Utility of neutrophil-to-high-density lipoprotein-cholesterol ratio in patients with coronary artery disease: a narrative review

Abstract

The neutrophil-to-high-density lipoprotein-cholesterol ratio (NHR) is thought to reflect inflammatory status and dyslipidaemia, both of which play significant roles in coronary artery disease (CAD). The objective of this narrative review is to summarise the results of studies that have explored the utility of NHR for the diagnosis and management of CAD. The PubMed, Google Scholar, Scopus, Embase and Web of Science databases were searched for articles related to NHR from their inception to October 2022. Seven relevant articles were obtained for review. There were unclear relationships of NHR with age, sex, smoking status, hypertension and diabetes. However, NHR had a sensitivity and specificity as high as 94.8% and 59%, respectively, for the identification of significant coronary stenosis. NHR was also a superior predictor of prognosis to conventional parameters. NHR had a sensitivity and specificity as high as 77.6% and 74.2%, respectively, for the prediction of adverse events, including mortality, associated with acute coronary syndrome. Thus, NHR could be used in clinical cardiovascular medicine for risk stratification and the prediction of the short-term and long-term outcomes of CAD. However, more studies are required before a quantitative assessment of the efficacy of NHR for use in patient management can be completed.

Introduction

Cardiovascular diseases are the most common cause of morbidity and mortality around the world. ¹ Coronary artery disease (CAD) is an atherosclerotic disease that can manifest as stable angina, unstable angina, acute myocardial infarction (AMI), or sudden cardiac death. Acute coronary syndrome (ACS) includes several myocardial ischaemic states: unstable angina, non-ST elevated myocardial infarction (NSTEMI) and ST-elevated MI (STEMI). Patients with AMI have a five-to-six-fold higher mortality rate than individuals who do not have the disease.^2,3

The pathophysiology of CAD is underpinned by inflammation and abnormal lipid metabolism. Low-density lipoprotein (LDL)-cholesterol increases the risk of atherosclerosis, whereas high-density lipoprotein (HDL)-cholesterol has a protective effect. ⁴ In addition, immune cells such as neutrophils, lymphocytes and monocytes cause atherosclerotic plaque rupture, which leads to AMI. ⁵ Laboratory parameters that include immune cell counts and concentrations of lipid species in the circulation have been widely used for the diagnosis and management of CAD. The most frequently used parameters are the neutrophil-to-lymphocyte ratio (NLR), the monocyte-to-HDL ratio (MHR), the triglyceride-to-HDL ratio (THR), the LDL-to-HDL (LDL/HDL) ratio and the platelet-to-lymphocyte ratio (PLR). ⁶ A relatively new parameter, the neutrophil-to-HDL-cholesterol ratio (NHR), is intended to reflect inflammatory status and lipid metabolism more comprehensively is being increasingly studied in the context of cardiovascular diseases. A high NHR in a patient implies the presence of a high neutrophil count or a low HDL-cholesterol concentration or both.

Although there has been a fall in the incidence of CAD in developed nations, developing regions around the world have been showing mixed trends. ³ These developing regions are characterised by limited availability, accessibility and affordability of health resources. NHR is a simple, inexpensive, readily available and non-invasive blood-based parameter. ⁷ Therefore, such a biomarker may be of particular use in resource-limited settings. Although no accepted normal range for NHR is available in the literature, multiple recent studies have identified specific cut-off values of NHR for the diverse aspects of CAD, including its diagnosis, management and prognosis. The cut-off values of NHR for the prediction of significant coronary stenosis have been determined to be 1.51 and 3.87 in two studies,^8,9 and the cut-off values for the prediction of adverse cardiac events, including deaths, have been reported to be 5.74 and 11.28.^7,10 However, there is no summary of the studies that have explored the utility of NHR in the literature. Therefore, through this narrative review, we aim to summarise the outcomes of the studies related to the use of NHR for the prediction of the occurrence, pathology, severity and outcomes of CAD in patients.

