Abstract
Ischemic heart disease (IHD) is a pressing public health concern with high prevalence, mortality, and morbidity. Although the value of neutrophil-lymphocyte ratio (NLR) and platelet-lymphocyte ratio (PLR) as markers of the acute coronary syndrome are well recognized, there is a paucity of data deciphering their role in screening for stable ischemic heart disease (SIHD) in the presence of type 2 diabetes mellitus (T2DM). The present study investigates the value of NLR and PLR as markers of SIHD in T2DM. We evaluated the predictive value of NLR and PLR for SIHD by comparing T2DM patients having angiographically proven SIHD to T2DM patients without IHD at different cutoff levels by evaluating the area under the curve (AUC) obtained from receiver-operating-characteristic analysis. Raised NLR and PLR were significantly associated with SIHD (P < .001 for each). On performing AUC-receiver-operating-characteristic analysis, NLR of > 2.39 and PLR of > 68.80 were associated with the highest prevalence of SIHD (NLR, AUC: 0.652 [0.605–0.699]; CI: 95%; P < .001, PLR, AUC: 0.623 [0.575–0.671] CI: 95%; P < .001). The sensitivities and specificities for these cutoff values were 50% and 73% for NLR and 73% and 46% for PLR, respectively. NLR and PLR were significantly higher in SIHD compared to those without; however, these markers had limited predictive potential in the setting of T2DM.
Keywords: inflammatory markers, neutrophil-lymphocyte ratio, platelet-lymphocyte ratio, ROC-AUC, stable ischemic heart disease
1. Introduction
Ischemic Heart Disease (IHD) grows as a public health challenge worldwide with increasing rates of prevalence, mortality, morbidity and economic burden. The paucity of cost-effective resources for diagnosing and screening IHD in developing countries results in delays in diagnosis and prompt administration of treatment.[1] Extensive literature linking inflammation to IHD has helped us recognize the value of various inflammatory markers as potential screening tools for the early diagnosis of ischemic heart disease.[2] C-reactive protein (CRP), vascular cell adhesion molecules (VCAMs), selectins, and cytokines, for example, Interleukin-4 (IL-4), are some of the markers explored earlier; however, these are expensive.[3] Neutrophil-lymphocyte ratio (NLR) and Platelet-lymphocyte ratio (PLR) have been studied as alternatives to the aforementioned biomarkers due to their cost-effectiveness and wide availability.
A high NLR has been observed to correlate significantly with the severity of IHD, the progression of atherosclerotic plaque, and major adverse cardiovascular events (MACE)[4,5] and a high PLR has also been recognized as a predictor of severe IHD[6]; however, most previous studies have focused on evaluating their predictive value for diagnosing acute coronary syndromes (ACS) or have correlated them with the severity of coronary artery stenosis. There is paucity of data evaluating the probable value of these economical tests as screening tools for stable ischemic heart disease (SIHD). Type 2 diabetes mellitus (T2DM), a frequent accompaniment of IHD, is another condition associated with the raised NLR and PLR.[7] Some investigators reported that a sub-group of their patients with T2DM had significantly raised NLR when accompanied with IHD compared to those without, but most of the studied patients had ACS, not SIHD.[8] The question of NLR’s predictive value for SIHD, thence, still remains unanswered. In this study we decided to explore the predictive value of NLR and PLR for SIHD in the presence of pro-inflammatory milieu of T2DM.
2. Methods
2.1. Study design and subjects
This single-center, retrospective, cross-sectional study was conducted at the tertiary health care facility attached to a postgraduate medical teaching institution. The institutional ethics committee (IEC) approved this study. Owing to the study’s retrospective design, taking participants’ consent was not applicable. All patients with IHD, who underwent coronary angiography (CAG) in the department of Cardiology from January 2019 to December 2019, were screened for inclusion into this study. Patients aged 40 years or more, having T2DM along with SIHD and not having any pre-defined exclusion criterion, were recruited. For the study purpose, SIHD was defined as presence of spontaneous or inducible myocardial ischemia along with coronary artery diameter stenosis of at least 50% in the left main coronary artery or ≥ 70% in any other epicardial coronary artery and no deterioration in ischemic symptoms over preceding 2 months’ period. The admission for angiography/intervention was based on the decision of the respective treating cardiologist. DM was diagnosed as per the American diabetes association guidelines.
