Baseline platelet count independently predicts long-term adverse outcomes in patients undergoing percutaneous coronary intervention: a single-center retrospective cohort study : Cardiology Plus

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Baseline platelet count independently predicts long-term adverse outcomes in patients undergoing percutaneous coronary intervention: a single-center retrospective cohort study

Hou, Xiangeng; Zheng, Yingying; Wu, Tingting; Chen, You; Yang, Yi; Ma, Yitong*,; Xie, Xiang*,

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doi: 10.1097/CP9.0000000000000023
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Abstract

Introduction

Both the incidence and the mortality of coronary artery disease (CAD) have been increasing in China[1]. CAD accounts for > 40% of all cardiovascular deaths[2]. Therapy with percutaneous coronary intervention (PCI) improved the outcomes of CAD patients[3]. The pathologic basis of adverse cardiovascular events after PCI may be involved vascular endothelial injury, inflammation, thrombosis, smooth muscle cell proliferation, migration, and matrix remodeling[4]. Injury to vascular endothelium by PCI procedures results in impaired function and inflammatory response[5-6]. Exposure of the basement membrane to circulating elements activates both endogenous and exogenous coagulation systems[7]. Activated platelets (PLTs) release a variety of vasoactive substances to activate fibrinogen, ultimately resulting in thrombosis.

Activated PLTs play an important role in the progression of atherosclerotic lesions, plaque instability, and thrombosis. However, the platelet count (PC) is not always parallel to its function. PLTs express and secrete many vasoactive substances, such as B-PLT globulin, PLT factor IV, PLT-derived growth factor, adenosine diphosphate, serotonin, catecholamines, thrombokinase, histamine, and thromboxane A2[8], which in turn promote leukocyte adhesion, aggregation, thrombosis, and vascular proliferation resulting[9]. Therefore, there was a close relationship between PLT and CAD. An association between PC with adverse outcomes in CAD patients after PCI has been reported by some[10-12], but not all previous studies[13].

We conducted a single-center retrospective cohort study to examine the potential association between baseline PC and long-term clinical outcomes in patients undergoing PCI for CAD.

Subjects and Methods

Subjects

The Clinical Outcomes and Risk Factors of Patients with Coronary Heart Disease after PCI (CORFCHD-PCI) study is a single-center retrospective cohort study based on case records and follow-up registry in the First Affiliated Hospital of Xinjiang Medical University from January 2008 to December 2016. This study is registered at http://www.chictr.org.cn (identifier: ChiCTR-ORC-16010153). The inclusion and exclusion criteria have been described previously[14]. Subjects must have a stenosis ≥70% (based on coronary angiography) and received at least one stent for inclusion. We excluded patients who had severe heart failure, rheumatic heart disease, valvular heart disease, congenital heart disease, pulmonary heart disease, and severe dysfunction of the liver or kidneys. Four patients with missing PCs at the baseline were also excluded from the analysis.

The study was conducted in accordance with the Declaration of Helsinki (as revised in 2013) and approved by ethics committee of the First Affiliated Hospital of Xinjiang Medical University (No. K201909-06, December 9, 2019). Due to the retrospective nature of the study, informed consent was waived by the ethics committee. The inclusion and exclusion process was shown in Figure 1.

F1
Figure 1.:
The flow chart of participants inclusion. Q1: Quartile 1 (<25%); Q2: Quartile 2 (25%–50%); Q3:Quartile 3 (50%–75%); Q4: Quartile 4 (≥75%); MACE: Major adverse cardiovascular events; MACCE: Major adverse cardiovascular and cerebrovascular events; PCI: Percutaneous coronary intervention; re-MI: Recurrent myocardial infarction.

Term definitions

Major adverse cardiovascular and cerebrovascular events (MACCE) was the composite of cardiac death, recurrent myocardial infarction (re-MI), target vessel revascularization (TVR), and stroke. Major adverse cardiovascular events (MACE) was the composite of cardiac death, re-MI, TVR.