Methods

A literature search of the PubMed, Google Scholar, Scopus, Embase and Web of Science databases was performed to identify relevant articles for review. Studies published in English from the inception of the databases to October 2022 were searched for using the terms “neutrophils”, “high-density lipoprotein”, “coronary artery disease”, “acute myocardial infarction”, “acute coronary syndrome”, “atherosclerosis” and “cardiovascular mortality”. These terms were used to retrieve as many articles as possible from Google Scholar, Scopus and Web of Science. The PubMed search was conducted after the identification of appropriate MeSH terms and the same search was performed in Embase using Emtree terms. Boolean operators such as “OR” and “AND” were used as appropriate between the MeSH and Emtree terms to identify the relevant articles in each database. The search was extended to include conference proceedings in journals, preprints and thesis repositories. We also searched the reference list of each of the included studies to identify other potential articles of interest. The search was started on 1 November 2022. The selection process involved an evaluation of the abstracts and the principal content of the articles using the following inclusion criteria: any English language article published in a peer-reviewed journal that evaluated the utility of NHR in patients with CAD. The exclusion criteria were reports of studies of the utility of NHR in patients who did not have CAD, case series, letters, commentaries and review articles. Duplicate articles were removed using Zotero 5.0.96.2 (Corporation for Digital Scholarship, Vienna, VA, USA). The primary findings of the studies that were evaluated were the associations of NHR with the characteristics, severity and outcomes of the patients, and the occurrence of CAD.

Because of its nature, the study did not require ethics approval or the informed consent of the participants. However, ethics approval for each of the constituent studies and the informed consent of each of the participants had been obtained.

Findings and discussion

The literature search identified 1354 articles from the five databases, of which seven met the eligibility criteria and were included in the narrative review (Table 1). The results of the study selection are shown in Figure 1. After the review, four studies were found to have investigated the utility of NHR in patients with stable CAD^8,9,11 and the remaining three studies investigated the utility of NHR in patients with ACS.^6,7,10 These seven articles will be discussed in detail in this review. The articles were placed into three major categories that describe the utility of NHR in terms of its relationships with patient characteristics, the pathology and severity of CAD and the outcomes of patients.

Table 1.

Characteristics of the included studies.

Author, year of publication	Study design	Nature of the participants	Study site	Sample size	Primary outcome of the study
Chen, 2022 11	Retrospective	STEMI	First Affiliated Hospital of Chongqing Medical University, China	532	Predictive ability of NHR for major adverse cardiac events
Huang, 2020 7	Prospective	AMI (STEMI and NSTEMI)	Tongji Hospital, Tongji Medical College, China	528	Predictive ability of NHR for long-term outcomes (mortality and recurrent infarction)
Ozgeyik, 2021 6	Retrospective	AMI (STEMI and NSTEMI)	Eskisehir City Hospital, Turkey	554	Long-term cardiovascular-related mortality
Kou, 2021 8	Retrospective	Stable CAD	Sichuan Provincial People’s Hospital, China	404	Predictive ability of NHR for the severity of coronary stenosis
Basyigit, 2022 10	Retrospective	CAD with documented myocardial ischaemia	Ankara City Hospital, Turkey	308	Predictive ability of NHR for the severity of coronary stenosis
Li, 2018 9	Retrospective	CAD	Yunnan Fuwai Hospital, Kunming, China	164	Relationship of NHR with the severity of coronary atherosclerosis
Manoochehri, 2021 12	Cross-sectional	Stable CAD	Hamedan University of Medical Sciences, Iran	64	Predictive ability of NHR for the severity of coronary stenosis

AMI, acute myocardial infarction; CAD, coronary artery disease; NHR, neutrophil-to-high-density lipoprotein-cholesterol ratio; NSTEMI, non-ST elevated myocardial infarction; STEMI, ST elevated myocardial infarction.

Figure 1.

Flowchart of the selection of the included studies.

Relationships of NHR with patient characteristics

Four studies of patients with CAD were found to have described the relationships of NHR with patient characteristics. These studies explored these relationships by placing the study participants into two categories: above and below the cut-off values of the NHR for the primary outcomes. These characteristics are described in detail in this section under three headings: Demographics, Patient history and Blood parameters.

