Small Dense Low Density Lipoprotein and Cardiovascular Events in Patients With Acute Coronary Syndrome Undergoing Percutaneous Coronary Intervention: A Cohort Study From China

Background: Residual risk remained signicant despite effective low density lipoprotein cholesterol (LDL-C) lowering treatment. Small dense low density lipoprotein cholesterol (sdLDL-C) as part of LDL-C has been found to be predictor of coronary heart disease (CHD) and cardiovascular (CV) events in patients with stable CHD independently of LDL-C. However, to date, few studies have explored the role of sdLDL-C in patients with acute coronary syndromes (ACS) undergoing percutaneous coronary intervention (PCI). Accordingly, this study aimed to evaluate the association of sdLDL-C with CV events in patients with ACS undergoing PCI. Methods: Patients hospitalized with ACS undergoing PCI were enrolled and followed up for 18 months. The risk of sdLDL-C for CV events was compared according to sdLDL-C quartiles. The primary outcome was the composite of death, nonfatal myocardial infarction, nonfatal stroke and unplanned repeat revascularization. A Cox proportional hazards regression model was performed to estimate the risk of CV events. Subgroup analysis according to diabetes status and dichotomized low-density lipoprotein cholesterol (LDL-C) and triglyceride (TG) level based on median value were performed separately for cardiovascular risk. Results: A total of 6092 patients were included in the analysis (age: 60.2±10.13 years, male: 75.3%, BMI: 25.9±3.33 kg/m 2 , dyslipidemia: 74.1% and diabetes: 44.5 %). During 18 months of follow-up, 320 (5.2%) incident CV events occurred. Compared to the lowest sdLDL-C quartile group, patients in the highest quartile had a greater risk of CV events after multivariable adjustment (HR: 1.92; 95% CI: 1.37-2.70). In the subgroup analyses, this greater risk remained signicant in patients, regardless of high or low LDL-C or TG (dichotomized by the median value) and diabetes status. Conclusions: Patients with elevated sdLDL-C


Background
Death rates related to cardiovascular disease (CVD) have decreased, but it was still a leading cause of deaths as a result of aging, obesity and diabetes mellitus (DM) 1 . Dyslipidemia are widely recognized as a contributing risk factor for coronary heart disease (CHD) and stroke 2-3 . However, residual risk remained signi cant despite effective low density lipoprotein cholesterol (LDL-C) lowering treatment in accordance with current guideline, including statin, ezetimibe and proprotein convertase subtilisin/kexin type 9 (PCSK9) antibodies 4-6 . In addition, LDL-C comprised of a heterogeneous lipoprotein particles including large, more buoyant LDL particles (lb-LDL) and small dense LDL (sdLDL) particles 7-8 , which could change independently from LDL-C 9 . Compared with lb-LDL, sdLDL-C had higher ability for penetration into arterial wall, lower binding a nity for receptor, longer plasma half-life and easier to oxidation 10 . Due to the atherogenic properties of sdLDL-C, using LDL-C alone may underestimate actual risk in individuals when we evaluated cholesterol-related CHD risk 11 . Therefore, risk assessment may be bene t from sdLDL-C measurement.
sdLDL-C has been found to be associated with increased risk for the development of CHD among the healthy participants with high or low risk of CVD 12-13 and increased risk for cardiovascular (CV) events in patients with stable CVD 14 . However, to date, few studies have explored the role of sdLDL-C in patients with acute coronary syndromes (ACS) undergoing percutaneous coronary intervention (PCI). Accordingly, this study aimed to evaluate the association of sdLDL-C with CV events in patients with ACS undergoing PCI.

Study Design and Patients
In this cohort study, we consecutively included 9282 patients hospitalized for ACS and PCI from a top-ranked cardiovascular hospitals in China from January 2018 to December 2018. The main exclusion criteria were a body mass index (BMI) > 45 kg/m 2 , left ventricular ejection fraction (LVEF)<30%, severe hepatic and renal insu ciency (eGFR<30 ml/min), suspected familial hypertriglyceridemia (triglyceride ≥5.65 mmol/L), brate use, and malignancy diseases. The study protocol was approved by the institutional review board of Beijing Anzhen Hospital, Capital Medical University with a waiver of informed consent. Participants' personal details were concealed.

