Development of a Novel Inflammatory Index to Predict Coronary Artery Disease Severity in Patients With Acute Coronary Syndrome

Prognosis impact of multiple novel lymphocyte-based inflammatory indices in patients with initially diagnosed coronary artery disease

BACKGROUND

This study aimed to evaluate six novel lymphocyte-based inflammatory markers (neutrophil-lymphocyte ratio, monocyte-lymphocyte ratio, platelet-lymphocyte ratio [PLR], systemic immune inflammation index [SII], systemic inflammatory response index, and systemic immune inflammation response index [SIIRI]) in patients with newly diagnosed coronary artery disease [CAD].

METHODS

A total of 959 patients newly diagnosed with CAD and underwent diagnostic coronary angiography were enrolled in this study and followed for major adverse cardiovascular events (MACEs), including cardiovascular death, nonfatal myocardial infarction, and nonfatal stroke. The best cutoff value was used to compare the six indicators. Cox risk regression analysis evaluated the relationship between novel lymphocyte-based inflammatory markers and MACEs in newly diagnosed CAD patients.

RESULTS

During a mean follow-up period of 33.3 ± 9.9 months, 229 (23.9%) MACEs were identified. Multivariate Cox regression analysis showed that only SIIRI (hazard ratio [HR]: 5.853; 95% confidence interval [CI]: 4.092-8.371; p < .001) and PLR (HR: 1.725; 95% CI: 1.214-2.452; p = .002) were independent predictors of MACEs. Nevertheless, following the adjustment for covariates, only the SIIRI was found to be a significant predictor MACEs and its corresponding specific endpoint occurrences. The predictive ability of the model was improved when six different inflammatory markers were added to the basic model established by traditional risk factors, namely, the C-index increased, and the SIIRI increased most significantly (AUC: 0.778; 95% CI: 0.743-0.812; p < .001). However, among the six novel inflammatory markers, only SIIRI had improved net reclassification improvement (NRI) and integrated discrimination improvement (IDI) (NRI: 0.187; 95% CI: 0.115-0.259, p < .001. IDI: 0.135; 95% CI: 0.111-0.159, p < .001), which was superior to the basic model established by traditional risk factors.

CONCLUSIONS

SIIRI is independent predictor of MACEs in newly diagnosed CAD patients. SIIRI was superior to other measures in predicting MACEs. The combination of SIIRI and traditional risk factors can more accurately predict MACEs.

Screening significance of systemic immune-inflammation index (SII) and systemic inflammation response index (SIRI) in coronary heart disease of symptomatic youth

BACKGROUND

The incidence of coronary heart disease (CHD) in youth is rapidly increasing but difficultly recognized in the early stage.

METHODS AND RESULTS

In this retrospective study, 194 CHD patients under the age of 45 who previously experienced chest pain symptoms and 170 non-CHD patients were included and demographic data were collected. Systemic inflammation index (SII) and systemic inflammation response index (SIRI) were increased in young CHD patients (p < 001). Spearman's correlation analysis showed that both SII and SIRI were negatively correlated with HDL and positively correlated with hypertension, Gensini score, and hsTnI. Logistic regression analysis indicated that SII and SIRI were independently associated with the presence of CHD in youth with chest pain symptoms. The area under the ROC curve (AUC) of the SII model for young CHD patients was 0.805 (0.728-0.869), and the sensitivity and specificity were 0.65 and 0.823, respectively. Meanwhile, the AUC for the SIRI model was 0.812 (0.739-0.872), and the sensitivity and specificity were 0.673 and 0.8022. The calibration curves of both SII and SIRI models are in good agreement with the actual curves. And the decision curves of both models indicated their clinical practicality.

CONCLUSION

SII and SIRI are independent risk factors for CHD in young adults, which can quickly and effectively identify CHD patients among young adults who have previously experienced chest pain symptoms.

