Prognostic Value of the Systemic Inflammatory Response Index in Patients with Acute Coronary Syndrome and Obstructive Sleep Apnea

Introduction

Obstructive sleep apnea (OSA) is a widespread sleep disorder that affects nearly 1 billion adults worldwide.¹ OSA is characterized by recurrent episodes of complete or partial upper airway collapse (apneas or hypopneas), resulting in the exposure of the cardiovascular system to cycles of hypoxia, excessive negative intrathoracic pressure, or sleep arousal.^2,3 In patients with acute coronary syndrome (ACS), the prevalence of OSA is as high as 36–68%.^4–6 Growing evidence, including our previous study, indicates that OSA worsens the prognosis in patients with ACS.^6–8

OSA can induce or exacerbate cardiovascular comorbidities, including ACS, through mechanisms such as intermittent hypoxia, oxidative stress, and systemic inflammation, with systemic inflammation being particularly significant. Increasing evidence suggests that intermittent hypoxia plays a role in the pathophysiology of cardiovascular complications in OSA by activating proinflammatory pathways.⁹ However, while the cause of coronary vessel disease (CVD) in OSA via the inflammatory pathway seems plausible and convincing in terms of basic science research, clinical trials are not as convincing.¹⁰ Therefore, there is a need to explore the impact of inflammation in patients with OSA combined with ACS in large prospective cohort studies.

Peripheral blood inflammatory cell counts and their derived indicators, such as the neutrophil-to-lymphocyte ratio (NLR), monocyte-to-lymphocyte ratio (MLR), and platelet-to-lymphocyte ratio (PLR), can reflect the systemic inflammatory response status within the body and are now widely used in clinical practice. These indicators have been demonstrated to effectively predict the prognosis of CVD.^11–13 The systemic inflammatory response index (SIRI) is a novel composite indicator first developed in 2016 to predict survival in patients with pancreatic adenocarcinoma after chemotherapy.¹⁴ Since its introduction, SIRI has been established as a prognostic marker in patients with malignancies.^15,16 In recent years, the diagnostic performance of the SIRI has been investigated in many diseases. For example, SIRI was found to be associated with CVD occurrence¹⁷ and identified as an independent predictor of OSA severity.¹⁸ Furthermore, SIRI has been widely considered for disease diagnosis and prognostic evaluation in recent years.^19–21 Although the pathophysiological processes of the inflammatory response have been demonstrated in both ACS and OSA, it remains unclear whether SIRI is an independent risk factor for poor prognosis in patients with both conditions. Therefore, in this prospective cohort study, we investigated the long-term prognostic value of SIRI in patients with ACS and OSA.

Methods

Study Design and Participants

This study was a substudy of the OSA-ACS project (NCT 03362385), the specific research methods of which have been previously reported.^6,7,22,23 From June 2015 to January 2020, consecutive patients with ACS were recruited from Beijing Anzhen Hospital. Inclusion criteria were as follows: adults aged 18–85 with a confirmed ACS diagnosis, including ST-segment elevation myocardial infarction (STEMI), non-ST-segment elevation myocardial infarction (NSTEMI), unstable angina (UA),²⁴ as well as a diagnosis of OSA.²⁵ Eligible patients were required to provide informed consent. Exclusion criteria included cardiac arrest or cardiogenic shock, a history of malignancy, failed sleep monitoring, central sleep apnea, prior or ongoing continuous positive airway pressure (CPAP) treatment, or discharge from the hospital with CPAP therapy. Patients without comprehensive SIRI data were also excluded.

This study followed the Helsinki Declaration’s recommendations and gained approval from Beijing Anzhen Hospital’s Ethics Committee (No. 2013025), and written informed consent was obtained from participants.

Sleep Study and Management

Once clinically stable during their hospital stay, participants underwent an overnight sleep study using a portable cardiorespiratory polygraphy device (ApneaLink Air; ResMed). Trained research staff, blinded to clinical details, conducted these studies adhering to the American Academy of Sleep Medicine.²⁶ Monitored signals encompassed nasal airflow, chest and abdominal movements, snoring episodes, heart rate, and oxygen saturation (SaO₂). Apnea was classified by an airflow cessation ≥ 10 seconds (distinguished as obstructive or central based on chest and abdominal movements). Hypopnea was identified by a ≥ 10-second airflow decrease of ≥ 30% coupled with a >4% SaO₂ drop. The AHI was calculated by dividing the total number of apneas and hypopneas by sleep hours.^25,27

Laboratory Measurements

Blood samples for complete blood count analysis were obtained from venous blood draws within 24 hours of hospital admission as part of routine clinical care. The timing of blood collection followed standard clinical protocols for ACS management at our institution, typically occurring before revascularization procedures, to minimize confounding effects of acute interventions on inflammatory biomarkers, and were measured in the Clinical Laboratory of Beijing Anzhen Hospital, using an Automated Hemocytometer (LH 570, Beckman Coulter), which we obtained from medical records.

