Impact of Obstructive Sleep Apnea on Platelet Function Profiles in Patients With Acute Coronary Syndrome Taking Dual Antiplatelet Therapy.

Background Obstructive sleep apnea ( OSA ) is a novel risk factor for acute coronary syndrome ( ACS ). Several studies have shown OSA to be associated with induced platelet reactivity. However, whether OSA have effects on platelet function profiles in ACS patients taking dual antiplatelet therapy remains unexplored. Methods and Results This was a cross-sectional observational study, in which ACS patients taking maintenance aspirin and clopidogrel therapy were included. OSA was defined as an apnea-hypopnea index ≥15 events/hour. The inhibitory rate of arachidonic acid or adenosine diphosphate pathway were assessed with thrombelastography and defined patients with high residual on-treatment platelet reactivity. Platelet indices were obtained from routine analysis of blood samples using an automated blood cell counter. A total of 127 ACS patients taking dual antiplatelet therapy were analyzed. Platelet volume indices, including mean platelet volume and platelet large cell ratio, were significantly increased in patients with OSA . Patients with OSA (n=68) had significantly lower inhibitory rate of adenosine diphosphate receptor pathway ( P=0.028) compared with those without (n=59). After adjustment for potential confounders, patients with OSA were more likely to have high residual on-treatment platelet reactivity after clopidogrel therapy (adjusted odds ratio: 3.25, 95% confidence interval: 1.19-8.87, P=0.021). Conclusions In ACS patients taking dual antiplatelet therapy, OSA is associated with an increased level of platelet volume indices, reduced clopidogrel-induced antiplatelet effects and a greater prevalence of high residual on-treatment platelet reactivity.

Clinical Perspective

What Is New?

In acute coronary syndrome (ACS) patients taking maintenance aspirin and clopidogrel therapy, obstructive sleep apnea (OSA) is associated with increased level of platelet volume indices, reduced clopidogrel‐induced antiplatelet effects and a greater prevalence of high residual on‐treatment platelet reactivity.

These findings may explain the elevated prevalence of ischemic complications among ACS patients with OSA.

What Are the Clinical Implications?

This results suggest that OSA affects platelet function and pharmacodynamic profiles of antiplatelet drugs in ACS patients.

These findings may explain why some ACS patients with OSA have worse clinical prognosis than others and suggest the potential need for further categorizing this already high‐risk cohort of patients into those with and without OSA.

This study enables a better understanding of individual risk profiles of patients with ACS and OSA, and suggests future development of targeted treatment strategies may be beneficial for these patients.

Obstructive sleep apnea (OSA) is characterized by repetitive upper airway obstruction during sleep, and is usually associated with a wide range of cardiovascular, metabolic, and neurocognitive disorders and may lead to increased morbidity and mortality.1, 2 A prevalence of OSA up to 66% has been reported in the early phase of acute coronary syndrome (ACS).3 And about 50% of patients with percutaneous coronary intervention (PCI) suffer from OSA.4, 5 Importantly, patients with OSA experience an increased risk of adverse outcomes after PCI.4, 5 Recent findings from meta‐analysis suggested that OSA appears to increase the risk of cardiac death, non‐fatal myocardial infarction (MI), and coronary revascularization in patients after PCI.4 Outcomes in ACS patients with moderate/severe OSA have shown to be worse compared with normal or mild OSA patients.6

In fact, OSA can impact the platelet function.7, 8 Gunbey et al have found that platelet aggregation was correlated with apnea‐hypopnea index (AHI).9 The platelet distribution width (PDW) and mean platelet volume (MPV) of OSA patients were significantly increased.9 Rahangdale et al have reported that adenosine 5′‐diphosphate (ADP)‐induced platelet aggregation was markedly increased in OSA patients.7 In addition, platelet reactivity and MPV levels decreased significantly after continuous positive airway pressure (CPAP) therapy in patients with OSA.10 Dual antiplatelet therapy (DAPT), consisting of the combination of aspirin and an oral inhibitor of the platelet P2Y12 receptor for ADP, is the cornerstone of drug therapy for post‐PCI or ACS patients. However, it remains unclear whether OSA affects platelet function and pharmacodynamic profiles of antiplatelet drugs in patients taking DAPT.