T2DM patients attending the Endocrinology outpatient department (OPD) with no historical, clinical or electrocardiographic evidence of IHD and/or of any other macro-vascular complication of diabetes, served as controls.
Patients with disease conditions having the potential to alter NLR and PLR, namely, thyroid disorders, active acute or chronic infections, chronic inflammatory diseases (rheumatoid arthritis, systemic lupus erythematosus, multiple sclerosis), active malignancy, hematological disorders (leukemia, clotting disorders), pregnancy or lactation, were excluded from the study. Subjects with insufficient demographic data and/or drug history (metformin, statins, angiotensin-converting enzyme inhibitors or angiotensin receptor blocker) were excluded.
2.2. Demographic and clinical data
Baseline characteristics including, age, gender, height, weight, smoking habit, hypertension, drug history including use of metformin, statins, angiotensin-converting enzyme inhibitors or angiotensin receptor blocker and instantaneous office blood pressure, were noted in all eligible subjects. All the patients included in this study were already diagnosed with T2DM according to the American diabetes association criteria. Body mass index (BMI) was calculated by the Quetelet index. Hypertension was defined as a systolic or diastolic blood pressure ≥ 140 or ≥ 90 mm Hg, respectively.
2.3. Determination of laboratory measurements
Blood samples for hematological analysis included total white blood cell (WBC) count, absolute counts of neutrophils, lymphocytes, platelets, and mean platelet volume (MPV). The hematological analysis was performed by Coulter LH 780 Hematology analyzer (Beckman Coulter corp., USA). NLR was calculated from the equation: NLR = absolute neutrophil count (cells/µL)/ absolute lymphocyte count (cells/µL). PLR was calculated using the equation: PLR = platelet count (cells/µL)/absolute lymphocyte count (cells/µL). Besides, fasting plasma glucose, glycated hemoglobin (HbA1c), serum creatinine, alanine aminotransferase (ALT), alkaline phosphatase (ALP), total cholesterol, triglycerides, high-density lipoprotein (HDL)-cholesterol, and low-density lipoprotein (LDL)-cholesterol were measured.
2.4. Statistical methods
The data was analyzed using SPSS version 26.0 (IBM SPSS Statistics, Somers, NY) and R programming language version 3.6.3. Categorical data were presented as frequencies and proportions and compared using the Chi-square test or Fischer’s exact t-test, as appropriate. Continuous data were presented as a median with an interquartile range and were compared using the Mann–Whitney U test. Multivariate logistic regression analysis was performed to determine the independent predictors of stable ischemic heart disease (SIHD). receiver-operating-characteristic (ROC) curve analysis was used to determine the optimum cutoff level of NLR and PLR for predicting SIHD. A P value of < .05 was considered statistically significant.
3. Results
A total of 2956 potential subjects were screened, including 1976 patients admitted for CAG (test group) and 980 T2DM patients attending Endocrinology OPD (control group). Of these, 1596 individuals had to be excluded from the test group due either to the absence of T2DM or to the presence of any of the predefined exclusion criteria. From the remaining 380 subjects, another 58 were excluded because of missing demographic data, and 61 were found to have evidence of ACS. Hence, 261 T2DM patients with SIHD finally qualified for the test group. Of the 980 potential controls, 520, with no symptomatic or electrocardiographic evidence of IHD, were screened further. Of them, 208 met 1 or more of the predefined exclusion criteria. In addition, 40 subjects with macrovascular complications of DM and 15 with insufficient demographic and drug history were also excluded. The remaining 257 subjects constituted the control group.
The baseline demographic data for the 2 studied groups, namely, T2DM with SIHD and T2DM without SIHD, are presented in Table 1, and their corresponding hematological parameters are shown in Table 2. Age distribution was higher in the SIHD group (P < .001), also the prevalence of male gender was significantly higher in the SIHD group (P < .001). As evident, both NLR and PLR were significantly higher in the SIHD group compared to the control group (P < .001).
Table 1.