Siri

SIRI was defined as neutrophils × monocytes/lymphocytes.¹⁴ Optimal SIRI thresholds for major adverse cardiovascular and cerebrovascular events (MACCE) were calculated using receiver operating characteristic (ROC) analysis. The Youden index, which combines sensitivity and specificity, aided in selecting a SIRI threshold. Our cohort’s ROC analysis identified an optimal SIRI cutoff of 1.16 × 10⁹/L, dividing patients into low and high SIRI groups. (Supplementary Figure 1).

Endpoints and Follow-Up

Patients were closely monitored after discharge through regular follow-up appointments at specified intervals. Any clinical adverse events were documented by an impartial committee unaware of the patients’ medical history and sleep study findings through outpatient visits or telephone follow-ups.

The main focus of the study was the occurrence of major adverse cardiac and cerebrovascular events (MACCE), which include cardiovascular death, myocardial infarction (MI), stroke, and ischemia-driven revascularization. Secondary endpoints included individual components of MACCE. Criteria for these endpoints were established according to standardized definitions outlined by the Cardiovascular Trials Standardized Data Collection Initiative.²⁸

Statistical Analysis

Quantitative data were expressed as mean ± standard deviation (SD) or median (first and third quartiles) and were examined using Student’s t-test or Mann–Whitney U-test. Qualitative data were displayed as percentages (%) and were analyzed using χ² statistics or Fisher’s exact test. A ROC curve analysis was conducted to establish the cutoff value for SIRI in predicting MACCE, with the area under the ROC curve being calculated. SIRI was then assessed as a categorical variable. The cumulative incidence rates for primary and secondary endpoints were illustrated through Kaplan–Meier curves, with differences between curves evaluated using the Log rank test. Furthermore, Cox proportional hazard analyses were performed using four models to identify independent risk factors by determining hazard ratios (HR) and 95% confidence intervals (CI). Subgroup analyses were carried out based on age, sex, hypertension, diabetes, dyslipidemia, and ACS type. Additionally, a restricted cubic spline (RCS) curve with four knots was employed to demonstrate the potential nonlinear relationship between SIRI as a continuous variable and the risk of clinical outcomes. We also assessed the correlation between SIRI and High sensitivity C-reactive protein (Hs-CRP) using Spearman’s rank correlation coefficient. The prognostic performance of SIRI and Hs-CRP was compared through receiver operating characteristic (ROC) curve analysis with DeLong’s test for statistical significance.

All statistical analyses were conducted using IBM SPSS 27 and R version 4.3.3. Significance was determined at P < 0.05 for two-sided tests.

Results

Demographic and Clinical Characteristics

A total of 1011 patients were included in the final analysis, with 435 (43%) classified into the high SIRI group (Figure 1). Compared to those with low SIRI, patients with high SIRI were more often male and had higher rates of hyperlipidemia, current smoking, MI, and percutaneous intervention (PCI). They also exhibited higher systolic blood pressure (BP), neutrophil and monocyte counts, Hs-CRP levels, and lower LVEF and lymphocyte counts. The poorer health status in the high SIRI group may explain their worse prognosis. As for medications on discharge, these patients were more frequently prescribed P2Y₁₂ inhibitors, β-blockers, and angiotensin-converting enzyme inhibitors (ACEIs)/angiotensin receptor blockers (ARBs). Other characteristics were generally well-matched in both the low and high SIRI groups (Table 1).

Table 1 Demographic and Clinical Characteristics by SIRI Categories

Figure 1 Study flowchart.

No significant differences were observed between the two groups in terms of OSA parameters, including AHI, minimum and mean SaO₂, T 90, and the Epworth Sleep Scale (ESS) scores (all P > 0.05) (Table 2).

