Prognostic Value of Neutrophil-to-lymphocyte Ratio for Patients with Acute Coronary Syndrome and Obstructive Sleep Apnea

Abstract

Objective: This study was aimed at investigating the effects of the neutrophil-to-lymphocyte ratio (NLR) on the long-term prognosis of patients with acute coronary syndrome (ACS) and obstructive sleep apnea (OSA).

Methods: This prospective study enrolled patients with ACS and OSA at Anzhen Hospital between June 2015 and January 2020. OSA was defined by an apnea-hypopnea index ≥15 events·h⁻¹. Baseline NLR was classified as high or low, according to the median. The primary endpoint was major adverse cardiovascular events (MACE), comprising cardiovascular death, recurrent myocardial infarction, stroke, and ischemia-driven revascularization.

Results: A total of 1011 patients with ACS and OSA were enrolled, 506 of whom were in the high NLR (≥2.54) group. No significant differences in sleep monitoring indicators were observed. During a median follow-up of 2.8 (1.4, 3.6) years, a non-linear correlation between NLR and the incident risk of MACE was observed. After adjustment for clinically relevant confounders, a high NLR was independently associated with elevated MACE risk (adjusted HR = 1.45, 95% CI: 1.02–2.06, P = 0.040).

Conclusions: In patients with ACS and OSA, a high NLR was associated with poorer clinical outcomes during long-term follow-up.

Trial registration: ClinicalTrials.gov; Number: NCT03362385; URL: www.clinicaltrials.gov.

Main article text

Abbreviations:

ACEI: angiotensin-converting enzyme inhibitor; ACS: acute coronary syndrome; AHI: apnea hypopnea index; ARB: angiotensin receptor blocker; BMI: body mass index; CABG: coronary artery bypass grafting; CAD: coronary artery disease; CPAP: continuous positive airway pressure; CVD: cardiovascular disease; eGFR: estimated glomerular filtration rate; MACE: major adverse cardiovascular events; MI: myocardial infarction; NLR: neutrophil-to-lymphocyte ratio; NSTE-ACS: non-ST-segment elevation acute coronary syndrome; OSA: obstructive sleep apnea; PCI: percutaneous coronary intervention; SaO₂: arterial oxygen saturation; STEMI: ST-segment elevation myocardial infarction.

Introduction

Obstructive sleep apnea (OSA) is a sleep disorder characterized by repetitive complete (apnea) or partial (hypopnea) upper airway collapse, which results in cyclical hypoxemia, recurrent arousal from sleep, and intrathoracic pressure oscillation, followed by sympathetic nervous activation, sustained elevation of arterial pressure, and associated complications [1–3]. OSA is recognized as a serious global health burden, given that it affects 17% of women and 34% of men in the general population, and has detrimental effects on neurocognition and cardiovascular systems [4–6]. Studies from our group and others increasingly indicate that OSA is a novel risk factor for the occurrence and progression of coronary artery disease (CAD) [7], particularly acute coronary syndrome (ACS) [8, 9]; moreover, untreated OSA is independently associated with an elevated risk of cardiovascular events in patients with established ACS during long-term follow-up [8, 10, 11]. OSA exerts detrimental effects on ACS through various routes including intermittent hypoxia, oxidative stress, and inflammation; among these, inflammation is critical, because an elevated inflammatory response is responsible for the development of atherosclerosis and acute thrombotic complications [12, 13]. Therefore, clarification of the role of the inflammatory response might provide novel insights into the association between OSA and ACS [7].

Recently, the neutrophil-to-lymphocyte ratio (NLR) has been used as a novel biomarker of systemic inflammation in response to infectious and non-infectious illnesses, and various pathological states. The NLR results from a dynamic balance between innate and adaptive immune system inflammation. Clinical studies have indicated that higher NLR values are associated with the development of cardiovascular diseases (CVDs) [13], and arterial stiffness significantly increases with the NLR [14]. Moreover, the NLR is higher in patients with ACS than in patients with stable ACS or a history of myocardial infarction (MI). Thus, the NLR holds promise as a reliable biomarker indicating the presence and severity of inflammation in ACS [15]. The NLR has also been validated as a predictor of subsequent major adverse coronary events (MACE) and death [16–20]. Additionally, in patients with OSA without ACS, a positive correlation has notably been observed between NLR and the severity of OSA [indicated by the apnea-hypopnea index (AHI)] [21–23]. Although ACS and OSA are both well-established chronic pathological processes with a marked inflammatory response, the clinical and prognostic value of the NLR in patients with ACS and OSA remains unclear.

Hence, this prospective study, based on a large-scale cohort, was performed to investigate the effects of NLR on the long-term prognosis of patients with ACS and OSA.

