In-stent restenosis estimation following carotid artery stenting: The robust predictive value of atherogenic index of plasma and other non-traditional lipid profiles

Abstract

Objective

Atherosclerotic carotid artery stenosis is a significant contributor to ischemic strokes, and carotid artery stenting (CAS) has emerged as a pivotal treatment option. However, in-stent restenosis (ISR) remains a concern, impacting the long-term patency of CAS. This study aimed to investigate the predictive value of non-traditional lipid profiles, including the atherogenic index of plasma (AIP), in ISR development.

Methods

This retrospective single-center study involved patients presenting at a tertiary healthcare facility with severe carotid artery disease between 2016 and 2020 who subsequently underwent CAS. A total of 719 patients were included in the study. The study cohort was divided into ISR and non-ISR groups based on restenosis presence, confirmed by angiography following ultrasonographic follow-up assessments. Non-traditional lipid indices, such as AIP, atherogenic index (AI), and lipoprotein combined index (LCI), were evaluated along with traditional risk factors.

Results

During a 24-month follow-up, ISR occurred in 4.03% of patients. To determine the predictors of restenosis, three different models were constructed in multivariate analysis for non-traditional lipid indices. Multivariate analysis revealed AIP as a robust independent predictor of ISR (OR: 4.83 (CI 95 % 3.05–6.63, p < .001). Notably, AIP demonstrated superior predictive accuracy compared to AI and LCI, with a higher Area Under the Curve (AUC) of 0.971.

Conclusion

Non-traditional lipid profiles, especially AIP, were found to be associated with an increased risk of ISR and may serve as predictors of ISR in patients undergoing CAS.

Keywords

Carotid artery stenosis carotid artery disease carotid artery stenting in-stent restenosis lipid profiles carotid stent restenosis atherogenic index of plasma

Introduction

Approximately 10%–15% of ischemic strokes are caused by atherosclerotic carotid artery stenosis.¹ Carotid artery stenting (CAS), positioned as an alternative to carotid endarterectomy (CEA), has established itself as a standard therapeutic approach in managing symptomatic or significantly asymptomatic carotid stenosis.² However, an important factor that impacts the long-term benefit and safety profile of CAS is in-stent restenosis (ISR), which can occur at rates ranging from 3.3% to 21% during the follow-up period of 6 months to 2 years.^3–5 The female gender, diabetes, hyperlipidemia, and smoking are regarded as risk factors for restenosis following CAS.⁶ While early restenosis after CAS is associated with neo-intimal hyperplasia, commonly seen in first year, late restenosis is linked to neo-atherosclerosis.^7,8 Neo-atherosclerosis aligns with the pathological characteristics of conventional atherosclerosis; therefore, the risk factors are shared.⁹

Dyslipidemia is acknowledged as a significant contributor to the development of ISR.⁶ Decreased levels of high-density lipoprotein cholesterol (HDL-C), coupled with increased levels of total cholesterol (TC), low-density lipoprotein cholesterol (LDL-C), and triglycerides (TG), actively contribute to the progression of atherosclerosis.^10,11 Recent investigations have demonstrated that comprehensive lipid indices, including non-HDL-C, TC/HDL-C, LDL-C/HDL-C, atherogenic index (AI), and lipoprotein combined index (LCI), which represent non-traditional lipid profiles, offer superior predictive value for coronary artery disease (CAD) compared to traditional lipid profiles.^12,13 The atherogenic index of plasma (AIP), a novel comprehensive lipid index capable of effectively encompassing the equilibrium between atherogenic and anti-atherogenic elements, has demonstrated substantial prowess as a predictor of CAD risk.^14–16 Furthermore, recent studies have shown a relationship between AIP and carotid stenosis as well as stroke.^17–19 However, there is no adequate information available regarding the predictive value of non-traditional lipid profiles on the development of ISR in patients undergoing CAS. Therefore, our research is focused on examining how non-traditional lipid profiles impact the occurrence of carotid ISR.

