Predictive Value of Lymphocyte Based Indices to Determine Major Adverse Cardiovascular Events in Acute Coronary Syndrome Undergoing Percutaneous Coronary Intervention

Abstract

Acute coronary syndrome (ACS) is leading cause of mortality worldwide. Percutaneous coronary intervention (PCI) is the main stay of treatment in patients presenting with ACS. However, studies have shown that PCI itself may induce and promote inflammatory process. Lymphocyte based hematological indices: neutrophil lymphocyte ratio (NLR), platelet lymphocyte ratio (PLR), monocyte lymphocyte ratio (MLR) and systemic inflammatory index (SII) have been shown as effective indicator of underlying inflammatory process. We conducted a prospective observational follow up study to observe the changes in NLR, PLR, MLR and SII before and after PCI in ACS patients and their predictive value in determining major adverse cardiac events (MACE) and prognosis in these patients. Blood samples were collected from 403 ACS patients at admission and within 48 h of PCI. NLR, PLR, MLR and SII decreased from baseline which was suggestive of resolving inflammation following PCI. ROC curve analysis showed post PCI SII has highest predictive value for incidence of MACE. Cox multivariate analysis showed post-PCI hematological indices were predictors of MACE including all-cause mortality. Patients with elevated inflammatory indices had poor survival outcomes compared to those having low values. Thus, it could be concluded that compared to pre-PCI inflammatory markers, post-PCI inflammatory markers showed stronger correlation in predicting MACE. Among post PCI indices, SII had the strongest correlation with incidence of MACE during the follow up.

Supplementary Information

The online version contains supplementary material available at 10.1007/s12291-024-01188-x.

Introduction

Globally, cardiovascular diseases (CVDs) are the leading cause of mortality and morbidity and contribute substantially to health care system of any country [1]. Acute coronary syndrome (ACS) is the most severe form of CVD and includes ST-segment elevation myocardial infarction (STEMI), non-ST-segment elevation myocardial infarction (NSTEMI) and unstable angina (UA) and carries highest risk of risk of mortality [2]. Percutaneous coronary intervention (PCI) is considered as standard treatment for ACS and have been shown to reduce mortality. However even after PCI, the residual risk of patients surviving until 1 year after ACS is still high, despite secondary prevention [3]. These patients still have a recurrent cardiovascular event like myocardial infarction (MI), stroke or cardiovascular death in the years following their initial admission. Even after first year, there is increased risk of major adverse cardiac events (MACE). A registry of ACS patients (GRACE UK-Belgian Study) has shown that 20% of patients have died after 5 years, 13% of them due to cardiovascular causes, implying that additional secondary prevention measures are warranted beyond first year of index event [4].

Studies have shown that inflammation not only plays an important role in pathogenesis of atherosclerosis but also in development of ACS by causing plaque rupture and erosion [5, 6]. Lymphocyte indices were initially developed as markers of inflammation in predicting prognosis in non-cardiac illness [7, 8]. However, recent studies have shown that these indices can also be used to determine prognosis in ACS patients [9]. They correlate with the complexity of coronary artery stenosis determined by SYNTAX score during coronary angiography, number of stents required, procedure related complication like coronary no flow, slow flow, stent thrombosis and restenosis [10–12]. Since these indices are cost effective and easy to calculate, they can be economical method to prognosticate patients undergoing PCI in a resource limited country like India.

The aim of our study was to observe the trends in lymphocyte base haematological indices like neutrophil lymphocyte ratio (NLR), platelet lymphocyte ratio (PLR), monocyte lymphocyte ratio (MLR) and systemic immune-inflammation (SII) index before and after PCI in ACS patients and their diagnostic and prognostic value in determine MACE during the follow up period.

