Abstract
We aim to test the hypothesis that blood leukocyte count adds prognostic information in patients with acute non–ST-elevation myocardial infarction (non-STEMI).
A total of 585 patients with acute non-STEMI (thrombolysis in myocardial infarction risk score ≥ 3) were enrolled in this cohort retrospective study. Blood leukocyte count was measured immediately after admission in the emergency department. The composite of death, reinfarction, urgent revascularization, and stroke during hospitalization were defined as the primary end point of the study.
The mean age of the patients was 61 ± 9.6 years and most of them were male (79%). Using multivariate Cox regression analysis involving seven variables (history of smoking, hypertension, heart rate > 100 beats/minute, serum creatinine level > 1.5 mg/dL, blood leukocyte count > 11,000/µL, use of β-blocker, and use of angiotensin-converting enzyme inhibitor), leukocyte count > 11,000/µL demonstrated to be a strong predictor of the primary end point (hazard ratio = 3.028; 95% confidence interval = 1.69–5.40, p < 0.001).
The high blood leukocyte count on admission is an independent predictor of cardiovascular events in patients with acute non-STEMI.
Keywords: leukocyte count, acute non-STEMI, predictor, cardiovascular event
Inflammation plays an important role in the course of atherosclerosis including acute plaque rupture leading to thrombosis, manifested as acute coronary syndrome (ACS).1 2 3 The leukocyte is one of the inflammatory biomarkers,4 and quantification of leukocyte density in blood is available in almost all the laboratories worldwide. Leukocytosis affects acute thrombosis by mechanisms involving inflammation, that will induce a hypercoagulability state and microvascular obstruction, leading to a more extensive of an infarction.5
Several studies have shown that leukocytosis is a predictor of cardiovascular events in healthy individuals,6 7 8 and also in patients with a history of myocardial infarction,9 10 11 but another study failed to find such an association.12 Furthermore, as the clinical laboratories in most developing countries lack the routine assay of established inflammatory markers—such as interleukins and C-reactive protein (CRP)—a simple, reliable, inexpensive but accurate marker is needed to be measured routinely in the daily management of infarct patients to identify patients who are at an increased risk for subsequent cardiovascular events. Therefore, this study was designed to assess the predictive role of baseline leukocyte count on in-hospital cardiovascular events of patients with acute non–ST-segment elevation myocardial infarction (non-STEMI) in Jakarta, Indonesia. One should keep in mind that studies which assess the association between blood leukocyte count and cardiovascular events in developing countries are relatively scarce and that measurement of blood leucocyte count is available in nearly all hospitals in Indonesia.
Methods
Study Population
Data were collected from the Jakarta Acute Coronary Syndrome Registry database involving 585 patients admitted to the emergency department of the National Cardiovascular Center Harapan Kita, Jakarta, Indonesia. The inclusion criteria were all patients diagnosed with moderate to high risk acute non-STEMI (thrombolysis in myocardial infarction [TIMI] risk score ≥ 3) who were hospitalized between January 2008 and December 2010. Patients with known history of infection or systemic inflammation during the last 2 weeks before admission, patients with severe gout or rheumatic disease, patients with liver disease, or patients with hematologic disease at admission were excluded.
Diagnosis of acute non-STEMI was based on (1) typical chest discomfort in the preceding 48 hours, (2) the absence of ST-segment elevation, and (3) the presence of at least one of the following two criteria: (a) positive serum marker of myocardial necrosis, defined as troponin T values above the 99th percentile of a healthy reference population, and (b) electrocardiographic indices of ischemia consisting of transient ST-segment depression (≥ 0.05 mV) or T-wave inversion (≥ 0.1 mV) in two or more contiguous leads.
TIMI risk score13 was calculated as the sum of each of the following variables of which its presence contributes one point to the total score: age 65 years or older, at least three risk factors for coronary artery disease, prior coronary stenosis of ≥ 50%, ST-segment deviation on electrocardiogram at presentation, at least two anginal events in the prior 24 hours, use of aspirin in the preceding week, and elevated cardiac marker levels in serum. Moderate- and high-risk patients are defined as having TIMI scores of 3 to 4 and 5 to 7, respectively. To investigate a homogenous study population, only moderate-to-high-risk patients (TIMI risk score ≥ 3) were included in the study.