Methods

Study Design and Patients

This prospective study, based on the OSA-ACS project (NCT03362385), enrolled patients with ACS and OSA treated at Anzhen Hospital between June 2015 and January 2020. The inclusion criteria for patients were 1) ACS diagnosis including ST-segment elevation myocardial infarction (STEMI), non-STEMI, or unstable angina; 2) diagnosis with OSA according to an AHI ≥15 event·h⁻¹, in accordance with the International Classification of Sleep Disorders, Third Edition, and the guidelines from the Adult Obstructive Sleep Apnea Task Force of the American Academy of Sleep Medicine [24]; and 3) age between 18 and 85 years. Patients were excluded if they had 1) cardiogenic shock, cardiac arrest, or malignancy with less than 2-year life expectancy; 2) inadequate or unsatisfactory sleep monitoring recording, or predominantly central sleep apnea (≥50% central events and central AHI ≥10 events·h⁻¹); or 3) regular continuous positive airway pressure therapy or loss to follow-up after discharge.

This study complied with the STrengthening the Reporting of OBservational studies in Epidemiology (STROBE) guidelines and with the principles of Declaration of Helsinki. The protocol was approved by the Ethics Committee of Beijing Anzhen Hospital, Capital Medical University (approval #2013025). All patients provided informed consent before participating in the study.

Overnight Sleep Monitoring

Eligible patients with ACS underwent overnight sleep studies with a type III portable cardiorespiratory polygraphy device (ApneaLink Air; ResMed), after clinical stabilization during their hospital stay. The sleep monitoring data were collected by trained research staff who were blinded to the patients’ clinical characteristics. An apnea event was defined as complete cessation of airflow for ≥10 s, and obstructive and central types were distinguished according to thoracoabdominal movement. Hypopnea was characterized by an airflow reduction exceeding 30% for ≥10 s, accompanied by a decline in arterial oxygen saturation (SaO₂) >4%. The AHI was computed as the number of apnea and hypopnea events per hour of total recording time. As outlined in the International Classification of Sleep Disorders, Third Edition, and the guidelines from the Adult Obstructive Sleep Apnea Task Force of the American Academy of Sleep Medicine [24], an obstructive AHI of ≥15 event·h⁻¹ served as the criterion for OSA, even in the absence of associated symptoms or disorders. Previous investigations have demonstrated that the presence of OSA (according to the AHI ≥15 event·h⁻¹ threshold) significantly predicts future events [25, 26]. Additional parameters, including nasal airflow, thoracoabdominal movements, instances of snoring, and nocturnal SaO₂, were also documented. The extent of hypoxemia was quantified by calculation of the oxygen desaturation index per hour of sleep and the proportion of time with SaO₂ <90% (T90). Patients with an AHI ≥15 events·h⁻¹, particularly those exhibiting excessive daytime sleepiness, as assessed with the Epworth Sleepiness Scale, were referred to a sleep center for potential OSA treatment considerations.

Clinical Data Collection and Procedures

The baseline patient characteristics were collected from the clinical records, and included age, sex, body mass index (BMI, kg·m⁻²), systolic blood pressure, diastolic blood pressure, medical history, familial history of CAD, smoking habit, medication history, ACS subtype, and laboratory markers. Sleep breathing monitoring outcomes were assessed with the AHI, minimum SaO₂, mean SaO₂, and T90. The lymphocyte and neutrophil counts, as measured in the Clinical Laboratory of Beijing Anzhen Hospital with an Automatic Blood Cell Counter (LH570, Bechman Coulter), were obtained from the medical records. The NLR was thus calculated by dividing the number of neutrophils by the number of lymphocytes. The NLR was classified as high and low according to the median cutoff value [27].

The management of ACS adhered to local protocols and prevailing guidelines, wherein patients received standard medications for ACS and underwent percutaneous coronary intervention or coronary artery bypass grafting if clinically indicated.

Follow-Up and Endpoints

Follow-up assessments were conducted at 1, 3, and 6 months after index hospitalization, and every 6 months thereafter. Clinical adverse events were recorded by investigators blinded to the patients’ sleep study outcomes. Data collection was performed through clinic visits, comprehensive medical record reviews, and telephone correspondence.

The primary endpoint was MACE, a composite of cardiovascular death, recurrent MI, stroke, and ischemia-driven revascularization. Secondary endpoints included every component of the primary endpoint, the composite of recurrent MI and ischemia-driven revascularization, all forms of revascularization, and all-cause mortality. All endpoints complied with the definitions published by the Standardized Data Collection for Cardiovascular Trials Initiative.

