Introduction {#section5-2040622320922020}
============

The rupture and erosion of unstable intravascular coronary plaques and the formation of thrombosis are direct causes of acute coronary syndrome (ACS).^[@bibr1-2040622320922020],[@bibr2-2040622320922020]^ Usually, plaque rupture and secondary thrombosis are considered to be complex pathophysiological events, and typical coronary heart disease risk factors play an important role in the development of ACS.^[@bibr3-2040622320922020][@bibr4-2040622320922020][@bibr5-2040622320922020]--[@bibr6-2040622320922020]^ We know that the occurrence of ACS can be caused by thrombosis or luminal obstruction after the rupture of a coronary plaque in patients with unstable angina pectoris; therefore, early identification and prediction of coronary plaque in unstable angina pectoris (UAP) patients is conducive to the clinical treatment and clinical prognosis of patients.

The immune response theory suggests that T lymphocytes including CD8+ and CD4+ T cells can be observed at various stages of atherosclerosis in both human and non-human primates. This suggests that the immune response plays a part in the progression of the disease.^[@bibr7-2040622320922020],[@bibr8-2040622320922020]^ Previous studies have confirmed that fatty macrophages, T lymphocytes (including CD8+ and CD4+), and smooth muscle cells are present mainly in the lipid stripes of atherosclerosis.^[@bibr9-2040622320922020],[@bibr10-2040622320922020]^ Therefore, the pathological mechanism suggests that CD4+ and CD8+ T cells are involved in the process of atherosclerotic plaque stability. A recent study showed that the CD4+/CD8+ ratio was correlated positively with the occurrence of ACS.^[@bibr11-2040622320922020]^ However, the association between the CD4+/CD8+ ratio and the risk of acute coronary events is unclear.

At present, coronary angiography is commonly used to evaluate coronary vascular status, and more accurate data can be obtained. Optical coherence tomography (OCT) can not only detect the vascular morphology of the coronary artery, but also analyze the details of lesions; thus OCT technology can evaluate the components and characteristics of coronary plaques. The use of imaging techniques can therefore better identify unstable plaques.^[@bibr2-2040622320922020],[@bibr7-2040622320922020]^

We investigated the potential association between the CD4+/CD8+ ratio and OCT-confirmed coronary artery instability in patients with UAP. Our results may help predict the risk of plaque rupture and provide an updated clinical basis for the prevention and treatment of coronary atherosclerotic unstable plaques in UAP patients.

Materials and methods {#section6-2040622320922020}
=====================

Study population and design {#section7-2040622320922020}
---------------------------

Continuous screening included a total of 266 patients. All participants were selected from UAP patients who were admitted to our center from January 2016 to January 2018 for percutaneous coronary interventional therapy (PCI) and OCT examination ([Figure 1](#fig1-2040622320922020){ref-type="fig"}). All patients underwent and completed PCI successfully without complications. The diagnosis of UAP was based on pre-established guidelines.^[@bibr12-2040622320922020]^ Meanwhile, demographic characteristics, clinical features, risk factors for coronary heart disease, blood biochemical data, electrocardiography, echocardiography, coronary angiography (CAG), and OCT results were collected. CAG diagnosed the culprit vessels, while OCT confirmed the vulnerability of plaques at these sites.

![Flowchart depicting patient selection. Among the 266 patients enrolled, OCT examination confirmed plaque rupture (*n* = 9), TCFA (*n* = 66), non-rupture and non-TCFA (*n* = 191). Plaque rupture and TCFA were classified as the instability group, non-rupture and non-TCFA comprised the stability group.\
OCT, optical coherence tomography; TCFA, thin-cap fibroatheroma.](10.1177_2040622320922020-fig1){#fig1-2040622320922020}

Follow up {#section8-2040622320922020}
---------

All patients were subsequently followed for 1 year. Primary endpoint was occurrence of a major adverse cardiovascular event (MACE), including all-cause death, target vessel myocardial infarction (MI), and clinically driven target vessel revascularization.