Materials and Methods

Research Patients

The was a single-centre, cross-sectional follow up observational study performed at tertiary care medical university in India. Patients ≥ 18 years of age diagnosed with ACS who underwent coronary angiography (CAG) followed by PCI from January 2022 to December 2022 and fulfilling inclusion criteria were included. STEMI was considered in presence of (1) at least two contiguous leads with ST-segment elevation ≥ 2 mm in chest leads and/or ST-segment elevation of ≥ 1 mm in other leads or new left bundle branch block and (2) detection of dynamic change of cardiac troponin-T with at least one value above 99th percentile upper reference limit. If electrocardiograph revealed ischemia patterns without persistent ST elevation and cardiac markers were elevated, patients were considered to have NSTEMI. Those who had typical chest pain and cardiac markers within normal range were classified UA. On admission, patients were evaluated and treated according to current guidelines, history of the patients was reviewed, including demographic data (age, gender, presence of risk factors for CAD like smoking, diabetes, hypertension, dyslipidaemia, family history). Patients who were on steroids, anticoagulant, had haematological disorders, chronic inflammation disease, malignant tumours, severe hepatic disease or renal disease (alanine aminotransferase or aspartate aminotransferase > 500 U/L or estimated glomerular filtration rate (eGFR) < 30 mL/min/1.73 m²) were excluded from study.

Research Methods

Haematological Indices

Peripheral venous blood samples were collected from each patient before PCI and within 48 h after PCI. Haematological parameters were measured using Sysmex XS-1000i automated Analyzer (Sysmex Corporation HQ: Japan) and biochemical parameters were measured using AU-480 Auto Analyzer (Beckman Coulter India Pvt. Ltd, Bengaluru, India). The glomerular filtration rate (GFR) was estimated using the Cockcroft-Gault formula. The hematologic indices were calculated pre and post PCI using following formulas:

$$\text{SII}=(\text{neutrophil}\text{count}\times \text{platelet}\text{count})/\text{lymphocyte}\text{count}$$

$$\text{NLR}=\text{neutrophil}\text{count}/\text{lymphocyte}\text{count}$$

$$\text{PLR}=\text{platelet}\text{count}/\text{lymphocyte}\text{count}$$

$$\text{MLR}=\text{monocyte}\text{count}/\text{lymphocyte}\text{count}$$

CAG and PCI

All patients underwent CAG using either Tiger diagnostic catheter through trans-radial route or Judkins catheter using trans-femoral route. Coronary angiograms were recorded on digital media for analysis. PCI was done as per relevant guidelines. Angioplasty technique and target vessel revascularisation was left at the discretion of the individual interventional cardiologists. Successful PCI was defined as absence of residual stenosis and achievement of TIMI III flow. PCI related parameters, such as the number of treated coronary arteries, number of implanted stents, average lengths and width of implanted stents, type of anti-platelets and concomitant medical treatments during hospitalization and after discharge were recorded. The patient was continued on Dual Antiplatelets Therapies (DAPT) for a period of at least 1 year.

MACE

MACE was defined as death from suspected cardiovascular events, new episode of myocardial infarction, unplanned PCI, Stroke or progression to class IV heart failure as per New York Heart Association (NYHA) classification.

The patients were followed up for a median period of 1 year from date of PCI. Follow up was done through OPD visits, WhatsApp or telephone according to their condition to observe the occurrence of MACE.

Statistical Analysis

Data were analysed using SPSS version 22.0 (SPSS Inc., Chicago, Illinois). Normality of data distribution was analysed using Kolmogorov–Smirnov test. Numeric variables with normal distribution were presented as mean ± standard deviation (SD), whereas those without normal distribution were presented as median and interquartile range. Categorical variables were presented as number and percentage (%) and compared using the chi-square or Fisher's exact test. A multivariate Cox regression model was used to analyse the factors influencing the incidence of MACE in patients with ACS. A receiver operating characteristic (ROC) curve was used to evaluate the predictive value of inflammation indicators for the incidence of MACE after PCI in patients with ACS. Independent predictors of MACE, all-cause mortality and death from cardiac causes was estimated by COX-Regression and Cox-Proportion model. Survival was analysed by Kaplan Meier estimator. Statistical significance was set at p < 0.05.