Demographics

Patients with an NHR higher than the cut-off value were found to be younger and more likely to be women by Chen et al. ¹⁰ In contrast, Manoochehri et al. ¹² reported that the NHRs of men with stable CAD were significantly higher, and no differences in sex or age were identified in the remaining two studies.^6,7 Hence, the relationships of NHR with the age and sex of patients remains unclear. Previous studies have shown that men with CAD have low HDL concentrations and that women have significantly higher HDL-C concentrations than age-matched men.^13,14 Furthermore, the neutrophil counts of men with CAD were found to be higher than those of healthy men (p < 0.001). However, no significant differences have been identified between women with and without CAD. ¹⁵ The neutrophil count fluctuates throughout the lifetime of a woman: before the menopause, the neutrophil counts of women are higher than those of men, but during the early post-menopausal period, they decrease, and after the menopause is complete, the count steadily increases.^15–17 Therefore, NHR might show differing relationships with sex according to the age of the women in the study cohort.

Patient history

In a study by Chen et al., ¹⁰ smokers were found to be overrepresented in the group of participants with NHRs above the cut-off value. Furthermore, the neutrophil count has been shown to be up to 23% higher in smokers than in non-smokers, and neutrophil function is also clearly influenced by cigarette smoking. The oxidative burst and chemotaxis of neutrophils, which may be involved in the pathogenesis of atherosclerosis, have been found to be more marked in smokers. ¹⁸ In addition, smoking can alter the expression and activities of critical enzymes that affect HDL metabolism and the distribution of HDL subfractions. In addition, the oxidative modification of HDL as a result of smoking produces dysfunctional HDL that does not have anti-atherosclerosis properties. Hence, smoking can have a significant effect to raise the NHRs of patients. ¹⁹ Despite this, three studies showed no significant differences between the two patient groups. ^6,7,12

Patients with diabetes were found to be present in higher proportions in the high NHR group in two out of the three studies.^6,7 Various kinds of neutrophil-related abnormalities, such as neutrophilia and a greater abundance of reactive oxygen species (ROS), have been identified in patients with type 2 diabetes mellitus (T2DM).^20,21 Neutrophils promote greater peripheral insulin resistance through adipose tissue inflammation. Abnormal neutrophil ROS generation exacerbates endothelial dysfunction and plaque instability, which play roles in the development of ACS. ²⁰ Insulin resistance also contributes to low HDL-cholesterol concentrations, and both predispose toward the development of diabetes. In addition, hyperglycaemia can lead to the formation of dysfunctional HDL in patients with T2DM²².

There were no significant associations identified between NHR and a history of hypertension in any of the studies. However, participants in the high NHR group had significantly lower systolic blood pressure (SBP) than those in the low NMR group.^7,10 In addition, Chen et al. ¹⁰ found that NHR negatively correlated with SBP in patients with STEMI (r = −0.078, p = 0.029). The presence of congestive heart failure and the Killip classification of patients at admission to hospital were evaluated in three of the studies.^6,7,10 Huang et al. ⁷ found no significant differences in the proportion of participants with heart failure in the two NHR groups. Ozgeyik et al. ⁶ found a significantly lower proportion of patients with a history of heart failure in the high NHR group, but no explanation for this was proposed. Conversely, Chen et al. ¹⁰ found that patients with NHR > 11.28 were more likely to have heart failure, with Killip classes III and IV, at admission. In addition, high NHR was also found to be significantly associated with Killip classes III to IV (r = 0.089, p = 0.012). This suggests that NHR may represent a useful biomarker of cardiac function. ¹⁰ Excessive infiltration or the delayed regression of neutrophils can aggravate myocardial injury via the release of inflammatory mediators and proteinases. ²³ Furthermore, in the tissue injury associated with AMI, damage-related molecular patterns (DAMPs) may induce the production of neutrophil extracellular traps (NETs) from neutrophils, thereby aggravating cardiac inflammation and fibrosis. These NETs promote thrombosis in coronary microvessels and are responsible for poor cardiac function. ²⁴