Demographic characteristics and drug history of Type 2 diabetic patients with stable ischemic heart disease and without ischemic heart disease.
| Variables | Overall (n = 518) | Control (n = 257) | SIHD (n = 261) | P value | |
|---|---|---|---|---|---|
| Age (yr) | 53.00 [48.00, 59.00] | 51.00 [46.00, 57.00] | 55.00 [49.00, 62.00] | <.001 | |
| Sex, n (%) | Female | 136 (26.3) | 93 (36.2) | 43 (16.5) | <.001 |
| Male | 382 (73.7) | 164 (63.8) | 218 (83.5) | ||
| BMI (kg/ m2) | 19.14 [15.06, 24.44] | 15.06 [13.73, 16.45] | 24.41 [22.23, 26.48] | <.001 | |
| HTN, n (%) | No | 258 (49.8) | 177 (68.9) | 81 (31.0) | <.001 |
| Yes | 260 (50.2) | 80 (31.1) | 180 (69.0) | ||
| Smoking, n (%) | No | 396 (76.4) | 196 (76.3) | 200 (76.6) | 1 |
| Yes | 122 (23.6) | 61 (23.7) | 61 (23.4) | ||
| Metformin, n (%) | No | 223 (43.1) | 24 (9.3) | 199 (76.2) | <.001 |
| Yes | 295 (56.9) | 233 (90.7) | 62 (23.8) | ||
| Statin, n (%) | No | 232 (44.8) | 208 (80.9) | 24 (9.2) | <.001 |
| Yes | 286 (55.2) | 49 (19.1) | 237 (90.8) | ||
| ACEi, n (%) | No | 383 (73.9) | 242 (94.2) | 141 (54.0) | <.001 |
| Yes | 126 (24.3) | 15 (5.8) | 111 (42.5) |
Data are presented as median (interquartile range) or number (percentage). categorical variables were analyzed using the Chi-square test, and the Mann–Whitney U test was used for continuous variables. P values ≤ 0.05 were considered statistically significant.
ACEi = angiotensin converting enzyme inhibitor, BMI = body mass index, HTN = hypertension, IHD = ischemic heart disease, SIHD = stable ischemic heart disease.
Table 2.
Hematological characteristics of patients with Type 2 Diabetes Mellitus with Stable Ischemic heart disease and without Ischemic heart disease.
| Variables | Overall (n = 518) | Control (n = 257) | SIHD (n = 261) | P value |
|---|---|---|---|---|
| PPG (mg/dL) | 213.00 [148.50, 298.00] | 257.00 [190.00, 335.00] | 168.00 [121.00, 232.75] | <.001 |
| HbA1c (mmol/mol) | 8.00 [6.70, 9.60] | 7.80 [6.60, 9.60] | 8.15 [7.18, 9.43] | .17 |
| WBC [(n × 103)/mm3] | 8.40 [7.10, 10.00] | 8.40 [7.00, 9.70] | 8.50 [7.30, 10.20] | .107 |
| PLT [(n × 103)/mm3] | 189.50 [140.00, 243.00] | 188.00 [135.00, 240.00] | 192.00 [146.00, 246.00] | .158 |
| MPV (fl) | 11.20 [9.80, 12.40] | 11.30 [10.00, 12.50] | 11.00 [9.80, 12.20] | .15 |
| ANC [(n × 103)/mm3] | 4.90 [4.00, 6.10] | 4.70 [3.80, 5.70] | 5.10 [4.20, 6.60] | <.001 |
| ALC [(n × 103)/mm3] | 2.30 [1.80, 2.90] | 2.40 [2.00, 3.00] | 2.10 [1.60, 2.70] | <.001 |
| NLR | 2.10 [1.58, 2.82] | 1.88 [1.46, 2.46] | 2.40 [1.77, 3.30] | <.001 |
| PLR | 83.23 [60.43, 115.20] | 74.17 [53.33, 106.67] | 91.76 [68.00, 127.00] | <.001 |
Data are presented as median (interquartile range) or number (percentage). categorical variables were analyzed using the Chi-square test, and the Mann–Whitney U test was used for continuous variables. P values ≤ 0.05 were considered statistically significant.