New Modifiable Risk Factors Influencing Coronary Artery Disease Severity

Cardiovascular diseases (CVDs) remain the leading cause of death worldwide with coronary artery disease (CAD) being the first culprit in this group. In terms of CAD, not only its presence but also its severity plays a role in the patient's treatment and prognosis. CAD complexity can be assessed with the indicator named the SYNTAX score (SS). A higher SS is associated with major adverse cardiovascular event (MACE) occurrence in short- and long-term observations. Hence, the risk factors affecting CAD severity based on SS results may help lower the risk among patients with already developed CAD to reduce their impact on coronary atherosclerosis progression. The well-established risk factors of CAD are consistent with those associated with the coronary plaque burden. However, recently, it was shown that new indicators exist, which we present in this paper, that significantly contribute to CAD complexity such as inflammatory parameters, C-reactive protein (CRP), ratios based on blood smear results, and uric acid. Moreover, microbiota alteration, vitamin D deficiency, and obstructive sleep apnea (OSA) also predicted CAD severity. However, sometimes, certain indicators were revealed as significant only in terms of chronic coronary syndromes (CCSs) or specific acute coronary syndromes (ACSs). Importantly, there is a need to apply the interdisciplinary and translational approach to the novel CAD severity risk assessment to maximize the impact of secondary prevention among patients at risk of coronary atherosclerosis progression.

Prediction of Osteoporotic Hip Fracture Outcome: Comparative Accuracy of 27 Immune-Inflammatory-Metabolic Markers and Related Conceptual Issues

Objectives: This study, based on the concept of immuno-inflammatory-metabolic (IIM) dysregulation, investigated and compared the prognostic impact of 27 indices at admission for prediction of postoperative myocardial injury (PMI) and/or hospital death in hip fracture (HF) patients. Methods: In consecutive HF patient (n = 1273, mean age 82.9 ± 8.7 years, 73.5% females) demographics, medical history, laboratory parameters, and outcomes were recorded prospectively. Multiple logistic regression and receiver-operating characteristic analyses (the area under the curve, AUC) were used to establish the predictive role for each biomarker. Results: Among 27 IIM biomarkers, 10 indices were significantly associated with development of PMI and 16 were indicative of a fatal outcome; in the subset of patients aged >80 years with ischaemic heart disease (IHD, the highest risk group: 90.2% of all deaths), the corresponding figures were 26 and 20. In the latter group, the five strongest preoperative predictors for PMI were anaemia (AUC 0.7879), monocyte/eosinophil ratio > 13.0 (AUC 0.7814), neutrophil/lymphocyte ratio > 7.5 (AUC 0.7784), eosinophil count < 1.1 × 109/L (AUC 0.7780), and neutrophil/albumin × 10 > 2.4 (AUC 0.7732); additionally, sensitivity was 83.1-75.4% and specificity was 82.1-75.0%. The highest predictors of in-hospital death were platelet/lymphocyte ratio > 280.0 (AUC 0.8390), lymphocyte/monocyte ratio < 1.1 (AUC 0.8375), albumin < 33 g/L (AUC 0.7889), red cell distribution width > 14.5% (AUC 0.7739), and anaemia (AUC 0.7604), sensitivity 88.2% and above, and specificity 85.1-79.3%. Internal validation confirmed the predictive value of the models. Conclusions: Comparison of 27 IIM indices in HF patients identified several simple, widely available, and inexpensive parameters highly predictive for PMI and/or in-hospital death. The applicability of IIM biomarkers to diagnose and predict risks for chronic diseases, including OP/OF, in the preclinical stages is discussed.

Lymphocyte-to-Red Blood Cell Ratio-The Guide Star of Acute Coronary Syndrome Prognosis

BACKGROUND

Beneath the surface of the acute ST-elevation myocardial infarction (STEMI) iceberg lies a hidden peril, obscured by the well-known cardiovascular risk factors that tip the iceberg. Before delving into the potential time bomb these risk factors represent, it is crucial to recognize the obscured danger lurking under the surface. What secrets does the STEMI iceberg hold? To unveil these mysteries, a closer look at the pathophysiology of STEMI is imperative. Inflammation, the catalyst of the STEMI cascade, sets off a chain reaction within the cardiovascular system. Surprisingly, the intricate interplay between red blood cells (RBC) and lymphocytes remains largely unexplored in previous research.

MATERIALS AND METHODS

The study encompassed 163 patients diagnosed with STEMI. Utilizing linear and logistic regression, the lymphocyte-to-red blood cell ratio (LRR) was scrutinized as a potential predictive biomarker.

RESULTS

There was a statistically significant correlation between LRR and the prognosis of STEMI patients. Building upon this discovery, an innovative scoring system was proposed that integrates LRR as a crucial parameter.

CONCLUSIONS

Uncovering novel predictive markers for both immediate and delayed complications in STEMI is paramount. These markers have the potential to revolutionize treatment strategies by tailoring them to individual risk profiles, ultimately enhancing patient outcomes.

