The association between the monocyte-to-HDL cholesterol ratio and coronary collateral circulation in patients with chronic total occlusion

Abstract

Background

Coronary collateral circulation (CCC) plays a crucial role in preserving myocardial perfusion in patients with chronic total occlusion (CTO) of the coronary arteries. However, the extent of collateral vessel development varies widely and cannot be explained solely by anatomical or hemodynamic factors. Systemic inflammation and lipid metabolism are critical modulators of arteriogenesis. The monocyte-to-high-density lipoprotein cholesterol ratio (MHR) has been proposed as a novel biomarker reflecting the balance between proinflammatory activity and anti-atherogenic protection. This study aimed to investigate the relationship between the MHR and the adequacy of the CCC in patients with stable coronary artery disease and angiographically confirmed CTO.

Methods

This retrospective study included 143 patients with stable angina who were diagnosed with at least one CTO lesion via coronary angiography. CCC was assessed via the Rentrop classification and categorized as poor (grades 0–1) or good (grades 2–3). Demographic, clinical, and laboratory data, including monocyte count, HDL cholesterol, and high-sensitivity C-reactive protein (hs-CRP) values, were collected. MHR values were calculated and compared between the groups. Logistic regression and receiver operating characteristic (ROC) curve analyses were performed to identify independent predictors and determine the diagnostic performance of the MHR.

Results

Patients with poor CCCs presented significantly higher MHR values (17.3 ± 4.7 vs. 12.0 ± 4.7, p < 0.001), higher hs-CRP levels, and lower HDL cholesterol concentrations. In the multivariate analysis, both the MHR (adjusted odds ratio [aOR]: 1.283, p < 0.001) and the hs-CRP level (aOR: 4.272, p = 0.009) emerged as independent predictors of poor collateral development. The MHR demonstrated good discriminative performance for poor CCC (AUC = 0.808, 95% CI: 0.735–0.881), with an optimal cutoff value of 13.8 (sensitivity 74%, specificity 71%).

Conclusions

An elevated MHR is significantly associated with poor CCC development in patients with CTO. As a readily available and cost-effective biomarker, it has potential clinical utility for identifying patients at risk of insufficient arteriogenesis. Further prospective studies are needed to validate its prognostic utility and explore its therapeutic implications in ischemic heart disease.

Introduction

Chronic total occlusion (CTO) in coronary arteries is a common finding in patients with stable coronary artery disease (CAD), with angiographic studies reporting its presence in up to 20% of individuals undergoing coronary angiography [1]. In the absence of spontaneous or procedural revascularization, myocardial perfusion in CTO patients is dependent primarily on the development of coronary collateral circulation (CCC), a compensatory vascular network that provides alternative blood flow to ischemic myocardial territories [1–3]. Robust CCC is associated with preserved left ventricular function, a reduced infarct size, and improved clinical outcomes [4, 5]. However, considerable heterogeneity exists in the extent of collateral development among patients with similar anatomical obstructions. These findings suggest that factors beyond the degree and duration of occlusion influence this adaptive response [5–7].

Recent research has revealed that arteriogenesis, the maturation and remodeling of preexisting arterioles into functional conduits, is driven not only by hemodynamic stimuli such as shear stress but also by complex biological signals, including inflammation, oxidative stress, and lipid metabolism [8, 9]. Among these factors, chronic low-grade inflammation has emerged as a crucial modulator of vascular adaptation. Monocytes play a central role in this process by infiltrating the vascular endothelium, releasing growth factors and cytokines, and coordinating endothelial and smooth muscle cell responses. High-density lipoprotein cholesterol (HDL-C) exerts concurrent vasculoprotective effects by inhibiting monocyte activation, reducing oxidative damage, and promoting endothelial homeostasis [10–12]. Consequently, the balance between monocyte-mediated inflammation and HDL-driven vascular protection is increasingly recognized as a determinant of successful collateral formation.