Table 2 Overnight Sleep Monitoring Results Stratified by SIRI

Outcome Analyses Between Low and High SIRI Groups

During a median follow-up of 2.8 years (1.5, 3.6), 179 patients experienced MACCE, with the incidence of MACCE being higher in the high SIRI group (23.2% vs 13.5%). In unadjusted analyses, the high-SIRI group demonstrated significantly elevated risks of recurrent MI (HR=1.72, 95% CI 1.09–2.71; P=0.02) and ischemia-driven revascularization (HR=2.07, 95% CI 1.31–3.27; P=0.002). While trends toward increased cardiovascular death (HR=1.56, 95% CI 0.86–2.83; P=0.14) and stroke (HR=1.32, 95% CI 0.67–2.62; P=0.42) were observed, these associations did not reach statistical significance. Kaplan–Meier survival analysis showed a higher cumulative incidence of MACCE in the high-SIRI group (log-rank P < 0.001) (Table 3 and Figure 2A). Considering the components of MACCE, patients with a higher SIRI had a higher cumulative incidence of recurrent MI (log-rank P = 0.02) (Table 3 and Figure 2B) and ischemia-driven revascularization (log-rank P = 0.002) (Table 3 and Figure 2C), However, there was no statistically significant difference between the two groups in terms of cardiovascular death (log-rank P = 0.116) (Table 3 and Figure 2D) and stroke (log-rank P = 0.889) (Table 3 and Figure 2E) events. Univariate Cox regression analysis further verified these associations. After adjusting for clinically relevant confounders such as age, sex, BMI, smoking status, hypertension, diabetes, dyslipidemia, prior MI and PCI, ACS type, hs-CRP, low-density lipoprotein cholesterol (LDL-C), high-density lipoprotein cholesterol (HDL-C), total cholesterol (TC), and triglyceride (TG), a high SIRI still independently predicted the occurrence of MACCE (adjusted HR = 1.44, 95% CI: 1.02–2.05, P = 0.039) and ischemia-driven revascularization (adjusted HR = 1.55, 95% CI: 1.03–2.33, P = 0.034) (Table 4). Based on univariate analysis, the RCS with four knots revealed that SIRI as a continuous variable was positively associated with MACCE (Figure 3).

Table 3 Kaplan-Meier Analysis for Clinical Outcomes According to SIRI Categories

Table 4 Cox Regression Analysis for Clinical Outcomes According to SIRI Categories During Follow-up

Figure 2 Kaplan-Meier curves in SIRI categories for (A) MACCE, and (B) Ischemia-driven revascularization, and (C) Recurrent MI, and (D) Cardiovascular death, and (E) Stroke. Abbreviations: SIRI, systemic inflammatory response index; MACCE, major adverse cardiovascular and cerebrovascular event; MI, myocardial infarction.

Figure 3 The association between SIRI and MACCE by unadjusted restricted cubic splines. Abbreviations: SIRI, systemic inflammatory response index; MACCE, major adverse cardiovascular and cerebrovascular event.

Sensitivity Analyses

In patients with an ODI ≥ 15, the high SIRI group had a significantly higher risk of MACCE (HR = 1.64, 95% CI: 1.2–2.25, P = 0.002). Similar associations were observed for nocturnal hypoxemia indicators, such as minimum SaO₂ < the median (HR = 2.12, 95% CI: 1.34–3.34, P = 0.001) and mean SaO₂ < the median (HR = 2.28, 95% CI: 1.34–3.87, P = 0.002). No such associations were found in patients with ODI < 15, minimum SaO₂ > the median, and mean SaO₂ > the median (Figure 4).

Figure 4 Forest plot for MACCE in Low SIRI group versus High SIRI group stratified by other OSA-related characteristics. Abbreviations: SIRI, systemic inflammatory response index; MACCE, major adverse cardiovascular and cerebrovascular event; ODI, oxygen desaturation index; SaO2, arterial oxygen saturation.

Subgroup Analyses

Subgroup analyses according to sex, age, hypertension, diabetes, dyslipidemia, and ACS type revealed no significant association between SIRI and MACCE in female patients or patients presenting with diabetes, STEMI, and NSTEACS, or those without hypertension and dyslipidemia (Figure 5).

Figure 5 Subgroup analyses for MACCE in the Low SIRI group versus the High SIRI group. Abbreviation: SIRI, systemic inflammatory response index.