Definitions of coronary heart disease risk factors {#section9-2040622320922020}
--------------------------------------------------

The diagnostic criteria of hyperlipidemia were based on the guidelines for prevention and treatment of dyslipidemia in Chinese adults (2016).^[@bibr13-2040622320922020]^ Hypertension was diagnosed if the patient had blood pressure of ⩾140/90 mmHg during at least three random examinations, or was actively using antihypertensive drugs.^[@bibr14-2040622320922020]^ Diabetes was diagnosed if the patient's fasting blood glucose was ⩾7.1 mmol/l or ⩾11.1 mmol/l 2 h after a meal, or there was a clear history of diabetes and the patient was receiving hypoglycemic drugs.^[@bibr15-2040622320922020]^ Body mass index (BMI) was calculated by dividing a patient's weight in kilograms by the square of their height in meters. Smoking was defined as current or previous smoking with cessation less than 3 months prior.

Laboratory data {#section10-2040622320922020}
---------------

Blood samples were taken from all patients before procedures and immediately sent to the laboratory for analysis. Routine examination included standard blood work-up, liver function, renal function, blood lipid levels, fasting blood glucose, etc. T lymphocyte counts were expressed as absolute and proportional CD3+ cell numbers and CD4+ and CD8+ cells were counted in all 266 test subjects, from which the CD4+/CD8+ ratio was calculated. Blood tests were conducted using standard methods at the central laboratory.

PCI procedure and OCT image acquisition {#section11-2040622320922020}
---------------------------------------

All patients underwent successful CAG and PCI after admission. After intracoronary nitroglycerine administration, the OCT catheter was advanced distal to the culprit lesion. Imaging of the culprit lesion was then acquired using the frequency-domain OCT C7XR system and the Dragonfly catheter (Lightlab Imaging, St. Jude Medical, Westford, MA).^[@bibr2-2040622320922020],[@bibr16-2040622320922020]^ All treatment strategies were determined by experienced interventional cardiologists. Angiographic images measured reference diameter, minimum lumen diameter, lesion length, and percent diameter stenosis. At the end of the procedure, patients undergoing stent implantation were subjected to final OCT imaging. The images were stored digitally and identified for offline analysis.

OCT image analysis {#section12-2040622320922020}
------------------

After determining the culprit lesions, two experienced cardiac interventional technicians analyzed the morphological characteristics of plaques according to the standards.^[@bibr2-2040622320922020],[@bibr16-2040622320922020][@bibr17-2040622320922020]--[@bibr18-2040622320922020]^ Plaques were divided into fibrous (uniform, high-backscatter area) and lipid (diffuse boundary of low signal region) plaques.^[@bibr16-2040622320922020],[@bibr19-2040622320922020]^ In lipid plaques, the thickness of the fiber cap at the thinnest point was measured three times and the mean value was calculated. Thin-cap fibroatheroma (TCFA) was defined as a plaque with lipid content in at least two quadrants, a plaque with a maximal lipid arc \>90° with the thinnest part of the fibrous cap measuring \<65 μm.^[@bibr20-2040622320922020]^ Plaque rupture (PR) was identified by the presence of fibrous cap discontinuity with a clear cavity formed inside the plaque ([Figure 2](#fig2-2040622320922020){ref-type="fig"}).^[@bibr2-2040622320922020],[@bibr21-2040622320922020],[@bibr22-2040622320922020]^

![Representative OCT images of normal, TCFA, and plaque rupture (left to right, respectively).\
OCT, optical coherence tomography; TCFA, thin-cap fibroatheroma.](10.1177_2040622320922020-fig2){#fig2-2040622320922020}

Statistical analysis {#section13-2040622320922020}
--------------------

All analyses were performed using SPSS 23.0 for Windows statistical software (SPSS Inc., Chicago, IL, USA). The CD4+/CD8+ ratio was not normally distributed, so non-parametrical testing was used to determine differences. The Spearman correlation coefficient was calculated to assess associations between CD4+/CD8+ ratio and all continuous variables in this study. The Mann--Whitney *U* test was used to study CD4+/CD8+ ratio as a continuous variable for all risk factors. Normally distributed continuous variables were expressed as means and standard deviations (SDs), whereas categorical variables were presented as percentages. The Chi-square (χ^2^) test was used for comparing categorical variables. Significant variables in univariate analysis were subsequently included in the multivariate logistic analysis. The cumulative event rate was estimated from Kaplan--Meier curves and compared using the log-rank test. A *p* value of \<0.05 was considered statistically significant.