Results

Baseline Characteristic of Study Population

In the present study, out of 403 patients, 337 were male and 66 were female. 39 patients had MACE in follow up whereas 364 remained event free. Significant difference was seen between both the groups with respect to family history of CAD, past history of CAD and baseline SYNTAX II score. Other baseline characteristics were comparable between both the groups (Table 1).

Table 1.

Comparison of baseline clinical characteristic of MACE group and non-MACE group

	MACE	Non-MACE	P value
No of patients	39	364
Male	30	306	0.255
Female	9	58
Age (mean ± SD)	61.15 ± 13.51	58.4 ± 10.6	0.137
Tobacco, n (%)	10 (25.6%)	79 (21.7%)	0.573
Smoker, n (%)	15 (38.5%)	141 (38.7%)	0.973
HTN, n (%)	23 (59%)	182 (50%)	0.287
Diabetes, n (%)	14 (35.9%)	153 (42.3%)	0.443
CVA, n (%)	2 (5.1%)	20 (5.5%)	0.924
CAD, n (%)	8 (20.5%)	34 (9.3%)	0.03
Family history, n (%)	9 (23.1%)	43 (11.8%)	0.04
Past CAG, n (%)	9 (23.1%)	56 (15.4%)	0.214
Past PCI, n (%)	8 (20.5%)	53 (14.6%)	0.324
STEMI, n (%)	24 (61.5%)	181 (49.7%)	0.073
Anterior wall STEMI, n (%)	15 (38.5%)	99 (27.2%)	0.138
Inferior wall STEMI, n (%)	7 (17.9%)	71 (19.5%)	0.815
Posterior wall STEMI, n (%)	2 (5.1%)	11 (3.0%)	0.479
Thrombolysis, n (%)	14 (35.9%)	92 (25.3%)	0.152
Streptokinase, n (%)	7 (17.9%)	21 (5.8%)	0.004
Reteplase, n (%)	10 (25.6%)	55 (15.1%)	0.08
Tenecteplase, n (%)	0 (0.0%)	7 (1.9%)	0.382
IRA LAD, n (%)	23 (59.0%)	183 (50.3%)	0.302
IRA non-LAD, n (%)	16 (41.0%)	180 (49.5%)	0.317
NSTEMI, n (%)	9 (23.1%)	125 (34.3%)	0.156
Prasugrel	17 (43.6%)	142 (39.0%)	0.578
Ticagrelor	17 (43.6%)	178 (48.9%)	0.528
Clopidogrel	5 (12.8%)	43 (11.8%)	0.854
Beta blockers	23 (59.0%)	230 (63.2%)	0.605
ACE/ARB	26 (66.7%)	232 (63.7%)	0.733
MRA	13 (33.3%)	123 (33.8%)	0.945
Diuretics	11 (28.2%)	101 (27.7%)	0.960
SGLT inhibitors	9 (23.1%)	92 (25.3%)	0.742
SYNTAX score	24.74 ± 10.10	22.14 ± 9.802	0.118
SYNTAX II score	35.19 ± 10.35	30.61 ± 10.33	0.009
SVD	8 (20.5%)	125 (34.3%)	0.081
DVD	14 (35.9%)	127 (34.9%)	0.902
TVD	17 (43.6%)	108 (29.7%)	0.076
Number of stents	1.69 ± 0.83	1.63 ± 0.78	0.681
Total length of stent (mm)	51.38 ± 30.61	46.27 ± 26.99	0.268
Average length of stent	29.17 ± 6.11	29.64 ± 9.104	0.751
Average diameter of stent	2.97 ± 0.37	3.71 ± 14.26	0.748

Changes in Blood Cell Components and Haematological Indices Before and After PCI

In ACS patients, post-PCI there was decrease in Neutrophil, Monocyte and platelet count with parallel increase in Lymphocyte count. These values were reflected in changes in NLR, PLR, MLR and SIIS suggestive of resolving trend of inflammation following myocardial revascularisation (Supplementary Table).

