European Journal of Cardiovascular Medicine

India bears a substantial burden of cardiovascular disease (CVD) on a global scale. Over the past decades, there have been assessments of the prevalence of coronary heart disease in India, ranging from 1.6% to 7.4% in rural areas and 1% to 13.2% in urban areas [1,2]. A key contributor to coronary artery disease (CAD) is the narrowing of coronary arteries caused by atherosclerosis. The clinical manifestation of CAD is influenced by the characteristics of atherosclerosis, with vulnerable or unstable plaques linked to atherothrombotic events defining Acute Coronary Syndrome (ACS), while stable plaques, characterized by a thick fibrous cap and poor-lipid core, present as Stable Coronary Artery Disease (SCAD) [3,4].

Rapid coronary revascularization is beneficial for ACS patients in reducing adverse events or mortality. Hence, early detection of ACS is crucial, considering that ACS patients face mortality rates up to seven times higher than those with SCAD. However, the limited availability of electrocardiograms (ECGs) and cardiac markers in primary care settings poses a significant challenge for physicians in developing countries when diagnosing ACS. A study found that ECG availability in rural primary care settings was only 63.3% [5-8]. Therefore, there is an urgent need for a simple and accessible screening method to aid in ACS diagnosis in primary care settings.

The pathogenesis of atherosclerosis is closely tied to inflammatory and hematologic responses, with various inflammatory substances and hematologic cells contributing to atherosclerotic lesion development [9-11]. Leukocytes and platelets play crucial roles in processes like foam cell generation, cytokine secretion (including Reactive Oxygen Species [ROS]), and cardiomyocyte death, all contributing to atherosclerosis progression. In ACS, the lesions exhibit an acute condition and activate neutrophils as proinflammatory cells, followed by inflammation regulation by anti-inflammatory cells like lymphocytes. Platelets also contribute to ACS by inducing higher inflammatory activity and thrombogenicity [12-14]. In contrast, lesions in SCAD show chronic and lower-grade inflammation compared to ACS. Studies have shown significantly higher white blood cell count and inflammatory markers in the ACS group compared to SCAD [9-11], though the comparison of other hematologic indices between ACS and SCAD remains to be explored.

Hence, this study aims to compare hematologic indices between ACS and SCAD patients and evaluate their predictive value in distinguishing ACS.

This retrospective cross-sectional investigation included all medical records of patients diagnosed with Acute Coronary Syndrome (ACS) or Stable Coronary Artery Disease (SCAD). Exclusion criteria comprised patients with renal and hepatic abnormalities, ongoing infections, cancer, hematologic malignancies, individuals undergoing corticosteroid treatment, and those receiving chemotherapy. Measures were taken to ensure privacy and confidentiality, as the data lacked personal patient identifiers. Data encompassing age, gender, coronary artery disease type (ACS or SCAD), erythrocyte indices (Mean Corpuscular Hemoglobin Concentration [MCHC], Hemoglobin [Hgb], Hematocrit [Hct]), leukocyte indices (White Blood Cell count [WBC], Neutrophil Percentage, Lymphocyte Percentage), and platelet indices (Mean Platelet Volume [MPV], Platelet Count [PLT]) were extracted from medical records.

ACS diagnosis was defined by ICD-10 codes I20.0 for Unstable Angina Pectoris (UAP), I21.0 and I21.1 for ST-Elevation Myocardial Infarction (STEMI), and I21.4 for Non-ST-Elevation Myocardial Infarction (NSTEMI). SCAD diagnosis was defined by ICD-10 code I25.0 without a history of ACS or myocardial infarction. To assess inflammatory markers, the Neutrophil-to-Lymphocyte Ratio (NLR) was computed by dividing Neutrophil Percentage by Lymphocyte Percentage. Additionally, the Platelet-to-Lymphocyte Ratio (PLR) was calculated by dividing PLT by the product of Lymphocyte Percentage and WBC.

Statistical analyses were performed using SPSS Statistics 21.0. Continuous variables, presented as mean ± SD, were compared using Independent T-test or Mann-Whitney test based on normality assessment. Specificity and sensitivity were derived from the ROC curve, with cut-off point analysis utilized to evaluate diagnostic efficacy.

Table 1: Demographic variables of study population

Table 2: Comparison of Hematological indices among ACS and SCAD cases

Table 3: ROC analysis and cut-off values for different hematological indices

Figure 1: Sensitivity and Specificity of different hematological indices

This study compared hematological indices between ACS and SCAD patients. The baseline characteristics of both ACS and SCAD groups are similar, with mostly male participants and a majority aged under sixty. This finding is in line with a previous study in Indonesia. Southeast Asian countries like India show a trend of younger morbidity and mortality due to noncommunicable diseases, especially cardiovascular diseases, compared to regions like Europe. This variation is likely due to the swift epidemiological transition seen in Southeast Asia [15,16].