Statistical Analysis

Continuous variables are presented as mean ± standard deviation, or as median (interquartile range: first and third quartiles), and were analyzed with Student’s t-test or the Mann-Whitney U-test according to the variable distribution. Categorical variables are expressed as n (%), and were analyzed with the chi-square test or Fisher’s exact test, as appropriate. Restricted cubic spline curves were plotted to evaluate potential nonlinear correlations between NLR (continuous variable) and the incident risk of clinical outcomes. Kaplan-Meier curves were used to illustrate time-to-event data and the cumulative incidence of the primary and secondary endpoints according to the NLR levels. The log-rank test was used to assess differences between curves. Univariable and multivariable Cox analyses were conducted to assess hazard ratios (HRs) and 95% confidence intervals (CIs) for MACE and significant secondary endpoints. The covariates incorporated into the multivariable Cox proportional hazards model were selected from the baseline variables deemed clinically relevant, or those demonstrating a univariate association with the primary endpoints. These covariates included age, sex, BMI, hypertension, diabetes mellitus, hyperlipidemia, prior MI, prior stroke, ACS subtypes, ACE inhibitor/angiotensin receptor blocker (ACEI/ARB) prescription, stent implantation, and multivessel disease. The selection of variables for inclusion considered both the availability of events and the objective of maintaining the final models’ parsimony and accuracy.

All statistical analyses were performed in SPSS 26.0 (IBM, Armonk, NY, USA) and R 4.2.0 (R Foundation for Statistical Computing, Vienna, Austria). A two-tailed P < 0.05 was considered statistically significant.

Results

Baseline Characteristics and Results of Overnight Sleep Monitoring

A total of 1011 patients met the eligibility criteria and were enrolled (Figure 1). These patients were divided into high (n = 506) and low (n = 505) NLR groups according to the median value of 2.54. Patients with high NLR, compared with those with low NLR, had higher heart rate (P < 0.001), fasting plasma glucose (P = 0.014), leukocytes (P < 0.001), neutrophils (P < 0.001), and monocytes (P < 0.001), and lower lymphocytes (P < 0.001) and triglycerides (P = 0.013). In addition, the high NLR patients were more likely than the low NLR patients to have STEMI (P < 0.001), and to receive ACEI/ARB treatment (P = 0.002) and stent implantation (P < 0.001) (Table 1). Most of the other variables were comparable between groups.

Figure 1

Flow Diagram of Patient Selection. ACS: acute coronary syndrome; CPAP: continuous positive airway pressure; OSA: obstructive sleep apnea.

Table 1

Baseline Characteristics.

Variables	High NLR (n = 506)	Low NLR (n = 505)	P
Age (years)	56 (50, 63)	57 (49, 65)	0.271
Male, n (%)	452 (89.3)	431 (85.3)	0.057
BMI (kg/m2)	27.68 (25.5, 30.0)	27.82 (25.8, 30.4)	0.178
Heart rate (bpm)	73 (66, 81)	70 (64, 78)	<0.001
Systolic blood pressure (mmHg)	126 (115, 139)	128 (120, 139)	0.231
Diastolic blood pressure (mmHg)	76 (70, 86)	79 (70, 85)	0.281
Waist circumference	101 (95, 107)	101 (96, 108)	0.259
Waist/hip ratio	1.0 (1.0, 1.0)	1.0 (1.0, 1.0)	0.686
History of MI, n (%)	79 (15.6)	97 (19.2)	0.132
Prior PCI, n (%)	113 (22.3)	120 (23.8)	0.589
Heart failure, n (%)	10 (2.0)	11 (2.2)	0.822
Hypertension, n (%)	358 (70.8)	332 (65.7)	0.087
Diabetes mellitus, n (%)	164 (32.4)	154 (30.5)	0.512
Hyperlipidemia, n (%)	153 (30.2)	188 (37.2)	0.019
Atrial fibrillation, n (%)	12 (2.4)	12 (2.4)	0.996
History of gastrointestinal bleeding, n (%)	9 (1.8)	4 (0.8)	0.164
Prior stroke, n (%)	67 (13.2)	54 (10.7)	0.212
Renal impairment, n (%)	12 (2.4)	9 (1.8)	0.511
History of cancer, n (%)	10 (2.0)	2 (0.4)	0.020
Smoking, n (%)			0.941
No	167 (33.0)	166 (32.9)
Current	249 (49.2)	245 (48.5)
Former	90 (17.8)	94 (18.6)
Alcohol consumption, n (%)	206 (40.7)	218 (43.2)	0.429
Family history of CAD, n (%)	32 (6.3)	19 (3.8)	0.063
Aspirin, n (%)	491 (97.0)	493 (97.6)	0.562
P2Y12 inhibitor, n (%)	476 (94.1)	459 (90.9)	0.055
β-blocker, n (%)	408 (80.6)	388 (76.8)	0.140
ACEI/ARB, n (%)	356 (70.4)	308 (61.0)	0.002
Statin, n (%)	499 (98.6)	495 (98.0)	0.461
ACS type, n (%)			<0.001
STEMI	181 (35.8)	69 (13.7)
NSTE-ACS	325 (64.2)	436 (86.3)
Multivessel disease, n (%)	335 (66.2)	338 (66.9)	0.807
Stent implantation, n (%)	318 (62.8)	260 (51.5)	<0.001
CABG, n (%)	22 (4.3)	37 (7.3)	0.043
LVEF (%)	60 (54, 65)	62 (58, 66)	<0.001
FPG (mmol/L)	6.2 (5.5, 8.1)	6.0 (5.3, 7.3)	0.014
HbA1c (%)	6.1 (5.6, 7.1)	6.1 (5.7, 7.1)	0.375
Hemoglobin (g/L)	147 (137, 158)	147 (138, 157)	0.823
Platelets (109/L)	215 (183, 251)	225 (186, 261)	0.054
Leukocytes (109/L)	8.6 (7.0, 10.6)	6.8 (5.8, 8.0)	<0.001
Neutrophils (109/L)	6.3 (5.0, 8.1)	4.0 (3.2, 4.8)	<0.001
Lymphocytes (109/L)	1.5 (1.2, 1.9)	2.2 (1.9, 2.7)	<0.001
Monocytes (109/L)	0.4 (0.3, 0.6)	0.4 (0.3, 0.5)	<0.001
Total cholesterol (mmol/L)	4.1 (3.5, 4.8)	4.2 (3.6, 5.0)	0.179
Triglyceride (mmol/L)	1.5 (1.1, 2.1)	1.6 (1.2, 2.4)	0.013
LDL-C (mmol/L)	2.4 (1.9, 3.1)	2.5 (2.0, 3.1)	0.675
HDL-C (mmol/L)	1.0 (0.9, 1.1)	1.0 (0.9, 1.1)	0.146
AST (IU/L)	28.5 (20, 70)	24 (19, 32)	<0.001
ALT (IU/L)	28 (19, 45)	26 (19, 38)	0.081
Creatinine (μmol/L)	75.6 (66.3, 85.9)	74.1 (64.9, 84.1)	0.135
eGFR (mL/min/1.73 m2)	102.1 (86.2, 118.5)	104.5 (89.9, 120.0)	0.284
High-sensitivity CRP	4.3 (1.4. 12.9)	1.8 (0.8, 4.5)	<0.001