The monocyte-to-HDL cholesterol ratio (MHR) has recently attracted particular attention as a composite biomarker reflecting the interplay between proinflammatory and anti-inflammatory forces in the vascular milieu. Elevated MHR values have been associated with adverse cardiovascular events, an increased atherosclerotic burden, and poor outcomes in patients with acute coronary syndrome and stable CAD. Notably, the MHR has been linked to impaired endothelial function, increased arterial stiffness, and reduced coronary flow reserve factors that may plausibly hinder arteriogenesis [13–15]. However, the relationship between the MHR and CCC in patients with CTO remains underexplored. Only limited data exist regarding whether systemic inflammatory status, as indexed by the MHR, correlates with the capacity for functional collateral vessel development in the chronically ischemic myocardium.

In light of this knowledge gap, the present study was designed to investigate the association between the MHR and the adequacy of CCC in patients with CTO. By examining a well-characterized cohort and stratifying patients on the basis of the Rentrop classification, we sought to determine whether an elevated MHR is independently associated with impaired collateralization. The objective was not only to elucidate the underlying inflammatory mechanisms that may contribute to inadequate vascular adaptation but also to assess the clinical utility of the MHR as a simple, readily available biomarker for risk stratification in patients with CTO.

Methods

Study design and population

This retrospective observational study was conducted at the Samsun Training and Research Hospital, a tertiary cardiology center. A total of 412 patients who underwent elective coronary angiography for stable angina pectoris between January 2018 and January 2020 were initially screened for CTO. After applying the exclusion criteria acute coronary syndrome within six months (n = 55), prior revascularization (PCI/CABG) (n = 143), LVEF < 40% (n = 32), renal/hepatic dysfunction (n = 18), active infection, malignancy, or chronic inflammatory disease (n = 21) a final cohort of 143 patients with angiographically confirmed CTO was included in the analysis. The patient selection process is summarized in Fig. 1.

Fig. 1.

Flowchart of the study population selection process and classification by coronary collateral circulation status in patients with chronic total occlusion

The study protocol was reviewed and approved by the institutional ethics committee (Approval Number 2020/9/7), and all procedures conformed to the ethical standards outlined in the Declaration of Helsinki. Owing to the retrospective design, the informed consent requirement was waived.

Patients were eligible for inclusion if they had at least one angiographically confirmed CTO, which was defined as a complete absence of antegrade blood flow (TIMI 0) persisting for a minimum duration of three months. Occlusion chronicity (≥ 3 months) was confirmed by prior angiographic records, a clinical history of myocardial infarction in the occluded artery’s territory, or a documented sudden onset/worsening of angina consistent with occlusion at least three months before angiography. The exclusion criteria were a history of acute coronary syndrome within the previous six months, a prior history of coronary revascularization procedures (either percutaneous coronary intervention or coronary artery bypass grafting), symptomatic heart failure with a left ventricular ejection fraction less than 40%, moderate to severe renal or hepatic dysfunction, active infection, malignancy, chronic inflammatory or pulmonary disease, and hematological disorders. In patients with more than one CTO lesion, the artery exhibiting the most prominent collateral filling was selected for evaluation.

Data collection

Demographic characteristics, cardiovascular risk factors (including hypertension, diabetes mellitus, hyperlipidemia, and smoking status), medication use, and laboratory data were retrieved from the hospital electronic medical records. Hypertension was defined as a systolic blood pressure ≥ 140 mmHg, a diastolic blood pressure ≥ 90 mmHg, or the current use of antihypertensive therapy. Diabetes mellitus was diagnosed on the basis of fasting plasma glucose ≥ 126 mg/dL, HbA1c ≥ 6.5%, or ongoing antidiabetic treatment. Hyperlipidemia was defined as total cholesterol ≥ 200 mg/dL or the use of lipid-lowering medications. Smoking status included current smokers and those who had quit within the preceding 12 months.