The aim of the present study was to assess the impact of OSA on platelet function profiles in ACS patients taking DAPT.

Methods

The data, analytic methods, and study materials will not be made available to other researchers for purposes of reproducing the results or replicating the procedure.

Study Design and Subjects

This cross‐sectional observational study is an ancillary study of the OSA‐ACS Project (a prospective cohort study of NCT03362385 [Impact of Obstructive Sleep Apnea and Continuous Positive Airway Pressure Therapy on Outcomes in Patients with Acute Coronary Syndrome: The OSA‐ACS Project]). The aim of that large‐scale, prospective cohort study was to delineate the whole picture of the association of OSA with short‐ and long‐term outcomes of patients with ACS and the effect of CPAP treatment on the incidence of new cardiovascular events. In this study, we evaluated patients consecutively admitted to Beijing Anzhen Hospital (Beijing, China) with a diagnosis of ACS from June 2015 to May 2017. ACS was defined according to ACS related guidelines.11, 12 Patients were eligible for platelet function analyses if they were in their maintenance steady‐state phase (at least 7 days) of DAPT with aspirin (100 mg/day) and clopidogrel (75 mg/day). After patients agreed to participate and the consent form was signed, all patients underwent an overnight sleep study to assess the presence of OSA.

Exclusion criteria included: patients aged >75 or <18 years; any previously diagnosed sleep disorder; known OSA on CPAP treatment; known allergies to aspirin or clopidogrel; dialysis; blood dyscrasia; active bleeding or bleeding diathesis; gastrointestinal bleed within last 6 months; hemodynamic instability; acute cerebrovascular event within 3 months; any malignancy; concomitant use of other antithrombotic drugs (oral anticoagulants, dypiridamole, cilostazol) or non‐steroid anti‐inflammatory drugs; life‐limiting chronic disease; serious hepatorenal functional impairment; and hematocrit <25%; platelet count <100 (1000/mm3). The study complied with the Declaration of Helsinki, and was approved by the ethics committee of Beijing Anzhen Hospital. All patients gave their informed written consent.

Overnight Sleep Study

All patients underwent an overnight sleep study after clinically stabilization during hospitalization, using a portable cardiorespiratory monitoring device (The ApneaLink, Resmed, Austrulia). Nasal airflow, arterial oxygen saturation, thoraco‐abdominal movements, and snoring episodes were recorded. An obstructive apnea episode was defined by a complete cessation of airflow lasting ≥10 seconds. An episode of hypopnea was defined as a reduction in airflow lasting ≥10 seconds and is associated with oxygen desaturation. Oxygen desaturation is considered as a decrease in SaO2 >4%. AHI was defined as the number of apneas and hypopneas per hour of sleep. All studies will be manually analyzed by an independent sleep technologist who is not aware of the patients’ clinical characteristics. To ensure the accuracy and consistency of analyzing, 50% of all studies will be audited by a masked investigator with expertise in sleep medical. Recruited patients were classified into OSA (AHI ≥15 events/hour) and non‐OSA (AHI <15 events/hour) groups.5, 13

Clinical Data Extraction

The following baseline demographic medical history and a detailed medication history were collected from the medical records of the recruited patients.