NLR: neutrophil-to-lymphocyte ratio; BMI: body mass index; MI: myocardial infarction; PCI, percutaneous coronary intervention; CAD: coronary artery disease; ACEI/ARB: angiotensin-converting enzyme inhibitor/angiotensin receptor blocker; STEMI: ST-segment elevation myocardial infarction; NSTE-ACS, non-ST-segment elevation acute coronary syndrome; CABG: coronary artery bypass grafting; LVEF: left ventricular ejection fraction; FPG: fasting plasm glucose; HbA1c: glycosylated hemoglobin; LDL-C: low-density lipoprotein cholesterol; HDL-C: high-density lipoprotein cholesterol; AST: aspartate transaminase; ALT: alanine transaminase; eGFR: estimated glomerular filtration rate; CRP: C-reactive protein.

Notably, no significant differences between groups were observed in OSA parameters, comprising AHI, T90, minimum SaO₂, and mean SaO₂ (all P > 0.05) (Table 2).

Table 2

Sleep Breathing Monitoring Between Groups.

Variables	High NLR (n = 506)	Low NLR (n = 505)	P
AHI (events·h−1)	29.4 (21.3, 42.4)	28.7 (20.5, 42.0)	0.415
T90 (%)	6.0 (2.0, 16.0)	6.0 (2.0, 15.7)	0.651
Minimum SaO2 (%)	83 (78, 86)	82 (77, 86)	0.351
Mean SaO2 (%)	93 (92, 94)	93 (92, 94)	0.437

NLR: neutrophil-to-lymphocyte ratio; AHI: apnea-hypopnea index; T90: proportion of time with arterial oxygen saturation <90%; SaO₂: arterial oxygen saturation.

Outcome Analyses between the Low and High NLR Groups

During a median follow-up of 2.8 (interquartile range: 1.4, 3.6) years, 147 patients experienced recurrent MACE: 90 in the high NLR group and 57 in the low NLR group. Ischemia-driven revascularization (72.1%) and recurrent MI (22.4%) constituted most of the MACE. To investigate the relationship between NLR and the incident risk of events, we plotted cubic spline curves, which indicated that the risks of MACE (primary endpoint), recurrent MI, and ischemia-driven revascularization increased with NLR, and reached a plateau after a value of 5 (Figure 2).

