Clinical data and four-variable score-based OSAHS and coronary heart disease correlation evaluation method

Abstract

The invention discloses an OSAHS and coronary heart disease correlation evaluation method based on clinical data and four-variable scoring. The method comprises the steps of clinical data collection, coronary artery total score calculation, polysleep respiration monitoring and four-variable scoring. According to the clinical data and four-variable score-based OSAHS and coronary heart disease correlation evaluation method, the four-variable score is taken as a reference variable, whether the four-variable score is OSAHS and the OSAHS-combined coronary heart disease are taken as grouping variables, ROC curves are drawn respectively, the four-variable score is calculated to screen cutting values of the OSAHS and the OSAHS-combined coronary heart disease, the area under the ROC curves is obtained, and the correlation of the OSAHS and the coronary heart disease is evaluated. According to the method, the sensitivity, the specificity, the positive predictive value and the negative predictive value are calculated, the predictive value of OSAHS merging / coronary heart disease correlation is judged, the optimal predictive score cut value is obtained through corresponding scoring and assignment, and when the cut value is larger than or equal to 10.5, the four-variable score shows good sensitivity and specificity when the OSAHS merging coronary heart disease is screened, and the correlation is high.

Description

Technical Field

[0001] The present invention relates to the technical field of four-variable score prediction, and in particular to an OSAHS and coronary heart disease correlation evaluation method based on clinical data and four-variable score. Background Art

[0002] Obstructive Sleep Apnea Hypopnea Syndrome (OSAHS) is a respiratory disease associated with sleep-disordered breathing, often accompanied by partial or complete obstruction of the upper airway. This condition causes patients to experience repeated intermittent hypoxia during sleep, thereby activating central and peripheral chemoreceptors and triggering a series of pathophysiological reactions. According to the latest data, approximately 936 million adults aged 30 to 69 suffer from OSAHS worldwide, with the largest number of patients in China, with a prevalence of 18.8%. OSAHS is closely related to a variety of cardiovascular diseases, such as coronary heart disease (CHD), hypertension, arrhythmias, and heart failure, which seriously affect the quality of life and life expectancy of patients.

[0003] Polysomnography (PSG) is regarded as the "gold standard" for diagnosing OSAHS. However, since this method requires specialized equipment and technicians, and the operation process is relatively complicated, the cost is high, and the hospital resources are limited, it is not suitable for large-scale disease screening. Therefore, simplified OSAHS screening scales have gradually attracted attention. These scales are efficient and easy to operate, and are easy to promote and apply. Commonly used screening scales include the Four-variable screening tool (4V), the Berlin questionnaire (Berlin questionnaire, BQ), and the STOP-Bang questionnaire (SBQ). The Four-variable scoring is a high-sensitivity and high-specificity OSAHS screening tool proposed by Takegami M et al. The screening indicators include gender, blood pressure level, body mass index (BMI), and self-reported snoring. Three of these variables can be obtained through objective measurement, which improves the reliability of OSAHS screening. When the four-variable score is used to assess the risk of OSAHS, the area under the ROC curve (AUC) can reach 0.9 when the cutoff value is set at 11 points, with a sensitivity of up to 93% and a low missed diagnosis rate. This scoring system was originally proposed based on research on Asian populations, so it may be more suitable for the screening needs of OSAHS patients in my country.

[0004] The recurring intermittent hypoxia of OSAHS triggers a series of pathophysiological processes, including oxidative stress, inflammatory response, sympathetic nerve activation, and endothelial dysfunction. Among them, oxidative stress plays a core role in the process of atherosclerosis and is also an important factor in the pathogenesis of CHD. The above pathophysiological changes further increase the burden on the cardiovascular system and promote the formation and development of coronary atherosclerotic plaques, thus becoming an important factor in the occurrence and development of CHD. Studies have shown that the prevalence of CHD in OSAHS patients is between 20% and 30%, while in the CHD population, the prevalence of OSAHS is as high as 38% to 65%. This means that people with OSAHS face a significantly increased risk of worsening cardiovascular disease and turning into CHD. In addition, some studies have pointed out that when OSAHS and CHD coexist, the risk of death in patients is significantly higher than that of individuals with OSAHS or CHD alone. Therefore, it is particularly important to conduct early risk assessment and primary prevention for OSAHS patients who may develop CHD. The "2024 Expert Consensus on the Evaluation and Management of Obstructive Sleep Apnea in Patients with Cardiovascular Disease" recommends the use of the STOP-Bang questionnaire for preliminary screening of OSAHS patients suspected of having CHD.