Laboratory Determination
Immediately after admission, venous blood samples were taken in tubes containing ethylenediaminetetraacetic acid (EDTA). One blood sample was used to measure the blood leukocyte count using flow cytometry (Sysmex Corporation, Kobe, Japan). Plasma sample of cardiac troponin T was assayed using a chemiluminescence immunoassay (Roche Diagnostics Corporation, Indianapolis, IN), and creatine kinase-MB activity was measured using an immuno-inhibition assay (Roche Diagnostics Corporation).
Study End Point
Primary end point of the study is major adverse cardiovascular event (MACE) defined as the composite of death, reinfarction, urgent revascularization, and stroke during hospitalization, as judged by an independent clinical event committee of which the members were blinded to the laboratory results.
Statistical Methods
Continuous variables are presented as mean values ± standard deviation (SD) or median (range) if not fitting a normal distribution. Categorical variables were expressed as percentages or proportions. Cut-off value for blood leukocyte count was determined using the receiver operator characteristic (ROC) test, based on a specificity of 70% and a sensitivity of 50%. A leukocyte count of 11,000/µL was chosen as the cut-off point. The specificity measured was the highest value, and concordant with this, Cannon and colleagues10 used a leukocyte count of > 10,000/µL as a cut-off point. Normally distributed variables were compared by Student t-test, skewed distribution data were compared by Mann–Whitney U-test, and categorical variables were compared by Pearson chi-square test. Univariate and multivariate Cox regression analyses were performed to identify whether a variable is a predictor of cardiovascular events. Variables with p value < 0.25 in univariate analysis were entered in the multivariate analysis. To detect a reduction in MACE by at least 16% MACE difference, each group should contain at least 85 patients at a study power of 80% and a probability of 5%. A p value < 0.05 was considered as statistically significant. All computations were performed using a statistical package (SPSS version 13.0, SPSS Inc., Chicago, IL).
Results
Most of the patients were men (79%) and the mean age was 61 ± 9.6 years. The mean blood leukocyte count at admission was 10,382 ± 4,007/µL. On admission, patients with a leukocyte count > 11,000/µL had a higher heart rate (p < 0.001), a higher creatine kinase-MB level on admission (p < 0.001), and a higher creatinine level (p = 0.014) than patients with a leukocyte count ≤ 11,000/µL. There are no treatment differences between the two groups (Table 1).
Table 1. Demographic and clinical characteristics including baseline blood chemistry of patients with acute non–ST-elevation myocardial infarction divided into two groups having blood leukocyte count > 11,000/µL and ≤ 11,000/µL.
| Variables | All patients (N = 585) |
Leukocyte count ≤ 11,000/µL (N = 397) |
Leukocyte count > 11,000/µL (N = 188) |
p-Value |
|---|---|---|---|---|
| Age (y) | 61 ± 9.6 | 61.3 ± 9.6 | 60.0 ± 9.4 | 0.223 |
| Male gender, N (%) | 462 (79%) | 306 (77%) | 156 (82%) | 0.102 |
| Systolic blood pressure (mm Hg) | 142.5 ± 29 | 143.3 ± 29 | 140.9 ± 28 | 0.383 |
| Heart rate (beats/min) | 90 ± 23.8 | 87 ± 23 | 97 ± 24 | < 0.001 |
| Prior myocardial infarction | 97 (16%) | 66 (17%) | 31 (16%) | 0.947 |
| Risk factor profile, N (%) | ||||
| Family history | 148 (25%) | 106 (27%) | 42 (22%) | 0.231 |