The Thrombelastography Platelet Mapping Assay

Thrombelastography Platelet Mapping assay used 4 channels to detect effects of antiplatelet therapy with arachidonic acid and ADP activators. A detailed description of this method is outlined previously.14 Percentage platelet inhibition is defined by the extent of non‐response of the platelet ADP (P2Y12) or thromboxane A2 receptor to the exogenous ADP and arachidonic acid as measured by maximum amplitude (MA). The percentage platelet aggregation to agonist can be calculated by: [(MAADP/AA−MAFibrin)/(MAThrombin−MAFibrin)×100]. Percentage platelet inhibition is thus 100%—the percentage platelet aggregation (%). This calculation is performed by the Thrombelastography Platelet Mapping software. Similarly, the percentage inhibition resulting from the antiplatelets clopidogrel and aspirin can be calculated.15

Statistical Analysis

Continuous variables are expressed as the mean±SD or median (interquartile range) for data with a skewed distribution. Patients characteristics were compared using Student t test, analysis of variance, or the non‐parametric Mann–Whitney test for skewed data. Categorical variables are presented as counts and percentages and were compared by means of the chi‐square test or Fisher exact test. Spearman correlation analysis was performed for determination of correlation. A multivariable linear regression model was used to evaluate the independent contribution of the OSA and non‐OSA groups to the inhibitory rate of ADP pathway. Control for potential confounders and analysis of independent correlates of high residual on‐treatment platelet reactivity (HRPR) were performed with a logistic regression model including age, sex, body mass index, diabetes mellitus, hypertension, prior PCI, and estimated glomerular filtration rate (eGFR) as independent control variables and OSA as the independent study variable of interest. Odds ratio (OR) and 95% confidence interval (CI) were calculated. All tests were 2‐sided, and a value of P<0.05 was considered statistically significant. Statistical analysis was performed with IBM SPSS Statistics, Version 22.0 (IBM Corp., Armonk, NY, USA).

Results

Patient Population

A total of 127 ACS patients were studied. Baseline demographic data, clinical characteristics, and laboratory data of patients with (n=68) and without (n=59) OSA were described in Table 1. Of the participants, 88.2% were men; the mean age was 55.23±9.93 years. There were no differences in terms of age, sex, or prevalence of cardiovascular risk factors (hypertension, diabetes mellitus, dyslipidemia, prior MI and smoking) among all groups. Patients with OSA have higher body mass index (Table 1). Sleep information was shown in Table 2. AHI, oxygen desaturation index, minimum, and average oxygen saturation, and time of SaO2 <90% were significantly different between groups (P<0.001).

Table 1

Patients Characteristics

Variables	All (n=127)	OSA Group (n=68)	Non‐OSA Group (n=59)	P Value
Age, y	55.2±9.9	55.9±10.5	54.5±9.2	0.42
Male	112 (88.2)	62 (91.2)	50 (84.7)	0.29
Diabetes mellitus	37 (29.1)	19 (27.9)	18 (30.5)	0.85
BMI, kg/m2	26.6 [24.6, 28.7]	27.7 [25.3, 29.3]	25.9 [24.2, 27.7]	0.02
Smoking	76 (59.8)	36 (52.9)	40 (67.8)	0.10
Alcohol	53 (41.7)	33 (48.5)	20 (33.9)	0.10
Medical history
Hypertension	76 (59.8)	44 (64.7)	32 (54.2)	0.28
Dyslipidemia	30 (23.6)	17 (25.0)	13 (22.0)	0.83
Prior MI	16 (12.6)	6 (8.5)	10 (16.2)	0.28
Prior PCI	20 (15.7)	14 (20.6)	6 (10.2)	0.14
Prior CABG	2 (1.6)	1 (1.5)	1 (1.7)	1.00
Prior stroke	11 (8.7)	8 (11.8)	3 (5.1)	0.22
ACS category
UA	45 (35.4)	26 (38.3)	19 (32.2)	0.60
NSTEMI	33 (26.0)	13 (19.1)	20 (33.9)	0.09
STEMI	49 (38.6)	29 (42.6)	20 (33.9)	0.41
PCI	100 (78.7)	55 (80.9)	45 (76.3)	0.66
Medication
PPIs	107 (84.3)	56 (82.4)	51 (86.4)	0.63
ACEI	78 (61.4)	43 (63.2)	35 (59.3)	0.72
ARB	21 (16.5)	12 (17.6)	9 (15.3)	0.81
Diuretics	5 (3.9)	3 (4.4)	2 (3.4)	1.00
Statin	127 (100.0)	68 (100.0)	59 (100)	‐
β‐blockers	111 (87.4)	58 (85.3)	53 (89.8)	0.59
Calcium antagonists	17 (13.4)	11 (16.2)	6 (10.2)	0.44
Laboratory data
Platelet count, 1000/mm3	211.5 [179.8, 248.3]	207.0 [172.0, 249.0]	213.0 [185.0, 248.0]	0.42
Plateletcrit (%)	0.20 [0.18, 0.24]	0.20 [0.18, 0.25]	0.21 [0.18, 0.24]	0.88
Hematocrit, %	41.94±3.63	41.82±3.43	42.08±3.88	0.68
WBC, 1000/mm3	8.56±2.77	8.87±2.76	8.20±2.76	0.17
HbA1c, %	6.58±1.37	6.55±1.29	6.60±1.46	0.85
Creatinine, μmol/L	75.0 [68.0, 85.0]	76.5 [71.0, 86.5]	74.0 [66.0 83.0]	0.08
eGFR, mL/min per 1.73 m2	97.7 [83.8, 109.0]	94.5 [83.0, 106.5]	102.0 [85.4, 114.3]	0.14