[0005] A search revealed that there are currently no literature reports in China on the use of four-variable scores to screen for OSAHS combined with coronary heart disease (OSAHS combined with / coronary heart disease correlation). Therefore, an OSAHS and coronary heart disease correlation evaluation method based on clinical data and four-variable scores was proposed to determine the sensitivity and specificity of the four-variable cut-off values ​​in OSAHS combined with coronary heart disease. Summary of the invention

[0006] The purpose of the present invention is to provide a method for evaluating the correlation between OSAHS and coronary heart disease based on clinical data and four-variable scores, so as to solve the problems raised in the above background technology.

[0007] To achieve the above object, the present invention provides the following technical solutions:

[0008] A method for evaluating the correlation between OSAHS and coronary heart disease based on clinical data and four-variable scores, the method steps are as follows:

[0009] S1: Clinical data collection, including patient gender, age, medical history, snoring, height and weight, as well as fasting blood test of liver function, renal function, blood lipids and fasting blood glucose the next morning after fasting for 8 hours. Fasting blood test was performed using Roche C8000 fully automatic biochemical analyzer. It also included the average systolic and diastolic blood pressure of 24-hour dynamic blood pressure monitoring. The 24-hour dynamic blood pressure monitoring was performed using the American Welch Allyn dynamic blood pressure monitor model 6100.

[0010] S2: Calculation of total coronary artery score, using the Gensini score to assess the severity of coronary artery lesions: the product of each vascular stenosis score and the lesion site score is the score for each vascular lesion, and the sum of all lesion scores is the total coronary score for each patient;

[0011] S3: Polysomnography, 7 hours of all-night polysomnography, using Australian Compumedics polysomnography, simultaneous monitoring of blood oxygen saturation, pulse, respiratory rate, snoring and oral and nasal airflow, and education on precautions before monitoring. After monitoring, Remlogic software was used for data analysis, and the sleep report was interpreted by a professionally trained physician and reviewed by a senior physician. Monitoring index data were collected;

[0012] S4: a four-variable score, including gender, blood pressure level, body mass index, and self-reported snoring;

[0013] S5: Statistical calculations. Data were analyzed using SPSS 26.0 software. The Shapiro-Wilk test was used to test the normality of continuous variables. Non-normally distributed quantitative data were analyzed using M (P 25 ,P 75 ), inter-group comparisons were performed using the Kruskal-Wallis H test, count data were expressed as frequency%, and inter-group comparisons were performed using the chi-squared X- 2 The correlation between the four-variable score and AHI, LSaO2, and Gensini score was analyzed by Spearman correlation analysis. The indicators with statistically significant differences in univariate logistic regression analysis were used for multivariate analysis using binary logistic regression model to screen out the risk factors for OSAHS combined with coronary heart disease. The results were expressed as odds ratios and 95% confidence intervals. The four-variable score was used as the reference variable, and whether it was OSAHS and OSAHS combined with coronary heart disease were used as grouping variables. ROC curves were drawn respectively, and the cut-off values ​​of the four-variable score for screening OSAHS and OSAHS combined with coronary heart disease were calculated. The area under the ROC curve was obtained, and the sensitivity, specificity, positive predictive value, and negative predictive value were calculated to determine the predictive value of the correlation between OSAHS combined with / and coronary heart disease.

[0014] As a further solution of the present invention: In S1, the body mass index is calculated by height and weight, and the body mass index is calculated as BMI, body mass index = weight / height 2 The unit of BMI is kg / m 2 .

[0015] As a further solution of the present invention: the total coronary score calculation in S2 includes the Gensini score of coronary angiography and the Gensini score of coronary CT angiography. The coronary angiography is performed by a cardiovascular specialist. The routine electrocardiogram, blood pressure, and blood oxygen monitoring are performed before the operation. The American GE Innova 2100 digital subtraction angiography machine is used. The Seldinger puncture technique is used to send a specific cardiac catheter into the opening of the left and right coronary arteries through the radial artery or femoral artery, and the contrast agent is injected. The standard Judkins method is used to perform selective left and right coronary angiography, and multi-position and multi-angle projections are performed. The coronary angiography results are analyzed by more than 2 cardiovascular specialists. Coronary CT angiography uses a dual-source CT (Somatom Definition Flash, Siemens) of Siemens, Germany, for image acquisition. The patient is instructed to lie flat, and the scanning range is from 1 cm below the tracheal carina to the level of the diaphragmatic surface of the heart. The enhanced scan used a two-phase injection technique. In the first phase, 60 to 80 mL of non-ionic contrast agent was injected into the patient's median cubital vein at a flow rate of 3.5 to 5.0 mL / s, and in the second phase, 30 mL of normal saline was injected at the same flow rate. The voltage was 120 kV and the current was 380 to 410 mA. The data was imported into the workstation and the corresponding volume data was calculated to obtain a three-dimensional image of the coronary artery and observe the stenotic lesions. The diagnosis was independently completed by two experienced imaging physicians.