Blood parameters

Only two studies have explored the relationship of NHR with other blood parameters. According to Chen et al., ¹⁰ high NHR was associated with high total leucocyte, neutrophil, lymphocyte, monocyte, platelet and red blood cell counts, and a high haemoglobin level in patients with STEMI. Similar associations were identified in another study conducted in older patients with AMI, except for the lack of association with lymphocyte count and haemoglobin level. ⁷ Furthermore, high NHR was found to be associated with significantly higher concentrations of triglycerides, fasting plasma glucose and glycated haemoglobin (HbA1c), and lower concentrations of HDL-cholesterol. ¹⁰ However, Huang et al. found that high NHR was not associated with high concentrations of LDL-cholesterol or triglycerides. ⁷

Utility of NHR for the assessment of pathology associated with CAD

Six studies have evaluated the utility of NHR for the characterisation of CAD-related pathology in terms of the prediction of the disease, its severity and location, and the number of stenotic vessels. Assessment of the severity of stenosis is vital for the categorisation of patients regarding their cardiovascular risk and to determine the optimal treatment strategies. The studies used the Gensini score (GS) to rate the degree of coronary stenosis after performing coronary angiography. ²⁵

Prediction of CAD and the severity of stenosis

Four studies have evaluated the utility of NHR as a predictor of stable CAD.^8,9,11,12 Kou et al. ⁸ found that NHR positively correlated with the degree of coronary stenosis, rated using the GS. Further analyses showed that NHR was also an independent predictor of CAD (odds ratio (OR) = 1.163, p = 0.012). The critical value of NHR for the prediction of CAD was found to be 1.51, with a sensitivity of 94.8%, a Yoden index of 0.024 and an area under the curve (AUC) of 0.617 (p < 0.001). This high sensitivity means that NHR could be used as an initial screening tool for patients in whom CAD is suspected. It is likely to be most useful in clinical settings with limited diagnostic facilities, but in more advanced clinical settings, the use of a combination of NHR and GS could assist cardiologists to identify high-risk patients with coronary artery stenosis. ⁸

Another study conducted in China also showed that high NHR is an independent risk factor for high GS (OR = 1.491, p = 0.001). The optimal cut-off value of NHR for the prediction of high GS was calculated to be 3.87, and this was associated with a sensitivity of 68% and specificity of 59%. ⁹ Although Manoochehri et al. ¹² showed no difference in the NHR values of patients with differing severities of coronary stenosis, multiple regression analysis revealed that NHR was a good predictor of GS (standardised coefficient beta = −0.702, p = 0.012).

A study conducted in Turkey also showed that high NHR is associated with anatomically significant stenosis in patients with stable CAD and documented myocardial ischaemia. Anatomically significant stenosis was defined as ≥50% stenosis in at least one of the major coronary arteries, demonstrated using invasive coronary angiography (ICA). NHR was found to be significantly higher in patients with anatomically significant stenosis than in those with no or minimal stenosis (121.1 ± 50.8 vs. 105.0 ± 46.6, respectively; p = 0.012). The cut-off value of NHR calculated for the prediction of anatomically significant CAD was 103.2. Additional analyses revealed that an NHR ≥103.2 was predictive of the presence of anatomically significant CAD, with a sensitivity of 61.2% and specificity of 58.1%. In addition, NHR was significantly higher in patients with stenosis of ≥50%, even though all of the patients had ischaemia documented by myocardial perfusion imaging using single-photon emission computed tomography (MPI-SPECT). Even when ischaemia is confirmed using MPI-SPECT, the frequency of diagnosis of no or insignificant coronary stenosis is high on ICA. Myocardial ischaemia owing to coronary vascular dysfunction without arterial occlusion is referred to as ischaemia with non-obstructed coronary arteries (INOCA). The study also provided data that NHR may be a superior predictor in patients with INOCA. Thus, NHR could be assessed before referring patients for ICA, which is associated with complications including haemorrhage at the access site, contrast nephropathy and even death.^11,26 Patients with low NHR, indicative of low risk of disease from coronary stenosis, would not undergo ICA ²⁷ .