Data given as n (%), mean±SD or median [IQR]. P value is moderate/severe OSA vs without or with mild OSA. ACEI indicates angiotensin‐converting enzyme inhibitors; ACS, acute coronary syndrome; ARB, angiotensin receptor blocker; BMI, body mass index; CABG, coronary artery bypass grafting; HbA1c, hemoglobin A1c; IQR, interquartile range; MI, myocardial infarction; NSTEMI, non‐ST‐segment elevation myocardial infarction; PCI, percutaneous coronary intervention; PPIs, proton pump inhibitors; SD, standard deviation; STEMI, ST‐segment elevation myocardial infarction; UA, unstable angina; WBC, white blood cell counts.

Table 2

Sleep Information

Variables	All (n=127)	OSA Group (n=68)	Non‐OSA Group (n=59)	P Value
AHI, events/h	16.0 [8.0, 34.0]	32.8 [24.0, 52.0]	8.0 [4.0, 10.9]	<0.001
ODI, events/h	16.0 [7.0, 36.0]	36.0 [22.5, 51.0]	7.0 [4.0, 11.0]	<0.001
Minimum SaO2 (%)	85.0 [80.0, 88.0]	83.0 [76.0, 86.0]	88.0 [85.0, 89.0]	<0.001
Mean SaO2 (%)	94.0 [93.0, 95.0]	93.0 [92.0, 94.0]	95.0 [94.0, 96.0]	<0.001
Total percentage of time of SaO2 <90%	1.0 [0.0, 8.0]	6.0 [1.0, 17.5]	0.0 [0.0, 1.0]	<0.001

Data given as median [IQR]. AHI indicates apnea‐hypopnea index; IQR, Interquartile range; ODI, oxygen desaturation index; OSA, obstructive sleep apnea.

The Impact of OSA on Platelet Volume Indices in ACS Patients Taking DAPT

Platelet volume indices are indicator of platelet activation and play an important role in the pathophysiology of cardiovascular diseases.16, 17 In the study, we found that patients with OSA have higher MPV and platelet large cell ratio values (Figure 1A and 1B). And PDW (%) in OSA group also tended to be higher than that in the non‐OSA group (13.1±2.3 versus 12.4±1.9, P=0.07), although this was not statistically significant (Figure 1C).

Figure 1

The impact of OSA on platelet volume indices in ACS patients taking DAPT. The level of MPV (A), P‐LCR (B) and PDW (C) in patients with and without OSA. ACS indicates acute coronary syndrome; DAPT, dual antiplatelet therapy; MPV, mean platelet volume; OSA, obstructive sleep apnea; PDW, platelet distribution width; P‐LCR, platelet large cell ratio.