Correlations Between Acute Coronary Syndrome and Novel Inflammatory Markers (Systemic Immune-Inflammation Index, Systemic Inflammation Response Index, and Aggregate Index of Systemic Inflammation) in Patients with and without Diabetes or Prediabetes

Purpose

Type 2 diabetes mellitus (DM) is a recognized independent risk factor for both chronic coronary syndrome (CCS) and its complication, acute coronary syndrome (ACS). Patients with DM and prediabetes (preDM) face an increased ACS risk. Inflammation plays a significant role in the pathogenesis of both CCS and ACS. This study delves into novel inflammatory markers, such as the systemic immune-inflammation index (SII), systemic inflammation response index (SIRI), and aggregate index of systemic inflammation (AISI, also known as SIIRI or PIV), to explore their relationship with ACS and CCS in patients that have been or have not been diagnosed with DM or preDM.

Patients and Methods

This study included data of 493 patients with chest pain undergoing coronary angiography. They were categorized into four groups: 1) without DM/preDM and with CCS; 2) with both DM/preDM and CCS; 3) without DM/preDM and with ACS, 4) with both DM/preDM and ACS. Standard methods of statistical analysis were used to reveal possible differences between groups and to find the most influential ACS risk factors in groups with DM/preDM and without DM/preDM.

Results

The analysis showed no significant differences in SII, SIRI, or AISI between the respective patient groups. A logistic regression analysis generated a model incorporating SII, high-density lipoprotein, and low-density lipoprotein levels as the influential ACS risk factors for patients with DM/preDM. The model demonstrated 71.0% accuracy, 37.0% sensitivity, and 89.4% specificity.

Conclusion

The findings suggest that the aforementioned inflammatory markers may have potential for distinguishing DM/preDM patients at higher risk of ACS at a low financial cost. However, further comprehensive and well-designed research is required to validate their clinical utility.

Systemic Immune-Inflammation Index and Systemic Inflammatory Response Index as Predictors of Mortality in ST-Elevation Myocardial Infarction

(1) Background: The systemic inflammatory response index (SIRI; neutrophil count × monocyte/lymphocyte count), and the systemic immune-inflammation index (SII; platelet count × neutrophil count/lymphocyte count) are recently proposed biomarkers to assess the immune and inflammatory status. However, data on SIRI and SII are still relatively lacking and do not definitively and exhaustively define their role as predictors of an adverse prognosis in acute myocardial infarction (AMI). The aim of the present study was to evaluate SII and SIRI determinants as well as to assess SIRI and SII prognostic power in ST-elevation myocardial infarction (STEMI). (2) Methods: A total of 105 STEMI patients (74 males, 70 ± 11 years) were studied (median follow-up 54 ± 25 months, 24 deaths). (3) Results: The main determinants of SIRI and SII were creatinine and brain natriuretic peptide (BNP) (multivariate regression). Patients with higher SIRI (>75th percentile, 4.9) and SII (>75th percentile, 1257.5) had lower survival rates than those in the low SIRI/SII group (Kaplan-Meier analysis). Univariate Cox regression revealed that high SIRI and SII were associated with mortality (HR: 2.6, 95% CI: 1.1-5.8, p < 0.05; 2.2, 1-4.9, p ≤ 0.05, respectively); however, these associations lost their significance after multivariate adjustment. (4) Conclusions: SIRI and SII association with mortality was significantly affected by confounding factors in our population, especially creatinine and BNP, which are associated with both the inflammatory indices and the outcome.

Prognostic value of systemic immune-inflammation index in CAD patients: Systematic review and meta-analyses

BACKGROUND

Systemic immune-inflammation index (SII) is a novel inflammatory marker based on neutrophils, platelets and lymphocytes counts, which has potential prognostic value among coronary artery disease (CAD) patients as described by some observational studies. We aimed to provide higher-certainty evidence to verify the association of SII with poor outcomes of CAD patients.

METHODS

PubMed, Web of Science, Embase, Ovid and Scopus were searched to find relevant literature exploring the prognostic value of SII among CAD patients. Hazard ratios (HRs) with 95% confidence intervals (CIs) extracted from the literature included were pooled with the fixed-effect or random-effect model. Sensitivity analyses and subgroup analyses were conducted to detect the source of heterogeneity and evaluate the stability of results.