ROC Curve of Inflammatory Markers for Predicting MACE in ACS Patients

Our Study showed NLR, PLR, SII (pre-PCI) and NLR, MLR, SII (post-PCI) could be used to predict incidence of MACE after PCI. The area under curve (AUC) for predicting incidence of MACE was greatest for post-PCI SII (AUC: 0.984; p < 0.001) (Table 2, Fig. 1). The optimal cut off point for pre-PCI NLR was 2.66 (sensitivity 79.5% and specificity 52.7%), for PLR was 112.83 (sensitivity 74.4% and specificity 45.3%) and for SII was 660.74 (sensitivity 76.9% and specificity 48.1%). Pre-PCI MLR showed no significant corelation for predicting MACE (AUC: 0.537; p = 0.447). Similarly, optimal cut off point for post-PCI NLR was 4.709 (sensitivity 97.4% and specificity 91.2%), for PLR was 172.86 (sensitivity 96.4% and specificity 87.9%), and for MLR was 0.198 (sensitivity 92.3% and specificity 75.5%). Post-PCI SII was 1781.17 (sensitivity 99.4% and specificity 98.9%). (Table 3).

Table 2.

Pre and post PCI AUC curve of inflammatory markers in predicting MACE and cut off for ROC curve

Markers	Pre PCI					Post PCI
	AUC	P value	Cut off	Sensitivity (%)	Specificity (%)	AUC	P value	Cut off	Sensitivity (%)	Specificity (%)
NLR	.744	< 0.001	2.66	79.5	52.5	.914	< 0.001	4.709	97.4	91.2
MLR	.537	0.447	0.096	61.5	45.3	.931	< 0.001	0.198	92.3	75.5
PLR	.682	< 0.001	112.83	74.4	45.3	.940	< 0.001	172.86	97.4	87.9
SII	.752	< 0.001	660.74	76.9	48.1	.984	< 0.001	1781.16	97.4	98.9

Fig. 1.

ROC curve of pre-PCI (A) and post-PCI (B) inflammatory markers for predicting MACE. (ROC, receiver operating curve; PCI, percutaneous coronary intervention; MACE, major adverse cardiovascular events)

Table 3.

Correlation analysis of post-PCI NLR, MLR, PLR and SII

	Post PCI NLR		Post PCI MLR		Post PCI PLR		Post PCI SII
	R	P value	r	P value	r	P value	r	P value
Age	0.076	0.13	0.116	0.091	0.110	0.28	0.098	0.059
SYNTAX score	0.031	0.533	0.010	0.841	0.004	0.937	0.067	0.181
SYNTAX II score	0.103	0.039	0.063	0.207	0.254	0.047	0.121	0.015
Number of stents	0.971	0.002	0.024	0.632	0.670	0.021	0.859	0.009
Average length of stent (mm)	0.971	0.019	0.004	0.938	0.654	0.022	0.953	0.003
Total length of stent (mm)	0.587	0.027	0.041	0.417	0.425	0.04	0.299	0.042
Average width of stent (mm)	0.006	0.905	0.050	0.314	0.004	0.937	0.013	0.797
Pre PCI NLR	0.411	< 0.001	0.199	< 0.001	0.262	< 0.001	0.373	< 0.001
Pre PCI MLR	0.287	< 0.001	0.392	0.005	0.222	< 0.001	0.336	0.048
Pre PCI PLR	0.259	< 0.001	0.142	< 0.001	0.344	< 0.001	0.331	< 0.001
Pre PCI SII	0.377	< 0.001	0.211	< 0.001	0.327	< 0.001	0.418	< 0.001
Post PCI NLR	1	< 0.001	0.691	< 0.001	0.844	< 0.001	0.935	< 0.001
Post PCI MLR	0.691	< 0.001	1	< 0.001	0.222	< 0.001	0.658	< 0.001
Post PCI PLR	0.822	< 0.001	0.670	< 0.001	1	< 0.001	0.884	< 0.001
Post PCI SII	0.935	< 0.001	0.658	< 0.001	0.327	< 0.001	1	< 0.001