Materials and methods

Study design and population

This retrospective single-center study comprised patients who presented at a tertiary healthcare facility with a diagnosis of atherosclerotic carotid artery disease between 2016 and 2020 and subsequently underwent CAS. A total of 853 patients were initially considered, and after applying inclusion and exclusion criteria (depicted in Figure 1), 719 patients were included in the study. The study cohort was stratified into two subgroups (ISR and non-ISR groups) based on the presence of restenosis, confirmed by angiography following ultrasonographic follow-up assessments. Exclusion criteria encompassed the following: (1) insufficient data availability, (2) the presence of non-atherosclerotic arterial stenosis (e.g., cerebral arteritis), (3) history of CEA, and (4) severe comorbidities such as advanced heart, lung, kidney disease, or malignancies expected to result in mortality within the 6-month follow-up period. Demographic information, clinical profiles, and laboratory results of all participants were extracted from the hospital’s electronic health records. The baseline values for laboratory parameters were determined from the national database, reflecting the patients’ status before undergoing the CAS procedure. This study adhered to the principles of the Declaration of Helsinki and received ethical approval from the Kartal Kosuyolu Training and Research Hospital. Due to the retrospective nature of this case–control study, which utilized patient medical record data, written informed consent was not obtained from the participants.

Figure 1.

Flowchart of study population.

Definitions

ISR was defined by DSA as the presence of ≥50% stenosis within the treated vessel, in accordance with the NASCET criteria.²⁰ Hypertension (HT) was defined as systolic pressure ≥140 mm Hg and/or diastolic pressure ≥90 mm Hg and/or the use of antihypertensive medications.²¹ Diabetes mellitus (DM) was defined according to the diagnostic criteria established by the American Diabetes Association, which encompassed fasting plasma glucose ≥126 mg/dl, HbA1C ≥6.5%, random plasma glucose ≥200 mg/dl, or the utilization of antidiabetic medications.²² Hyperlipidemia (HL) was defined as total cholesterol levels >200 mg/dl, low-density lipoprotein cholesterol (LDL-C) levels >116 mg/dl, triglyceride levels >150 mg/dl, or the use of lipid-lowering medications.²³ Current smokers or individuals with a history of tobacco use were categorized as a smoker.

Data collection and measurement of non-traditional lipid profiles

Demographic and clinical characteristics of the patients, along with laboratory data including complete blood count and blood biochemistry, were extracted from the hospital database system and electronic health records. Blood samples were collected from the antecubital vein, before CAS procedure, and were documented in the medical reports. Biochemical measurements were determined using a molecular analyzer (Roche Diagnostics, Mannheim, Germany).

All lipid parameters’ concentrations are expressed in mmol/L. Non-HDL-C is defined as the difference between TC and HDL-C. The AI is defined as the ratio of non-HDL-C to HDL-C. The LCI is defined as the ratio of TC multiplied by TG and LDL to HDL-C. The AIP is defined as the base 10 logarithm of the ratio of the concentration of TG to HDL-C.^14–16,24

Procedure of CAS

Patients received standard daily dual antiplatelet therapy (acetylsalicylic acid 100 mg and clopidogrel 75 mg) at least 5 days before the procedure. All procedures were conducted using the femoral approach with the Seldinger method. Following the confirmation of the target stenosis through angiography, an 8F guiding catheter was advanced to the common carotid artery proximal to the stenosis. Systemic heparinization was consistently maintained throughout the entirety of the procedure. After a 0.014-inch microwire was advanced through the stenotic lesion under roadmap fluoroscopy guidance, an embolic protection device was released. Subsequently, a self-expandable stent, such as a closed-cell stent (WALLSTENT; Boston Scientific, Natick, MA, USA or Xact; Abbott Vascular, Redwood City, CA, USA) or an open-cell stent (Acculink; Abbott Vascular, Redwood City, CA, USA or Protégé; EV3 Endovascular Inc, Plymouth, MN, USA), appropriately sized, was deployed. In cases of severe stenosis, pre-dilation was performed. In cases where residual stenosis was present, post-dilatation was conducted using a 5.0 × 15 mm non-compliant balloon. Comprehensive angiography was conducted immediately after stenting to assess any residual stenosis. Following the procedure, all patients were prescribed dual antiplatelet therapy.

Follow-up assessments

All patients received follow-up evaluations using duplex ultrasound at the hospital’s outpatient clinic at 3, 6, 12, and 24 months following the CAS procedure. Those individuals who were suspected of having ISR underwent additional assessment through digital subtraction angiography (DSA).