RESULTS

A total of nine studies with 15,832 participants were included. The quantitative synthesis including eight studies with 15,657 participants showed that the high SII was related to the major adverse cardiovascular event in CAD patients (HR with 95% CI: 2.36 [1.67, 3.33]). After eliminating heterogeneity and adjusting for publication bias, the above result was still robust (HR with 95% CI: 1.67 [1.32, 2.12]). Additionally, we also demonstrated the prognostic values of SII for all-cause death, cardiovascular death, myocardial infarction and stroke.

CONCLUSION

Higher SII has prognostic values for adverse outcomes in CAD patients.

The associations of two novel inflammation indexes, systemic immune-inflammation index (SII) and system inflammation response index (SIRI), with periodontitis: evidence from NHANES 2009-2014

OBJECTIVES

The research's goal is to look for any potential relationships between the systemic immune-inflammation index (SII) and the system inflammation response index (SIRI), along with inflammation indicators and the likelihood of periodontitis.

METHODS

Ten thousand two hundred eighty-two individuals in sum were determined to be eligible for this cross-sectional study from the National Health and Nutrition Examination Survey (NHANES) between 2009 and 2014. Multiple logistic regression, generalized additive model, smooth curve fitting, subgroup analysis, and interaction tests were done for analyzing the association between periodontitis and SII, SIRI, and other inflammatory indicators.

RESULTS

The analysis, adjusted for population weighting, revealed that individuals with moderate/severe periodontitis had SII levels of 545.46 (95% CI (529.10, 561.82), P = 0.0044) and SIRI levels of 1.33 (95% CI (1.29, 1.37), P < 0.0001). In a fully adjusted multivariate logistic regression model, SII was not sensibly associated with moderate/severe periodontitis among the continuous and quartile Q1-Q4 groups (OR = 0.97, 95% CI (0.91, 1.02)). The continuous variable of SIRI (OR = 1.11, 95% CI (1.06, 1.17)) and the quartile Q4 group (OR = 1.58, 95% CI (1.28, 1.94)) had a deemed significant positive association with moderate to severe periodontitis. In addition, other inflammatory indicators, especially NLR, PPN, PLR, MLR, PC, NC, and MC were observed to be notably involved moderate/severe periodontist in this research.

CONCLUSION

We explored the association between periodontitis and two novel comprehensive markers of inflammation (SII and SIRI).

CLINICAL RELEVANCE

These inflammatory markers are expected to serve as tools to assist clinicians in diagnosing periodontitis.

The Systemic Inflammation Index Predicts Poor Clinical Prognosis in Patients with Initially Diagnosed Acute Coronary Syndrome Undergoing Primary Coronary Angiography

Background

Systemic inflammation index (SII: neutrophil count * platelet count/lymphocyte count) is a new inflammatory marker that can reflect the degree of systemic inflammatory response after coronary artery disease (CAD). However, the predictive value of the SII for clinical prognosis in patients with initially diagnosed acute coronary syndrome (ACS) has yet to be thoroughly studied.

Patients and Methods

Patients with initially diagnosed ACS who underwent primary coronary angiography in our hospital from January 2019 to April 2021 were included in this study. 757 patients with ACS who underwent primary coronary angiography were enrolled. According to the baseline SII level, the patients were divided into a high SII group and a low SII group. The primary endpoint was major cardiovascular events (MACEs), defined as cardiac death, non-fatal myocardial infarction (MI), and non-fatal stroke.

Results

At a median follow-up of 33.9 months, 140 (18.5%) MACEs were recorded. Receiver operating characteristic (ROC) curve analysis showed that SII's best cut-off value for predicting MACEs was 713.9*109/L. Kaplan-Meier survival curve analysis showed that the survival rate of the low SII group was higher than the high SII group (P<0.001). Compared with the low SII group, the risk of MACEs was significantly increased in the high SII group (89 cases (33.3%) vs.51 patients (10.4%), P<0.001). Univariate and multivariate Cox regression analysis manifested that high SII level was independently associated with the occurrence of MACEs in patients with ACS undergoing primary coronary angiography (adjusted hazard ratio [HR]: 2.915, 95% confidence interval (CI%): 1.830-4.641, P<0.001). Adding SII to the conventional risk factor model improved the predictive value of MACEs.

Conclusion

This study showed that elevated SII was associated with adverse cardiovascular prognosis in patients with ACS undergoing primary coronary angiography, making SII a valuable predictor of poor prognosis in patients with ACS undergoing primary coronary angiography.