Two studies investigated the utility of NHR to assess the degree of stenosis in patients with ACS. Huang et al. ⁷ found a positive association between NHR and the degree of coronary stenosis or GS in patients who presented with AMI. A significant association between NHR values and GS values could not be demonstrated by Chen et al (p = 0.527). ¹¹

Four studies showed significant positive correlations between NHR and the severity of coronary stenosis, and the sensitivities for the prediction of a higher degree of coronary stenosis ranged from 61.2% to 94.8%. In addition, the specificities for the prediction of a higher degree of coronary stenosis using NHR were found to be 58.1% and 59% in two studies (Table 2). An implication of these findings is that the addition of NHR to the GS should improve the cardiovascular risk stratification of patients with CAD. The utility of NHR for the prediction of atherosclerosis and the degree of stenosis has also been studied using vessels other than coronary arteries. One study showed a positive association between NHR and atherosclerosis for patients with values of NHR ≤ 3.32, ²⁸ and another showed that NHR had a higher sensitivity, of 77.6%, for the identification of asymptomatic carotid stenosis. ²⁹

Table 2.

Studies showing an association of NHR with the degree of stenosis.

Author, year of publication	Studied outcome	Correlation coefficient (p-value)	Critical value of NHR for prediction	Area under the curve (95% CI)	Sensitivity	Specificity
Kou, 2021	Prediction of significant CAD (>50% stenosis)	0.225 (<0.001)	1.51 #	0.617 (0.560–0.675)	94.8%	N/A
Li, 2018	Prediction of the highest tertile of GS	0.324 (<0.001)	3.87 #	0.66 (0.58–0.74)	68%	59%
Manoochehri, 2021	Prediction of high GS	0.207 (0.101)	N/A	N/A	N/A	N/A
Basyigit, 2022	Prediction of significant CAD (>50% stenosis)	N/A	103.2*	0.607, (0.535–0.678)	61.2%	58.1%
Huang, 2020	Relationship of NHR with GS	0.15 (<0.001)	N/A	N/A	N/A	N/A
Chen, 2022	Relationship of NHR with GS	N/A	N/A	N/A	N/A	N/A

^#NHR was calculated using the HDL-cholesterol concentration, measured in mmol/L. *NHR was calculated using the HDL-concentration, measured in mg/dL.

CAD, coronary artery disease; CI, confidence interval; GS, Gensini score; NHR, neutrophil-to-high-density lipoprotein-cholesterol ratio; N/A, not applicable.

Number of diseased arteries and the location of lesions

Two studies have investigated the relationship between NHR and the location of stenosis in patients with AMI. Ozgeyik et al. ⁶ found that high NHR, above the cut-off value, was significantly more frequent in patients with proximal culprit lesions than more distally located lesions. The implication of this finding is discussed in the following sections of this paper. However, no association was identified between NHR and the number of diseased coronary arteries. Conversely, in older patients, a high NHR value was associated with a larger number of diseased vessels (p < 0.001). ⁷

Utility of NHR for the prediction of outcomes in patients with acute coronary syndrome

Three studies have explored the utility of NHR to determine the prognosis of patients diagnosed with STEMI or NSTEMI (Table 3). AMI is associated with numerous early complications, such as cardiogenic shock, ventricular aneurysm, arrhythmias, pericarditis, post-infarction angina and embolic complications. ³⁰ Chen et al. ¹⁰ characterised the short-term in-hospital adverse events that occurred in patients with STEMI who underwent a primary percutaneous coronary intervention. These outcomes were referred to as “major adverse cardiac events” (MACE), and included stent thrombosis, cardiac rupture, cardiac arrest, ventricular aneurysm, malignant arrhythmia and cardiac death. A higher neutrophil count and a lower HDL-cholesterol concentration characterised the MACE group vs. the MACE-free group, and the NHR of the MACE group was significantly higher than that of the MACE-free group (10.93 vs. 8.13, respectively; p = 0.001). The AUC for NHR for the prediction of MACE was 0.617 (p = 0.0029) and the optimal cut-off value was calculated to be 11.28, with a sensitivity of 47.2% and a specificity of 77.6%. Furthermore, the risk of in-hospital MACE was found to be more than two-fold higher in patients with NHRs above the cut-off value. ¹⁰ Therefore, such patients should be prioritised for care and carefully observed to facilitate an early diagnosis of MACE. The early diagnosis of such complications and prompt intervention should reduce the in-hospital mortality of high-risk patients identified using their NHRs.