Statistical analysis

Clinical outcomes were compared in patients with varying PCs at the baseline (divided into four quarters). Continuous variables were analyzed using one-way analysis of variance (ANOVA), and expressed as mean ± standard deviation (SD). Least-Significant Difference method was used to perform posthoc pairwise comparison. Categorical variables were analyzed using χ2 test, and expressed by the number and percentage. Survival analysis was conducted using the Kaplan-Meier method. A multivariable Cox proportional hazards model was conducted to identify the risks associated with clinical outcomes; results are shown as adjusted hazard ratio (aHR) and 95% confidence interval (CI). P < 0.05 was considered statistically significant. All data were analyzed using SPSS 20. 0 statistical software.

Results

Demographic and baseline characteristics

The final analysis included a total of 6,046 subjects (59.49 ± 10.84 years of age; male = 4,495, female = 1,551). PC at the baseline was 215.2 ± 60.2. The follow-up time was 32 (1–120) months. Table 1 shows demographic and baseline characteristics of the four groups, as divided by the baseline PC into Q1 (PC < 173 × 1012, n = 1,473), Q2 (173 ≤ PC < 208 × 1012, n = 1,529), Q3 (208 × 1012 ≤ PC < 250 × 1012, n = 1,507) and Q4 (PC ≥ 250 × 1012, n = 1,537). The average PC was 144.8 ± 21.3 There was significant difference among these four groups in terms of age, gender, alcohol consumption, hypertension, systolic blood pressure, diastolic blood pressure, blood urea nitrogen, and creatinine (Cr) (P < 0.05). There were not significant difference among the four groups in the use of calcium channel blocker, β-receptor blockers, angiotensin-converting enzyme inhibitors or angiotensin II receptor antagonist (ARB), clopidogrel, aspirin, and statins (Tables 1 and 2).

Table 1 - Comparison of demographic and baseline characteristics of participants among four quartiles
Variables Total (n = 6,046) Q1 (n = 1,399) Q2 (n = 1,462) Q3 (n = 1,429) Q4 (n = 1,447) t or χ2 P
Age, year 59.5 ± 10.8 62.2 ± 10.5 59.7 ± 11.0 59.2 ± 10.6 56.9 ± 10.6 61.346 <0.001
Male sex, n (%) 4,495 (74.3) 1,166 (79.2) 1,185 (77.5) 1,073 (71.2) 1,071 (69.7) 52.219 <0.001
Smoking, n (%) 2,419 (40.0) 596 (40.5) 649 (42.4) 568 (37.7) 606 (39.4) 7.500 0.058
Alcohol drinking, n (%) 1,766 (29.2) 425 (28.9) 497 (32.5) 410 (27.2) 434 (28.2) 11.749 0.008
Diabetes, n (%) 1,451 (24.0) 376 (25.5) 364 (23.8) 363 (24.1) 348 (22.6) 3.474 0.324
Hypertension, n (%) 2,555 (42.3) 590 (40.1) 632 (41.3) 640 (42.5) 693 (45.1) 8.538 0.036
CCB, n (%) 690 (11.4) 152 (10.4) 162 (10.7) 177 (11.8) 199 (13.0) 6.444 0.092
β-blockers, n (%) 2,426 (40.1) 566 (38.6) 628 (41.3) 630 (41.9) 602 (39.4) 4.595 0.204
Clopidogrel, n (%) 1,836 (30.4) 432 (29.5) 460 (30.4) 462 (30.8) 482 (31.6) 1.629 0.653
Aspirin, n (%) 4,048 (67.0) 991 (67.7) 1,039 (68.4) 1,022 (68.1) 996 (65.3) 4.159 0.245
Statins, n (%) 3,256 (53.9) 805 (55.2) 826 (54.6) 830 (55.4) 795 (52.2) 3.858 0.277
SBP, mmHg 127.0 ± 18.8 126.4 ± 18.8 126.3 ± 17.9 127.4 ± 18.5 127.9 ± 19.7 2.725 0.043
DBP, mmHg 76.31 ± 11.31 75.37 ± 11.14 76.23 ± 10.99 76.49 ± 11.38 77.13 ± 11.60 6.173 <0.001
Length of stent, mm 27.9 ± 7.0 27.7 ± 6.9 27.8 ± 7.0 28.3 ± 7.1 28.1 ± 6.9 2.163 0.090
Diameter of stent, mm 2.85 ± 0.37 2.83 ± 0.37 2.85 ± 0.37 2.85 ± 0.37 2.86 ± 0.38 1.601 0.187
Number of stent 1.04 ± 0.22 1.04 ± 0.21 1.04 ± 0.22 1.05 ± 0.22 1.05 ± 0.24 1.042 0.373
Drug eluting stent, n (%) 5,697 (94.2) 1,378 (93.6) 1,443 (94.4) 1,418 (94.1) 1,458 (94.9) 2.263 0.520
CTO, n (%) 1,414 (23.4) 333 (22.6) 336 (22.0) 345 (22.9) 400 (26.0) 8.354 0.039
LM, n (%) 3,925 (64.9) 116 (7.9) 105 (6.9) 116 (7.7) 96 (6.2) 3.932 0.269
ACS, n (%) 2,042 (33.8) 519 (35.2) 514 (33.6) 527 (35.0) 482 (31.4) 6.390 0.094
Continuous variables were analyzed using one-way analysis of variance, and expressed as mean ± standard deviation. Categorical variables were analyzed using χ2 test, and expressed by the number and percentage.
ACS: Acute coronary syndrome; CCB: Calcium channel blocker; CTO: Chronic total occlusion; DBP: Diastolic blood pressure; LM: Left main disease; Q1: Quartile 1 (<25%); Q2: Quartile 2 (25%–50%); Q3: Quartile 3 (50%–75%); Q4: Quartile 4 (≥75%); SBP: Systolic blood pressure.