Corelation Analysis of Post-PCI PLR, MLR, NLR and SII

Corelation analysis showed that post-PCI NLR, PLR and SII showed positive corelation with age, pre-PCI lymphocyte-based indices, no of stents required, average and total length of stents and SYNTAX II score though no corelation was seen with average width of stent used and SYNTAX score (Table 3). In contrast, no significant corelation was seen between post-PCI MLR with no of stents required, average and total length of stents and SYNTAX II score.

Predictors MACE and All-Cause Mortality in Patients with ACS

Of the 403 patients who were followed for a median period of 12 months, 39 patients (9.6%) experienced MACE. Multivariate Cox-Regression Model was used to analyse the possible factors influencing MACE. Result showed post-PCI NLR (Hazard Ratio [HR] = 1.348; p < 0.001); post-PCI PLR (Hazard Ratio [HR] = 1.013; p < 0.001); post-PCI MLR (Hazard Ratio [HR] = 3.921; p < 0.001); post-PCI SII (Hazard Ratio [HR] = 1.001; p < 0.001); SYNTAX II score (Hazard Ratio [HR] = 1.036; p = 0.015) and presence of STEMI (Hazard Ratio [HR] = 3.921; p < 0.001) were independent factors predicting incidence of MACE after PCI whereas Pre-PCI NLR, PLR, MLR and SII had no effect on incidence of MACE after PCI (Table 4).

Table 4.

Multivariate Cox-regression analysis of the factors predicting MACE in patients with ACS

	B	Wald	P value	HR	95% CI
					Lower bound	Upper bound
Age	.026	2.732	.098	1.026	.995	1.057
Sex	− .600	2.493	.114	.549	.260	1.156
Tobacco	− .345	.887	.346	.708	.345	1.453
Smoker	.010	.001	.975	1.010	.530	1.926
HTN	− .332	1.038	.308	.718	.379	1.358
Diabetes	.244	.534	.465	1.276	.663	2.455
CVA	.263	.131	.717	1.301	.313	5.397
Family History	− .882	5.381	.020	.414	.197	.872
Past CAG	− .556	2.141	.143	.573	.272	1.208
Past PCI	− .449	1.281	.258	.638	.293	1.389
STEMI	1.366	67.529	< .001	3.921	2.830	5.431
NSTEMI	.321	.711	.399	1.378	.654	2.903
SYNTAX score	.024	2.073	.150	1.024	.991	1.059
SYNTAX II score	.035	4.713	.030	1.036	1.003	1.070
Number of stents	.170	.757	.384	1.185	.808	1.738
Total Length of stent (mm)	.006	1.455	.228	1.006	.996	1.017
Pre PCI NLR	.055	4.070	.054	1.056	1.002	1.114
Pre PCI MLR	.815	1.233	.267	2.260	.536	9.528
Pre PCI MHR	.001	.004	.952	1.001	.961	1.043
Pre PCI PLR	− .003	1.623	.203	.997	.991	1.002
Pre PCI SII	.000	2.929	.087	1.000	1.000	1.001
Post PCI NLR	.299	102.287	< .001	1.348	1.272	1.429
Post PLR	.013	92.827	< .001	1.013	1.010	1.015
Post MLR	1.366	67.529	< .001	3.921	2.830	5.431
Post SII	.001	122.839	< .001	1.001	1.001	1.001

Kaplan Meier Survival Analysis

The patients were divided into two groups based on NLR, PLR, MLR and SII values: Group 1 (NLR, PLR, MLR and SII < optimal diagnostic cut off) and Group 2 (any of NLR, PLR, MLR or SII > optimal diagnostic cut off). The median survival in group 1 was 51 weeks and in group 2 was 29.7 weeks. Kaplan Meier survival analysis showed poor long term survival outcomes in group 2 compared to group 1 (HR 2.819, 95% CI 1.719 to 5.173; p < 0.001) (Fig. 2).