Results {#section14-2040622320922020}
=======

CD4+/CD8+ ratio and clinically relevant characteristics {#section15-2040622320922020}
-------------------------------------------------------

Baseline clinical characteristics for all patients are described in [Table 1](#table1-2040622320922020){ref-type="table"}. A higher CD4+/CD8+ ratio was observed in patients who smoked (*p = *0.021), whereas laboratory data showed a positive correlation between CD4+/CD8+ ratio and low density lipoprotein (LDL) levels (*r* = 0.22, *p* \< 0.001), and total cholesterol (*r* = 0.191, *p* = 0.002). CD4+/CD8+ ratio was shown to have a negative correlation with high density lipid levels (*r* = --0.167, *p* = 0.006).

###### 

Baseline characteristics of the patients in relation to ratio of CD4+/CD8+ plasma levels.

![](10.1177_2040622320922020-table1)

                                             (*n* = 266)          CD4/8               *p* value
  ------------------------------------------ -------------------- ------------------- -----------------------------------------------------------------
  Age, year                                  65 (24--88)          *r* = −0.42         0.490
   Male                                      194 (72.9%)          1.74 (0.77--2.79)   0.360
   Female                                    72 (27.1%)           1.75 (0.66--2.80)   
  BMI, kg/m^2^                               24.8 (17.6--37.8)    *r* = −0.05         0.450
  Hypertension, *n* (%)                                                               
   Yes                                       183 (68.8)           1.74 (0.66--2.80)   0.310
   No                                        83 (31.2)            1.77 (0.74--2.39)   
  Hyperlipidemia, *n* (%)                                                             
   Yes                                       185 (69.5)           1.77 (0.66--2.80)   0.319
   No                                        81 (30.5)            1.71 (0.74--2.79)   
  Diabetes, *n* (%)                                                                   
   Yes                                       81 (30.5)            1.75 (0.84--2.63)   0.980
   No                                        185 (69.5)           1.74 (0.66--2.80)   
  Prior or current smoker, *n* (%)                                                    
   Yes                                       126 (47.4)           1.80 (0.68--2.80)   0.021
   No                                        140 (52.6)           1.73 (0.66--2.77)   
  Prior stroke, *n* (%)                                                               
   Yes                                       33 (12.4)            1.75 (0.68--2.36)   0.890
   No                                        233 (87.6)           1.74 (0.66--2.80)   
  Prior MI, *n* (%)                                                                   
   Yes                                       27 (10.2)            1.71 (0.84--2.80)   0.606
   No                                        239 (89.8)           1.75 (0.66--2.79)   
  Prior peripheral vessel disease, *n* (%)                                            
   Yes                                       14 (5.3)             1.77 (1.29--2.36)   0.670
   No                                        252 (94.7)           1.75 (0.66--2.80)   
  Prior kidney failure, *n* (%)                                                       
   Yes                                       5 (1.9)              1.59 (1.18--1.99)   0.681
   No                                        261 (98.1)           1.75 (0.66--2.80)   
  Prior COPD, *n* (%)                                                                 
   Yes                                       12 (4.5)             1.60 (1.22--1.99)   0.293
   No                                        254 (95.5)           1.75 (0.66--2.80)   
  Prior HF, *n* (%)                                                                   
   Yes                                       31 (11.7)            1.73 (1.00--2.37)   0.518
   No                                        235 (88.3)           1.75 (0.66--2.80)   
  **Medication:**                                                                     
  Prior use of statin, *n* (%)                                                        
   Yes                                       113 (42.5)           1.74 (0.66--2.80)   0.780
   No                                        153 (57.5)           1.75 (0.69--2.79)   
  Prior use of β-blockers, *n* (%)                                                    
   Yes                                       65 (24.4)            1.77 (0.66--2.80)   0.954
   No                                        201 (75.6)           1.74 (0.68--2.79)   
  Prior use of CCB, *n* (%)                                                           
   Yes                                       106 (39.8)           1.74 (0.68--2.67)   0.572
   No                                        160 (60.2)           1.75 (0.66--2.80)   
  Prior use of ACEI/ARB, *n* (%)                                                      
   Yes                                       90 (33.8)            1.75 (0.68--2.80)   0.718
   No                                        176 (66.2)           1.74 (0.66--2.63)   
  **Laboratory**                                                                      
  WBC                                        6.54 (3.48--15.47)   0.029               0.637
  Hemoglobin                                 136 (72--179)        0.022               0.725
  PLT                                        197 (62--539)        −0.03               0.623
  HDL                                        1.10 (0.6--2.21)     −0.167              0.006[\*\*](#table-fn1-2040622320922020){ref-type="table-fn"}
  LDL-c                                      1.87 (0.70--4.72)    0.22                \<0.001[\*\*](#table-fn1-2040622320922020){ref-type="table-fn"}
  TC                                         3.49 (1.50--6.19)    0.191               0.002[\*\*](#table-fn1-2040622320922020){ref-type="table-fn"}
  TG                                         1.58 (0.43--6.34)    0.092               0.133
  Apo A1                                     1.22 (0.76--1.86)    −0.074              0.348
  Apo B                                      0.73 (0.29--1.43)    0.128               0.105
  Lipoprotein a                              169 (7--1694)        −0.015              0.848
  Creatinine                                 72 (38--723)         −0.005              0.940
  Uric acid                                  319 (175--731)       −0.054              0.494
  AST                                        21 (9--475)          0.006               0.923
  ALT                                        21.5 (5--404)        −0.009              0.881
  GLU                                        5.21 (3.14--19.83)   −0.055              0.369