Table 2 - Comparison of laboratory test results among four quartiles
Variables Total (n = 6,046) Q1 (n = 1,399) Q2 (n = 1,462) Q3 (n = 1,429) Q4 (n = 1,447) t or χ2 P
PLT, 109/L 215.2 ± 80.2 144.8 ± 21.3 190.7 ± 10.4 277.6 ± 11.6 294.9 ± 41.6 9907 <0.001
GLU, mmol/L 6.6 ± 3.1 6.6 ± 2.2 6.6 ± 3.3 6.5 ± 2.9 6.6 ± 3.1 0.502 0.681
BUN, mmol/L 5.5 ± 1.7 5.7 ± 1.8 5.5 ± 1.6 5.5 ± 1.7 5.4 ± 1.7 5.705 <0.001
Cr, μmol/L 75.9 ± 20.4 78.1 ± 21.1 76.6 ± 20.8 74.7 ± 19.3 74.4 ± 20.3 10.902 <0.001
UA, μmol/L 323.2 ± 90.1 323.5 ± 95.0 322.3 ± 85.7 325.2 ± 88.9 322.2 ± 91.0 0.361 0.781
TG, mmol/L 1.9 ± 1.3 1.8 ± 1.7 1.9 ± 1.35 1.9 ± 1.3 1.9 ± 1.3 1.264 0.285
TC, mmol/L 4.0 ± 1.1 3.9 ± 1.1 4.0 ± 1.1 4.0 ± 1.1 4.0 ± 1.1 1.596 0.188
HDL-C, mmol/L 1.0 ± 0.5 1.0 ± 0.5 1.0 ± 0.4 1.0 ± 0.5 1.0 ± 0.5 0.678 0.566
LDL-C, mmol/L 2.5 ± 0.9 2.4 ± 0.9 2.5 ± 0.9 2.4 ± 0.9 2. 5 ± 0.9 2.495 0.058
ApoAI, g/L 1.2 ± 0.3 1.2 ± 0.3 1.2 ± 0.3 1.2 ± 0.3 1.2 ± 0.3 1.000 0.394
ApoB, g/L 0.9 ± 0.4 0.8 ± 0.4 0.6 ± 0.4 0.8 ± 0.4 0.9 ± 0.4 1.328 0.263
Lp (a), g/L 220.3 ± 176.8 217.8 ± 172.2 220.3 ± 175.7 215.8 ± 171.8 227.0 ± 186.8 1.085 0.354
Continuous variables were analyzed using one-way analysis of variance, and expressed as mean ± standard deviation.
ApoAI: Apolipoprotein AI; ApoB: Apolipoprotein B; BUN: Blood urea nitrogen; Cr: Creatinine; GLU: Glucose; HDL-C: High-density lipoprotein cholesterol; LDL-C: Low-density lipoprotein cholesterol; Lp (a): Lipoprotein (a); Q1: Quartile 1 (<25%); Q2: Quartile 2 (25%–50%); Q3: Quartile 3 (50%–75%); Q4: Quartile 4 (≥75%); PLT: Platelet; TC: Total cholesterol; TG: Triglyceride; UA: Uric acid.