Statistical analysis and modeling

Continuous research data were expressed as mean and standard deviation values, whereas categorical data were expressed as absolute and percentage values. Independent samples t test and Mann–Whitney U test were used for the comparisons of independent continuous data groups, and Pearson’s chi-squared or Fisher’s exact test was used for the comparisons of categorical data groups. Crude univariable and adjusted multivariable regression analyses were used to determine the independent predictors of the dependent (ISR) variable. Model’s coefficients were represented using odds ratio (OR), and confidence interval (CI) was taken as 95 %. For all statistical analyses, 2-tailed probability (p) values less than 0.05 were deemed to indicate statistical significance. All statistical analyses were performed using Jamovi and R 4.01 software (Vienna, Austria) with “ggplot,” “Hmisc,” and “rms” packages.

Results

A total of 853 patients initially treated with CAS were included in the study. Patients who met the exclusion criteria were subsequently excluded from the analysis. Ultimately, 719 patients (comprising 189 women (26.5 %)) were subjected to analysis in this study. Over the 24-month follow-up period, ISR which was angiographically confirmed was observed in 29 patients (4.03%). The demographic and clinical characteristics of patients with and without ISR are presented in Table 1. Mean age of the study population did not differ between the groups (65.9 ± 7.18 years). While HT and antiplatelet usage were lower in the ISR group, ezetimibe usage was lower in the non-ISR group (p = .049, p = .002, and p = .003, respectively).

Table 1.

Comparison of baseline clinical and demographic characteristics of study population according to in-stent restenosis (ISR).

Variables	All patients (N = 719)	ISR (n = 29, 4.03%)	Non-ISR (n = 690, 95.96%)	p
Gender (female)	189 (26.5 %)	6 (20.0 %)	183 (26.8 %)	0.407
Age (years)	65.9 ± 7.18	66.0 ± 6.90	65.9 ± 7.19	0.963
BMI (kg/m²)	27.6 ± 3.97	28.1 ± 4.09	27.6 ± 3.97	0.325
BSA	1.91 ± 0.17	1.92 ± 0.16	1.91 ± 0.17	0.774
DM, n (%)	304 (42.7 %)	15 (50 %)	289 (42.4 %)	0.409
HT, n (%)	592 (83.1 %)	21 (70.0 %)	571 (83.7 %)	0.049
HL, n (%)	528 (74.2 %)	26 (86.7 %)	502 (73.6 %)	0.110
CAD, n (%)	536 (75.3 %)	22 (73.3 %)	514 (75.4 %)	0.801
PCI history, n (%)	368 (51.7 %)	14 (46.7 %)	354 (51.9 %)	0.574
CABG history, n (%)	200 (28.1 %)	12 (40.0 %)	188 (27.6 %)	0.138
CKD, n (%)	120 (16.9 %)	5 (16.7 %)	115 (16.9 %)	0.978
PAD, n (%)	160 (22.5 %)	9 (30.0 %)	151 (22.1 %)	0.313
Smoking, n (%)	400 (56.2 %)	17 (56.7 %)	383 (56.2 %)	0.956
Alcohol usage, n (%)	32 (4.5 %)	2 (6.7 %)	30 (4.4 %)	0.557
Antiplatelet usage, n (%)
No antiplatelet	40 (5.6 %)	6 (20.0 %)	34 (5.0 %)	0.002
Single antiplatelet	344 (48.3 %)	11 (36.7 %)	333 (48.8%)
Dual antiplatelet	328 (46.1 %)	13 (43.3 %)	315 (46.2 %)
Statin usage, n (%)
No statin	248 (34.8 %)	12 (40.0 %)	236 (34.6 %)	0.594
Low-dose statin	264 (37.1 %)	12 (40.0 %)	252 (37.0 %)
High-dose statin	200 (28.1 %)	6 (20.0 %)	194 (28.4 %)
Ezetimibe, n (%)	8 (1.1 %)	2 (6.7 %)	6 (0.9 %)	0.003
ACEI, n (%)	272 (38.2 %)	9 (30.0 %)	263 (38.6 %)	0.345
Beta blocker, n (%)	424 (59.6 %)	17 (56.7 %)	407 (59.7 %)	0.742
OAD, n (%)	256 (36.0 %)	10 (33.3 %)	246 (36.1 %)	0.760
Cilostazol, n (%)	8 (1.1 %)	0	8 (1.2 %)	0.551
Valsartan, n (%)	80 (11.2 %)	2 (6.7 %)	78 (11.4 %)	0.418