[0016] As a further solution of the present invention: the monitoring index data in S3 includes apnea-hypopnea index, average blood oxygen saturation and minimum blood oxygen saturation, the apnea-hypopnea index is recorded as AHI, the average blood oxygen saturation is recorded as MSaO 2 The lowest blood oxygen saturation is recorded as LSaO 2 .

[0017] As a further solution of the present invention: the gender in S4 includes male and female, male is scored 4 points, female is scored 0 points, blood pressure level includes normal blood pressure, primary hypertension, secondary hypertension and tertiary hypertension, normal blood pressure is scored 1 point, primary hypertension is scored 2 points, secondary hypertension is scored 3 points, and tertiary hypertension is scored 4 points, and body mass index includes BMI<21.0, 21.0≤BMI≤22.9, 23.0≤BMI≤24.9, 25.0≤BMI≤26. 9. 27.0≤BMI≤29.9 and 30.0<BMI, BMI<21.0 was calculated as 1 point, 21.0≤BMI≤22.9 was calculated as 2 points, 23.0≤BMI≤24.9 was calculated as 3 points, 25.0≤BMI≤26.9 was calculated as 4 points, 27.0≤BMI≤29.9 was calculated as 5 points, and 30.0<BMI was calculated as 6 points. Self-reported snoring included snoring almost every day or often and others. Almost every day or often snoring was calculated as 4 points, and others were calculated as 0 points.

[0018] As a further solution of the present invention: in the statistical calculation, p < 0.05 is considered to be statistically significant.

[0019] Compared with the prior art, the present invention has the following beneficial effects:

[0020] 1. The present invention is a four-variable evaluation and prediction method for obstructive sleep apnea-hypopnea syndrome combined with coronary heart disease. Through data collection in four aspects, including clinical data collection, total coronary score calculation, polysomnography and four-variable scoring, the four-variable scoring is used to calculate the cut-off value for screening OSAHS and OSAHS combined with coronary heart disease. The optimal prediction score cut-off value is obtained through corresponding scoring and assignment. When the cut-off value is ≥10.5, the four-variable scoring shows good sensitivity and specificity in screening OSAHS combined with coronary heart disease, and has a high correlation. BRIEF DESCRIPTION OF THE DRAWINGS

[0021] Figure 1 This is a comparison chart between the four-variable score groups in the OSAHS and coronary heart disease correlation evaluation method based on clinical data and four-variable score.

[0022] Figure 2 This is a comparison chart of the correlation between the four-variable scores of OSAHS patients and AHI in the OSAHS and coronary heart disease correlation evaluation method based on clinical data and four-variable scores.

[0023] Figure 3 This is a comparison chart of the correlation between the four-variable scores of OSAHS patients and the Gensini scores in the OSAHS and coronary heart disease correlation evaluation method based on clinical data and four-variable scores.

[0024] Figure 4 The correlation between the four-variable score and LSaO in OSAHS patients was evaluated based on clinical data and four-variable score in the OSAHS and coronary heart disease correlation evaluation method. 2 Correlation comparison chart of .

[0025] Figure 5 This is the forest plot of the multivariate logistic regression analysis of the risk factors for coronary heart disease in OSAHS patients in the OSAHS and coronary heart disease correlation evaluation method based on clinical data and four-variable scores.

[0026] Figure 6 This is the ROC curve analysis diagram of the four-variable score screening for OSAHS in the OSAHS and coronary heart disease correlation evaluation method based on clinical data and four-variable score.

[0027] Figure 7This is the ROC curve analysis diagram of the four-variable score for screening OSAHS combined with coronary heart disease in the OSAHS and coronary heart disease correlation evaluation method based on clinical data and four-variable score. DETAILED DESCRIPTION

[0028] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0029] See also Figures 1 to 7 In an embodiment of the present invention, a method for evaluating the correlation between OSAHS and coronary heart disease based on clinical data and four-variable scoring is as follows:

[0030] S1: Clinical data collection, including patient gender, age, medical history, snoring, height and weight, as well as fasting blood test of liver function, renal function, blood lipids and fasting blood glucose the next morning after fasting for 8 hours. Fasting blood test was performed using Roche C8000 fully automatic biochemical analyzer. It also included the average systolic and diastolic blood pressure of 24-hour dynamic blood pressure monitoring. The 24-hour dynamic blood pressure monitoring was performed using the American Welch Allyn dynamic blood pressure monitor model 6100.