Table 3.

Area under the curve, sensitivity and specificity associated with NHR for the prediction of outcomes of ACS.

Author, year of publication	Studied outcome	Critical value of NHR for prediction	Area under the curve (95% CI)	Sensitivity	Specificity
Chen, 2022	Prediction of MACE	11.28	0.617 (0.57–0.66)	47.22%	77.61%
Huang, 2020	Prediction of RMI and mortality	5.74	0.69 (0.63–0.76)	77.60%	50.80%
Ozgeyik, 2021	Prediction of mortality	0.269	0.830 (0.753–0.908)	74.2%	74.2%

ACS, acute coronary syndrome; CI, confidence interval; MACE, major adverse cardiac events; RMI, recurrent myocardial infarction.

AMI is also associated with long-term consequences, such as recurrent myocardial infarction (RMI) and a higher risk of death. Huang et al. ⁷ demonstrated that NHR could be used to determine the long-term prognosis of older patients with AMI. They found that a high NHR was associated with higher risks of long-term all-cause mortality and RMI. The cut-off value of NHR for the evaluation of long-term clinical outcomes was calculated to be 5.74, with a sensitivity of 77.6% and a specificity of 50.8%. The AUC for NHR was calculated to be 0.69 (p < 0.001), which is larger than those for MHR and LDL-C/HDL-C, and implies that the NHR is superior to MHR and the LDL/HDL ratio for the prediction of long-term outcomes. Furthermore, NHR was found to be an independent predictor of long-term mortality (hazard ratio (HR): 1.96, p = 0.044), but MHR and LDL/HDL were not. In addition, NHR was found to be a potential predictor of RMI (HR: 1.96, p = 0.044). ⁷ No ideal method for the identification of patients who are likely to experience recurrence after an episode has been identified. Conventional risk factors, such as the concentrations of LDL-cholesterol and other lipid species, were found to be of limited use for the secondary prevention of AMI. ³¹ Another marker of inflammation, C-reactive protein, is also significantly associated with cardiovascular events, which implies that persistent inflammation might have a larger effect on residual cardiovascular risk than dyslipidaemia. ³² Therefore, NHR may be superior to these conventional risk factors for the prediction of RMI, owing to its composite nature and its ability to reflect the complex interactions between neutrophils and HDL-cholesterol that are responsible for causing repeat events.

A study by Ozgeyik et al. ⁶ showed that NHR is a better predictor of long-term mortality than any other lipid or cell-related biomarker. The AUC for NHR was calculated to be 0.830 (p < 0.001) and the cut-off value was found to be 0.269, with sensitivity and specificity values of 74.2%. This study also identified NHR to be an independent predictor of cardiovascular mortality (HR = 0.202, p = 0.002). Moreover, a high NHR was significantly more common in patients with proximal culprit lesions than in those with more distal lesions. This could be explained by proximal lesions causing more myocardial damage, which increases the risk of cardiovascular mortality in such patients. ⁶

Rationale for the use of NHR in patients with coronary artery disease

Atherosclerosis is a key pathological contributor to CAD. Vascular inflammation and dyslipidaemia have been identified as key factors responsible for the development of atherosclerosis.^33,34 Neutrophils are considered to mediate the early stages of the inflammatory response and are involved in the activation of monocytes and lymphocytes.^35,36 A high neutrophil count is significantly associated with greater arterial wall stiffness ³⁵ and higher risks of conditions such as ACS, stroke and heart failure.^38,39 Neutrophils are present at all stages of the development of atherosclerosis and promote the progression of atherosclerosis by increasing the inflammatory response and oxidative stress.^5,40 Apart from being involved in the initiation and progression of atherosclerosis, neutrophils are also involved in plaque destabilisation, which leads to ACS. Consistent with this, neutrophil accumulation has been identified at the site of atherosclerotic lesions. ⁴¹ Neutrophil-induced aggregation and infiltration of inflammatory cells, along with platelet aggregation, result in vascular stenosis and blockage. ⁴² Furthermore, neutrophil count is associated with the risk of death in patients with AMI. NETs, proteases and collagenases that are released by neutrophils predispose toward the rupture of atheromatous plaque and cause AMI. ⁴³ Furthermore, multiple studies have shown that neutrophil count is a better predictor of cardiovascular and long-term mortality than the monocyte or lymphocyte counts.^44,45