Laboratory measurements

Blood samples were obtained after overnight fasting on the morning of angiography. Hematological parameters, including monocyte and white blood cell counts, were analyzed in EDTA-anti-coagulated whole blood via automated hematology analyzers. Biochemical parameters, such as lipid profiles and high-sensitivity C-reactive protein (hs-CRP) levels, were measured via standardized automated assays (Abbott, USA). MHR values were calculated by dividing the absolute monocyte count (×10³/µL) by the HDL-C level (mg/dL). Renal function was estimated via the Modification of Diet in Renal Disease equation to calculate the glomerular filtration rate.

Coronary angiography and collateral assessment

Selective coronary angiography was performed via the standard Judkins technique. All angiograms were independently reviewed by two experienced interventional cardiologists blinded to the patients’ clinical and laboratory data. Significant coronary artery disease was defined as ≥ 50% luminal diameter stenosis in any major epicardial artery (left anterior descending, circumflex, or right coronary artery). The number of diseased vessels was counted accordingly. CTO was defined as total luminal occlusion with no antegrade flow (TIMI 0) and a duration of at least three months. The CCC was assessed according to the Rentrop classification system: grade 0 indicated no visible collateral vessels; grade 1, filling of side branches without visualization of the epicardial segment; grade 2, partial filling of the epicardial segment; and grade 3, complete filling of the distal vessel. Patients were categorized into two groups on the basis of the degree of collateralization: poor CCC (Rentrop grades 0–1) and good CCC (Rentrop grades 2–3) [16]. SYNTAX scores, a measure of coronary anatomical complexity, were also calculated for each patient via an established scoring algorithm by observers blinded to the laboratory results. The reliability of the data collection instruments was assessed in terms of interobservers consistency via the intraclass correlation coefficient (ICC). The ICC was 0.94 for the Rentrop classification and 0.92 for the SYNTAX score, both indicating excellent agreement and statistical significance (p < 0.001).

Statistical analysis

Statistical analyses were performed via SPSS software (version 21.0, IBM Corp., Armonk, NY, USA). Continuous variables were tested for normality via the Kolmogorov–Smirnov test and are presented as the means ± standard deviations or medians with interquartile ranges, as appropriate. Comparisons between two groups were performed via Student’s t test or the Mann–Whitney U test for continuous variables and the chi-square test or Fisher’s exact test for categorical variables. Multivariate logistic regression (enter method) was used to identify independent predictors of poor collateral circulation. The model was adjusted for age, sex, diabetes mellitus, number of diseased vessels, statin use, creatinine, MHR, hs-CRP, and triglyceride levels. Results are presented as adjusted odds ratios (aOR) with 95% confidence intervals (CI). Receiver operating characteristic (ROC) curve analysis was conducted to evaluate the diagnostic performance of the MHR in predicting poor collateral development. The optimal cutoff value was determined by maximizing the Youden index. A two-sided p-value < 0.05 was considered statistically significant for all analyses.

Results

One hundred forty-three patients with angiographically confirmed CTO were included in the final analysis. According to the Rentrop classification, 69 patients (48.3%) presented good CCCs corresponding to grades 2 or 3, and 74 patients (51.7%) presented poor collateral development (Rentrop grades 0–1). The baseline demographic and clinical characteristics were comparable between the two groups. There were no statistically significant differences in age, sex distribution, body mass index, or cardiovascular risk factors, including hypertension, diabetes mellitus, hyperlipidemia, or smoking status. Similarly, the left ventricular ejection fraction, medical treatment profiles, distribution of the target vessels with CTOs (left anterior descending, circumflex, or right coronary artery), number of diseased coronary vessels, and SYNTAX scores did not differ significantly between the poor and good CCC groups. These findings are detailed in Table 1.

Table 1.