Additionally, correlation of MPV with parameters of sleep was noted. MPV weakly correlated with AHI (r=0.204, P=0.022), oxygen desaturation index (r=0.216, P=0.023), and minimum SaO2 (%) (r=−0.180, P=0.044) (Figure 2). These results suggested that OSA patients have higher MPV and platelet large cell ratio values and tend to have relatively increased platelet activation and atherothrombotic risk.

Figure 2

Correlation between MPV and parameters of sleep. Correlation between MPV and AHI (A), ODI (B), and minimum SaO2 (%) (C), mean SaO2 (%) (D), and total percentage of time of SaO2<90% (E). AHI indicates apnea‐hypopnea index; MPV, mean platelet volume; ODI, oxygen desaturation index.

The Impact of OSA on Pharmacodynamic Profiles of Antiplatelet Drugs

No significant difference in inhibitory rate of arachidonic acid pathway was observed between patients with OSA and those without (Figure 3A). Significant lower inhibitory rate of ADP pathway in patients with OSA compared with those without (Figure 3B). Additionally, correlation of the inhibitory rate of ADP pathway with parameters of sleep was analyzed by Spearman correlation analysis. The inhibitory rate of ADP pathway weakly correlated with mean SaO2 (%) (r=0.188, P=0.034) and total percentage of time SaO2 <90% (r=−0.198, P=0.038) (Figure 4).

Figure 3

The impact of OSA on the inhibitory rate of arachidonic acid or ADP pathway. (A) No significant differences in inhibitory rate of arachidonic acid pathway was observed between patients with OSA and those without; (B) Patients with OSA had significantly lower inhibitory rate of ADP pathway compared with those without. The central box represents the values between the lower and upper quartiles, and the middle line is the median. AA indicates arachidonic acid; ADP, adenosine diphosphate; OSA, obstructive sleep apnea.

Figure 4

Correlation between inhibitory rate of ADP pathway and parameters of sleep. Correlation between inhibitory rate of ADP pathway and AHI (A), ODI (B), and minimum SaO2 (%) (C), mean SaO2 (%) (D), and total percentage of time of SaO2<90% (E). ADP indicates adenosine diphosphate; AHI, apnea‐hypopnea index; ODI, oxygen desaturation index.

Previous studies have demonstrated that suboptimal response to antiplatelet agents was affected by many factors.18, 19 Simple linear regression analysis showed that the inhibitory rate of ADP pathway may be associated with age, sex, OSA, hypertension, eGFR, platelet counts and β‐blockers (P<0.1) (Table S1). To further examine the relationship OSA and the inhibitory rate of ADP pathway, we used a multivariable linear regression model to evaluate the independent contribution of the OSA and non‐OSA groups to the inhibitory rate of ADP pathway after adjusting for age, sex, hypertension, eGFR, platelet counts and β‐blockers. These results showed that the presence or not of OSA significantly contributed to the inhibitory rate of ADP pathway (β: −10.57, 95% CI: −19.68 to −1.45, P=0.023) (Table 3), suggesting that OSA is associated with reduced clopidogrel‐induced antiplatelet effects.

Table 3

Multivariable Linear Regression Analysis of the Inhibitory Rate of ADP Receptor Pathway (Presence or Not of OSA)

Variables	β (95% CI)	P Value
Age, y	−0.03 (−0.58, 0.53)	0.930
Male	9.56 (−5.36, 24.48)	0.207
Group
Non‐OSA	Reference
OSA	−10.57 (−19.68, −1.45)	0.023
Hypertension	5.09 (−4.02, 14.20)	0.271
eGFR, mL/min per 1.73 m2	0.24 (0.02, 0.47)	0.035
Platelet counts, 1000/mm3	0.08 (0.00, 0.16)	0.043
β‐blockers	−13.918 (−27.72, −0.12)	0.048

ADP indicates adenosine diphosphate; CI, Confidence interval; eGFR, estimated glomerular filtration rate; OSA, obstructive sleep apnea.