ALC = absolute lymphocyte count, ANC = absolute neutrophil count, HBA1C = glycosylated Haemoglobin, MPV = mean platelet volume, NLR = neutrophil lymphocyte ratio, PLR = platelet lymphocyte ratio, PLT = platelet count, PPBS = post prandial blood sugar, SIHD = stable ischemic heart disease, WBC = white blood cell count.
We included Age, Sex, WBC, PLT, MPV, ANC, ALC, NLR, PLR, and hypertension (HTN) in multivariate analysis to determine the independent predictors of SIHD. Age, Sex, and HTN were independent predictors of SIHD (Table 3). Increasing age, male gender, and the presence of HTN was associated with higher odds of SIHD by multivariate logistic regression analysis.
Table 3.
Multivariate logistic regression analysis of selected variables on in-SIHD.
| Characteristic | OR | 95% CI | P value |
|---|---|---|---|
| Age | 1.03 | 1.01, 1.06 | .017 |
| Sex | |||
| Female | Ref | ||
| Male | 2.98 | 1.86, 4.87 | <.001 |
| WBC [(n × 103)/mm3] | 1.06 | 0.75, 1.53 | .7 |
| PLT [(n × 103)/mm3] | 1.01 | 1.00, 1.01 | .091 |
| MPV (fl) | 0.97 | 0.88, 1.07 | .6 |
| ANC [(n × 103)/mm3] | 0.92 | 0.54, 1.49 | .7 |
| ALC [(n × 103)/mm3] | 0.94 | 0.54, 1.67 | .8 |
| NLR | 1.55 | 0.99, 2.84 | .11 |
| PLR | 1.00 | 0.98, 1.01 | .6 |
| HTN | |||
| No | Ref | ||
| Yes | 5.10 | 3.40, 7.74 | <.001 |
P values ≤ 0.05 were considered statistically significant.
ALC = absolute lymphocyte count, ANC = absolute neutrophil count, CI = confidence interval, HTN = hypertension, MPV = mean platelet volume, NLR = neutrophil lymphocyte ratio, OR = odds ratio, PLR = platelet lymphocyte ratio, WBC = white blood cell count.
The accuracy of NLR and PLR in diagnosing SIHD was poor. The optimum cutoff value for NLR to predict SIHD was 2.39 using a ROC curve with a sensitivity of 50.0% and a specificity of 73.0% (NLR, area under the curve [AUC]: 0.652 [0.605–0.699]; CI: 95%; P < .001). The optimum cutoff value for PLR to predict SIHD was 68.80 using a ROC curve with a sensitivity of 73.0% and a specificity of 46.0% (PLR, AUC: 0.623 [0.575–0.671] CI: 95%; P < .001)(Table 4, Fig. 1).
Table 4.
Area under the curve by Receiver operating characteristics of Neutrophil lymphocyte ratio and Platelet lymphocyte ratio in Stable ischemic heart disease.
| Area under the ROC curve | |||||||
|---|---|---|---|---|---|---|---|
| AUC | cutoff | P value | 95% Confidence interval | Sensitivity | Specificity | ||
| NLR | 0.652 | 2.390 | .000 | 0.605 | 0.699 | 0.5 | 0.730 |
| PLR | 0.623 | 68.800 | .000 | 0.575 | 0.671 | 0.73 | 0.460 |
NLR = neutrophil lymphocyte ratio, PLR = platelet lymphocyte ratio, ROC = receiver-operating-characteristic.
Figure 1.
Area under the curve by Receiver operating characteristics of Neutrophil lymphocyte ratio and Platelet lymphocyte ratio in Stable ischemic heart disease.