Dyslipidaemia, which typically includes high concentrations of LDL-cholesterol and low concentrations of HDL-cholesterol, is causally linked to the progression of atherosclerosis. HDL is the major lipoprotein involved in reverse cholesterol transport, in which excess cholesterol is transferred from adipocytes or macrophages back to the liver. HDL also has protective effects in endothelial cells through its antioxidant, anti-apoptotic, anti-inflammatory, anti-thrombotic and anti-proteolytic properties.^4,46,47 Low HDL-cholesterol concentrations have been shown to be associated with higher risks of cardiovascular mortality and cardiovascular diseases in the general population.^48,49 Furthermore, HDL-cholesterol can inhibit inflammation, as illustrated by its effects to reduce neutrophil activation, adhesion and migration.^49,50 Thus, there is an important and complex interaction between neutrophils and HDL-cholesterol. These parameters are related to one-another and together they play a major role in the pathogenesis of CAD. Overall, a high NHR may be related to aberrant lipid metabolism and inflammation because of the interplay between a low HDL-cholesterol concentration and a high neutrophil count in CAD. A more complex marker of disease, such as NHR, may be more useful than a single-parameter marker, given the close relationship between neutrophils and HDL-cholesterol.

Multiple previous studies have shown that NHR is superior to other indicators, such as NLR, PLR, MLR, THR and LDL-C/HDL-C, for the prediction of prognosis in patients with AMI.^6,7,10 In addition, NHR has been found to be useful for the prediction of adverse cardiovascular outcomes in individuals with prediabetes and in those undergoing peritoneal dialysis.^51,52 Moreover, NHR has been shown to have a linear relationship with cardiovascular mortality in the general population, and therefore it may reflect the fundamental pathogenesis of cardiovascular diseases. ⁵³

Calculation of NHR and the pitfalls of its use

NHR can be calculated simply, as NHR = neutrophil count (×10⁹/L)/HDL concentration (mmol/L). The neutrophil count used in the analyses can be obtained using an autoanalyzer and confirmed using smear analyses. The NHRs for patients with CAD must be interpreted cautiously. The timing of blood sampling for the measurement of NHR in patients with ACS can affect its value. The neutrophil count increases rapidly within a few hours of AMI as a result of emergency granulopoiesis to respond to the greater demand and restock the bone marrow reservoir.^54,55 With the resolution of inflammation, the count returns close to the normal range, usually within a week. ²³ Therefore, the change in neutrophil count post-AMI can lead to variability in the NHR. The neutrophil count can also be affected by concomitant conditions, such as infections, haematological disorders and neutropenic drug use. These may cause unusually high or low NHR values, leading to misinterpretation.

Limitations of the study

The small number of articles included is the major limitation of the review. In addition, there was heterogeneity among the included studies, in terms of the participants and the primary outcomes, which prevented a quantitative assessment being made. Another limitation is that all of the included studies were of Chinese, Turkish and Iranian populations, which might constrain the generalisability of the findings presented. Finally, the majority of the included studies were retrospective in design, which limits the persuasiveness of the findings.

Conclusion

An increasing number of studies are investigating the utility of NHR in patients with CAD. The results of previous studies suggest that NHR could be used in cardiovascular medicine for the stratification of risk and the prediction of short and long-term outcomes in patients. However, more studies are required before a quantitative assessment of the utility of NHR for patient management can be made. The present study should provide researchers with a more comprehensive understanding of the potential applications of NHR before they explore other dimensions in the field of cardiovascular medicine.