[0031] S2: Calculation of total coronary artery score, using the Gensini score to assess the severity of coronary artery lesions: the product of each vascular stenosis score and the lesion site score is the score for each vascular lesion, and the sum of all lesion scores is the total coronary score for each patient;

[0032] S3: Polysomnography, 7 hours of all-night polysomnography, using Australian Compumedics polysomnography, simultaneous monitoring of blood oxygen saturation, pulse, respiratory rate, snoring and oral and nasal airflow, and education on precautions before monitoring. After monitoring, Remlogic software was used for data analysis, and the sleep report was interpreted by a professionally trained physician and reviewed by a senior physician. Monitoring index data were collected;

[0033] S4: a four-variable score, including gender, blood pressure level, body mass index, and self-reported snoring;

[0034] S5: Statistical calculations. Data were analyzed using SPSS 26.0 software. The Shapiro-Wilk test was used to test the normality of continuous variables. Non-normally distributed quantitative data were analyzed using M (P 25 ,P 75), inter-group comparisons were performed using the Kruskal-Wallis H test, count data were expressed as frequency%, and inter-group comparisons were performed using the chi-squared X- 2 The correlation between the four-variable score and AHI, LSaO2, and Gensini score was analyzed by Spearman correlation analysis. The indicators with statistically significant differences in univariate logistic regression analysis were used for multivariate analysis using binary logistic regression model to screen out the risk factors for OSAHS combined with coronary heart disease. The results were expressed as odds ratios and 95% confidence intervals. The four-variable score was used as the reference variable, and whether it was OSAHS and OSAHS combined with coronary heart disease were used as grouping variables. ROC curves were drawn respectively, and the cut-off values ​​of the four-variable score for screening OSAHS and OSAHS combined with coronary heart disease were calculated. The area under the ROC curve was obtained, and the sensitivity, specificity, positive predictive value, and negative predictive value were calculated to determine the predictive value of the correlation between OSAHS combined with / and coronary heart disease.

[0035] In S1, body mass index is calculated by height and weight. BMI is calculated as: BMI = weight / height 2 The unit of BMI is kg / m 2 .

[0036] The total coronary score calculation in S2 includes the Gensini score of coronary angiography and the Gensini score of coronary CT angiography. Coronary angiography is performed by cardiovascular specialists. Routine ECG, blood pressure, and blood oxygen monitoring are performed before surgery. The American GE Innova 2100 digital subtraction angiography machine is used. The Seldinger puncture technique is used to insert a specific cardiac catheter into the opening of the left and right coronary arteries through the radial artery or femoral artery, and contrast agent is injected. The standard Judkins method is used to perform selective left and right coronary angiography. Multi-position and multi-angle projections are performed, and the results of coronary angiography are analyzed by more than two cardiovascular specialists. Coronary CT angiography uses a dual-source CT (Somatom DefinitionFlash, Siemens) from Siemens, Germany, for image acquisition. Patients are instructed to lie flat, and the scanning range is from 1 cm below the tracheal carina to the level of the diaphragmatic surface of the heart. The enhanced scan used a two-phase injection technique. In the first phase, 60 to 80 mL of non-ionic contrast agent was injected into the patient's median cubital vein at a flow rate of 3.5 to 5.0 mL / s, and in the second phase, 30 mL of normal saline was injected at the same flow rate. The voltage was 120 kV and the current was 380 to 410 mA. The data was imported into the workstation and the corresponding volume data was calculated to obtain a three-dimensional image of the coronary artery and observe the stenotic lesions. The diagnosis was independently completed by two experienced imaging physicians.

[0037] The monitoring index data in S3 include apnea-hypopnea index, average blood oxygen saturation and minimum blood oxygen saturation. The apnea-hypopnea index is recorded as AHI, and the average blood oxygen saturation is recorded as MSaO 2 The lowest blood oxygen saturation is recorded as LSaO 2 .