OSA and HRPR

In the overall study population, inhibitory rates of ADP pathway quartile cut points for the 25th, 50th, and 75th percentiles of the study population were 26.8%, 47.8%, and 66.9%, respectively. The lower quartile identified patients with HRPR.20 As Figure 5 showed, patients with OSA were more likely to have HRPR than those non‐OSA (33.8% versus 13.6%, P=0.012).

Figure 5

Prevalence of HRPR in patients with OSA and non‐OSA. HRPR indicates high residual on‐treatment platelet reactivity; OSA, obstructive sleep apnea.

To further investigate the impact of OSA on HRPR, we classified the included patients into 2 groups (non‐HRPR and HRPR) according to the inhibitory rates of ADP pathway. The characteristics and demographic variables of the patient groups are shown in Table S2. AHI, OSA, Prior MI, and eGFR were significantly different between groups (Table S2). Logistic regression analysis showed that OSA significantly associated with HRPR (OR: 3.26, 95% CI: 1.33–8.01, P=0.010). After adjustment for potential confounders (age, sex, body mass index, diabetes mellitus, hypertension, prior PCI, and eGFR), OSA remained markedly associated with HRPR (adjusted OR: 3.25, 95% CI: 1.19–8.87, P=0.021).

Discussion

The present study showed that in ACS receiving maintenance aspirin and clopidogrel therapy, the presence of OSA is associated with higher levels of MPV and L‐PCR compared with patients with non‐OSA. In particular, these patients with OSA also have higher degrees of platelet reactivity after clopidogrel therapy. Additionally, after adjustment for potential confounders, patients with OSA had a 3.25‐fold increase in the likelihood of showing HRPR after clopidogrel therapy. Overall, these findings are indicative not only of the presence of a hyper‐reactive platelet phenotype but also of dysfunctional ADP signaling mediated P2Y12 receptor. Therefore, these observations might explain the elevated prevalence of ischemic complications, including stent thrombosis, among CAD patients with OSA.

OSA is now considered a novel cardiovascular risk factor, according to the “European Guidelines on Cardiovascular Disease Prevention in Clinical Practice (2012)”.21 Up to 66% of ACS patients have OSA and about 50% of patients with PCI suffer from OSA.3, 4, 5 Meta‐analysis demonstrated that cardiac death is 2‐fold higher in patients with OSA after successful PCI.4 The OSA patients also have more aggressive atherosclerotic disease and a greater risk of thrombotic complications, including stent thrombosis.22 The Sleep and Stent Study enrolled 1311 patients successfully treated with PCI, and >98% of these patients were treated with DAPT. The result of the study showed that OSA is independently associated with subsequent major adverse cardiac and cerebrovascular events, claiming the need for additional studies to evaluate of therapeutic approaches to mitigate OSA‐associated risk.5 Interestingly, some clinical studies showed that severe OSA significantly increases the level of MPV and platelet reactivity, and CPAP therapy significantly reversed this effect.7, 9 Rahangdale et al have previously reported in a small cohort ADP‐induced platelet aggregation was markedly increased in OSA patients.7 However, it remains unclear whether OSA affects the clinical outcomes of CAD patients taking DAPT by influencing platelet function and antiplatelet agent efficacy.

Platelet volume indices are known as indicators of platelet activation and play an important role in the pathophysiology of cardiovascular diseases.16, 17 Recently, Wasilewski et al have reported that all‐cause mortality is 1.5‐fold higher in non‐ST‐segment elevation myocardial infarction patients with high MPV values.17 In earlier studies, MPV and PDW were found to be significantly higher in patients with severe OSA when compared with control subjects.23, 24 In this study, we firstly found that MPV and platelet large cell ratio values of ACS patients taking DAPT with moderate/severe OSA were significantly higher than those without, and that MPV correlated with AHI, oxygen desaturation index, and minimum SaO2 (%) (Figures 1 and 2). Our results suggested that ACS patients taking DAPT with OSA tend to have an increased platelet activation. Increased platelet activity could contribute to an increased atherothrombotic risk in patients with OSA. CPAP reported to cause a significant decrease in the MPV and PDW values in patients with OSA,9, 10 and this suggested that early diagnosis and CPAP therapy may confer some cardioprotective effects through the reduction of platelet activation.