Clinical outcomes

All-cause mortality did not differ significantly among there four groups (Table 3). The rate of MACCE occurred during the follow-up period, including 12.8% (188/1,473) in the Q1 group, 12.8% (196/1,529) in the Q2 group, 15.1% (228/1,507) in the Q3 group, and 16.3% (150/1,537) in the Q4 group (P = 0.010). The rate of MACE was 11.3% (167/1,473) in the Q1 group, 11.6% (177/1,529) in the Q2 group, 13.9% (210/1,507) in the Q3 group, and 15.0% (231/1,537) in the Q4 group (P = 0.004). These four groups did not differ in heart failure, stroke, bleeding, re-MI, and TVR.

Table 3 - Comparison of the incidence of clinical outcomes among four groups
Variables Total (n = 6,046) Q1 (n = 1,399) Q2 (n = 1,039) Q3 (n = 1,429) Q4 (n = 1,447) χ2 P
ACM, n (%) 309 (5.1) 74 (5.0) 67 (4.4) 78 (5.2) 90 (5.9) 3.469 0.325
CM, n (%) 251 (4.2) 54 (3.7) 54 (3.5) 69 (4.6) 74 (4.8) 4.738 0.192
MACCE, n (%) 862 (14.3) 188 (12.8) 196 (12.8) 228 (15.1) 250 (16.3) 11.286 0.010
MACE, n (%) 785 (13.0) 167 (11.3) 177 (11.6) 210 (13.9) 231 (15.0) 13.114 0.004
Heart failure, n (%) 181 (3.0) 41 (2.8) 42 (2.7) 47 (3.1) 51 (3.3) 1.183 0.757
Stroke, n (%) 82 (1.4) 23 (1.6) 21 (1.4) 19 (1.3) 19 (1.2) 0.735 0.865
Bleeding, n (%) 175 (2.9) 31 (2.1) 56 (3.7) 35 (2.3) 53 (3.4) 9.910 0.190
Re-MI, n (%) 194 (3.2) 35 (2.4) 48 (3.1) 53 (3.5) 58 (3.8) 5.352 0.148
TVR, n (%) 313 (5.2) 72 (4.9) 70 (4.6) 73 (4.8) 98 (6.4) 6.209 0.102
Categorical variables were analyzed using χ2 test, and expressed by number and percentage.
ACM: All-cause mortality; CM: Cardiac mortality; MACE: Major adverse cardiovascular events; MACCE: Major adverse cardiovascular and cerebrovascular events; Q1: Quartile 1 (<25%); Q2: Quartile 2 (25%–50%); Q3: Quartile 3 (50%–75%); Q4: Quartile 4 (≥75%); Re-MI: Recurrent myocardial infarction; TVR: Target vessel reconstruction.