Figure 2

Relationship Between the Neutrophil-to-Lymphocyte Ratio (NLR) and Clinical Outcomes. The blue curve with the blue area indicates the unadjusted hazard ratio with the 95% confidence interval for major adverse cardiovascular events (MACE) (A), recurrent myocardial infarction (B), and ischemia-driven revascularization (C).

Table 3 illustrates all relevant outcomes. Subsequently, we observed that patients with high NLR had a significantly greater crude incidence of MACE than patients with low NLR (17.8% vs. 11.3%, log rank P = 0.008, Table 3 and Figure 3A). Univariable Cox analyses further verified this difference (unadjusted HR = 1.56, 95% CI: 1.12–2.17, P = 0.009; Table 3 and Figure 3A). Moreover, after adjustment for clinically relevant confounders, including age, sex, BMI, hypertension, diabetes mellitus, hyperlipidemia, prior MI, prior stroke, ACS type, ACEI/ARB prescription, stent implantation, and multivessel disease, a high NLR still independently predicted the occurrence of MACE (adjusted HR = 1.45, 95% CI: 1.02–2.06, P = 0.040, Figure 3A and Table 3) during long-term follow-up.

Figure 3

Kaplan-Meier Curves for Study Endpoints According to The Neutrophil-to-Lymphocyte Ratio (NLR). A higher NLR was associated with greater incidence of major adverse cardiovascular events (MACE) (A) and ischemia-driven revascularization (B) in patients with acute coronary syndrome and obstructive sleep apnea.

Table 3

Cox proportional Hazard Model Analysis.

Clinical outcomes	High NLR (n, %)	Low NLR (n, %)	Unadjusted HR (95% CI)	P	Adjusted HR* (95% CI)	P
MACE	90 (17.8)	57 (11.3)	1.56 (1.12–2.17)	0.009	1.45 (1.02–2.06)	0.040
Composite of recurrent MI and ischemia-driven revascularization	66 (13.0)	40 (7.9)	1.63 (1.10–2.41)	0.015	1.49 (0.98–2.26)	0.061
Cardiovascular death	12 (2.4)	7 (1.4)	1.62 (0.64–4.13)	0.308	1.96 (0.73–5.31)	0.183
Recurrent MI	22 (4.3)	11 (2.2)	1.91 (0.93–3.94)	0.080	1.98 (0.92–4.27)	0.083
Stroke	14 (2.8)	11 (2.2)	1.21 (0.55–2.66)	0.639	1.07 (0.45–2.52)	0.881
Ischemia-driven revascularization	57 (11.3)	36 (7.1)	1.56 (1.02–2.36)	0.039	1.40 (0.90–2.18)	0.137
All revascularization	78 (15.4)	50 (9.9)	1.56 (1.09–2.22)	0.015	1.32 (0.90–1.92)	0.155
All-cause death	13 (2.6)	10 (2.0)	1.23 (0.54–2.80)	0.624	1.37 (0.57–3.30)	0.490

*Adjusted for age, sex, BMI, hypertension, diabetes mellitus, hyperlipidemia, prior MI, prior stroke, ACS types, ACEI/ARB prescription, stent implantation, and multivessel disease. NLR: neutrophil-to-lymphocyte ratio; HR: hazard ratio; CI: confidence interval; MACE: major adverse cardiovascular event; MI: myocardial infarction.

However, in analyses of secondary endpoints, a high NLR was nominally associated with ischemia-driven revascularization (unadjusted HR = 1.56, 95% CI: 1.02–2.36, P = 0.039; adjusted HR = 1.40, 95% CI: 0.90–1.92, P = 0.137), recurrent myocardial infarction (unadjusted HR = 1.91, 95% CI: 0.93–3.94, P = 0.080; adjusted HR = 1.98, 95% CI: 0.92–4.27, P = 0.083), and cardiovascular death (unadjusted HR = 1.62, 95% CI: 0.64–4.13, P = 0.308; adjusted HR = 1.96, 95% CI: 0.73–5.31, P = 0.183) (Table 3, and Figures 3 and S1). Although the association between NLR and every secondary endpoint was not statistically significant, relatively high HRs were notably observed.

Discussion

This study was aimed at investigating the influence of the NLR on the clinical outcomes of patients with ACS and OSA. The results suggested that in these patients, a high NLR was independently associated with elevated risk of the occurrence of MACE, despite comparable OSA severity between groups. The NLR may be used to stratify patients and identify those at elevated risk of poor prognosis, who might require more aggressive treatments.

Patients with OSA show elevated basal systemic inflammation, which plays a crucial and synergistic role in the development and progression of atherosclerosis [7, 28], owing to repeated episodes of hypoxemia and oxidative stress. Because atherosclerosis is the major cause of ischemic heart disease and ischemic stroke [29], patients with OSA have high incidence and prevalence of ischemic diseases, and OSA is an independent risk factor associated with such diseases and related mortality [30–32]. Therefore, evaluation of the inflammatory response in patients with OSA might help identify those at high risk of cardiovascular events.