According to our findings, the MCHC value was notably higher in the ACS group, consistent with prior research showing elevated MCHC values in CAD patients compared to healthy individuals. However, there are discrepancies in the literature, as one study reported lower MCHC in acute myocardial infarction patients compared to SCAD patients, though not reaching statistical significance. Current theories suggest a complex relationship involving inflammation, iron metabolism, and anemia impacting MCHC values. Inflammation tends to lower iron serum levels, potentially leading to iron-deficiency anemia and reduced MCHC values. Our study proposes that the heightened inflammation in ACS triggers oxidative stress, causing hemolysis and an increase in MCHC values. Oxidative stress can impair erythrocyte metabolism and induce hemolysis, leading to increased hemoglobin production and subsequently elevated MCHC values, which represent the hemoglobin-to-hematocrit ratio [17-19].

The findings regarding WBC levels are consistent with previous studies, showing that ACS patients have significantly higher WBC counts compared to SCAD patients [10,11]. In our study, the WBC count for ACS was higher, possibly due to a larger proportion of STEMI patients compared to previous studies focused on Unstable Angina [11]. The elevation in WBC is intricately linked to the complex inflammatory response at local and systemic levels. Leukocytes play a crucial role in atherosclerotic lesion development and progression. Early-stage lesions, endothelial dysfunction, and foam cell production are associated with leukocyte activities. These activities also impact plaque stability, with ongoing activation and infiltration of neutrophils contributing to plaque instability through MPO and MMPs release. Myocardial damage from atherosclerosis can further increase neutrophil and macrophage numbers via cytokine and chemokine stimulation [20].

Previous studies consistently show that ACS patients typically have higher MPV compared to SCAD patients. Elevated MPV is linked to various cardiovascular risks and increased thrombogenicity due to platelet metabolic and enzymatic activities. However, our study revealed a contradictory finding, with ACS patients having significantly lower MPV than SCAD patients. This difference suggests a dynamic and intricate regulation of platelets during ACS, involving both platelet production and consumption. Inflammation typically leads to larger platelet production, but in ACS's atherothrombotic lesions, there's notable consumption of large and hyperactive platelets. Diseases with high-grade inflammation, like rheumatoid arthritis and inflammatory bowel disease, also exhibit lower MPV levels due to active local inflammation and significant platelet consumption. Activated platelets are highly adhesive to polymorphonuclear cells and monocytes, supporting the theory of increased platelet consumption during ACS without a corresponding rise in MPV [21,22].

In our study, both NLR and PLR were found to be higher in ACS compared to SCAD. Consistent with prior research, elevated NLR has been observed in both ACS and SCAD compared to healthy controls. The increased NLR in ACS is attributed to a more pronounced inflammatory response, where neutrophils act as pro-inflammatory agents and lymphocytes as anti-inflammatory agents. Lower lymphocyte levels can be attributed to the intricate interplay between cytokines, neutrophils, and lymphocytes. ACS shows the highest levels of circulating interferon-gamma (IFN-γ), followed by SCAD and healthy controls. Activated neutrophils release IFN-γ, which suppresses lymphocyte proliferation via Programmed Death Ligand 1 expression The elevation in PLR is mainly due to a lower lymphocyte count. In ACS, the decreased lymphocyte count could be associated with cortisol release or the migration of lymphocytes from the bloodstream [23-27].

The platelet count in ACS and SCAD has shown inconsistent results across studies. Some investigations reported a higher platelet count in the ACS group compared to SCAD and healthy controls, while others observed a lower platelet count. Additionally, another study indicated that platelet count is higher in myocardial infarction patients than in healthy controls but lower in unstable angina patients. The hypothesis for this inconsistency revolves around the complex relationship between thrombopoietin and platelet regulation in inflammatory settings. Thrombopoietin, a hormone regulating platelet production, is elevated in unstable angina patients compared to SCAD and healthy controls. This increase is attributed to platelet consumption during acute myocardial attacks, stimulating megakaryocyte proliferation. Another theory suggests that thrombopoietin interaction with its platelet surface receptor results in decreased thrombopoietin, leading to low platelet production. Platelets with high MPV have numerous receptors, inducing inhibitory feedback and resulting in a lower platelet count [28-30].

This study analyzed cut-off points for hematologic indices. The cut-off point for MPV was determined as 7.93 fL, with a lower MPV indicating a diagnosis of ACS. A meta-analysis also suggested NLR cut-off points ranging from 1.95 to 3.97 to predict severe atherosclerotic lesions. Regarding WBC count, a value exceeding 9.64 was indicative of an ACS diagnosis in this study. Previous reports on WBC cut-off points include 6.91, 7.37, and 8.89 x 10^3/μL, each with different sensitivities and specificities. Overall, this study suggests that MPV, NLR, and WBC are comparable to other inflammation markers like IL-6 in diagnosing ACS [31,32].

The investigation highlighted significant distinctions in hematologic parameters between patients with ACS and those with SCAD. ACS patients displayed elevated Mean Corpuscular Hemoglobin Concentration (MCHC), White Blood Cell (WBC) count, Neutrophil-to-Lymphocyte Ratio (NLR), Platelet-to-Lymphocyte Ratio (PLR), and reduced Mean Platelet Volume (MPV) compared to the SCAD cohort. Particularly noteworthy was MPV, which exhibited the highest Area Under the Curve (AUC). The optimal threshold for MPV was determined as 7.93 fL, yielding a sensitivity of 92.2% and specificity of 95.3%.

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