Correlation is significant at the 0.01 level (2-tailed).

Data are presented as *n* (%) and median ± \[IQR\] or *r* = Spearman's rank correlation coefficient.

ACEI, angiotensin-converting enzyme inhibitors; ALT, alanine aminotransferase; apo-AI, apolipoprotein A1; apo-B, apolipoprotein B; ARB, angiotensin receptor blocker; AST, aspartate transaminase; BMI, body mass index; CCB, calcium channel blockers; COPD, chronic obstructive pulmonary disease; HDL, high density lipoprotein; HF, heart failure; GLU, glucose; IQR, interquartile range; LDL-c, low density lipoprotein-cholesterol; MI, myocardial infarction; PLT, platelet; TC, total cholesterol; TG, total triglycerides; WBC, white blood cell.

CAG and OCT findings in relation to CD4+/CD8+ ratio {#section16-2040622320922020}
---------------------------------------------------

CAG and OCT findings in relation to CD4+/CD8+ ratio are presented in [Table 2](#table2-2040622320922020){ref-type="table"}. A higher CD4+/CD8+ ratio was observed in patients with plaque rupture (*p* = 0.019) and TCFA (*p* = 0.027), whereas a lower CD4+/CD8+ ratio was found in patients with calcified plaques (*p* = 0.045). There were no significant differences in other CAG or OCT findings between those with high or low CD4+/CD8+ ratio levels.

###### 

CD4+/CD8+ ratio according to OCT and angiography findings.

![](10.1177_2040622320922020-table2)

                               (*n* = 266)   CD4+/CD8+           *p* value
  ---------------------------- ------------- ------------------- -----------
  Target vessel                                                  
  LM                           5 (1.9)       1.93 (1.64--2.08)   0.141
  LAD                          207 (77.8)    1.73 (0.66--2.80)   0.611
  LCX                          25 (9.4)      1.84 (0.89--2.36)   0.517
  RCA                          39 (14.7)     1.78 (0.68--2.63)   0.764
  Characteristic of plaque                                       
  Lipid                        92 (34.6)     1.81 (0.68--2.80)   0.066
  Calcified                    68 (25.6)     1.68 (0.66--2.40)   0.045
  Fibrotic                     106 (39.8)    1.75 (0.77--2.58)   0.998
  Rupture                      9 (3.4)       1.92 (1.74--2.63)   0.019
  TCFA, *n*(%)                 66 (24.8)     1.84 (0.91--2.8)    0.027
  Number of vascular lesions                                     
  1                            123 (46.2)    1.74 (0.68--2.80)   0.610
  2                            79 (29.7)     1.77 (0.77--2.35)   0.976
  3                            64 (24.1)     1.74 (0.66--2.63)   0.530
  Bifurcation lesion           72 (27.1)     1.82 (0.89--2.58)   0.151
  CTO                          12 (4.5)      1.57 (0.91--2.80)   0.208

Data are presented as *n* (%) and median ± \[IQR\] or *p* value for Mann--Whitney *U* test.