The NLR is increasingly being used as a biomarker for managing various inflammation-associated diseases, such as CVD, cancer, and autoimmune diseases [33–36]. Kim et al. [37] and Sunbul et al. [21] have shown that the NLR can be used to predict OSA and its severity. The main advantage of the NLR is that its components are routinely available when a complete blood count is performed in all cardiovascular inpatients [38]. Furthermore, associations exist between the NLR and ACS. Indeed, patients with ACS have higher NLRs than those with stable CAD [15]. Moreover, lymphocyte-based inflammatory indices, including NLR, are independently associated with the occurrence of MACE in patients with ACS, with an HR of 1.77 (95%CI: 1.16–2.69, P = 0.008) for the NLR [19]. An earlier meta-analysis by Dong et al. [20] also supports that a higher NLR in patients with ACS is associated with a higher risk of death or MACE. Given the high prevalence of OSA in patients with ACS [39], those studies were likely to have included large numbers of patients with OSA. The value of NLR in these specific patients remains to be elucidated. However, in the present study of patients with OSA and ACS, we observed no significant differences in AHI, T90, minimum SaO₂, and mean SaO₂ between the low and high NLR groups (all P > 0.05). Given that OSA and ACS were both correlated with high NLR, we speculated that the concurrent presence of OSA and ACS might potentially exert a ceiling effect on this inflammatory biomarker. Although OSA severity did not distinguish patients with ACS with low vs. high NLR, high NLR was independently associated with the occurrence of MACE after adjustments for traditional CVD risk factors and treatments. Given that Kivanc et al. [40] have reported a lack of association between the NLR and the presence of CVD in patients with OSA, additional studies are necessary to examine the association between NLR and the prognosis of OSA and ACS.

Limitations

This study has several limitations. First, the patients were from a single center serving a limited geographical area, thus limiting the generalizability of the results. Because no reference value for the NLR is available, this study used the median NLR. Hence, the cutoff value might differ among studies and patient populations, thereby limiting the potential direct comparison among studies. In addition, only patients with ACS and OSA were enrolled, and no control groups were included. Finally, our study did not exclude patients with infections or autoimmune diseases, because the diagnosis and medical history from the original medical record did not include these diseases. Although these patients might represent only a small population, bias was inevitable.

Future Directions

Future studies must incorporate comprehensive angiographic and clinical data to evaluate the relationship between the severity of coronary plaques and NLR in patients with ACS and OSA. Moreover, a rigorously designed study with larger sample size, with exclusion of patients with infections and autoimmune diseases, is required to verify the prognostic value of NLR in patients with ACS and OSA, and to avoid underlying bias.

Conclusions

In current prospective cohort study in patients with ACS and OSA, the severity of OSA did not differ between patients with low vs. high NLR. However, a non-linear correlation between NLR and the risk of events was still observed, wherein the risk increased with NLR. Further outcome analyses demonstrated that high NLR was independently associated with the occurrence of MACE after adjustment for relevant clinical confounders in this population. Our study emphasizes that elevated NLR might be used to stratify patients with ACS and OSA at high risk of poor prognosis, who might require aggressive treatments.

Data Availability Statement

All individual patient data collected during the study will be shared. All available data can be obtained by contacting the corresponding author (Shaoping Nie, [e-mail]). A detailed protocol for the proposed study must be provided and approved by an ethics committee before a signed data access agreement is supplied, and discussions with the original authors are initiated for re-analysis.

Ethics Statement

This study protocol (NCT03362385) was complied with the principles of Declaration of Helsinki and was approved by the Ethics Committee of Beijing Anzhen Hospital, Capital Medical University (approval number: 2013025). All patients provided informed consent before participating in the study.

Author Contributions

S. Nie and W. Gong conceived the study. L. Zhen, X. Chen, X. Wang, S. Nie, and W. Gong designed the study. L. Zhen, X. Chen, and J. Fan contributed to the statistical analysis. L. Zhen and H. Ai interpreted the data. L. Zhen and X. Chen drafted the manuscript. S. Nie, W. Gong, and B. Que modified the manuscript. All authors critically read the manuscript and approved the final manuscript.

Competing Interests

All authors declare that they have no competing interests.

Citation Information

Download Citation.