4. Discussion
It is a well-recognized fact that atherosclerosis is a chronic inflammatory disease as suggested by the intra-vascular imaging studies, histopathological evidence of inflammatory plaque changes and the abnormally raised levels of circulating inflammatory cellular and the biomarkers.[3,9] Previous studies have shown WBC count, absolute neutrophil count (ANC) and absolute lymphocyte count (ALC) to be independently associated with ACS and SIHD; however, evaluation of these parameters as markers for IHD provided inconsistent results. These inconsistencies were caused by fluctuations in common physiological conditions like stress induced release of catecholamines and cortisol, which are known to cause neutrophil and lymphocyte proliferation.[10] However, NLR was found to be less dependent on these fluctuations, proving its superiority as an indicator or predictor of the inflammatory state.[11]
Similarly, the effect of these hematological parameters has also been extensively studied in T2DM wherein, the rise in NLR was found significantly linked with pre-diabetes, diabetes, as well as poor glycemic control[7]; consequently, this marker has even been proposed as a tool to monitor the disease control and its progression in diabetic patients. Despite these data, there remain some unanswered questions in this context including, whether the hematological markers of inflammation retain their value as indicators of IHD in presence of preexisting inflammatory milieu of T2DM which by itself causes raised NLR; and secondly, since previous studies focused on evaluating their IHD correlation either in ACS patients or in mixed populations with majority of patients having ACS, the strength of the predictive value of these markers in SIHD per se is not known. Hence, in the current study, we explored the predictive value of NLR and PLR for SIHD in the presence of pro-inflammatory milieu of T2DM.
Owing to the pivotal role of leukocytes in inflammation, total WBC count was expected to be a good predictor of IHD. On the contrary, specific subsets of lymphocytes, namely T-regulatory cells and T-helper-2 cells, were found to play a protective role in atherosclerosis[12] and lower lymphocyte count was demonstrated to be a good prognostic marker for ACS and SIHD being significantly associated with longer survival in IHD patients.[13] In confluence with these observations, the current study also revealed that the leukocyte and the neutrophil counts were significantly higher in patients with SIHD, while the absolute lymphocyte count was considerably lower in this group as compared to controls.
On evaluating the validity of NLR and PLR as markers of SIHD, our data demonstrated that high NLR and PLR strongly correlated with SIHD in patients with T2DM. However, the predictive value of these markers for SIHD in patients with T2DM was limited. On performing AUC-ROC analysis, NLR of > 2.39 and PLR of > 68.80 were associated with the highest prevalence of SIHD (NLR, AUC: 0.652 [0.605–0.699]; CI: 95%; P < .001, PLR, AUC: 0.623 [0.575–0.671] CI: 95%; P < .001). The sensitivities and specificities for these cutoff values were 50% and 73% for NLR and 73% and 46% for PLR, respectively.
Numerous studies demonstrated the positive correlation between NLR and the severity of IHD as estimated by 2 scoring systems, namely, SYNTAX and Gensini scoring systems.3 A study by Arbel et al and Iranirad et al demonstrated that NLR > 3 was associated with advanced obstructive IHD and a worse prognosis.[14,15] In these studies, however, the severity of IHD was categorized by the number of vessels involved. In 2 studies by Kaya et al and Sonmez et al, patients with SIHD were investigated, and NLR cutoff values of 2.5 and 1.95 were proposed.[16,17] In the study by Sonmez et al, although patients with DM were included, only a few subjects with the disease were analyzed; moreover, these patients were compared to controls without SIHD (n = 71).[17] Similarly, the study by Kaya et al also studied SIHD in a small sample population of DM (n = 47).[16] In 2018, a large meta-analysis involving 17 studies and 7017 cases was conducted to investigate NLR as a predictor of IHD.[4] This study analyzed data from 3 studies with SIHD, 2 studies with ACS, and 12 studies that broadly included mixed patients with IHD. cutoff values for NLR ranging from 1.95 to 3.97 were proposed.[4] However, none of the above-mentioned studies exclusively studied patients with DM and SIHD. Fernando et al conducted a study in patients with T2DM (n = 150), testing the significance of NLR in subjects with and without IHD (n = 100, n = 50, respectively). It was observed that NLR had significant predictive outcomes in detecting IHD (AUC under ROC = 0.997, 95% CI = 0.993–1.000). This study demonstrated a higher mean NLR for patients with IHD than our study (4.09 ± 1.67 vs 3.06 ± 2.91).[18] The study, however, did not differentiate ACS and SIHD, which may be the cause for the disparity.