Fig. 2.

Kaplan Meier analysis curve to determine survival in ACS patients who underwent PCI in relation of Inflammatory Indices. (Group 1—NLR, PLR, MLR and SII < optimal diagnostic cut off; Group 2—any of NLR, PLR, MLR or SII > optimal diagnostic cut off; ACS, acute coronary syndrome; PCI, percutaneous coronary intervention)

Discussion

Inflammation not only plays key role in the pathogenesis of atherosclerotic cardiovascular disease but also determine prognosis in ACS patients [13]. Lymphocyte based indices has been correlated with degree of inflammation and complexity of CAD. The use of these indices in prognostication of ACS patients undergoing PCI has recently been studied by many authors but none of these studies was from India. In our study, we found that these lymphocytes based haematological indices: NLR, PLR, MLR and SII decreased within 48 h post-PCI in ACS patients. These findings were in contrast to study done by Sheng et al. who concluded that NLR and PLR increased post-PCI, though values were calculated at 24 h [14]. Studies on the changing trend of SII and MLR in ACS patients undergoing PCI are lacking.

The relationship of these lymphocyte indices with MACE varies in different studies. Sheng et al. studied the changes in complete blood count in 205 patients with ACS at admission and at 24 h and 30 days post PCI [14]. They found acute STEMI and 24 h post-PCI NLR and PLR to be independent influencing factors for the incidence of MACE after PCI. 24 h post-PCI NLR was a better predictor of the incidence of MACE and significantly correlated with the number and length of implanted stents and operation duration. Our study also showed similar results, with NLR, PLR, MLR and SII at 48 h post-PCI to be independent risk factors for MACE. Post PCI NLR, PLR and SII correlated significantly with total number and average length of stent implanted. In our study, even Pre-PCI NLR, PLR and SII has been shown to have significant corelation with incidence of MACE.

NLR has been studied widely in different medical conditions including ACS patients and reflects changes in inflammatory state between innate and adaptive inflammation driven by neutrophils and lymphocytes respectively. The normal value of NLR has been considered between 1 to 3 and the value above 3 and below 0.7 suggests pathological inflammation (innate immunity and adaptive immunity respectively). Elevated NLR is independently associated with the development of no reflow, in-hospital MACEs and long-term prognosis in patients with STEMI undergoing primary PCI [15, 16]. This is because PCI itself induces inflammatory state leading to neutrophil chemotaxis which causes platelet activation and release of inflammatory mediators. This creates a vicious cycle leading to plaque instability, thrombosis, coronary no-reflow and increased risk of in-stent restenosis (ISR) [12]. Our study found that compared to pre-PCI cut value > 2.66, post PCI NLR > 4.709 had a greater sensitivity (79.5% vs 97.4%) and specificity (52.7% vs 91.2%) for predicting MACE in ACS patient undergoing PCI. Recent study by Ha et al. has also shown that high NLR (> 3.4) to be associated with worse 1-year survival post-PCI in ACS patients [17]. Another study by Hong et al. in patients with acute myocardial infarction, showed post-PCI NLR ≥ 3.88 to be associated with risk of a large-sized infarction (≥ 20%) (OR 2.91, 95% CI 1.73–4.88, p < 0.001) and significantly higher MACE than in the low NLR group (15.8% vs. 7.4%, HR 2.60, 95% CI 1.21–5.60, p = 0.015) [18]. These findings shows that post-PCI indices were related to complexity and severity of CAD leading to need to revascularize a large area of the myocardium. Consequently, these patients were at increased risk of cardiovascular events in the future.