[0038] In S4, gender included male and female, with male scored 4 points and female scored 0 point. Blood pressure levels included normal blood pressure, stage 1 hypertension, stage 2 hypertension and stage 3 hypertension. Normal blood pressure was scored 1 point, stage 1 hypertension was scored 2 points, stage 2 hypertension was scored 3 points and stage 3 hypertension was scored 4 points. Body mass index included BMI < 21.0, 21.0 ≤ BMI ≤ 22.9, 23.0 ≤ BMI ≤ 24.9, 25.0 ≤ BMI ≤ 26.9, 27.0 ≤ BMI ≤ 29.9 and 30.0 < BMI. BMI < 21.0 was scored 1 point, 21.0 ≤ BMI ≤ 22.9 was scored 2 points, 23.0 ≤ BMI ≤ 24.9 was scored 3 points, 25.0 ≤ BMI ≤ 26.9 was scored 4 points, 27.0 ≤ BMI ≤ 29.9 was scored 5 points and 30.0 < BMI was scored 6 points. Self-reported snoring included almost every day or often snoring and others. Almost every day or often snoring was scored 4 points and others were scored 0 point.

[0039] In statistical calculations, p < 0.05 was considered statistically significant.

[0040] Detailed embodiments of the present invention:

[0041] Selection of research subjects: 1567 patients with suspected coronary heart disease who were hospitalized in the First Affiliated Hospital of Xinjiang Medical University from January 2018 to March 2024 were selected. All patients underwent coronary angiography or coronary artery CTA to confirm the diagnosis, and completed polysomnography and respiratory monitoring. They were divided into control group (group A, n = 116), coronary heart disease group (group B, n = 202), OSAHS group (group C, n = 807), and OSAHS combined with coronary heart disease group (group D, n = 442). Among them, there were 1356 males and 211 females, with an average age of (49.73 ± 10.18) years old.

[0042] Inclusion criteria: ① Age 18 to 80 years old; ② The diagnostic criteria for coronary heart disease were based on the "Guidelines for the Diagnosis and Treatment of Stable Coronary Heart Disease"; ③ The diagnosis of OSAHS was based on the 2017 "Clinical Practice Guidelines for the Diagnosis of Obstructive Sleep Apnea in Adults" of the American Academy of Sleep Medicine.

[0043] Exclusion criteria: ① Central sleep apnea; ② Combined with severe heart, liver, and kidney dysfunction, or malignant tumors; ③ Combined with chronic respiratory diseases, lung or other body infections; ④ Combined with endocrine system diseases such as hyperthyroidism, hypothyroidism, and acromegaly; ⑤ Combined with primary systemic vasculitis; ⑥ Combined with mental illness and currently using sedatives and hypnotic drugs.

[0044] The general baseline data of group A, group B and group C were compared with those of group A. Compared with group A, group B had higher age, coronary artery lesions ≥ 3 vessels, higher Gensini score, and LSaO 2 The difference was statistically significant (p<0.05); the male proportion, smoking history, BMI, UA, TG, TC, LDL-C, FBG, 24hSBP, AHI, and four-variable scores of group C were higher, and MSaO2, LSaO 2 The difference was statistically significant (p<0.05); the male proportion, history of hypertension, smoking history, BMI, UA, TG, TC, LDL-C, FBG, 24hSBP, AHI, coronary artery disease ≥3 branches, Gensini score, and four-variable score were higher in group D, while HDL-C, MSaO 2 , LSaO 2 The difference was statistically significant (p<0.05).

[0045] Compared with group B, group D had higher male proportion, history of hypertension, smoking history, BMI, UA, TG, TC, LDL-C, FBG, 24hSBP, 24hDBP, AHI, coronary artery lesions ≥ 3 branches, four-variable score, age, HDL-C, MSaO 2 , LSaO 2 The difference was statistically significant (p<0.05).

[0046] Compared with group C, group D had higher male proportion, age, history of hypertension, smoking history, BMI, AHI, coronary artery disease ≥ 3 vessels, Gensini score, and four-variable score ( Figure 1 ), HDL-C, MSaO 2 , LSaO 2 The difference was statistically significant (p<0.05). The comparison results of general baseline data are shown in the following table.

[0047] Comparison of general baseline data [n(%) or M(P 25 , P 75 )]

[0048]

[0049] Compared with group A, p a<0.05; compared with group B, p b <0.05; compared with group C, p c <0.05

[0050] BMI: body mass index; BUN: urea; Scr: serum creatinine; UA: uric acid; TG: triglyceride; TC: total cholesterol; HDL-C: high-density lipoprotein cholesterol; LDL-C: low-density lipoprotein cholesterol; ALT: alanine aminotransferase; AST: aspartate aminotransferase; FBG: fasting blood glucose; 24hSBP: 24-hour systolic blood pressure; 24hDBP: 24-hour diastolic blood pressure; AHI: sleep apnea-hypopnea index; MSaO2: mean blood oxygen saturation; LSaO2: minimum blood oxygen saturation.