Bold values denote statistical significance at the p<0.005 level.BMI, body mass index; BAS, body surface area; DM, diabetes mellitus; HT, hypertension; HL, hyperlipidemia; CAD, coronary artery disease; PCI, percutaneous coronary intervention; CABG, coronary artery by-pass grafting; CKD, chronic kidney disease; PAD, peripheric arterial disease; ACEI, angiotensin-converting enzyme inhibitors; OAD, oral anti-diabetic; ISR, in-stent restenosis; non-ISR, non-in-stent restenosis.

The comparison of laboratory parameters according to presence of restenosis is shown in Table 2. While TG, non-HDL-C, AIP, Total-C/HDL-C, LDL-C/HDL-C, AI, and LCI were significantly higher in the ISR group, ALT and HDL-C were significantly lower than in the non-ISR group (p < .001, p = .006, p < .001, p < .001, p = .035, p < .001, p < .001, p = .047, and p < .001, respectively).

Table 2.

Comparison of laboratory parameters in study population according to in-stent restenosis.

Variables	All patients (N = 719)	ISR (n = 29, 4.03%)	Non-ISR (n = 690, 95.96%)	p
HbA1c (%)	6.66 ± 1.44	6.54 ± 0.942	6.66 ± 1.46	0.835
Urea (mg/dL)	40.2 ± 17.6	38.4 ± 13.5	40.3 ± 17.7	0.672
Creatinine (mg/dL)	0.96 (0.83 – 1.17)	0.86 (0.84 – 1.22)	0.96 (0.83 – 1.17)	0.772
Sodium (mEq/L)	139 ± 2.88	139 ± 2.54	139 ± 2.90	0.331
Potassium (mmol/L)	4.59 ± 0.42	4.52 ± 0.48	4.59 ± 0.42	0.380
CRP (mg/L)	3.10 (1.15 – 5.70)	3.83 (2.31 – 11.5)	3.10 (1.14 – 5.70)	0.064
Albumin (g/L)	4.40 (4.00 – 4.70)	4.10 (3.80 – 4.50)	4.40 (4.00 – 4.70)	0.086
Uric acid (mg/dL)	5.69 ± 1.80	6.43 ± 2.94	5.65 ± 1.73	0.447
AST (U/L)	18.6 ± 7.13	19.1 ± 5.96	18.6 ± 7.18	0.327
ALT (U/L)	16.4 (12.0 – 21.6)	12.6 (8.72 – 18.2)	16.4 (12.0 – 22.0)	0.047
Total bilirubin (mg/dL)	0.48 ± 0.23	0.45 ± 0.19	0.48 ± 0.23	0.507
WBC count (10³/μL)	8.35 ± 2.40	7.73 ± 0.89	8.38 ± 2.44	0.312
Hb (g/dL)	13.4 ± 2.15	12.7 ± 2.22	13.4 ± 2.14	0.066
Platelet count (10³/μL)	263 ± 73.1	238 ± 64.8	264 ± 73.3	0.160
Traditional lipid profiles
TC (mmol/L)	4.42 ± 1.20	4.89 ± 1.40	4.40 ± 1.19	0.064
LDL-C (mmol/L)	2.42 ± 1.06	2.57 ± 1.41	2.41 ± 1.05	0.521
TG (mmol/L)	1.73 (1.25 – 2.22)	3.07 (2.71 – 3.24)	1.70 (1.20 – 2.05)	<0.001
HDL-C (mmol/L)	1.19 ± 0.25	0.96 ± 0.08	1.20 ± 0.25	<0.001
Non-traditional lipid profiles
Non-HDL-C (mmol/L)	3.24 ± 1.19	3.93 ± 1.38	3.21 ± 1.17	0.006
AIP	0.14 ± 0.23	0.49 ± 0.06	0.13 ± 0.22	<0.001
Total-C/HDL-C	3.85 ± 1.22	5.09 ± 1.45	3.79 ± 1.18	<0.001
LDL-C/HDL-C	2.11 ± 1.03	2.67 ± 1.45	2.09 ± 1.00	0.035
AI	2.85 ± 1.22	4.09 ± 1.45	2.79 ± 1.18	<0.001
LCI	5.94 ± 3.63	9.21 ± 4.65	5.80 ± 3.51	<0.001