Survival analysis

The event-free survival was significantly shorter in patients with high PCs (Figure 2). After adjustment of confounders using multivariable Cox regression analysis the differences remain significant. Using Q1 as reference, the aHR for MACCE was 1.212 (95% CI: 1.004–1.455, P < 0.001) in Q2, 1.455 (95% CI: 1.200–1.766, P < 0.001) in Q3, and 1.754 (95% CI: 1.426–2.118, P < 0.001) in Q4 (Table 4). Relative to Q1, the aHR for MACE was 1.201 (95% CI: 0.968–1.492, P = 0.096) for Q2, 1.489 (95% CI: 1.206–1.837, P < 0.001) for Q3, and 1.847 (95% CI: 1.500–2.275, P < 0.001) for Q4 (Table 5).

Table 4 - Multivariable Cox regression analysis of MACCE
Variables β SE HR 95% CI P
Age, years 0.006 0.004 1.006 0.999–1.013 0.115
Sex 0.152 0.091 1.164 0.975–1.390 0.094
Alcohol drinking 0.145 0.083 1.156 0.982–1.360 0.082
SBP −0.003 0.002 0.997 0.993–1.002 0.221
DBP 0.004 0.004 1.004 0.997–1.012 0.251
Hypertension −0.316 0.072 1.372 1.189–1.578 <0.001
BUN 0.059 0.022 1.060 1.017–1.106 0.006
Cr −0.001 0.002 0.999 0.995–1.003 0.651
PLT counts (Q1 as reference)
Q2 0.192 0.094 1.212 1.004–1.455 <0.001
Q3 0.376 0.099 1.455 1.200–1.766 <0.001
Q4 0.553 0.101 1.754 1.426–2.118 <0.001
Categorical variables were analyzed using χ2 test, and expressed by number and percentage.
BUN: Blood urea nitrogen; CI: Confidence interval; Cr: Creatinine; DBP: Diastolic blood pressure; HR: Hazard ratio; MACCE: Major adverse cardiovascular and cerebrovascular events; PLT: Platelet; Q1: Quartile 1 (<25%); Q2: Quartile 2 (25%–50%); Q3: Quartile 3 (50%–75%); Q4: Quartile 4 (≥75%); SBP: Systolic blood pressure; SE: Standard error.

Table 5 - Multivariable Cox regression analysis of MACE
Variables β SE HR 95% CI P
Alcohol -0.133 0.087 0.875 0.738–1.037 0.124
Sex -0.159 0.095 0.853 0.708–1.029 0.097
Age, years 0.003 0.004 1.003 0.996–1.010 0.423
SBP −0.002 0.002 0.998 0.993–1.002 0.324
DBP 0.005 0.004 1.005 0.997–1.013 0.197
Hypertension 0.333 0.076 1.395 1.202–1.619 <0.001
BUN 0.065 0.023 1.068 1.021–1.116 0.004
Cr -0.001 0.002 0.999 0.995–1.002 0.461
PLT counts (Q1 as reference)
Q2 0.184 0.110 1.201 0.968–1.492 0.096
Q3 0.398 0.107 1.489 1.206–1.837 <0.001
Q4 0.614 0.106 1.847 1.500–2.275 <0.001
BUN: Blood urea nitrogen; CI: Confidence interval; Cr: Creatinine; DBP: Diastolic blood pressure; HR: Hazard ratio; MACCE: Major adverse cardiovascular and cerebrovascular events; PLT: Platelet; Q1: Quartile 1 (<25%); Q2: Quartile 2 (25%–50%); Q3: Quartile 3 (50%–75%); Q4: Quartile 4 (≥75%); SBP: Systolic blood pressure; SE: Standard error.

F2
Figure 2.:
Cumulative Kaplan-Meier estimates of the time to the first adjudicated occurrence of primary endpoint and secondary endpoints. A, Major adverse cardiovascular and cerebrovascular events (MACCE); B, Major adverse cardiovascular events (MACE); C, Adjusted Major adverse cardiovascular and cerebrovascular events (MACCE); D, Adjusted major adverse cardiovascular events (MACE). PLT: Platelet.