Biomarker Performance Between SIRI and Hs-CRP

Spearman’s test revealed a moderate positive correlation between SIRI and Hs-CRP (r=0.42, P<0.001), indicating partial overlap yet distinct biological information (Supplementary Table 1 and Supplementary Figure 2). While SIRI and Hs-CRP showed comparable discriminative capacity for MACCE (AUC 0.59 vs 0.56, respectively) (Supplementary Table 2 and Supplementary Figure 3). SIRI’s unique composition reflects distinct pathophysiological processes: neutrophil-monocyte axis activation from OSA-related hypoxia coupled with lymphocyte depletion from ACS-induced stress responses. This integrative profile enables SIRI to bridge OSA-driven inflammation with ACS prognosis more effectively than acute-phase reactants.

Discussion

This study explored the effects of SIRI on clinical outcomes in patients with ACS and OSA. In these patients, a high SIRI was found to be independently associated with an increased risk of MACCE, even though OSA severity was similar across the patient groups.

Cumulative epidemiological evidence suggests that the prevalence of OSA increases the risk of cardiovascular mortality or morbidity.^18,29 More and more evidence indicates that OSA is associated with the pathogenesis and prognosis of ACS.^30,31 OSA may result in oxidative stress and systemic inflammation, which contribute to coronary atherosclerosis.³ Despite a great deal of effort up front, the pathophysiologic mechanisms between OSA and ACS remain unclear. Previous findings emphasize that systemic inflammatory cascade might play an important role in the cardiovascular effects of OSA,³² but clinical trials remain controversial. Therefore, evaluating the inflammatory response status of OSA combined with ACS patients in a large cohort study may help explain the relationship between systemic inflammation and patients with OSA combined with ACS.

Various inflammatory markers, such as hs-CRP, neutrophil count, and monocyte count, are associated with the prognosis of coronary heart disease. However, a single inflammatory marker is insufficient to predict the severity of inflammation. Although the NLR effectively identifies patients at higher risk for poor outcomes,^33–35 as the fundamental component of non-specific immunity, the roles of monocytes and macrophages must also be considered. SIRI, which incorporates neutrophils, monocytes, and lymphocytes as the three inflammatory biomarkers, represents an integrated indicator that reflects the status of systemic inflammation and immune response and stands out as a comprehensive, easily obtainable, and cost-effective marker of chronic low-grade inflammation. Li et al³⁶ evaluated the prognostic values of five lymphocyte-based inflammatory indices—PLR, NLR, MLR, systemic immune inflammation index (SII), and SIRI—in patients with ACS and found that lymphocyte-based inflammatory indices were significantly and independently associated with MACCE in patients with ACS who underwent PCI. SIRI outperformed the other four indices in predicting MACCE. Zhao et al²⁰ investigated the value of preoperative inflammatory biomarkers in predicting aorta-related adverse events (AAEs) after thoracic endovascular aortic repair (TEVAR) for type B aortic dissection and found that increased preoperative SIRI was an independent risk factor for AAEs after TEVAR. Intermittent hypoxia in OSA triggers systemic inflammation through the activation of pro-inflammatory cytokines and oxidative stress, which contribute to endothelial dysfunction and atherosclerotic plaque instability.^9,32 These mechanisms may explain the increased cardiovascular risk in OSA patients. Notably, our study provides novel evidence supporting this inflammatory paradigm. Despite similar OSA severity (AHI, SaO₂) between high- and low-SIRI groups, elevated SIRI (≥1.16×10⁹/L) independently predicted MACCE (adjusted HR=1.44, P=0.039), with heightened risk in patients experiencing significant nocturnal hypoxemia (ODI≥15: HR=1.64, P=0.002). This dissociation suggests that SIRI—a composite marker integrating neutrophils, monocytes, and lymphocytes—may more sensitively capture OSA-driven systemic inflammation than conventional metrics like AHI, thereby serving as a prognostic bridge between OSA and adverse cardiovascular outcomes.

In ACS patients without OSA, reported SIRI thresholds range widely (1.5–2.848×10⁹/L). For example, Han et al found that SIRI ≥1.7×10⁹/L predicted increased MACCE risk in ACS patients undergoing PCI. A similar result was reported in another cohort, and the SIRI threshold was 2.848×10⁹/L.³⁷ Our observed lower threshold (1.16×10⁹/L) in ACS-OSA patients suggests that OSA-induced chronic low-grade inflammation and immune dysregulation further modify prognostic thresholds. This may arise from OSA-driven intermittent hypoxia, which promotes neutrophil activation and monocyte polarization, exacerbating coronary plaque instability even at lower SIRI values.