In the present study, although we found NLR to be significantly elevated in SIHD compared to the controls, it could not adequately predict the presence of SIHD. This may be reasoned that NLR is more indicative of an acute response than a chronic inflammatory response, as seen in SIHD.[8] The co-existence of a pro-inflammatory state as that seen in T2DM, which by itself is independently associated with high NLR,[7] might have further masked any substantial difference in the levels of inflammatory markers that 1 may expect. The association between higher platelet count and cardiovascular disease has received support from recent studies.[19] Due to the thrombotic nature of the disease process, platelets have been indicted for playing a significant role in the initiation and progression of the thrombus.[20] Higher platelet counts were observed in states with underlying inflammation due to the increased stimulation of megakaryocyte proliferation in the bone marrow.[21] In the present study, we did not observe a significant relationship between high platelet count and the presence of SIHD. However, the Platelet-Lymphocyte ratio was observably higher in patients with SIHD when compared to the controls. By combining the pro-thrombotic response of platelets and controlled inflammatory response by lymphocytes, PLR has been proven to be a more reliable indicator of inflammation.[22] PLR was found to be positively associated with the severity of coronary atherosclerosis in ACS and was also found to be an independent predictor of severe IHD when the latter was stratified using Gensini score.[23,24] In a study by Cho KI et al, high PLR was reported to be an independent predictor of long-term adverse events after percutaneous intervention in ACS but not in SIHD.[25] In a study by Yüksel M. et al, PLR of > 111 predicted severe atherosclerosis (n = 388); however, this study primarily comprised of subjects with no history of T2DM (n = 296).[6] In the present study, exclusively involving subjects with T2DM, we propose a cutoff value of PLR > 68.80.Area under the ROC curve for PLR in the present study and the Yüksel M. et al study was comparable (0.623, 0.575–0.671, 95% CI; P < .001 vs 0.645, 95% CI: 0.587–0.703; P < .001).[6]
5. Conclusion
NLR and PLR are inflammatory cellular markers that have been studied for their association with IHD, more so in patients presenting with ACS. In this study, we explored their role as rapid and inexpensive markers of SIHD in the pro-inflammatory milieu of T2DM.With a cutoff NLR value of > 2.39, we could predict the presence of SIHD in T2DM with a sensitivity of 50% and a specificity of 73%. Similarly, at PLR cutoff value of > 68.80, the SIHD could be predicted with a sensitivity of 73% and specificity of 46%. Hence, NLR and PLR are significantly higher in diabetics with SIHD, compared to the once without IHD; these ratios, however, have limited predictive potential in this setting.
6. Limitations
Our study has some limitations including: this was a single-center study with a relatively small sample size; silent ischemia was ruled out by stress test only in those control group subjects who either had symptoms or EKG findings that raised suspicion of IHD.
A larger multi-center study may be conducted for further clarification on this subject.
Author contributions
Conceptualization: Amey Joshi.
Data curation: Amey Joshi, Abdelrahman M Attia.
Formal analysis: Abdelrahman M Attia.
Investigation: Amey Joshi, Anupam Bhambhani, Abdelrahman M Attia.
Methodology: Amey Joshi, Anupam Bhambhani, Vijaya Sarathi, Abdelrahman M Attia.
Project administration: Anupam Bhambhani.
Software: Abdelrahman M Attia, Abhigan Babu Shrestha.
Supervision: Vikash Jaiswal.
Validation: Amey Joshi, Anupam Bhambhani, Samhitha Gonuguntla, Vijaya Sarathi, Abdelrahman M Attia, Abhigan Babu Shrestha, Vikash Jaiswal.
Visualization: Amey Joshi, Anupam Bhambhani, Samhitha Gonuguntla, Vijaya Sarathi, Vikash Jaiswal.
Writing – original draft: Amey Joshi, Anupam Bhambhani, Ramdas Barure, Samhitha Gonuguntla, Vijaya Sarathi.
Writing – review & editing: Amey Joshi, Anupam Bhambhani, Ramdas Barure, Samhitha Gonuguntla, Vijaya Sarathi, Abdelrahman M Attia, Abhigan Babu Shrestha, Vikash Jaiswal.