Measurements
The data including patient demographics, smoking status, past medical history, laboratory results, PCI data, and medical treatments were collected from medical and nursing records. Blood samples were drawn after an overnight at least 8 hours fasting. For patients with STEMI, blood samples were collected immediately on admission. Lipid pro le were measured on the same day of collection. Fasting plasma glucose (FPG), glycosylated hemoglobin (HbA1c), Total cholesterol (TC) and triglyceride (TG) were measured by standard laboratory techniques. The measurement of sdLDL-C was performed in an automated homogeneous assay (Denka Seiken Co., Ltd., Tokyo, Japan) and analyzed on a Hitachi 7180 automatic analyzer 15 .

Treatment and Procedure
All medication and operation were performed according to the guidelines 16 . All patients received aspirin and clopidogrel or ticagrelor prior to the procedure and 70-100 IU/kg unfractionated heparin intraoperative. A radial approach was used by 6 or 7 F guiding catheters. Second-generation drug eluting stents was implanted following appropriate predilation. The type of stent, fractional ow reserve (FFR), intravascular ultrasound (IVUS) and optical coherence tomography (OCT) were at the discretion of the interventionalist.

Outcomes
All patients were followed up to incident primary outcome or for 18 months by telephone and only index events were included in the analysis. All events were recorded by two telephone records and inconsistent events were a rmed by a third record. Hospital records were also screened for clinical events. The primary outcome was the composite of death, nonfatal MI, nonfatal stroke or unplanned repeat revascularization.
Death was de ned as all causes of death regardless of cause of death 17 . Myocardial infarction was de ned as the criteria for the fourth universal de nition 18 . Stroke was adjudicated by the presence of as acute cerebral infarction established by the imaging or typical symptoms 19 . Unplanned repeat revascularization was de ned as repeat PCI or surgical bypass of any segment of the target vessel or target lesion 17,19 . Unstable angina was de ned as rest, new-onset, or worsening angina without cardiac enzyme elevation 20 .
Obesity was de ned as BMI≥ 28 kg/cm 2 . Hypertension was de ned as a systolic blood pressure ≥140 mm Hg, diastolic blood pressure ≥90 mm Hg, or use of antihypertensive medications 21 . Diabetes mellitus was de ned as taking hypoglycemic agents, a fasting (≥8 hours) blood glucose of ≥7.0 mmol/L, or a nonfasting blood glucose of ≥11.10 mmol/L 22 . Dyslipidemia was de ned as a fasting HDL-C 40mg/dL, TC > 200mg/dL, LDL-C > 130mg/dL, TG > 150mg/dL or use of any lipid-lowering drug.

Statistical Analyses
Baseline patient characteristics were presented according to baseline sdLDL-C quartiles. Continuous variables were expressed as the mean ± standard deviation (SD) or median (interquartile range). The differences were estimated by one-way Analysis of Variance (ANOVA) for normal data or Kruskal-Wallis tests for non-normal distribution data followed by Bonferroni's post hoc test. Categorical variables are expressed as numbers (percentage) and compared with a χ2 test or Fisher's exact test.
Survival analyses were performed using Kaplan-Meier methods, log rank tests, and Cox proportional hazards regression models with backward stepwise selection methods according to baseline sdLDL-C quartiles. The following three models were adjusted for multivariate analysis: Model 1: age, gender, BMI; Model 2: model 1 + smoking status, hypertension, previous MI, previous stroke, syntax score, number of stents, total length of stents. Model 3: model 2 + HDL-C, high sensitivity C-reactive protein (hs-CRP), lipid-lowering medication use.
Additionally, subgroups strati ed according to diabetes status and dichotomized LDL-C and TG level (based on median value) were analyzed separately for cardiovascular events. Subgroup analyses were also conducted in each subgroup of age, sex, obesity, hypertension, previous MI, ACS type, hs-CRP. The heterogeneities in the relationship between subgroups were evaluated by adding multiplicative interaction terms in the multivariable models. In addition, we present the comparisons of baseline characteristics between participants who were eligible or not for the nal analyses to test whether missing data would potential bias the results. All statistical analyses were performed using SPPS 24.0 software (IBM Corp., Armonk, NY, USA). A two-tailed value of P<0.05 was required for statistical signi cance.