CTO, chronic total occlusion; IQR, interquartile range; LAD, left anterior descending artery; LCX, left circumflex; LM, left main; OCT, optical coherence tomography; RCA, right coronary artery; TCFA, thin-cap fibroatheroma.

Coronary risk factors and laboratory data in relation to plaque instability {#section17-2040622320922020}
---------------------------------------------------------------------------

Coronary risk factors and laboratory data based on plaque instability are shown in [Table 3](#table3-2040622320922020){ref-type="table"}, including the instability (plaque rupture and TCFA patients, *n* = 75), and stable (non-rupture and non-TCFA patients, *n* = 191) groups. CD4+/CD8+ ratio \>1.725, prior stoke, hemoglobin, and triglyceride (all *p* \< 0.05) were statistically different between the two groups.

###### 

Characteristics of coronary risk factors and laboratory data according to OCT indicated plaque vulnerability.

![](10.1177_2040622320922020-table3)

                           Ruptured plaque and TCFA   Nonrupture and non-TCFA   t/χ^2^   *p* value
  ------------------------ -------------------------- ------------------------- -------- -----------
  Male                     52 (69.3)                  142 (74.3)                0.147    0.701
  Age (year)               65.38 ± 11.09              63.83 ± 10.37             1.067    0.287
  Hypertension             54 (72.0)                  129 (67.5)                1.255    0.263
  Diabetes mellitus        22 (29.3)                  59 (30.9)                 0.005    0.945
  Prior or current smoke   35 (46.7)                  91 (47.6)                 0.013    0.908
  Hyperlipidemia           55 (73.3)                  130 (68.1)                1.595    0.207
  CHF                      10 (13.3)                  21 (11.0)                 0.408    0.523
  Family history of CAD    9 (12.0)                   27 (14.1)                 0.125    0.724
  Prior MI                 6 (8.0)                    21 (11.0)                 0.411    0.521
  Prior stroke             35 (46.7)                  18 (9.4)                  5.543    0.019
  Prior COPD               1 (1.3)                    11 (5.8)                  1.409    0.235
  BMI                      24.92 ± 2.77               25.05 ± 3.08              0.312    0.775
  WBC (mmol/l)             6.66 ± 1.75                6.93 ± 2.05               0.982    0.326
  Hemoglobin (mmol/l)      130.34 ± 19.30             136.66 ± 15.46            6.273    0.014
  PLT (mmol/l)             199.83 ± 56.00             203.22 ± 60.75            0.41     0.682
  HDL-c (mmol/l)           1.16 ± 0.33                1.15 ± 0.27               0.315    0.753
  LDL-c (mmol/l)           1.94 ± 0.67                1.87 ± 0.62               0.747    0.455
  TC (mmol/l)              3.22 ± 0.96                3.63 ± 0.96               0.835    0.393
  TG (mmol/l)              2.10 ± 1.09                1.72 ± 0.88               7.305    0.008
  ApoA1 (g/L)              1.21 ± 0.16                1.25 ± 0.21               1.397    0.165
  ApoB (g/L)               0.74 ± 0.22                0.75 ± 0.23               2.69     0.789
  Lipoprotein a (g/L)      139 (100,292)              202 (98,363)              1.319    0.189
  Creatinine (μmol/L)      73 (39,723)                72 (39,162)               1.225    0.225
  Uric acid (μmol/L)       351.64 ± 98.49             326.41 ± 96.70            1.501    0.135
  GLU (mmol/l)             5.94 ± 1.92                5.92 ± 2.14               0.046    0.964
  CD4+/CD8+ \>1.725        53 (70.7)                  91 (47.6)                 11.497   0.001

Data are presented as *n* (%) and mean ± (SD).

apo-AI, apolipoprotein A1; apo-B, apolipoprotein B; BMI, body mass index; CAD, coronary artery disease; CHF, congestive heart failure; COPD, chronic obstructive pulmonary disease; GLU, glucose; HDL-c, high density lipoprotein-cholesterol; LDL-c, low density lipoprotein-cholesterol; OCT, optical coherence tomography; PLT, platelet; SD, standard deviation; TC, total cholesterol; TCFA, thin-cap fibroatheroma; TG, total triglycerides; WBC, white blood cell.