The role of SIRI in diagnosing malignant diseases has been extensively studied, and its diagnostic performance has also been studied in many diseases characterized by inflammation. SIRI has been positively associated with the risk and poor prognosis of ischemic stroke.^19,38 SIRI can identify patients with ACS at high risk of MACCE²¹ and is an independent predictor of 30-day and 90-day mortality in patients with acute myocardial infarction (AMI).³⁹ In this study, we found that a higher SIRI was associated with poor clinical presentation, including higher rates of hyperlipidemia, current smoking, MI, and PCI. Patients with a high SIRI also had higher neutrophil and monocyte counts and Hs-CRP levels but lower LVEF and lymphocyte counts, indicating more severe low-grade inflammation.

In this study, we compared the biomarker performance between SIRI and the classic inflammatory index Hs-CRP, While the discriminative capacity of SIRI for MACCE did not statistically surpass Hs-CRP in either the overall cohort (AUC 0.59 vs 0.55, P=0.15) or severe OSA subgroup (AUC 0.61 vs 0.58, P=0.21), its novel composite formula (neutrophil × monocyte/lymphocyte) provides unique pathophysiological insights into OSA-ACS comorbidity. Unlike Hs-CRP – a downstream marker of IL-6-mediated hepatic responses⁴⁰ – SIRI directly quantifies three cellular processes amplified by chronic intermittent hypoxia (CIH): (1) neutrophil activation via HIF-1α-driven NETosis that destabilizes plaques through histone release,⁴¹ (2) monocyte polarization toward pro-inflammatory CD14++CD16+ subsets secreting MMP-9,⁴² and (3) lymphocyte depletion via Fas/FasL-mediated apoptosis, reducing plaque-stabilizing Tregs.⁴³ This triad captures hypoxia-adapted immune dysregulation more precisely than acute-phase reactants. Clinically, SIRI’s rapid component turnover (neutrophils: 6–8 hr⁴⁴ vs Hs-CRP half-life 19 hr⁴⁵) may better track nocturnal hypoxemia-induced inflammatory bursts. Importantly, SIRI’s cellular targets align with emerging therapies – DNase I for NET degradation,⁴⁶ CCR2 inhibitors for monocyte recruitment blockade,⁴⁷ and IL-7 for lymphocyte reconstitution⁴⁸ – offering a mechanistically grounded stratification tool beyond pure prognostic prediction. Thus, even in the absence of superior discriminative performance, SIRI advances our understanding of OSA-driven vascular inflammation through its cell-specific resolution.

While SIRI can predict the severity of OSA and ACS, this study found no significant differences in AHI, T90, minimum SaO₂, mean SaO₂, or ESS (all P > 0.05) between the low- and high-SIRI groups. Although the severity of OSA could not be distinguished in patients with ACS having low and high SIRI, after adjusting for traditional CVD risk factors and inflammatory factors, a high SIRI remained independently associated with the occurrence of MACCE. Further research is needed to clarify the value of SIRI in these patients and explore its impact on the prognosis of patients with OSA and ACS.

Limitation

This study has certain limitations. First, it was a single-center cohort study, and potential confounders may not have been fully accounted for. Second, the diagnosis of OSA relied on portable polygraphy, which could underestimate the AHI by overestimating actual sleep time. Third, the dataset lacked information regarding formal follow-up visits at sleep centers and OSA treatment adherence after hospital discharge, preventing evaluation of the impact of OSA treatment on MACCE. Fourth, We recruited patients over a wide range of periods, and we cannot rule out the influence of seasonal fluctuations on the results of blood draws. Fifth, our study did not exclude patients with infections or recent glucocorticosteroid therapies since the original medical records lacked corresponding diagnoses and medical histories. While these patients likely constitute a minority of the population, this unavoidable selection bias should be acknowledged.Finally, this study was conducted using a prospective cohort design, which may have resulted in an overestimation of the extent of the association between exposure and outcome compared to the results of randomized controlled trials.

Conclusion

In this prospective cohort study, elevated SIRI independently predicted major adverse cardiovascular events in ACS and OSA. As a composite biomarker integrating neutrophil activation, monocyte-driven inflammation, and lymphocyte exhaustion, SIRI uniquely bridges OSA-induced systemic inflammation with coronary plaque vulnerability, outperforming traditional OSA severity metrics like apnea-hypopnea index. Future studies should explore whether SIRI-guided interventions improve cardiovascular outcomes in this high-risk population.