Monocyte acts a precursor of foam cells which oxidize LDL-C and destabilize the fibrous cap and plays an important role in thrombus propagation in coagulation cascade [19, 20]. MLR have shown to predict stent thrombosis in ACS patients [21]. In our study, no significant correlation was observed between MLR and number and length of stent. Monocytes are markers of chronic inflammation associated with atherosclerosis. Although these cardiac monocytes increase rapidly after myocardial inflammation, they reach peak by 7 days and may take up to 2 weeks to decrease to baseline. Since the indices in our study were calculated within 48 h after PCI rather than a greater follow up period, this could be one of the factors why the changes in MLR could not have been interpreted with greater accuracy.

PLR has been shown to indicate inflammation and the activity of thrombotic processes similar to NLR [22]. High PLR has been correlated with poor hospital outcomes and 30-day MACE in acute myocardial infarction [23]. Similarly, our studied showed that higher post PCI PLR cut off of 172.86 compared to pre-PCI PLR cut off of 112.83 had greater sensitivity (96.4% vs 74.4%) and specificity (87.9% vs 45.3%) for predicting MACE in these ACS patients.

SII is a relatively new index used to predict prognosis in CAD patients and correlates with severity of disease based on SYNTAX score [24, 25]. Since it includes both neutrophil and lymphocyte components it has shown to be a better predictor of cardiovascular outcomes in ACS patients. Our study also concluded the same with AUC and cut off value of post PCI SII in predicting MACE had highest sensitivity and specificity.

Another interesting observation from our study was significant corelation was observed between post PCI NLR, MLR, PLR and SII with SYNTAX II score but not SYNTAX score. This may be because SYNTAX score takes into account only anatomical consideration whereas SYNTAX II score incorporates clinical variable also and hence a better predictor of long-term outcomes in patients undergoing myocardial revascularization [26, 27].

Cox-Multivariate analysis showed that STEMI at presentation, strong family history of CAD, SYNTAX II score and post PCI inflammatory indices (NLR, MLR, PLR and SII) were independent predictors of MACE in ACS patients. Thus, it can be concluded that though PCI is the gold standard treatment for ACS, PCI itself can induce inflammation and such patients are at increased risk of cardiovascular events. Possible mechanism in these includes direct endothelial damage, reperfusion injury, plaque debris causing inflammation and occlusion of small subendocardial blood vessel not visualized by angiography [28].

When survival analysis was done based on Kaplan Meier estimate, our study concluded that patient with elevated inflammatory indices had poor survival outcomes compared to those whose values were below the optimal diagnostic cut off. These findings were similar to study done by Gao et al. where higher values of the inflammatory indices predicted poor survival and increased all-cause mortality [29].

Limitations

The study has several limitations. It was a single center follow up study with a small sample size. Larger scale multicentric studies are required to derive stronger conclusion. Secondly, the duration of follow up in our study was limited to 12-months. Long term follow up period may provide better insights of predictive value of these lymphocyte based indices to determine MACE in ACS patients. Also, drug compliance in follow up was determined only on patient and attendant statement in absence of any standard operating protocol. Additionally other factors like uncontrolled diabetes, anemia, pre-existing structural defects, newly diagnosed inflammatory conditions like rheumatoid arthritis which could have influenced MACE during follow up were not taken into consideration during final analysis.

Conclusion

Post-PCI hematological indices showed stronger correlation with MACE in ACS patients undergoing PCI compared to pre-PCI indices possibly due to residual ongoing inflammation. Among these lymphocytes based inflammatory indices post-PCI SII had the best predictive value for MACE. Post-PCI indices also showed strong correlation with severity of disease based on SYNTAX II score, number and length of stent required for myocardial revascularization.

Supplementary Information

Below is the link to the electronic supplementary material.

Authors Contribution

All authors contributed to the study conception and design. Material preparation, data collection and analysis were performed by VM, AK. Formal analysis and investigations were done by RC, DY. The first draft of the manuscript was written by SD, AK and editing was done by KS. All authors read and approved the final manuscript.

Funding

Nil.

Declarations

Conflict of interest

The authors declare that they have no conflict of interest.