| Smoker | 141 (24%) | 89 (22%) | 52 (27%) | 0.230 |
| Hypertension | 423 (72%) | 287 (72%) | 136 (72%) | 0.990 |
| Diabetes mellitus | 220 (38%) | 141 (35%) | 79 (42%) | 0.104 |
| Dyslipidemia | 277 (47%) | 192 (48%) | 85 (45%) | 0.529 |
| Lipid profile | ||||
| Total cholesterol (mg/dL) | 188 ± 50 | 190 ± 49 | 184 ± 50 | 0.313 |
| LDL-cholesterol (mg/dL) | 123 ± 42 | 124.3 ± 42 | 120 ± 42 | 0.420 |
| HDL-cholesterol (mg/dL) | 37.8 ± 12 | 38.2 ± 12 | 36.8 ± 11 | 0.235 |
| Triglyceride (mg/dL) | 142 ± 91 | 146 ± 93 | 133 ± 86 | 0.060 |
| CK-MB (U/L) | 25 (3–523) | 23 (4–324) | 32 (3–523) | < 0.001 |
| Troponin T > 0.03 µg/L | 512 (88.6) | 342 (86) | 170 (90) | 0.142 |
| Creatinine (mg/dL) | 1.4 ± 0.9 | 1.38 ± 0.9 | 1.52 ± 1.1 | 0.014 |
| Length of stay (d) | 8.77 ± 7.14 | 8.82 ± 6.7 | 8.68 ± 7.8 | 0.501 |
| Coronary angiography, N (%) | 221 (38%) | 161 (40%) | 60 (32%) | 0.042 |
| PCI, N (%) | 79 (13%) | 54 (13%) | 25 (13%) | 0.262 |
| CABG, N (%) | 29 (5%) | 22 (5%) | 7 (3%) | 0.696 |
| Medication at enrollment, N (%) | ||||
| ACE inhibitor | 313 (53%) | 205 (51%) | 108 (57%) | 0.188 |
| Beta-blocker | 373 (64%) | 273 (68%) | 100 (53%) | < 0.001 |
| MACE, N (%) | 52 (9%) | 21 (5%) | 31 (16%) | < 0.001 |
Abbreviations: ACE, angiotensin-converting enzyme; CABG, coronary artery bypass grafting; CK-MB, creatine kinase-MB; MACE, major adverse cardiac event; PCI, percutaneous coronary intervention.
Continuous data presented as mean ± standard deviation or median (range) and categorical variables as number and percentages.
During the hospitalization period, MACE occurred in 52 patients (9%). Incidence of MACE was significantly higher in patients with leukocyte count > 11,000/µL than in patients with leukocyte count ≤ 11,000/µL (16 vs. 5%, p < 0.001).
In univariate analysis, patients with leukocyte count > 11,000/µL had a higher risk of MACE than patients with leukocyte count ≤ 11,000/µL (hazard ratio = 3.17, 95% confidence interval [CI], 1.81 to 5.57; p < 0.001), and in multivariate analysis, the hazard ratio was 3.028 (95% CI 1.69 to 5.40, p < 0.001) (Tables 2 and 3).
Table 2. Univariate predictors of cardiovascular events.
| Variables | HR (95% CI) | p-Value |
|---|---|---|
| Age (> 65 y) | 0.913 (0.50–1.63) | 0.759 |
| Male gender | 1.085 (0.54–2.17) | 0.818 |
| History of MI | 0.915 (042–1.96) | 0.820 |
| Risk factor profile | ||
| Family history | 0.774 (0.39–1.51) | 0.453 |
| Diabetes mellitus | 1.240 (0.70–2.17) | 0.453 |
| Hypertension | 0.701 (0.39–1.24) | 0.227* |
| Dyslipidemia | 1.089 (0.61–1.93) | 0.772 |
| Smoker | 0.749 (0.51–1.08) | 0.130* |
| Systolic blood pressure < 100 mm Hg | 0.853 (0.26–2.78) | 0.792 |
| Heart rate > 100 beats/min | 1.425 (0.80–2.54) | 0.229* |
| Lipid profile | ||
| Total cholesterol > 200 mg/dL | 1.202 (0.57–2.51) | 0.625 |
| HDL-cholesterol < 40 mg/dL | 0.780 (0.37–1.61) | 0.501 |
| LDL-cholesterol > 130 mg/dL | 1.210 (0.58–2.51) | 0.609 |
| Triglyceride > 150 mg/dL | 0.883 (0.37–2.10) | 0.779 |
| Creatinine > 1.5 mg/dL | 1.958 (1.10–3.47) | 0.022* |
| Leukocyte count > 11,000/µL | 3.178 (1.81–5.57) | < 0.001 |
| Medication at enrollment | ||
| Beta-blocker | 0.676 (0.38–1.17) | 0.167* |
| ACE inhibitor | 0.638 (0.36–1.11) | 0.116* |
Abbreviations: ACE, angiotensin-converting enzyme; CI, confidence interval; HR, hazard ratio; MI, myocardial infarction.
Variables with p value < 0.25 were entered into multivariate Cox regression analysis.