Bold values denote statistical significance at the p<0.005 level.HbA1c, glycated hemoglobin; CRP; C reactive protein; AST, aspartate transaminase; ALT, alanine transaminase; WBC, white blood cell; Hb, hemoglobin; TC, total cholesterol; LDL-C, low-density lipoprotein; TG, triglyceride; HDL-C, high-density lipoprotein cholesterol; non-HDL-C, non-high-density lipoprotein cholesterol; AIP, atherogenic index of plasma; AI, atherogenic index; LCI, lipoprotein combined index; ISR, in-stent restenosis; non-ISR, non-in-stent restenosis.

Comparison of carotid artery disease, lesion characteristics, and periprocedural features of carotid stenting in the study population is shown in Table 3. In the ISR group, overlap stenting and residual stenosis were significantly higher than the non-ISR group (4 (13.3 %) versus 20 (3.0 %), p = .002; 13 (43.4 %) versus 13 (2.1 %), p < .001; respectively). Symptomatic carotid artery disease, asymptomatic carotid artery disease, bilateral carotid artery disease, location of stent (right, left, or bilateral), contralateral occlusion, lesion type (calcific, thrombotic, dissected, fibrous, or ulcerating), stent length, predilatation, post dilatation, and cell type of stent (closed or open) did not differ between groups.

Table 3.

Comparison of carotid artery disease, lesion characteristics, and periprocedural features of carotid stenting in the study population according to in-stent restenosis.

Variables	All patients (N = 719)	ISR (n = 29, 4.03%)	Non-ISR (n = 690, 95.96%)	p
Symptomatic carotid disease, n (%)	400 (56.2 %)	21 (70.0 %)	379 (55.6 %)	0.119
Asymptomatic carotid disease, n (%)	312 (43.8 %)	9 (30.0 %)	303 (44.4 %)	0.119
Bilateral carotid artery disease, n (%)	616 (86.5 %)	27 (90.0 %)	589 (86.4 %)	0.568
Location of stent, n (%)
Right carotid artery	320 (44.9 %)	18 (60.0 %)	302 (44.3 %)	0.223
Left carotid artery	272 (38.2 %)	9 (30.0 %)	263 (38.6 %)
Bilateral carotid artery	120 (16.9 %)	3 (10.0%)	117 (17.2 %)
Contralateral occlusion, n (%)	56 (7.9 %)	3 (10.0 %)	53 (7.8 %)	0.657
Lesion type, n (%)
Calcific	352 (49.9 %)	19 (63.3 %)	333 (48.8 %)	0.120
Thrombotic	120 (16.9 %)	7 (23.3 %)	113 (16.6 %)	0.333
Dissected	24 (3.4 %)	0	24 (3.5 %)	0.296
Fibrous	576 (80.9 %)	26 (86.7 %)	550 (80.6 %)	0.412
Ulcerating	40 (5.6 %)	4 (13.3 %)	36 (5.3 %)	0.061
Stent length, n (%)	35.1 ± 6.24	35.2 ± 5.09	35.1 ± 6.29	0.706
Overlap stenting, n (%)	24 (3.4 %)	4 (13.3 %)	20 (3.0 %)	0.002
Predilatation, n (%)	72 (10.2 %)	0	72 (10.7 %)	0.059
Post-dilatation, n (%)	592 (84.1 %)	24 (80.0 %)	568 (84.3 %)	0.561
Cell type of stent (closed cell), n (%)	528 (75.9 %)	19 (65.9 %)	509 (76.3 %)	0.184
Residual stenosis, n (%)	27 (3.8 %)	13 (43.4 %)	13 (2.1 %)	<0.001

Bold values denote statistical significance at the p<0.005 level.ISR, in-stent restenosis; non-ISR, non-in-stent restenosis.