Abbreviations:
- ACS
- acute coronary syndrome
- AUC
- area under the curve
- IHD
- ischemic heart disease
- NLR
- neutrophil-lymphocyte ratio
- PLR
- platelet-lymphocyte ratio
- ROC
- receiver-operating-characteristic
- SIHD
- stable ischemic heart disease
- T2DM
- type 2 diabetes mellitus
This manuscript is a unique submission and is not being considered for publication by any other source in any medium. Further, the manuscript has not been published, in part or in full, in any form.
The authors have no funding and conflicts of interest to disclose.
The datasets generated during and/or analyzed during the current study are available from the corresponding author on reasonable request.
How to cite this article: Joshi A, Bhambhani A, Barure R, Gonuguntla S, Sarathi V, Attia AM, Shrestha AB, Jaiswal V. Neutrophil-lymphocyte ratio and platelet-lymphocyte ratio as markers of stable ischemic heart disease in diabetic patients: An observational study. Medicine 2023;102:5(e32735).
Contributor Information
Amey Joshi, Email: dr.amey.joshi95@gmail.com.
Anupam Bhambhani, Email: anupam.bhambhani@yahoo.in.
Ramdas Barure, Email: dr.rambarure@gmail.com.
Samhitha Gonuguntla, Email: samhithagonuguntla@gmail.com.
Vijaya Sarathi, Email: drvijayasarathi@gmail.com.
Abdelrahman M Attia, Email: abdelrahman-m-attia@students.kasralainy.edu.eg.
Vikash Jaiswal, Email: vikash29jaxy@gmail.com.
References
- [1].Dai H, Much AA, Maor E, et al. Global, regional, and national burden of ischaemic heart disease and its attributable risk factors, 1990-2017: results from the global burden of disease study 2017. Eur Heart J Qual Care Clin Outcomes. 2022;8:50–60. [DOI] [PMC free article] [PubMed] [Google Scholar]
- [2].Zakynthinos E, Pappa N. Inflammatory biomarkers in coronary artery disease. J Cardiol. 2009;53:317–33. [DOI] [PubMed] [Google Scholar]
- [3].Myers GL, Christenson RH, Cushman M, et al. National academy of clinical biochemistry laboratory medicine practice guidelines: emerging biomarkers for primary prevention of cardiovascular disease. Clin Chem. 2009;55:378–84. [DOI] [PubMed] [Google Scholar]
- [4].Li X, Ji Y, Kang J, et al. Association between blood neutrophil-to-lymphocyte ratio and severity of coronary artery disease: Evidence from 17 observational studies involving 7017 cases. Medicine (Baltim). 2018;97:e12432. [DOI] [PMC free article] [PubMed] [Google Scholar]
- [5].Adamstein NH, MacFadyen JG, Rose LM, et al. The neutrophil-lymphocyte ratio and incident atherosclerotic events: analyses from five contemporary randomized trials. Eur Heart J. 2021;8:1034. [DOI] [PMC free article] [PubMed] [Google Scholar]
- [6].Yüksel M, Yildiz A, Oylumlu M, et al. The association between platelet/lymphocyte ratio and coronary artery disease severity. Anatol J Cardiol. 2015;15:640–7. [DOI] [PMC free article] [PubMed] [Google Scholar]
- [7].Mertoglu C, Gunay M. Neutrophil-lymphocyte ratio and platelet-lymphocyte ratio as useful predictive markers of prediabetes and diabetes mellitus. Diabetes Metab Syndr. 2017;11:1. [DOI] [PubMed] [Google Scholar]
- [8].Verdoia M, Schaffer A, Barbieri L, et al. Impact of diabetes on neutrophil-to-lymphocyte ratio and its relationship to coronary artery disease. Diabetes Metab. 2015;41:304–11. [DOI] [PubMed] [Google Scholar]
- [9].Garcia-Garcia HM, Costa MA, Serruys PW. Imaging of coronary atherosclerosis: intravascular ultrasound. Eur Heart J. 2010;31:2456–69. [DOI] [PubMed] [Google Scholar]
- [10].Benschop RJ, Rodriguez-Feuerhahn M, Schedlowski M. Catecholamine-induced leukocytosis: early observations, current research, and future directions. Brain Behav Immun. 1996;10:77–91. [DOI] [PubMed] [Google Scholar]