Suboptimal response to antiplatelet agents or HRPR, in fact, has been associated with an enhanced risk of major cardiovascular events and acute ischemic complications, especially with clopidogrel, where a high HRPR has been described in almost 30% of patients.18, 25, 26 In patients with ACS or undergoing PCI, HRPR is associated with ≈2‐ to 3‐fold greater risk of recurrent ischemic events and about 1.5‐fold greater risk of all‐cause mortality.27, 28, 29 In particular, this study shows a broad variability platelet function profiles in patients receiving clopidogrel, and OSA is associated with reduced clopidogrel‐induced antiplatelet effects and a greater likelihood of having HRPR. Our study findings might contribute to explain why some OSA patients have worse clinical prognosis than others and suggest the potential need for further categorizing this already high‐risk cohort of patients into those with and without OSA. This might enable a better understanding of their individual risk profile and allow the future development of targeted treatment strategies for these patients.

The persistence of high‐platelet reactivity despite adjunctive clopidogrel therapy underscores the need for more potent platelet inhibition strategies to reduce the risk of recurrence of ischemic events, including high dose of clopidogrel and new antiplatelet agents. The new P2Y12 inhibitors (prasugrel and ticagrelor) have a more predictable response, greater potency and faster onset of characteristics, thus making them the treatment of choice in patients receiving clopidogrel therapy with HRPR. Nowadays, new oral P2Y12 inhibitors have evidentially been recommended for the treatment of ACS, as they show a reduction in cardiovascular events compared with clopidogrel.11, 12 However, it may be argued that high‐platelet reactivity alone cannot be used as a good indicator for using more potent platelet inhibition, because if OSA also exists, then reducing the potential benefits of ischemic events may be offset by the bleeding rate. In fact, OSA is well‐established to be associated with increased bleeding risk.30, 31, 32 Indeed, evaluating outcome data in OSA patients will provide more insights on the risk‐benefit ratio of antithrombotic strategies, particularly with the introduction of novel and more potent agents.

Several limitations of this study should be noted. First, this is a cross‐sectional observational study of independent groups and suffers from the apparent limitations of a non‐randomized trial. In an attempt to account for these limitations, we also made comparisons that were adjusted for several clinical variables. Because of the large number of variables introduced, we cannot rule out a potential of overfitting models. Second, in the present study, we assessed the impact of OSA on pharmacodynamic profiles of antiplatelet drugs according to thrombelastography. No data (eg, glycoprotein IIb/IIIa activation and P‐selectin expression) were available to evaluate platelet activation. Third, this study excluded elderly patients (aged >75 years), which could have included patients who exhibited the most severe OSA.

Conclusion

To the best of our knowledge, this is the first study providing a potential underlying mechanism to explain why OSA patients with CAD have worse outcomes. In ACS patients taking maintenance aspirin and clopidogrel therapy, OSA is associated with an increased level of platelet‐volume indices, reduced clopidogrel‐induced antiplatelet effects, and a greater prevalence of HRPR.

Sources of Funding

This study was supported by grants from the National Natural Science Foundation of China (81600213, 81600209, and 81670222), Capital Medical University Foundation‐Clinical Research Cooperation Fund (16JL17), International Science & Technology Cooperation Program of China (2015DFA30160), Beijing Municipal Science & Technology Commission (Z141100006014057), Beijing Municipal Administration of Hospitals’ Youth Program (QML20160605).

Disclosures

None.

Table S1. Simple Linear Regression Analysis of the Inhibitory Rate of ADP Receptor Pathway

Table S2. Characteristics of Patients With Non‐HRPR and HRPR

Click here for additional data file.