In prediction of ISR, a base logistic regression model was developed using covariates that are found to be associated with ISR in univariate analysis (p < .05), and adjusted for traditional risk factors such as gender, age, DM, HT, HL, and smoking status. Then, AIP, AI, and LCI were individually added to the base model and three different models were then created (Model 1, Model 2, and Model 3, respectively) (Table 4). In Model 1, dual antiplatelet therapy, use of ezetimibe, residual stenosis, and AIP independently served as predictors of ISR (OR: 0.06, 95% CI: 0.01–0.47, p = .007; OR: 99.73, 95% CI: 1.55–6392.8, p = .03; OR: 89.21, 95% CI: 14.79–537.89, p < .001; OR: 4.84, 95% CI: 3.05–6.63, p < .001; respectively). In addition, the probability of ISR with given AIP values is illustrated in Figure 2. In Model 2, use of ezetimibe, overlap stenting, residual stenosis, DM, and AI independently served as predictors of ISR (OR: 29.69, 95% CI: 1.29–681.36, p = .034; OR: 21.75, 95% CI: 3.77–125.34, p < .001; OR: 56.98, 95% CI: 15.05–215.74, p < .001; OR: 3.75, 95% CI: 1.04–13.49, p = .043; OR: 2.47, 95% CI: 1.62–3.76, p < .001; respectively). In Model 3, dual antiplatelet therapy, overlap stenting, residual stenosis, and LCI independently served as predictors of ISR (OR: 0.19, 95% CI: 0.04–0.93, p = .040; OR: 14.17, 95% CI: 2.61–77.00, p = .002; OR: 57.15, 95% CI: 16.67–195.85, p < .001; OR: 1.24, 95% CI: 1.10–1.39, p < .001; respectively).

Table 4.

Multivariable Model 1, Model 2, and Model 3 for prediction of carotid ISR.

Variables	Model 1		Model 2		Model 3
Variables	Adjusted OR (95% CI)	p	Adjusted OR (95% CI)	p	Adjusted OR (95% CI)	p
Dual antiplatelet (reference: single antiplatelet)	0.06 (0.01–0.47)	0.007	0.21 (0.04–1.07)	0.061	0.19 (0.04–0.93)	0.040
Ezetimibe usage	99.73 (1.55–6392.8)	0.03	29.69 (1.29–681.36)	0.034	16.79 (0.84–333.18)	0.064
Overlap stenting	4.07 (0.53–30.88)	0.174	21.75 (3.77–125.34)	<0.001	14.17 (2.61–77.00)	0.002
Residual stenosis	89.21 (14.79–537.89)	<0.001	56.98 (15.05–215.74)	<0.001	57.15 (16.67–195.85)	<0.001
Gender	1.76 (0.47–6.54)	0.393	1.41 (0.43–4.53)	0.565	1.55 (0.49–4.89)	0.456
Age	1.00 (0.91–1.09)	0.968	1.04 (0.96–1.13)	0.287	1.02 (0.94–1.10)	0.533
DM	2.54 (0.63–10.31)	0.189	3.75 (1.04–13.49)	0.043	2.84 (0.79–10.14)	0.108
HT	0.77 (0.14–4.23)	0.766	0.70 (0.13–3.81)	0.688	0.47 (0.09–2.27)	0.348
HL	4.53 (0.56–36.30)	0.155	2.56 (0.41–15.92)	0.312	2.08 (0.37–11.44)	0.400
Smoking	0.73 (0.20–2.71)	0.649	1.75 (0.55–5.59)	0.341	2.39 (0.74–7.71)	0.143
AIP	4.84 (3.05–6.63)	<0.001	-	-	-	-
AI	-	-	2.47 (1.62–3.76)	<0.001	-	-
LCI	-		-	-	1.24 (1.10–1.39)	<0.001

Bold values denote statistical significance at the p<0.005 level.CI, confidence interval; OR, odds ratio; DM, diabetes mellitus; HT, hypertension; HL, hyperlipidemia; AIP, atherogenic index of plasma; AI, atherogenic index; LCI, lipoprotein combined index.

Figure 2.

Probability of carotid in-stent restenosis (ISR) with given atherogenic index of plasma (AIP) values.

When comparing three models, Model 1, which included AIP, exhibited superior predictive accuracy compared with other models. Particularly, Model 1 had a lower Akaike Information Criterion (AIC) of 133, lower Bayesian Information Criterion (BIC) of 192, higher pseudo R² value of 0.613, and a greater Area Under the Curve (AUC) value of 0.971. In contrast, Model 2 had an AIC of 171, BIC of 230, pseudo R² of 0.458, and AUC of 0.917, while Model 3 had an AIC of 179, BIC of 238, pseudo R² of 0.425, and AUC of 0.907. These results indicate that Model 1 demonstrated a better fit and higher predictive capability.

