gensini score and LaSO2(r = 0.446,P < 0.01);There was a negative correlation between Gensini score and average SO2(r = 0.307,P < 0.01).7.Multiple linear stepwise regression analysis was conducted with Gensini score as dependent variables,and logAHI,logLaSO2,log average SO2 and logBMI as independent variables were included in the regression analysis.The results showed that logAHI might be the main predictor of Gensini score in patients with OSAHS(? = 0.527,P < 0.01,adjusted R square 0.323).Conclusion:1.In patients with coronary heart disease,with the aggravation of the severity of OSAHS disease,the proportion of coronary artery disease increased,that is,the probability of multi-vessel disease increased.2.The more severe the OSAHS in patients with coronary heart disease,the higher the Gensini score.3.Through the comparison of BMI between groups,it was found that BMI in patients with severe OSAHS was significantly higher than that in other groups,and the difference was statistically significant.In correlation analysis,BMI was positively correlated with AHI and Gensini scores,that is,the higher the BMI,the higher the AHI and Gensini scores.4.There is a significant positive correlation between AHI and Gensini score.Through multiple stepwiseregression analysis,it is found that logAHI may be the main predictor of Gensini score. |
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