Predictors of plaque vulnerability {#section18-2040622320922020}
----------------------------------

Receiver operating curve (ROC) analysis showed that CD4+/CD8+ ratio was predictive of plaque instability ([Figure 3](#fig3-2040622320922020){ref-type="fig"}), and the threshold for CD4+/CD8+ ratio was 1.725 with a sensitivity and specificity of 70.7% and 52.4%, respectively (Youden's index = 0.23). Based on the threshold for the CD4+/CD8+ ratio, the cohort was divided into two groups: a higher CD4+/CD8+ ratio group (CD4+/CD8+ ratio \>1.725, *n* = 144) and a lower CD4+/CD8+ ratio group (CD4+/CD8+ ratio ⩽1.725, *n* = 122). Significant variables in the univariate analysis were subsequently included in a binary logistic regression analysis, which showed that CD4+/CD8+ ratio \>1.725 and prior stroke were predictors of plaque instability (all *p* \< 0.05, [Table 4](#table4-2040622320922020){ref-type="table"}). In this study, 53 (70.7%) of the 75 patients with unstable plaques had a CD4+/CD8+ ratio \>1.725 (χ^2^ = 11.497, *p* \< 0.01). Patients with a CD4+/CD8+ ratio \>1.725 had an increased risk of plaque instability compared with patients with a CD4+/CD8+ ratio \<1.725 \[odds ratio (OR) = 2.679, 95% confidence interval (CI): 1.497--4.794\].

![ROC analyses for the predictive efficacy of CD4+/CD8+ ratio for plaque instability.\
ROC, receiver operating curve.](10.1177_2040622320922020-fig3){#fig3-2040622320922020}

###### 

Association between patient characteristics and the prevalence of plaque vulnerability: results of binary logistic regression analysis.

![](10.1177_2040622320922020-table4)

  independent variables           OR      95% CI           *p* value
  ------------------------- ----- ------- ---------------- -----------
  CD4+/CD8+ ratio \>1.725   No    1                        
                            Yes   2.651   (1.474--4.768)   0.001
  Prior stroke              No    1                        
                            Yes   2.960   (1.380--6.348)   0.005

Outcome {#section19-2040622320922020}
-------

Of 266 patients, 23 suffered from MACE and 7 died during a 1-year follow-up. The Kaplan--Meier estimate for all-cause mortality and MACE showed no significant differences in the lower CD4+/CD8+ ratio group compared with the higher CD4+/CD8+ ratio group (all-cause mortality, 2.5% *versus* 2.8%, *p* = 0.858; MACE, 7.4% *versus* 9.7%, *p* = 0.488; [Figures 4](#fig4-2040622320922020){ref-type="fig"} and [5](#fig5-2040622320922020){ref-type="fig"}). However, after correcting for smoking in a Cox regression analysis, prior stroke, ruptured plaque, CD4+/CD8+ ratio, and hemoglobin were not predictive (all *p* \> 0.05), but levels of LDL were statistically significant for MACE \[hazard ratio (HR) = 2.26; 95% CI, 1.039--4.915, *p* = 0.04\] and all-cause mortality (HR = 2.66; 95% CI, 1.068--6.623, *p* = 0.036).

![The Kaplan--Meier analysis from MACE.\
MACE, major adverse cardiovascular event.](10.1177_2040622320922020-fig4){#fig4-2040622320922020}

![The Kaplan--Meier analysis from all-cause mortality.](10.1177_2040622320922020-fig5){#fig5-2040622320922020}

Discussion {#section20-2040622320922020}
==========

In this retrospective study, we found that CD4+/CD8+ ratio correlated with coronary plaque instability in patients with UAP and could predict plaque rupture and TCFA. These findings suggest that CD4+/CD8+ ratio may represent a cost-effective marker for risk stratification in patients with UAP.