Discussion

In this retrospective study, we investigated the impact of non-traditional lipid profiles, including AIP, on the development of ISR in patients who underwent CAS. We found that non-traditional lipid parameters such as AIP, AI, and LCI were independent predictors of carotid ISR. Particularly, AIP demonstrated a strong association with ISR, suggesting its potential utility as a predictive biomarker in this context.

Previous studies have indicated that the incidence of restenosis following CAS exhibits variability, with reported rates ranging from 5% to 11% across various follow-up durations.⁶ Our results confirm that ISR remains a relevant clinical issue, as it was observed in 4.03% of the study population during the 24-month follow-up. This finding aligns with the findings of systematic reviews conducted by Wholey et al.²⁵ in 2000 and Clavel²⁶ et al. in 2019, in which they reported cumulative restenosis rates of 5.7% and 3.46%, respectively, in the first year. These consistent observations emphasize the importance of identifying predictors for ISR to effectively guide clinical management.

Non-traditional lipid indices may offer a more comprehensive evaluation of lipid metabolism than traditional measures such as LDL-C and HDL-C. AIP, reflecting the balance between atherogenic and anti-atherogenic lipids, has been identified as a predictor of CAD and a prognostic marker for CAD.^15,27 Recent studies have highlighted the relationship between AIP and carotid stenosis as well as stroke.^17–19 Huang et al.¹⁷ revealed an association between carotid atherosclerosis and AIP in a cohort study. Additionally, Min Q and colleagues uncovered a linear association between AIP control level and future stroke among middle-aged and elderly Chinese individuals with abnormal glucose metabolism.¹⁸ Furthermore, Nam K et al.¹⁹ found that AIP predicts early recurrent ischemic lesion (ERIL) in acute ischemic stroke patients. The authors also suggested that AIP, a marker of atherogenic dyslipidemia, is more closely related to ERIL than LDL cholesterol.¹⁹ In our study, we observed that non-traditional lipid profiles, particularly AIP, were associated with an increased risk of ISR and may serve as predictors of ISR in patients undergoing CAS. Considering these recent and comprehensive studies, our study further extends the scope of this relationship between AIP and atherosclerosis by shedding light on the association between AIP and carotid ISR.

Our study has identified several risk factors associated with ISR following CAS. Notably, the use of dual antiplatelet therapy emerged as a protective factor against ISR, highlighting the significance of employing aggressive antiplatelet treatment strategies for these patients. This finding aligns with the study by Glotzer et al.,²⁸ which reported lower restenosis rates in patients who underwent carotid endarterectomy and received dual antiplatelet therapy than those on single antiplatelet therapy. However, it is essential to acknowledge that studies specifically investigating the effects of dual antiplatelet therapy versus single antiplatelet therapy on carotid ISR are currently limited in the existing literature. Sussman et al.²⁹ demonstrated that dual antiplatelet therapy was correlated with decreased stroke rates but an elevated risk of hemorrhagic complications. Despite these findings, the optimal duration of dual antiplatelet therapy remains unclear. In patients with predictors of restenosis, such as increased AIP, prolonging the duration of antiplatelet therapy may warrant consideration. These results suggest that a personalized approach to the duration of dual antiplatelet therapy may be beneficial in patients with specific risk factors for restenosis, such as elevated AIP levels. Further studies are needed to determine the optimal duration of dual antiplatelet therapy in this patient population.

Furthermore, our results may appear contradictory to the study conducted by Wang et al.³⁰ in patients with type 2 DM. Wang et al.³⁰ demonstrated that the combination of ezetimibe and atorvastatin reduced carotid intima-media thickness and plaque area to a greater extent than atorvastatin monotherapy. In contrast, our study found that the use of ezetimibe was associated with a higher risk of ISR. The exact mechanism underlying this association warrants further investigation but may be linked to the complex role of lipids in atherosclerosis and vascular inflammation. This association between ezetimibe usage and ISR may be attributed to the fact that patients using ezetimibe have a higher atherosclerotic burden. These findings collectively emphasize the multifactorial nature of ISR and highlight the need for additional research to elucidate the intricate interactions between medications, lipid profiles, and the development of ISR in patients undergoing CAS.