Results
There were 9282 patients who met the inclusion criteria, of whom 3190 were excluded due to loss to follow-up (n= 781) or meet the major exclusion criteria (n= 2409). Finally, a total of 6092 patients were included in the analysis. Additional le 1: Figure S1 shows the patients' owchart. Comparison of baseline characteristics between participants who were eligible or not for the nal analyses was displayed in Additional le 1: Table   S1. Compared with the lost participants, eligible participants were signi cantly older. Though statistically signi cant, differences in BMI, current smoker and hypertension were not clinically relevant. Additionally, there was no statistically signi cant difference in lipid parameters.

Baseline Characteristics
The sdLDL-C had an approximately normal distribution with a mean of 28.2±13.16 mg/dl (Additional le 1: Figure S2). Among high or low LDL-C (de ned by the median of LDL-C) group of patients, wide variation in sdLDL-C was observed (Additional le 1: Figure S3a-b). With respect to diabetes status, signi cant differences of sdLDL-C were found (p=0.002, Additional le 1: Figure S3c-d). Baseline characteristics data presented in Table 1. Among the included patients, there were 4586 (75.3%) male and mean ± SD age was 60.2±10.13 years and BMI 25.9±3.33 kg/m2. Diabetes and dyslipidemia was seen in 44.5% (2712) and 74.1% (4512) of patients, respectively. For the ACS type, 86.8% were unstable angina and the others were acute myocardial infarction (AMI). Among 2712 subjects with diabetes, 2171 were treated with oral hypoglycemic agents or insulin. Overall, almost all of patients were taking at least one prescription lipid-lowering medication and 98.4% were taking a statin with or without ezetimibe (20%). Of the analyzed coronary artery lesions, 16.9% were in left main artery, 59% were multivessel lesions, 15.2% were CTO lesion and the mean syntax score was 14±7.49. FFR, IVUS and OCT were not widely practiced. The comparison of baseline characteristics according to sdLDL-C quartile are also shown in Table 1 Relationship sdLDL-C of with cardiovascular events A total of 320 (5.2%) incident cardiovascular events occurred during 18 months of follow-up. Hazard ratios for incidence of CV events by quartile of sdLDL-C are presented in Table 2 Finally, strati ed analysis by age, sex, obesity, hypertension, previous MI, ACS type, hs-CRP was conducted as shown in Fig.3. The multivariable-adjusted risk for CV events tended to be higher in subjects with highest quartile of sdLDL-C than in those with lowest quartile of sdLDL-C with or without statistically signi cant in all of subgroups analyzed in model 3. No signi cant interaction between sdLDL-C and these subgroups was observed. (all P values for interaction 0.05).