Baseline characteristics of patients with chronic total occlusion stratified by coronary collateral circulation (CCC) status

	Good CCC (Rentrop class 2–3) (n = 69)	Poor CCC (Rentrop class 0–1) (n = 74)	p- value
Clinical characteristics
Age (years), mean ± SD	64.6 ± 9.7	62.4 ± 9.8	0.245
Sex, male (n, %)	55 (79.7%)	63 (85.1%)	0.393
Body mass index (kg/m2)	26.9 ± 1.9	27.2 ± 1.5	0.543
Hypertension (n, %)	51 (73.9%)	56 (75.7%)	0.808
Diabetes mellitus (n, %)	20 (29.0%)	26 (35.1%)	0.431
Smoker (n, %)	22 (31.9%)	23 (31.1%)	0.918
Hyperlipidemia (n, %)	24 (34.8%)	27 (36.5%)	0.832
Stroke (n, %)	2 (2.9%)	1 (1.4%)	0.519
LVEF, mean ± SD	53.5 ± 7.7	53.2 ± 8.0	0.897
Angiographic characteristics
Left anterior descending artery (LAD) (n, %)	20 (29.0%)	26 (35.1%)	0.431
Circumflex artery (Cx) (n, %)	9 (13.0%)	7 (9.5%)	0.497
Right coronary artery (RCA) (n, %)	40 (58.0%)	41 (55.4%)	0.757
Number of diseased coronary vessels, mean ± SD	1.3 ± 0.7	1.4 ± 0.8	0.500
SYNTAX score, mean ± SD	17.2 ± 4.0	17.2 ± 4.2	0.882
Complete blood count
Hemoglobin (g/dL), mean ± SD	13.5 ± 1.7	14.0 ± 1.5	0.113
WBC (x103/µL), mean ± SD	8.1 ± 2.6	8.5 ± 2.0	0.103
Neutrophil (x10³/µL), mean ± SD	4.8 ± 1.7	5.1 ± 1.9	0.317
Lymphocyte (x10³/µL), mean ± SD	2.1 ± 0.7	1.9 ± 0.7	0.342
NLR, mean ± SD	2.5 ± 1.1	2.7 ± 1.3	0.241
Monocyte count (x10³/µL), mean ± SD	0.54 ± 0.20	0.70 ± 0.19	< 0.001
Biochemical parameters
Glucose (mg/dL), median (IQR)*	114.0 (97.0–138.0)	119.0 (100.0–170.0)	0.226
Creatinine (mg/dL), mean ± SD	0.9 ± 0.2	0.9 ± 0.2	0.485
GFR (mL/min/1.73 m2), mean ± SD	90.2 ± 21.5	90.1 ± 18.4	0.913
Total cholesterol(mg/dL), mean ± SD	191.8 ± 48.1	200.3 ± 44.6	0.141
Triglycerides (mg/dL), median (IQR)*	133.0 (100.0–186.0)	194.0 (136.0–279.0)	< 0.001
HDL-Cholesterol (mg/dL), median (IQR)*	45.0 (38.0–53.0)	40.0 (36.0–45.0)	< 0.001
LDL-Cholesterol (mg/dL), mean ± SD	118.4 ± 41.8	122.2 ± 37.9	0.508
MHR, mean ± SD	12.0 ± 4.7	17.3 ± 4.7	< 0.001
hs-CRP, mean ± SD	1.9 ± 0.4	2.1 ± 0.4	0.003
Medical treatment
Antiplatelet (n, %)	63 (91.3%)	68 (91.9%)	0.899
Beta-blockers (n, %)	50 (72.5%)	50 (67.6%)	0.523
Calcium channel blockers (n, %)	2 (2.9%)	5 (6.8%)	0.285
ACE inhibitors or ARB (n, %)	43 (62.3%)	44 (59.5%)	0.726
Statins (n, %)	34 (49.3%)	39 (52.7%)	0.682
Diuretic (n, %)	6 (8.7%)	6 (8.1%)	0.899

Abbreviations: ACE angiotensin-converting enzyme, ARB angiotensin II receptor blocker, GFR glomerular filtration rate, HDL high-density lipoprotein, hs-CRP high-sensitivity C-reactive protein, NLR Neutrophil-to-Lymphocyte Ratio, MHR monocyte/HDL ratio, LDL Low-density lipoprotein, LVEF left ventricular ejection fraction, WBC white blood cell