The relationship between stent design and carotid ISR has been thoroughly explored in the literature. Multiple studies have indicated that closed-cell stents exhibit a higher restenosis rate than open-cell stents.^31–33 Closed-cell stents are constructed with a more rigid and denser material in contrast to open-cell stents. Müller et al. have proposed that this feature of closed-cell stents could contribute to heightened irritation of the vessel wall, potentially triggering neointimal hyperplasia and leading to an increased rate of restenosis.³¹ However, our study did not observe any relationship between stent design and restenosis. The limited follow-up period in our study and the low restenosis rate observed may have initially hindered our ability to determine the difference in restenosis between the two types of stents. In Müller et al.’s study, the median follow-up duration was 4.0 years (interquartile range, 2.3–5.0), with some patients being followed for up to 10 years.³¹ Therefore, a longer follow-up period may help to elucidate potential differences in restenosis rates between the two stent designs.

Similar to our study, the presence of residual stenosis after stent placement has been shown to be an independent risk factor for restenosis.^34–37 This underscores the importance of employing meticulous procedural techniques to minimize residual stenosis during CAS. Post-dilatation is recommended when residual stenosis exceeds 30% to achieve maximum stent expansion.³⁶ Additionally, as previously suggested by Simon et al.,³⁸ increasing the post-dilatation balloon diameter may facilitate maximum stent expansion and reduce the likelihood of restenosis in the long term. However, further research is needed to evaluate this relationship. Contrary to previous findings, our study did not find a significant relationship between post-dilatation and ISR. Furthermore, since the same-sized balloon was used for post-dilatation, the relationship between post-dilatation balloon diameter and restenosis could not be evaluated. This is among the limitations of our study and could serve as a guide for future research. On the other hand, a meta-analysis found that post-dilatation was associated with perioperative hemodynamic instability and neurological events during and 30 days after the procedure.³⁶ Therefore, based on these findings, we recommend that post-dilatation should only be performed in cases where significant residual stenosis is observed following CAS, rather than being routinely applied.

On the other hand, DM was identified as an independent predictor of ISR.³⁹ In a study conducted by Achim and colleagues,³⁹ published in 2022 and involving 1940 patients, it was demonstrated that the ISR rate among individuals with diabetes was notably higher than those without diabetes. DM is a well-known risk factor for atherosclerosis and may contribute to the development of ISR through various mechanisms, including endothelial dysfunction and increased inflammation.

In conclusion, our study highlights the relevance of non-traditional lipid profiles, especially AIP, as predictors of ISR in patients undergoing CAS. These findings may contribute to risk stratification and the development of targeted interventions to reduce the incidence of ISR in this population. Further studies with larger cohorts are needed to validate these results and explore the potential clinical applications of AIP in the context of carotid artery stenosis.

Limitations

This study has some limitations. It is retrospective and based on data from medical records, which may introduce selection and information bias. The follow-up period for patients in our study was limited to 24 months, which may not provide sufficient data to predict the long-term outcomes of the relationship between AIP and carotid ISR. In addition, since the same-sized balloon was used for post-dilatation, the relationship between post-dilatation balloon diameter and restenosis could not be evaluated. A significant limitation of our study is the inability to histologically determine the underlying pathological mechanism (neo-intimal hyperplasia or neo-atherosclerosis) responsible for restenosis. Therefore, the exact mechanisms linking AIP and ISR remain to be elucidated and should be investigated in future studies.

Conclusion

In summary, non-traditional lipid profiles, especially AIP, were found to be associated with an elevated risk of ISR and may serve as predictors of ISR in patients undergoing CAS. This relationship may contribute to risk stratification and the development of targeted interventions for ISR management.

Footnotes

Author contributions

All authors substantially contributed to: (1) conception and design, or acquisition of data, or analysis and interpretation of data, (2) drafting the article or revising it critically for important intellectual content, and (3) final approval of the version to be published.

Declaration of conflicting interests

The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding

The author(s) received no financial support for the research, authorship, and/or publication of this article.

ORCID iDs

Cemalettin Yılmaz

Büşra Güvendi Şengör

Regayip Zehir

Ahmet Karaduman

Barkın Kültürsay

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