Correlation between leukocyte count and infarct size in ST segment elevation myocardial infarction

Elevated Leukocyte Count and Platelet-Derived Thrombogenicity Measured Using the Total Thrombus-Formation Analysis System in Patients with ST-Segment Elevation Myocardial Infarction

AIMS

High platelet-derived thrombogenicity during the acute phase of ST-segment elevation myocardial infarction (STEMI) is associated with poor outcomes; however, the associated factors remain unclear. This study aimed to examine whether acute inflammatory response after STEMI affects platelet-derived thrombogenicity.

METHODS

This retrospective observational single-center study included 150 patients with STEMI who were assessed for platelet-derived thrombogenicity during the acute phase. Platelet-derived thrombogenicity was assessed using the area under the flow-pressure curve for platelet chip (PL-AUC), which was measured using the total thrombus-formation analysis system (T-TAS). The peak leukocyte count was evaluated as an acute inflammatory response after STEMI. The patients were divided into two groups: the highest quartile of the peak leukocyte count and the other three quartiles combined.

RESULTS

Patients with a high peak leukocyte count (＞15,222/mm3; n=37) had a higher PL-AUC upon admission (420 [386-457] vs. 385 [292-428], p=0.0018), higher PL-AUC during primary percutaneous coronary intervention (PPCI) (155 [76-229] vs. 96 [29-170], p=0.0065), a higher peak creatine kinase level (4200±2486 vs. 2373±1997, p＜0.0001), and higher PL-AUC 2 weeks after STEMI (119 [61-197] vs. 88 [46-122], p=0.048) than those with a low peak leukocyte count (≤ 15,222/mm3; n=113). The peak leukocyte count after STEMI positively correlated with PL-AUC during primary PPCI (r=0.37, p＜0.0001). A multivariable regression analysis showed the peak leukocyte count to be an independent factor for PL-AUC during PPCI (β=0.26, p=0.0065).

CONCLUSIONS

An elevated leukocyte count is associated with high T-TAS-based platelet-derived thrombogenicity during the acute phase of STEMI.

Machine learning-based prediction of infarct size in patients with ST-segment elevation myocardial infarction: A multi-center study

BACKGROUND

Cardiac magnetic resonance imaging (CMR) is the gold standard for measuring infarct size (IS). However, this method is expensive and requires a specially trained technologist to administer. We therefore sought to quantify the IS using machine learning (ML) based analysis on clinical features, which is a convenient and cost-effective alternative to CMR.

METHODS AND RESULTS

We included 315 STEMI patients with CMR examined one week after morbidity in final analysis. After feature selection by XGBoost on fifty-six clinical features, we used five ML algorithms (random forest (RF), light gradient boosting decision machine, deep forest, deep neural network, and stacking) to predict IS with 26 (selected by XGBoost with information gain greater than average level of 56 features) and the top 10 features, during which 5-fold cross-validation were used to train and optimize models. We then evaluated the value of actual and ML-IS for the prediction of adverse remodeling. Our finding indicates that MLs outperform the linear regression in predicting IS. Specifically, the RF with five predictors identified by the exhaustive method performed better than linear regression (LR) with 10 indicators (R² of RF: 0.8; LR: 0). The finding also shows that both actual and ML-IS were independently associated with adverse remodeling. ML-IS ≥ 21% was associated with a twofold increase in the risk of LV remodeling (P < 0.01) compared with patients with reference IS (1st tertile).

CONCLUSION

ML-based methods can predict IS with widely available clinical features, which provide a proof-of-concept tool to quantitatively assess acute phase IS.

Leukocyte and its Subtypes as Predictors of Short-Term Outcome in Cardiogenic Shock Complicating Acute Myocardial Infarction: A Cohort Study

BACKGROUND

Patients with cardiogenic shock (CS) complicating acute myocardial infarction (AMI) are at high risk of death. Inflammation is involved in both CS and AMI, and our present study aimed to investigate the changes of leukocyte and its subtypes as well as their prognostic value in patients with CS complicating AMI.

METHODS

Data of 217 consecutive patients with CS complicating AMI were analyzed. The primary endpoint was 30-day all-cause mortality. The secondary endpoint was the composite events of major adverse cardiovascular events (MACE) including 30-day all-cause mortality, ventricular tachycardia/ventricular fibrillation, atrioventricular block, gastrointestinal hemorrhage and nonfatal stroke. The association of leukocyte and its subtypes with the endpoints was analyzed by Cox regression analysis.