*Data are presented as mean ± standard deviation or median (interquartile range) based on the Kolmogorov-Smirnov normality test. Glucose, HDL-C, and triglyceride levels were non-normally distributed and are therefore reported as median (IQR)

The values in bold represent statistically significant results

Biochemical and hematological evaluations revealed significant differences between the groups in terms of biomarkers related to inflammation and lipid metabolism. Patients with poorly developed collaterals had significantly higher circulating monocyte counts and serum triglyceride levels, together with markedly lower levels of HDL-C than those with adequate collateral flow. As a result of these divergent patterns, MHR, a composite index reflecting both proinflammatory and anti-atherogenic mechanisms, was substantially elevated in patients with poor CCCs. Specifically, the mean MHR was 17.3 ± 4.7 in the poor CCC group and 12.0 ± 4.7 in the good CCC group, and the difference was highly statistically significant (p < 0.001). Serum hs-CRP concentrations were also significantly greater in patients with inadequate collateralization (2.1 ± 0.4 vs. 1.9 ± 0.4 mg/L, p = 0.003), further supporting the role of systemic inflammation in the impairment of arteriogenic processes. These findings are illustrated in Fig. 2 and summarized in Table 1.

Fig. 2.

Comparison of Monocyte-to-HDL Ratio (MHR) values between patients with good and poor coronary collateral circulation

Logistic regression analysis was applied to identify independent determinants of poor CCC. According to the univariate analyses, an elevated monocyte count, an increased MHR, increased hs-CRP levels, and elevated triglyceride concentrations were positively associated with poor collateral development, whereas increased HDL-C levels appeared to exert a protective effect. In the multivariate model, both MHR (adjusted odds ratio [aOR]: 1.283, 95% CI: 1.146–1.436; p < 0.001) and hs-CRP (aOR: 4.272, 95% CI: 1.437–12.703; p = 0.009) were independent predictors of poor collateral development. No other variables, including age, sex, diabetes, number of diseased vessels, statin use, creatinine, or triglycerides, showed significant associations. The full regression results are shown in Table 2.

Table 2.

Univariate and multivariate analyses of poorly developed coronary collateral circulation

Variables	Univariate Regression		Multivariate Regression*
	OR (95% CI)	P value	aOR (95% CI)	p-value
Age	0.977 (0.944–1.011)	0.187	1.012 (0.966–1.061)	0.606
Sex (Male)	1.458 (0.612–3.475)	0.395	1.219 (0.370–4.020)	0.744
Diabetes Mellitus (+)	1.327 (0.655–2.688)	0.432	1.270 (0.521–3.099)	0.599
Number of Diseased Vessels	1.189 (0.749–1.889)	0.463	1.190 (0.665–2.129)	0.558
Monocyte	1.005 (1.002–1.007)	< 0.001
MHR	1.305 (1.181–1.442)	< 0.001	1.283 (1.146–1.436)	< 0.001
hs-CRP	4.045 (1.704–9.604)	0.002	4.272 (1.437–12.703)	0.009
Creatinine	1.423 (0.265–7.639)	0.681	0.475 (0.050–4.503)	0.517
Triglyceride	1.006 (1.003–1.010)	0.001	1.005 (0.999–1.009)	0.052
HDL	0.928 (0.888–0.969)	0.001
Statins (+)	1.147 (0.595–2.212)	0.682	0.610 (0.258–1.443)	0.260

Abbreviations: HDL high-density lipoprotein, hs-CRP high-sensitivity C-reactive protein, MHR monocyte/HDL ratio

*The multivariate logistic regression model was constructed by including clinically relevant variables known or suspected to influence collateral development. The model included the following pre-specified variables: age, sex, diabetes mellitus, number of diseased vessels, statin use, creatinine, MHR, hs-CRP, and triglyceride. Although absolute monocyte count was significantly associated with poor collateral development in univariate analysis, it was not included in the multivariate model alongside MHR to avoid collinearity, as MHR already incorporates monocyte count together with HDL-C