The current immune response theory of atherosclerotic lesions suggests that T cells exist in atherosclerotic plaques in experimental animals and humans,^[@bibr23-2040622320922020]^ and there is evidence of different T cell subsets in coronary plaques.^[@bibr24-2040622320922020][@bibr25-2040622320922020][@bibr26-2040622320922020][@bibr27-2040622320922020]--[@bibr28-2040622320922020]^ Multiple studies have shown that CD4+T cells are involved in the induction and regulation of atherosclerosis,^[@bibr29-2040622320922020][@bibr30-2040622320922020][@bibr31-2040622320922020][@bibr32-2040622320922020]--[@bibr33-2040622320922020]^ and these studies also confirm that CD4+/CD8+ ratio was significantly correlated with LDL levels. Furthermore, LDL is also an important factor in the progression of coronary atherosclerosis, and the positive correlation between CD4+/CD8+ ratio and LDL was also confirmed in our study. It is undeniable that LDL is related closely to the progression of coronary plaque, but the vulnerability of coronary plaque is not completely dependent on LDL, such as unstable calcification nodules, and there is a high risk of plaque rupture. Many patients with coronary plaque instability are detected by OCT, even if they have no history of smoking, hypertension, diabetes, dyslipidemia or any other traditional coronary heart disease risk, so we sought a new indicator to predict coronary plaque instability.

Recent reports suggest that CD8+ T cells are also important regulatory factors involved in atherosclerosis.^[@bibr34-2040622320922020][@bibr35-2040622320922020][@bibr36-2040622320922020]--[@bibr37-2040622320922020]^ Immunohistochemical staining of CD3, CD4, and CD8 showed progressive T cell accumulation during atherosclerosis, the early stages of which were mainly diffuse cytotoxic T cell infiltration, but increasing numbers of T helper cells were found during disease progression, leading to an elevated CD4+/CD8+ ratio.^[@bibr38-2040622320922020],[@bibr39-2040622320922020]^ Previous studies have found that the number of T lymphocytes in the blood and lymph nodes of patients with atherosclerosis and the ratio of CD4+/CD8+ were different. In this study, the ratio of CD4+/CD8+ T cells and coronary plaque instability was detected in the peripheral blood of patients in a predictive manner.^[@bibr34-2040622320922020],[@bibr38-2040622320922020]^

Coronary atherosclerosis is a chronic process of development; we know that UAP is caused mainly by the development of atherosclerotic plaques in coronary arteries, such as ulcers, erosion, rupture, etc., which leads to an inflammatory response in the vascular intima or lumen blockage. Patients with UAP are more likely to have acute MI, and the probability of cardiovascular events is increased. We therefore screened UAP patients with coronary plaque progression for plaque instability or even plaque rupture. In this study, we found that the ratio of CD4+/CD8+ increased with instability of plaques, further validating the above studies.^[@bibr34-2040622320922020],[@bibr38-2040622320922020],[@bibr39-2040622320922020]^

Recently, in one study, Gao and his team confirmed that the Chinese elderly patients with ACS in the peripheral blood CD4+/CD8+ ratio is increased significantly compare to stable angina pectoris patients. ACS patients showed a significantly increased CD4+/CD8+ ratio, which was involved in the progress of coronary artery plaque,^[@bibr11-2040622320922020]^ but only based on the clinical diagnosis of ACS in the study. We know that in the real world, for patients with angina pectoris the situation can be quite different, with many interfering factors making the diagnosis of stable or unstable angina pectoris difficult. We therefore used the most direct and ideal intravascular imaging technique, OCT, to diagnose plaque instability. In our study, the correlation between plaque characteristics confirmed by OCT and the ratio of CD4+/CD8+ cells was then compared. CD4+/CD8+ ratio was found to be an predictor of coronary plaque instability in patients with UAP.

We also followed the all patients for 1 year, with telephone and outpatient follow up being conducted at the 1st, 3rd, 6th and 12th months after the operation. Postoperative anti-platelet aggregation drug therapy was standardized, and CAG review was conducted at the 13th month. It was found that CD4+/CD8+ ratio had no significant statistical significance on patient MACE or death. However, the survival time of the group with a high CD4+/CD8+ ratio was lower than that of the group with a low CD4+/CD8+ ratio, although patients' prognosis was affected by various other factors. We will await the 3-year follow-up information to further elucidate any role of CD4+/CD8+ ratio in patient survival.