Discussion

The results from the present study confirmed higher PC as a risk for long-term adverse outcomes, including MACCE and MACE, in CAD patients underwent PCI. A strength in the current study is the relatively large sample size and long-term follow-up.

PCI is the preferred treatment in patients with CAD[1]. Recent evidence suggest elevated baseline PC is associated with poor prognosis of CAD patients. There is an inextricable link between PLT activation and atherosclerosis. The underlying mechanisms are complex. First, local asymmetrical thickening of the arterial intimal layer leads to atherosclerotic fissures, which constitute a main component including a variety of cells, connective tissue, lipids, and some debris. The role of PLTs in blood coagulation, maintenance of homeostasis, and pathogenesis of thrombotic diseases is evident. Second, PLTs accumulated in the areas of vascular injury promote the migration of additional PLTs and other blood components to form a thrombus. Most of the areas where PLTs accumulate are concentrated on the surface of damaged or eroded plaques, causing a partial or complete blockage of blood flow. Third, PLTs can induce atherosclerosis by interacting with endothelial cells and white blood cells, and participate in the formation of late complications of atherosclerosis. Fourth, inflammatory response triggers PLT activation, which constitutes an important component of atherosclerotic thrombosis. PLT activation can occur at various stages of atherosclerosis, especially in the early stages. Fifth, the interaction of GPIb (glycoprotein lb) with endothelial cell PLT-selectin receptor and plasma von Willebrand factor (vWF) activates PLTs, which is mediated by vWF to adhere to damaged areas of the vessel wall[15].

In a prospective cohort study with 13.5-years follow-up, higher PC was associated with increased mortality[16]. A study of 5,256 CAD patients receiving 600 mg clopidogrel before PCI[17], elevated PC was also an independent risk factor for 1-month mortality after PCI.

In the current study, the risk for MACCE was increasingly higher with increasingly higher baseline PC was associated with increasingly higher risk of MACCE as well as MACE. Using Q1 as a reference, the aHR was 1.212 (95% CI: 1.004–1.455, P < 0.001) for Q2, 1.455 (95% CI: 1.200–1.766, P < 0.001) for Q3, and 1.754 (95% CI: 1.426–2.118, P < 0.001) in Q4. Similarly, the aHR for MACE was 1.201(95% CI: 0.968–1.492, P = 0.096) in Q2, 1.489 (95% CI: 1.206–1.837, P < 0.001) in Q3, and 1.847 (95% CI: 1.500–2.275, P < 0.001) in Q4. Such a “dose-dependent” profile adds to the robustness of the findings and is clinically relevant.

The current study has several limitations. First, this is a single-center retrospective cohort study. Accordingly, the findings require verification by further multi-center prospective studies. Second, sampling time point for determination of PC was not uniform. Third, not all patients received anti-PLT treatments. Accordingly, whether the findings can be extrapolated to patients receiving anti-PLT therapy is unknown. Also, we only examined the baseline PC, and did not analyze the temporal profile of PC and function.

In conclusion, the present study confirmed the elevated PC as an independent predictor of long-term adverse outcomes, including MACCE and MACE, in CAD patients undergoing PCI.

FUNDING

This work was supported by the National Natural Science Foundation of China (82000238 and 82170345).

AUTHOR CONTRIBUTIONS

XH, TW, and YZ made substantial contributions to study conception and design and to the drafting and critical revision of the manuscript for important intellectual content. YY and YC made substantial contributions to the study conception and design and critical revision of the manuscript for important intellectual content. XX and YM made substantial contributions to study conception and design, drafting and critical revision of the manuscript for important intellectual content, including study supervision.

CONFLICTS OF INTEREST STATEMENT

Yitong Ma is an Editorial Board members of Cardiology Plus. The article was subject to the journal conception and design, drafting and critical revision of the manuscript for important intellectual content, including The other authors declare that they have no financial conflict of interest with regard to the content of this report.

DATA SHARING STATEMENT

Research data will be available to other researchers upon request to the corresponding author.

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Keywords:

Clinical outcome; Coronary artery disease; Percutaneous coronary intervention; Platelet

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