[0051] The correlation between the four-variable scores and AHI, LSaO in OSAHS patients 2 The Spearman correlation analysis showed that the four-variable score was positively correlated with AHI (r=0.217, p<0.05) and Gensini score (r=0.501, p<0.05); 2 There was a negative correlation (r=-0.205, p<0.05).

[0052] Multivariate logistic regression analysis:

[0053] Male (OR=5.403, 95%CI=2.193-13.313, p=0.000), age ≥45 years (OR=2.353, 95%CI=1.683-3.290, p=0.000), history of hypertension (OR=2.053, 95%CI=1.378-3.057, p=0.000), BMI ≥25 kg / m 2 (OR=2.025, 95%CI=1.385-2.961, p=0.000), FBG≥6.1mmol / L (OR=1.772, 95%CI=1.246-2.520, p=0.001), AHI≥30 times / hour (OR=1.913, 95%CI=1.197-3.056, p=0.007), and four-variable score≥10.5 points (OR=4.046, 95%CI=2.736-5.984, p=0.000) are independent risk factors for OSAHS combined with coronary heart disease.

[0054] The four variable assignment table is as follows:

[0055] Variable assignment table

[0056]

[0057] BMI: body mass index; TG: triglyceride; TC: total cholesterol; HDL-C: high-density lipoprotein cholesterol; LDL-C: low-density lipoprotein cholesterol; FBG: fasting blood glucose; 24hSBP: 24-hour systolic blood pressure; 24hDBP: 24-hour diastolic blood pressure; AHI: sleep apnea-hypopnea index; MSaO 2 : Average blood oxygen saturation; LSaO 2 : Minimum blood oxygen saturation.

[0058] The multivariate logistic regression analysis of risk factors for coronary heart disease in OSAHS patients is as follows:

[0059] Multivariate logistic regression analysis of risk factors for coronary heart disease in patients with OSAHS

[0060]

[0061] BMI: body mass index; FBG: fasting blood glucose; AHI: sleep apnea-hypopnea index.

[0062] ROC curve analysis of the four-variable score for predicting OSAHS and OSAHS combined with coronary heart disease.

[0063] The area under the ROC curve of the four-variable score for screening OSAHS was 0.701 (95% CI: 0.669-0.734, p < 0.05), the optimal cut-off value was 9.5 points, the sensitivity was 64.6%, the specificity was 64.5%, the positive predictive value was 0.645, and the negative predictive value was 0.646. Both the sensitivity and specificity were low. The area under the ROC curve for screening OSAHS combined with coronary heart disease was 0.819 (95% CI: 0.796-0.843, p < 0.05), the optimal cut-off value was 10.5 points, the sensitivity was 76.7%, the specificity was 71.4%, the positive predictive value was 0.728, and the negative predictive value was 0.754. It has good predictive value for the correlation between OSAHS combined with / and coronary heart disease.

[0064] The relevant parameter table of the four-variable score for OSAHS and OSAHS combined with coronary heart disease screening is as follows:

[0065] Correlation between the four-variable score and the screening parameters of OSAHS and OSAHS combined with coronary heart disease

[0066]

[0067] Summary: Compared with the other three groups, group D had a higher male proportion, history of hypertension, smoking history, and BMI, but lower HDL-C (p < 0.05), which are traditional risk factors or protective factors for coronary heart disease and have been verified in a large number of studies. OSAHS is often accompanied by the above risk factors for coronary heart disease, and can directly activate a series of intermediate mechanisms leading to atherosclerosis, further causing a variety of cardiovascular diseases including coronary heart disease. When compared with group B and group C, it was found that group D had significantly increased Gensini score, multivessel disease involvement rate, and AHI, and correspondingly MSaO 2 , LSaO 2 The four-variable score of group D was significantly higher than that of group C, which may be related to the fact that patients with coronary heart disease basically have problems such as overweight and hypertension involved in this scale. Correlation analysis found that the four-variable score was positively correlated with AHI and Gensini score, but not with LSaO. 2 There is a negative correlation, which to some extent reflects the severity of OSAHS and coronary artery disease.