In our study, most MACE incidences in our higher CD4+/CD8+ ratio group occurred in the first 6 months, and the probability of MACE in months 6--12 was almost identical in both groups. We can assume that PCI can be optimized under precise guidance by OCT, while the early detection of plaque instability may lead to personalized post-operative treatment, such as intensive statin therapy and antithrombotic therapy. After individualized treatment, the prognosis of patients with unstable plaques is not significantly different from that of patients with stable plaques. Therefore, early prediction of coronary plaque instability in patients with UAP is of utmost importance for PCI and post-operative treatment regimens. Our findings further highlight the importance of correctly predicting diagnosis and optimizing treatment. We emphasize the need for early detection and individualized treatment to achieve survival benefits. We know that, in China, some basic hospitals lack OCT devices, even in large medical or cardiology centers because OCT examination is expensive. This examination method has further drawbacks, such as the need for enhanced contrast, specially trained professional technical personnel, limitations of blood vessel lumen diameter, and low penetration. Despite these, OCT examination remains vastly superior to other intravascular examinations. Therefore, when OCT cannot be used because of the limitations detailed above, the CD4+/CD8+ ratio in the peripheral blood can be detected to predict coronary plaque instability, so as to optimize personalized treatment and reduce the MACE rate.

Several limitations should be recognized in this study. First, this study was a single-center retrospective observational study. Secondly, we observed the coronary artery plaques of patients with targeted lesions and did not analyze predictors of the composition of non-target lesions. Furthermore, this study only included UAP patients with successful PCI, so the results could not be extended to all ACS patients. Finally, prognostic survival analysis was based on multi-factor interventions, such as smoking, lifestyle, nutrition, and exercise habits, that might affect mortality, but this information was not available in the data, and the small sample size limited the predicted results.

Despite these limitations, our research also has a number of strengths. Most reports on the prediction of atherosclerotic plaque characteristics by lymphocytes comprise studies of the aorta, carotid and renal arteries, and animal experiments, but there are few studies regarding the direct prediction of coronary plaque. Our study directly predicted the characteristics of coronary plaque in UAP patients by calculating the CD4+/CD8+ T lymphocyte ratio. Extravascular ultrasound, angiography, intravascular ultrasound, pathological biopsy, and other techniques are most commonly used to define the characteristics of plaques; however, studies on the relationship between the determination of atherosclerotic plaque and CD4+/CD8+T lymphocyte ratio by OCT have not been previously reported. It is of great scientific and clinical significance to predict the instability of coronary atherosclerotic plaques for efficient prevention and treatment. This study is thus both innovative and practical.

Conclusion {#section21-2040622320922020}
==========

Higher CD4+/CD8+ ratio is associated with higher risk of plaque instability, as confirmed by OCT in our cohort of UAP patients. CD4+/CD8+ ratio was not an independent predictor of 1-year MACE and all-cause mortality.

We deeply appreciate Ling Lin for remote monitoring and data collection throughout the study. We thank Xiao-Fei Gao for analysing data. We also thank Gillian Campbell, from Liwen Bianji, Edanz Group China, for editing the English text of a draft of this manuscript.

**Author contributions:** ZJJ and LS designed the statistical analysis, led the interpretation of research findings, and revised the manuscript. CDY and KXQ participated in design, data collection, dataset generation, statistical analysis, and drafting of the manuscript. All of the authors read and approved the final manuscript.

**Funding:** The authors disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This work was supported by a project grant from Science and Technology Program of Taicang City, China (No.TC2018JCYL25).

**Conflict of interest statement:** The authors declare that there is no conflict of interest.

**Ethics approval and consent to participate:** The study was approved by the institutional ethics committee of the First People's Hospital of Taicang (No.TCYY2019-KY0013) and was carried out in accordance with the guidelines of the Declaration of Helsinki. Written informed consent was formally obtained from all participants.

**ORCID iD:** Dayang Chai ![](10.1177_2040622320922020-img1.jpg) <https://orcid.org/0000-0002-3389-5555>

[^1]: These authors contributed equally to this work.