The values in bold represent statistically significant results

The discriminative capacity of the MHR to identify patients at risk of poor collateral ability was further assessed via ROC curve analysis. The MHR demonstrated good diagnostic accuracy, with an area under the curve (AUC) of 0.808 (95% CI: 0.735–0.881). The optimal cutoff value of 13.8 was determined on the basis of the Youden index, yielding a sensitivity of 74% and a specificity of 71% in predicting poor CCC (Fig. 3). These findings indicate that increased MHR values, in conjunction with elevated hs-CRP, are strongly associated with insufficient coronary collateral development in patients with CTO, independent of other conventional cardiovascular risk factors or anatomical disease severity.

Fig. 3.

Receiver Operating Characteristic (ROC) curve analysis of the Monocyte-to-HDL Ratio (MHR) for predicting poor coronary collateral circulation

Discussion

The results of this retrospective cohort study involving patients with CTO revealed a significant and independent association between an elevated MHR and the presence of poorly developed CCC. These findings suggest that the MHR, a biomarker integrating inflammatory activity and lipid-mediated vascular protection, may reflect the biological milieu that influences the extent of arteriogenesis in patients with advanced CAD. To our knowledge, this is among the first studies to robustly demonstrate an association between an elevated MHR and impaired collateral vessel formation in patients with stable CTO, underscoring the pathophysiological role of inflammatory-lipid imbalance in this context.

Collateral development is a complex adaptive response to chronic myocardial ischemia that involves both angiogenesis, the sprouting of new capillaries, and arteriogenesis, the remodeling and maturation of preexisting arterioles into functional conductance vessels [6–9, 17–19]. While hemodynamic forces, particularly shear stress across pressure gradients, have been identified as the primary initiators of collateral growth, the efficiency of this process is increasingly recognized as being critically modulated by systemic inflammatory status, endothelial function, and lipid homeostasis [1, 3]. The present study aligns with this paradigm by identifying the MHR and hs-CRP as independent correlates of poor CCC, suggesting that inflammation-related pathways may inhibit the vascular remodeling required for effective collateralization.

Monocytes play a pivotal role in the early stages of arteriogenesis. Once activated, they infiltrate the vascular endothelium, secrete cytokines and growth factors, and facilitate smooth muscle cell proliferation and matrix remodeling, key steps in the maturation of collateral vessels. However, when inflammation is excessive or dysregulated, as is common in patients with metabolic syndrome, diabetes, or atherosclerosis, these monocyte-driven processes may become maladaptive [20–23]. In the present study, elevated monocyte counts and hs-CRP levels were significantly associated with poor CCC, suggesting that a heightened systemic inflammatory state may suppress effective arteriogenic signaling. Although the absolute difference in hs-CRP levels was modest (0.2 mg/L), it was statistically significant and consistent with low-grade systemic inflammation. Its independent predictive value in the multivariate model suggests that even subtle, persistent inflammation can impair arteriogenesis.

Conversely, HDL-C is well known for its anti-inflammatory, anti-oxidant, and endothelial-protective properties. HDL inhibits monocyte adhesion to the endothelium, promotes nitric oxide bioavailability, and enhances endothelial repair capacity. Low levels of HDL-C, as observed in the poor CCC group, may thus represent a diminished capacity for vascular resilience and regeneration. By simultaneously capturing elevations in monocyte burden and reductions in HDL-C, MHR values serve as a pathophysiologically relevant index of the imbalance between injury and repair mechanisms in the vascular wall [24–26].

While our findings position MHR as a potential biological barrier to arteriogenesis, it may also be a biomarker of broader metabolic dysregulation (e.g., insulin resistance, oxidative stress, endothelial dysfunction). This dysregulated milieu itself could be the primary driver of impaired vascular remodeling. Thus, MHR likely reflects both a contributor to and a consequence of an environment hostile to successful arteriogenesis.