Discussion
In this study, we report that patients with a high sdLDL-C were more likely to be have a high risk of CV events in Chinese patients with ACS undergoing PCI. This higher risk remained signi cant in patients regardless of diabetes status, LDL-C and TG levels. To our knowledge, our study is the rst large-scale trial estimating the association between sdLDL-C and the risk of CV events in patients with ACS undergoing PCI. Actually, there may be no signi cant increase in LDL-C levels in some patients with diabetes or metabolic syndrome 23-24 .
Therefore, it is clinically valuable to measure sdLDL-C for estimating the risk of CV events in patients with ACS undergoing PCI for its highly atherogenic properties. Overall, sd-LDL-C was favorable for distinguishing patients with high risk of CV events beyond LDL-C level.
There are several observational studies reported the associations between sdLDL-C and subclinical atherosclerosis 13, [25][26]27 . In a small prospective study, an increase of sdLDL-C was shown to predict intima media thickness (IMT) and insulin resistance 28 . Results from a trial with 816 patients without diabetes or CVD showed sdLDL-C can independently predict arterial stiffness progression 29 .
Moreover, several studies have indicated that sdLDL-C was independently associated with the progression of carotid atherosclerosis 13,25-26 . The Suita Study followed 2,034 general urban Japanese residents for an average of 11 years and have suggested that the highest quartile of sdLDL-C level was associsated with a 3.3fold higher risk of incident CHD compared with the lowest quartile (95% CI, 1.3-8.2) 30 . The Multi-Ethnic Study of Atherosclerosis, which included 4387 USA patients and followed up for an average of 8.5 year, demonstrated that adjusted hazard ratios for incident CHD between extreme quartile of sdLDL-C was 2.4 11 .
The ARIC study, which included 11,419 patients and followed up for 11-year, demonstrated that sdLDL-C was associated with incident CHD 31 . And the association remained signi cant regardless of LDL-C levels in these studies. Meanwhile, Duran EK et al. also indicated that sdLDL-C affected atherogenesis independently of LDL-C and hs-CRP 32 , which was consistent with results of the above mentioned research. Furthermore, sdLDL-C predicted the CHD risk not only in patients at high cardiovascular risk 12 , but also at low cardiovascular risk according to LDL-C values 31 , therefore providing additional value for better risk assessment.
In addition, several studies reported the association between sdLDL-C and coronary stenosis severity or prognosis in patients with CAD. Koba S et al. recruited 482 stable CHD patients and 389 patients without CHD and indicated sdLDL-C level was more e cacious in predicting coronary severity 33 . A cohort study from china suggested that increased sdLDL-C were associated with higher risk of CV events in patients with diabetes and stable CAD 14 . Therefore, the current study might provide valuable further information on the relationship of sdLDL-C and CV events in patients with ACS undergoing PCI. Also, several studies have shown sdLDL-C was closely related to stroke 26 . A cross-sectional study included a total of 754 acute ischemic stroke (AIS) patients indicated that sdLDL-C levels was an independent predictor of NIHSS scores and the severity of cerebral artery calci cation 34 . A study enrolled 530 elderly patients hospitalized within 48 h after stroke suggested high sdLDL-C were associated with a greater risk for ischemic stroke 35 . Another study recruited 355 AIS and 171 non-AIS patients and found that elevated sdLDL-C was associated with a higher incidence of AIS 36 .
In this study, we also report that sdLDL-C was associations with increased risk of CV events regardless of diabetes status, which seems to be not very consistent with previous study. The Multi-Ethnic Study of Atherosclerosis demonstrated that elevated sdLDL-C was an independent risk factors for CHD only in nondiabetic patients but not in diabetes patients 11 . A cohort study from china indicated that elevated sdLDL-C was associated with greater risk of CV events in DM patients with stable CAD but not non-diabetic patients 14 . There were several limits for these studies. First, TG had a strong relationship with sdLDL-C 9 , which means the inclusion of both variables in the nal multivariable regression model may bias the results.
Second, the small sample size in the subgroup may explain the overall positive results but negative in subgroup analysis in these studies. Therefore, the negative result should not be used as a de nite conclusion.
Actually diabetic and non-diabetic patients accounted for almost half of the patients in the nal analysis in our study, which means that our research may come up with positive results. In another study, the relationship between sdLDL-C and CHD was signi cant regardless of diabetes ststus, which was consistent with our study 12 . Moreover, patients with DM was likely to have smaller LDL 37 . sdLDL-C had strong association with metabolic syndrome 38 , insulin resistance 9,39 and subclinical diabetes status 40 .
The multiple characteristics of sdLDL-C, including greater propensity for endothelial penetration, lower a nity with LDL receptors, longer time in circulation and greater susceptibility to desialylation, glycation and oxidation, played an important role in the atherosclerosis 31 . Krychtiuk et al. showed that sdLDL-C was associated with an increase of non-classical monocytes (NCM; CD14+CD16++) and a decrease of classical monocytes (CM; CD14++CD16-) 41 . In a prospective study within the Women's Health Study, sdLDL-C was a strong risk factor for MI but not peripheral artery disease (PAD), which indicated that elevated sdLDL-C may be relevant to instability and vulnerability plaque rather than the more stable plaque 32 . Compared with LDL-C, sdLDL-C are more vulnerable to oxidative and easily engulfed by macrophages 42-43 , which strongly correlated with plaque instability in coronary 44 and carotid artery disease 45-46 . This study has several limitations to consider. First, our results may be affected by residual confounding in this observational study. Second, there may be a signi cant decrease in sdDL-C in patients with AMI, but our study still found a close relationship between preoperative sdLDL-C concentration and prognosis. In addition, we collected blood samples immediate after admission to reducing the effect on sdLDL-C. Third, timedependent analysis was not available for only once measurement of sdLDL-C at baseline. Fourth, unable to obtain follow-up information of medical treatments may bias the results. Finally, current research ndings may not be generalizable to other ethnic groups because the participants in our study were only Chinese. Therefore, our ndings should be con rmed in other ethnic populations.

Conclusions
Among Chinese patients with ACS undergoing PCI, patients with high sdLDL-C were at a higher risk of developing CV. These ndings may help identify high-risk patients with cardiovascular events beyond LDL-C and those patients may bene t from more aggressive therapy.