Supplementary Materials

Supplementary Materials for this paper are available at the following links: https://cvia-journal.org/wp-content/uploads/2024/02/Supplementary-Figure-1-caption.pdf; https://cvia-journal.org/wp-content/uploads/2024/02/supplementary_figure.pdf; https://cvia-journal.org/wp-content/uploads/2024/02/Supplementary_Methods.pdf

References

1. VK Kapur, DH Auckley, S Chowdhuri, DC Kuhlmann, R Mehra, K Ramar, et al. Clinical practice guideline for diagnostic testing for adult obstructive sleep apnea: an American Academy of Sleep Medicine clinical practice guideline. J Clin Sleep Med 2017;13(3):479–504.

2. M Greenstone, M Hack. Obstructive sleep apnoea. BMJ 2014;348:g3745.

3. LJ Epstein, D Kristo, PJ Strollo Jr., N Friedman, A Malhotra, SP Patil, et al. Clinical guideline for the evaluation, management and long-term care of obstructive sleep apnea in adults. J Clin Sleep Med 2009;5(3):263–76.

4. AS Jordan, DG McSharry, A Malhotra. Adult obstructive sleep apnoea. Lancet 2014;383(9918):736–47.

5. CV Senaratna, JL Perret, CJ Lodge, AJ Lowe, BE Campbell, MC Matheson, et al. Prevalence of obstructive sleep apnea in the general population: a systematic review. Sleep Med Rev 2017;34:70–81.

6. Y Yeghiazarians, H Jneid, JR Tietjens, S Redline, DL Brown, N El-Sherif, et al. Obstructive sleep apnea and cardiovascular disease: a scientific statement from the American Heart Association. Circulation 2021;144(3):e56–67.

7. S Ryan. Mechanisms of cardiovascular disease in obstructive sleep apnoea. J Thorac Dis 2018;10(Suppl 34):S4201–11.

8. X Wang, J Fan, R Guo, W Hao, W Gong, Y Yan, et al. Association of obstructive sleep apnoea with cardiovascular events in women and men with acute coronary syndrome. Eur Respir J 2023;61(1):2201110.

9. W Randerath, MR Bonsignore, S Herkenrath. Obstructive sleep apnoea in acute coronary syndrome. Eur Respir Rev 2019;28(153):180114.

10. J Fan, X Wang, X Ma, VK Somers, S Nie, Y Wei. Association of obstructive sleep apnea with cardiovascular outcomes in patients with acute coronary syndrome. J Am Heart Assoc 2019;8(2):e010826.

11. M Sanchez-de-la-Torre, E Gracia-Lavedan, ID Benitez, A Zapater, G Torres, A Sanchez-de-la-Torre, et al. Long-term effect of obstructive sleep apnea and continuous positive airway pressure treatment on blood pressure in patients with acute coronary syndrome: a clinical trial. Ann Am Thorac Soc 2022;19(10):1750–9.

12. V Lubrano, S Balzan. Consolidated and emerging inflammatory markers in coronary artery disease. World J Exp Med. 2015;5(1):21–32.

13. EA Dziedzic, JS Gasior, A Tuzimek, W Kochman. Blood count-derived inflammatory markers and acute complications of ischemic heart disease in elderly women. J Clin Med 2023;12(4):1369.

14. XY Yu, XS Li, Y Li, T Liu, RT Wang. Neutrophil-lymphocyte ratio is associated with arterial stiffness in postmenopausal women with osteoporosis. Arch Gerontol Geriatr 2015;61(1):76–80.

15. EA Dziedzic, JS Gasior, A Tuzimek, M Dabrowski, P Jankowski. Neutrophil-to-lymphocyte ratio is not associated with severity of coronary artery disease and is not correlated with vitamin D level in patients with a history of an acute coronary syndrome. Biology (Basel) 2022;11(7):1001.

16. Z Fan, H Ji, Y Li, X Jian, L Li, T Liu. Relationship between monocyte-to-lymphocyte ratio and coronary plaque vulnerability in patients with stable angina. Biomark Med 2017;11(11):979–90.

17. AH Ates, K Aytemir, D Kocyigit, MU Yalcin, KM Gurses, H Yorgun, et al. Association of neutrophil-to-lymphocyte ratio with the severity and morphology of coronary atherosclerotic plaques detected by multidetector computerized tomography. Acta Cardiol Sin 2016;32(6):676–83.

18. S Balta, C Ozturk. The platelet-lymphocyte ratio: a simple, inexpensive and rapid prognostic marker for cardiovascular events. Platelets 2015;26(7):680–1.

19. Q Li, X Ma, Q Shao, Z Yang, Y Wang, F Gao, et al. Prognostic impact of multiple lymphocyte-based inflammatory indices in acute coronary syndrome patients. Front Cardiovasc Med 2022;9:811790.

20. CH Dong, ZM Wang, SY Chen. Neutrophil to lymphocyte ratio predict mortality and major adverse cardiac events in acute coronary syndrome: a systematic review and meta-analysis. Clin Biochem 2018;52:131–6.