[0068] Compared with group B, the age of group D in this study was relatively young, which is different from the existing conclusions. This difference can be attributed to the following points: ① The age of patients included in the existing conclusions was 35 to 75 years old, while the age of patients included in this study was 18 to 80 years old. This age difference may lead to different research results; ② In the existing conclusions, 81.18% of the patients were male, while in this study, 86.53% were male. The difference in gender composition may have caused the difference in research results; ③ The existing conclusions showed that the AHI in the coronary heart disease combined with OSAHS group was 26.30±17.90 times / hour, while in this study it was 29.43±16.51 times / hour. The severity of OSAHS accelerated the process of atherosclerosis and the occurrence of coronary heart disease, which made the age of patients with coronary heart disease show a younger trend.

[0069] OSAHS and coronary heart disease are closely related, mutually causal, and form a vicious cycle. The multivariate logistic regression analysis of this study showed that male, age, history of hypertension, BMI, fasting blood glucose, and AHI were risk factors for OSAHS combined with coronary heart disease. The Framingham series of studies have confirmed that male, age, hypertension, obesity, and diabetes are traditional risk factors for coronary heart disease, and these factors also increase the risk of OSAHS. The results of this study are consistent with this. AHI ≥ 30 times / hour is an independent risk factor for OSAHS combined with coronary heart disease, that is, the risk of coronary heart disease in severe OSAHS is 1.913 times that of mild and moderate OSAHS, which is consistent with the results of the multicenter Sleep Heart Health Study (SHHS). Intermittent hypoxia and reoxygenation at night in patients with severe OSAHS will induce oxidative stress, initiate an inflammatory cascade, increase sympathetic nerve activity, lead to vascular endothelial dysfunction, metabolic regulation disorder, and promote platelet aggregation, stimulate a series of pathophysiological changes, and then promote the occurrence and development of atherosclerosis, leading to an increased risk of coronary heart disease. The four-variable score is also an independent risk factor for OSAHS combined with coronary heart disease. When the four-variable score is ≥10.5 points, the risk of coronary heart disease in the OSAHS population is 4.046 times that of the four-variable score <10.5 points. The four-variable score may be a useful tool for screening OSAHS combined with coronary heart disease.

[0070] The results of this study showed that the optimal cut-off value of the four-variable score for screening OSAHS was 9.5 points, with an area under the ROC curve of 0.701, a sensitivity of 64.6%, a specificity of 64.5%, a positive predictive value of 0.645, and a negative predictive value of 0.646. It can be seen that the sensitivity and specificity of this scale in screening OSAHS are not high, so it has certain limitations in the screening and evaluation of OSAHS. The optimal cut-off value of the four-variable score for screening OSAHS combined with coronary heart disease is 10.5 points, with an area under the ROC curve of 0.819, a sensitivity of 76.7%, a specificity of 71.4%, a positive predictive value of 0.728, and a negative predictive value of 0.754, showing good sensitivity and specificity, and has high clinical application value. The results of this study are consistent with the findings of existing studies when using the four-variable score to screen moderate to severe OSAHS combined with acute ischemic stroke, showing similar AUC values, sensitivity, and specificity, indicating that the predictive efficacy of the two may be similar. The 2024 Expert Consensus on the Assessment and Management of Obstructive Sleep Apnea in Patients with Cardiovascular Disease recommends the use of the STOP-Bang questionnaire for preliminary screening of patients with coronary heart disease suspected of having OSAHS. The questionnaire is concise, easy to operate, well accepted by patients, and has high sensitivity. The four-variable score showed its high efficiency and convenience in screening OSAHS combined with coronary heart disease in this study, and also showed its strong objectivity, providing a new screening method for our future clinical work. In the study on the relationship between NoSAS scores and cardiovascular disease in OSAHS patients, the results showed that the screening questionnaire was related to the severity of cardiovascular disease, and three variables in the four-variable score were consistent with the NoSAS score, which laid a good foundation for this study. In summary, our results show that the four-variable score has good predictive power in screening OSAHS combined with coronary heart disease, and can be used for preliminary screening of OSAHS in patients with coronary heart disease in clinical practice, providing a valuable basis for early follow-up diagnosis and treatment activities.

[0071] In summary, the four-variable score is positively correlated with the Gensini score, and can reflect the severity of coronary artery lesions to a certain extent; the four-variable score ≥10.5 points is an independent risk factor for OSAHS combined with coronary heart disease, and it is expected to become a new tool for screening OSAHS combined with coronary heart disease; the four-variable score shows good sensitivity and specificity in screening OSAHS combined with coronary heart disease, is efficient, convenient, and highly objective, and has good predictive value for screening patients with OSAHS combined with coronary heart disease, and has certain application value in clinical practice.