- [11].Horne BD, Anderson JL, John JM, et al. Which white blood cell subtypes predict increased cardiovascular risk? J Am Coll Cardiol. 2005;45:1638–43. [DOI] [PubMed] [Google Scholar]
- [12].Li J, Ley K. Lymphocyte migration into atherosclerotic plaque. Arterioscler Thromb Vasc Biol. 2015;35:40–9. [DOI] [PMC free article] [PubMed] [Google Scholar]
- [13].Zouridakis EG, Garcia-Moll X, Kaski JC. Usefulness of the blood lymphocyte count in predicting recurrent instability and death in patients with unstable angina pectoris. Am J Cardiol. 2000;86:449–51. [DOI] [PubMed] [Google Scholar]
- [14].Arbel Y, Finkelstein A, Halkin A, et al. Neutrophil/lymphocyte ratio is related to the severity of coronary artery disease and clinical outcome in patients undergoing angiography. Atherosclerosis. 2012;225:456–60. [DOI] [PubMed] [Google Scholar]
- [15].Iranirad L, Sadeghi M, Ahmadi M, et al. Relationship between neutrophil-to-lymphocyte ratio and the severity of coronary artery disease in patients undergoing cardiac catheterization. J Cardiothorac Med. 2018;6:246–50. [Google Scholar]
- [16].Kaya A, Kurt M, Tanboga IH, et al. Relation of neutrophil to lymphocyte ratio with the presence and severity of stable coronary artery disease. Clin Appl Thromb Hemost. 2014;20:473–7. [DOI] [PubMed] [Google Scholar]
- [17].Sönmez O, Ertaş G, Bacaksiz A, et al. Relation of neutrophil-to-lymphocyte ratio with the presence and complexity of coronary artery disease: an observational study. Anadolu Kardiyol Derg. 2013;13:662–7. [DOI] [PubMed] [Google Scholar]
- [18].Fernando ML, Silambanan S, Malar J. Neutrophil to lymphocyte ratio as an indicator of presence of coronary artery disease in diabetic patients. Int J Clin Biochem Res. 2015;2:143–7. [Google Scholar]
- [19].Lassale C, Curtis A, Abete I, et al. Elements of the complete blood count associated with cardiovascular disease incidence: findings from the EPIC-NL cohort study. Sci Rep. 2018;8:3290. [DOI] [PMC free article] [PubMed] [Google Scholar]
- [20].Gill D, Monori G, Georgakis MK, et al. Genetically determined platelet count and risk of cardiovascular disease. Arterioscler Thromb Vasc Biol. 2018;38:2862–9. [DOI] [PMC free article] [PubMed] [Google Scholar]
- [21].Azab B, Shah N, Akerman M, et al. Value of platelet/lymphocyte ratio as a predictor of all-cause mortality after non-ST-elevation myocardial infarction. J Thromb Thrombolysis. 2012;34:326–34. [DOI] [PubMed] [Google Scholar]
- [22].Gasparyan AY, Ayvazyan L, Mukanova U, et al. The platelet-to-lymphocyte ratio as an inflammatory marker in rheumatic diseases. Ann Lab Med. 2019;39:345–57. [DOI] [PMC free article] [PubMed] [Google Scholar]
- [23].Kurtul A, Murat SN, Yarlioglues M, et al. Association of platelet-to-lymphocyte ratio with severity and complexity of coronary artery disease in patients with acute coronary syndromes. Am J Cardiol. 2014;114:972–8. [DOI] [PubMed] [Google Scholar]
- [24].Akboga MK, Canpolat U, Yayla C, et al. Association of platelet to lymphocyte ratio with inflammation and severity of coronary atherosclerosis in patients with stable coronary artery disease. Angiology. 2016;67:89–95. [DOI] [PubMed] [Google Scholar]
- [25].Cho KI, Ann SH, Singh GB, et al. Combined usefulness of the platelet-to-lymphocyte ratio and the neutrophil-to-lymphocyte ratio in predicting the long-term adverse events in patients who have undergone percutaneous coronary intervention with a drug-eluting stent. PLoS One. 2015;10:e0133934. [DOI] [PMC free article] [PubMed] [Google Scholar]