21. M Sunbul, EA Sunbul, B Kanar, O Yanartas, S Aydin, A Bacak, et al. The association of neutrophil to lymphocyte ratio with presence and severity of obstructive sleep apnea. Bratisl Lek Listy. 2015;116(11):654–8.

22. MS Rha, CH Kim, JH Yoon, HJ Cho. Association between the neutrophil-to-lymphocyte ratio and obstructive sleep apnea: a meta-analysis. Sci Rep 2020;10(1):10862.

23. S Shetty, S Chandrashekhar, SK Chaya, A Surendran, D Dey. Role of neutrophil to lymphocyte ratio in predicting severity of obstructive sleep apnea. Indian J Otolaryngol Head Neck Surg. 2022;74(Suppl 3):5003–7.

24. MJ Sateia. International classification of sleep disorders-third edition: highlights and modifications. Chest 2014;146(5):1387–94.

25. CR Laratta, NT Ayas, M Povitz, SR Pendharkar. Diagnosis and treatment of obstructive sleep apnea in adults. CMAJ 2017;189(48):E1481–E8.

26. MA Martinez-Garcia, M Sanchez-de-la-Torre, DP White, A Azarbarzin. Hypoxic burden in obstructive sleep apnea: present and future. Arch Bronconeumol 2023;59(1):36–43.

27. JL Ethier, D Desautels, A Templeton, PS Shah, E Amir. Prognostic role of neutrophil-to-lymphocyte ratio in breast cancer: a systematic review and meta-analysis. Breast Cancer Res 2017;19(1):2.

28. JR Tietjens, D Claman, EJ Kezirian, T De Marco, A Mirzayan, B Sadroonri, et al. Obstructive sleep apnea in cardiovascular disease: a review of the literature and proposed multidisciplinary clinical management strategy. J Am Heart Assoc 2019;8(1):e010440.

29. W Herrington, B Lacey, P Sherliker, J Armitage, S Lewington. Epidemiology of atherosclerosis and the potential to reduce the Global Burden of Atherothrombotic Disease. Circ Res 2016;118(4):535–46.

30. RN Aurora, SP Patil, NM Punjabi. Portable sleep monitoring for diagnosing sleep apnea in hospitalized patients with heart failure. Chest 2018;154(1):91–8.

31. CLA Bassetti, W Randerath, L Vignatelli, L Ferini-Strambi, AK Brill, MR Bonsignore, et al. EAN/ERS/ESO/ESRS statement on the impact of sleep disorders on risk and outcome of stroke. Eur Respir J 2020;55(4):1901104.

32. S Javaheri, Y Peker, HK Yaggi, CLA Bassetti. Obstructive sleep apnea and stroke: the mechanisms, the randomized trials, and the road ahead. Sleep Med Rev 2022;61:101568.

33. Y Chen, W Wang, L Zeng, K Mi, N Li, J Shi, et al. Association between neutrophil-lymphocyte ratio and all-cause mortality and cause-specific mortality in US adults, 1999-2014. Int J Gen Med 2021;14:10203–11.

34. A Buonacera, B Stancanelli, M Colaci, L Malatino. Neutrophil to lymphocyte ratio: an emerging marker of the relationships between the immune system and diseases. Int J Mol Sci 2022;23(7):3636.

35. T Angkananard, T Anothaisintawee, M McEvoy, J Attia, A Thakkinstian. Neutrophil lymphocyte ratio and cardiovascular disease risk: a systematic review and meta-analysis. Biomed Res Int 2018;2018:2703518.

36. MA Cupp, M Cariolou, I Tzoulaki, D Aune, E Evangelou, AJ Berlanga-Taylor. Neutrophil to lymphocyte ratio and cancer prognosis: an umbrella review of systematic reviews and meta-analyses of observational studies. BMC Med 2020;18(1):360.

37. M Kim, SW Cho, TB Won, CS Rhee, JW Kim. Associations between systemic inflammatory markers based on blood cells and polysomnographic factors in obstructive sleep apnea. Clin Exp Otorhinolaryngol 2023;16(2):159–64.

38. IH Seo, YJ Lee. Usefulness of complete blood count (CBC) to assess cardiovascular and metabolic diseases in clinical settings: a comprehensive literature review. Biomedicines 2022;10(11):2697.

39. MR Le Grande, A Beauchamp, A Driscoll, AC Jackson. Prevalence of obstructive sleep apnoea in acute coronary syndrome patients: systematic review and meta-analysis. BMC Cardiovasc Disord. 2020;20(1):147.

40. T Kivanc, S Kulaksizoglu, H Lakadamyali, F Eyuboglu. Importance of laboratory parameters in patients with obstructive sleep apnea and their relationship with cardiovascular diseases. J Clin Lab Anal 2018;32(1):e22199.