[0072] Although the present invention has been described in detail with reference to the aforementioned embodiments, it is still possible for those skilled in the art to modify the technical solutions described in the aforementioned embodiments, or to make equivalent substitutions for some of the technical features therein. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present invention should be included in the protection scope of the present invention.

Claims

1. A method for evaluating the correlation between OSAHS and coronary heart disease based on clinical data and four-variable scoring, characterized in that: The method steps are as follows: S1: Clinical data collection, including patient gender, age, medical history, snoring, height and weight, as well as fasting blood test results of liver function, renal function, blood lipids and fasting blood glucose the next morning after fasting for 8 hours, and average systolic and diastolic blood pressure of 24-hour ambulatory blood pressure monitoring; S2: Calculation of total coronary artery score, using the Gensini score to assess the severity of coronary artery lesions: the product of each vascular stenosis score and the lesion site score is the score for each vascular lesion, and the sum of all lesion scores is the total coronary score for each patient; S3: Polysomnographic sleep monitoring, which involves 7 hours of polysomnographic sleep monitoring throughout the night, and simultaneous monitoring of blood oxygen saturation, pulse, respiratory rate, snoring, and oral and nasal airflow. After the monitoring, Remlogic software is used for data analysis and collection of monitoring index data; S4: a four-variable score, including gender, blood pressure level, body mass index, and self-reported snoring; S5: Statistical calculations. Data were analyzed using SPSS 26.0 software. The Shapiro-Wilk test was used to test the normality of continuous variables. Non-normally distributed quantitative data were analyzed using M (P 25 ,P 75 ), the Kruskal-Wallis H test was used for inter-group comparison, count data were expressed as frequency%, and the chi-squared X- 2 The correlation between the four-variable score and AHI, LSaO2, and Gensini score was analyzed by Spearman correlation analysis. The indicators with statistically significant differences in univariate logistic regression analysis were used for multivariate analysis using binary logistic regression model to screen out the risk factors for OSAHS combined with coronary heart disease. The results were expressed as odds ratios and 95% confidence intervals. The four-variable score was used as the reference variable, and whether it was OSAHS and OSAHS combined with coronary heart disease were used as grouping variables. ROC curves were drawn respectively, and the cut-off values ​​of the four-variable score for screening OSAHS and OSAHS combined with coronary heart disease were calculated. The area under the ROC curve was obtained, and the sensitivity, specificity, positive predictive value, and negative predictive value were calculated to determine the predictive value of the correlation between OSAHS combined with / and coronary heart disease.

2. The method for evaluating the correlation between OSAHS and coronary heart disease based on clinical data and four-variable scoring according to claim 1, characterized in that: In S1, the body mass index is calculated by height and weight. The body mass index is BMI, body mass index=weight / height², and the unit of BMI is kg / m².

3. The method for evaluating the correlation between OSAHS and coronary heart disease based on clinical data and four-variable scoring according to claim 1, characterized in that: The total coronary score calculation in S2 includes the Gensini score of coronary angiography and the Gensini score of coronary CT angiography.

4. The method for evaluating the correlation between OSAHS and coronary heart disease based on clinical data and four-variable scoring according to claim 1, characterized in that: The monitoring index data in S3 include apnea-hypopnea index, average blood oxygen saturation and minimum blood oxygen saturation.

5. The method for evaluating the correlation between OSAHS and coronary heart disease based on clinical data and four-variable scoring according to claim 1, characterized in that: In S4, gender includes male and female, with male scoring 4 points and female scoring 0 points. Blood pressure levels include normal blood pressure, primary hypertension, secondary hypertension and tertiary hypertension, with normal blood pressure scoring 1 point, primary hypertension scoring 2 points, secondary hypertension scoring 3 points and tertiary hypertension scoring 4 points. Body mass index includes BMI<21.0, 21.0≤BMI≤22.9, 23.0≤BMI≤24.9, 25.0≤BMI≤26.9, 27.0≤ BMI≤29.9 and 30.0<BMI, BMI<21.0 was scored as 1 point, 21.0≤BMI≤22.9 was scored as 2 points, 23.0≤BMI≤24.9 was scored as 3 points, 25.0≤BMI≤26.9 was scored as 4 points, 27.0≤BMI≤29.9 was scored as 5 points, and 30.0<BMI was scored as 6 points. Self-reported snoring included snoring almost every day or often and others, snoring almost every day or often was scored as 4 points, and others were scored as 0 points.

6. The method for evaluating the correlation between OSAHS and coronary heart disease based on clinical data and four-variable scoring according to claim 1, characterized in that: In the S5 statistical calculation, p < 0.05 was considered statistically significant.

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