Several previous studies have explored the role of the MHR in various cardiovascular contexts. An elevated MHR has been linked to the severity of coronary artery disease, stent thrombosis, the coronary slow-flow phenomenon, and adverse outcomes following acute coronary syndrome [15, 27–31]. However, its specific relationship with coronary collateral development in CTO patients has not been adequately addressed in the literature. The results of this study fill this gap and indicate that the MHR is not merely a risk marker but may also reflect a pathobiological barrier to endogenous revascularization in chronically ischemic myocardium. Importantly, the MHR retained its predictive value even after adjustment for conventional risk factors and angiographic disease burden, highlighting its potential clinical utility. The predictive power of the MHR was further confirmed by ROC curve analysis, which yielded an AUC of 0.808 (95% CI: 0.735–0.881), a level generally considered to reflect good discriminatory capacity. The identified cutoff value of 13.8 achieved balanced sensitivity and specificity, suggesting that the MHR may be feasibly integrated into clinical workflows to identify patients at a greater risk of impaired collateral development. Such risk stratification may help select candidates for early revascularization, intensified medical therapy, or closer clinical surveillance. Although statins can elevate HDL-C and exert anti-inflammatory effects—potentially confounding the MHR—their use was balanced between groups. Moreover, MHR remained an independent predictor after adjusting for statin use, suggesting it captures a pathophysiological interplay not fully suppressed by baseline statin therapy.

The study findings also support existing evidence implicating hs-CRP as a negative regulator of collateral formation. Inflammatory cytokines such as tumor necrosis factor-alpha and interleukin-6 have been shown to impair endothelial function and inhibit the monocyte recruitment necessary for arteriogenesis. Previous studies, including those by Seiler et al. and Güray et al., demonstrated that patients with poor CCCs presented increased levels of systemic inflammatory mediators and soluble adhesion molecules, corroborating our observations [32, 33].

From a translational standpoint, these insights open potential avenues for therapeutic modulation. However, it remains to be determined whether interventions that reduce MHR values, such as lifestyle modifications, lipid-raising agents such as niacin or cholesteryl ester transfer protein (CETP) inhibitors, or targeted anti-inflammatory therapies, can favor collateral vessel growth. Future prospective and interventional studies are needed to address this clinically relevant question.

Strengths of the study

One of the principal strengths of this study is its focus on a well-defined, clinically relevant patient population, individuals with angiographically confirmed CTO, who are at heightened risk of adverse cardiovascular outcomes and for whom the CCC has meaningful prognostic implications. By employing a homogenous cohort with stable CAD and clear inclusion and exclusion criteria, we minimized potential confounding due to acute ischemic events or recent revascularization, thereby enhancing internal validity.

Another important strength of this research is the systematic and blinded assessment of angiographic data by experienced interventional cardiologists. Despite its semi-quantitative character, the Rentrop classification remains one of the most widely applied and clinically interpretable grading systems for collateral flow. Moreover, the study incorporated a robust statistical framework, including both univariate and multivariate regression models, to identify independent predictors of poor collateral development while controlling for relevant clinical and laboratory variables.

Most notably, this study introduces the MHR as a novel and independent biomarker of impaired collateralization in the CTO population. As a readily available, cost-effective, and easily interpretable laboratory parameter, it possesses significant potential for routine clinical use. The integration of the MHR with classical biomarkers such as hs-CRP strengthens the mechanistic interpretation of the current findings and supports the pathophysiological relevance of inflammatory imbalance in arteriogenesis.

The diagnostic performance of the MHR was rigorously evaluated through ROC curve analysis, which revealed good discriminative ability. The identification of a specific cutoff value further contributes to the translational applicability of this parameter in clinical decision-making.