Table 3. Multivariate predictors of cardiovascular events.
| Variables | HR (95% CI) | p-Value |
|---|---|---|
| History of smoking | 0.727 (0.49–1.06) | 0.101 |
| Hypertension | 0.410 (0.15–1.09) | 0.076 |
| Heart rate > 100 beats/min | 1.803 (0.71–4.56) | 0.214 |
| Creatinine > 1.5 mg/dL | 1.642 (0.90–2.97) | 0.102 |
| Leukocyte count > 11,000/µL | 3.028 (1.69–5.40) | < 0.001 |
| Use of β-blocker | 0.775 (0.43–1.37) | 0.384 |
| Use of ACE inhibitor | 0.575 (0.32–1.02) | 0.058 |
Abbreviations: ACE, angiotensin-converting enzyme; CI, confidence interval; HR, hazard ratio.
Discussion
In this study involving 585 patients with acute non-STEMI, we found a strong relationship between leukocyte count on admission and incidence of MACE during hospitalization. This is the first study evaluating the predictive role of leukocyte count on MACE in moderate-to-high-risk non-STEMI patients in Jakarta, Indonesia.
The result of this study is consistent with a study by Cannon and colleagues10 who showed that patients with acute myocardial infarction or high risk unstable angina pectoris with a leukocyte count > 10,000/µL had a high mortality rate. Barron et al9 also showed that acute myocardial infarction patients with a white blood cell count in the highest quintile (> 13,600/µL) had a higher 30-day mortality rate than patients with a leukocyte count in the lower quintiles.
Several mechanisms may explain how leukocytosis increases MACE in ACS patients: (1) Leukocytes may cause endothelial cell injury by proteolytic and oxidative damage, (2) leukocytes may plug the microvasculature, (3) leukocytes may induce hypercoagulability,5 and (4) activated monocytes have increased expressions of tissue factor.14 It is hypothesized that these mechanisms may lead to activation of the extrinsic pathway of the coagulation system,15 thrombus formation,16 and promote infarct expansion.5 The prognostic value of inflammatory markers is observed across a wide clinical spectrum of atherosclerotic diseases.17
In this study, the higher MACE rate in patients with a leukocyte count > 11,000/µL could be explained by several reasons. First, patients with a leukocyte count > 11,000/µL may have a larger infarct size as shown by higher initial creatine kinase-MB level in the group with high leukocyte count than in the group with low leukocyte count (32 vs. 23 U/L, p < 0.001), and deserves further investigation. Second, the heart rate on admission was higher in patients with a leukocyte count > 11,000/µL (p < 0.001) than in patients with low leukocyte count, and heart rate on admission is also known as a risk factor in patients with acute myocardial infarction.18 Third, the baseline creatinine level was higher in patients with a leukocyte count > 11,000/µL (p = 0.014) than in patients with low leukocyte count, and elevated creatinine levels are a risk factor for developing cardiac events as described in the GRACE (Global Registry of Acute Coronary Events) risk score.18 After adjustment of all those variables and other variables—such as history of smoking, hypertension, use of β-blocker, and use of angiotensin-converting enzyme inhibitor—a leukocyte count > 11,000/µL was a strong predictor of in-hospital cardiovascular events (p < 0.001).
This study demonstrates that there is a relationship between a high leukocyte count and incidence of MACE. Thus, for patients with acute non-STEMI, who have a blood leukocyte count > 11,000/µL, aggressive treatment seems clearly indicated. In Jakarta, Indonesia, the group of patients with acute non-STEMI is larger than the group of patients with STEMI, and since our data cover the majority of ACS patients referred from other hospitals, the reported data are considered representative for all non-STEMI patients in Jakarta, Indonesia.19 As the measurement of leukocyte count is cheap, rapid, and available in almost every laboratory worldwide, the leukocyte count might be used as an additional marker for immediate bedside risk stratification of patients with non ST-elevation ACS, and particularly in rural areas where other established markers, such as interleukin-6, interleukin-1β, and CRP, are not available.
Study Limitation
Several limitations of this study should be considered. The design of the study was a retrospective analysis and data were collected from an existing registry. Furthermore, the assay of additional inflammatory markers, such as CRP, is lacking which would have strengthened the role of leukocyte count in this study.
Conclusion
The high blood leukocyte count on admission is an independent predictor of MACE during hospitalization of patients with acute non-STEMI.
Funding
No external funding support.
Conflict of Interest No conflict of interest.
Note
This article is original and has not been published or being submitted elsewhere.
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