Limitations of the study

Despite these strengths, the study also has certain limitations that should be acknowledged when the findings are interpreted. First, the retrospective and single-center nature of the study design inherently limits the ability to draw causal inferences and may reduce the generalizability of the results to other populations or healthcare settings. Further multicenter, prospective validation studies are needed to confirm the predictive value of the MHR in broader patient cohorts.

Second, although our sample size was sufficient to detect significant associations, it was relatively modest for a multivariate regression model with multiple predictors, potentially affecting model stability and generalizability. Validation in larger cohorts is warranted.

Third, the assessment of coronary collateral circulation was based solely on the Rentrop classification, which, despite being widely used, is a semi-quantitative and observer-dependent method. The absence of more objective and quantitative measurements, such as the collateral flow index obtained via pressure‒wire studies [34] or myocardial perfusion imaging techniques, restricts the precision with which true functional collateral capacity can be evaluated. Furthermore, coronary computed tomography angiography (CCTA) has demonstrated potential for non-invasive collateral evaluation and could be a valuable tool in future prospective studies [35, 36].

Fourth, our study included only symptomatic patients referred for angiography, limiting generalizability to asymptomatic CTO patients who may have different inflammatory and collateralization profiles.

Finally, unmeasured confounders could have influenced our results. We lacked detailed data on statin type, dosage, and duration, which can affect HDL-C and inflammation. Other factors like genetic polymorphisms, physical activity, diet, and precise ischemia duration may also modulate arteriogenesis and warrant investigation in future studies.

Conclusion

This study of patients with CTO revealed a strong and independent association between an elevated MHR and insufficient CCC, as determined on the basis of the Rentrop classification. These findings support the hypothesis that systemic inflammatory activation, as reflected by an increased MHR, may represent a biological barrier to effective arteriogenesis in the chronically ischemic myocardium. Importantly, this relationship was observed independently of traditional cardiovascular risk factors and angiographic disease burden.

High MHR values were not only associated with unfavorable collateral development but also demonstrated significant predictive utility in risk stratification, with acceptable diagnostic accuracy based on ROC curve analysis. Elevated hs-CRP levels further highlight the pathophysiological importance of systemic inflammation in modulating the coronary collateral response.

Taken together, these results underscore the potential usefulness of the MHR as a simple, inexpensive, and clinically accessible biomarker for identifying patients with CTO who may be at increased risk of suboptimal collateralization. Early identification of such individuals could inform revascularization strategies and optimize medical therapy, pending validation from prospective studies with clinical endpoints.

Abbreviations

AUC

Area under the curve

aOR

Adjusted odds ratio

CAD

Coronary artery disease

CCC

Coronary collateral circulation

CI

Confidence interval

CETP

Cholesteryl ester transfer protein

CTO

Chronic total occlusion

HDL-C

High-density lipoprotein cholesterol

hs-CRP

High-sensitivity C-reactive protein

ICC

Intraclass correlation coefficient

MHR

Monocyte-to-high-density lipoprotein cholesterol ratio

ROC

Receiver operating characteristic

Authors' contributions

AY, FB, and MKS contributed to the conceptualization, methodology, data curation, formal analysis, investigation, resources, writing of the original draft, review and editing of the manuscript, visualization, supervision, and project administration. All authors read and approved the final manuscript.

Funding

This research received no external funding.

Data availability

The original contributions presented in this study are included in the article. Further inquiries can be directed to the corresponding authors.

Declarations

Ethics approval and consent to participate

The ethical approval for this retrospective analysis was obtained from the Samsun University Non-Interventional Clinical Research Ethics Committee (Approval No: 2020/9/7). The study conforms to the ethical standards of the Declaration of Helsinki, the Turkish Regulation on Non-Interventional Clinical Research, and the Law on the Protection of Personal Data. All data extracted from clinical records were irreversibly anonymized prior to analysis, with all direct and indirect identifiers removed. Consequently, the ethics committee formally waived the requirement for obtaining written informed consent from participants.

Consent for publication

Not applicable.

Competing interests

The authors declare no competing interests.