RESULTS

Leukocyte and its subtypes including neutrophil, eosinophil, lymphocyte, monocyte and basophil were all statistically significant between survivors and nonsurvivors (all P < 0.05). Among the leukocyte subtypes, eosinophil had the highest predictive value for 30-day all-cause mortality (AUC = 0.799) and the composite of leukocyte and its subtypes improved the predictive power (AUC = 0.834). The 30-day mortality and MACE K-M curves of leukocyte and its subtypes reveal a distinct trend based on the cut-off value determined by Youden Index (all log rank P < 0.001). After multivariable adjustment, high leukocyte (>11.6 × 109/L) (HR 1.815; 95%CI 1.134, 2.903; P = 0.013), low eosinophil (<0.3%) (HR 2.562; 95%CI 1.412, 4.648; P = 0.002) and low basophil (≤0.1%) (HR 1.694; 95%CI 1.106, 2.592; P = 0.015) were independently associated with increased risk of 30-day mortality. Similarly, high leukocyte (>11.6 × 109/L) (HR 1.894; 95%CI 1.285, 2.791; P = 0.001), low eosinophil (<0.3%) (HR 1.729; 95%CI 1.119, 2.670; P = 0.014) and low basophil (≤0.1%) (HR 1.560; 95%CI 1.101, 2.210; P = 0.012) were independently associated with increased risk of 30-day MACE.

CONCLUSIONS

Leukocyte and its subtypes changed significantly in patients with CS complicating AMI. In addition to leukocyte, eosinophil and basophil also served as independent prognostic factors for 30-day outcomes. Moreover, as the composite of leukocyte and its subtypes increased the predictive power, thus leukocyte and its subtypes, especially eosinophil and basophil should be taken into consideration for the current risk stratification model.

Reperfusion Cardiac Injury: Receptors and the Signaling Mechanisms

It has been documented that Ca2+ overload and increased production of reactive oxygen species play a significant role in reperfusion injury (RI) of cardiomyocytes. Ischemia/reperfusion induces cell death as a result of necrosis, necroptosis, apoptosis, and possibly autophagy, pyroptosis and ferroptosis. It has also been demonstrated that the NLRP3 inflammasome is involved in RI of the heart. An increase in adrenergic system activity during the restoration of coronary perfusion negatively affected cardiac resistance to RI. Toll-like receptors are involved in RI of the heart. Angiotensin II and endothelin-1 aggravated ischemic/reperfusion injury of the heart. Activation of neutrophils, monocytes, CD4+ T-cells and platelets contributes to cardiac ischemia/reperfusion injury. Our review outlines the role of these factors in reperfusion cardiac injury.

Pharmacological inhibition of GLUT1 as a new immunotherapeutic approach after myocardial infarction

Myocardial infarction (MI) is one of the major contributors to cardiovascular morbidity and mortality. Excess inflammation significantly contributes to cardiac remodeling and heart failure after MI. Accumulating evidence has shown the central role of cellular metabolism in regulating the differentiation and function of cells. Metabolic rewiring is particularly relevant for proinflammatory responses induced by ischemia. Hypoxia reduces mitochondrial oxidative phosphorylation (OXPHOS) and induces increased reliance on glycolysis. Moreover, activation of a proinflammatory transcriptional program is associated with preferential glucose metabolism in leukocytes. An improved understanding of the mechanisms that regulate metabolic adaptations holds the potential to identify new metabolic targets and strategies to reduce ischemic cardiac damage, attenuate excess local inflammation and ultimately prevent the development of heart failure. Among possible drug targets, glucose transporter 1 (GLUT1) gained considerable interest considering its pivotal role in regulating glucose availability in activated leukocytes and the availability of small molecules that selectively inhibit it. Therefore, we summarize current evidence on the role of GLUT1 in leukocytes (focusing on macrophages and T cells) and non-leukocytes, including cardiomyocytes, endothelial cells and fibroblasts regarding ischemic heart disease. Beyond myocardial infarction, we can foresee the role of GLUT1 blockers as a possible pharmacological approach to limit pathogenic inflammation in other conditions driven by excess sterile inflammation.

The Role of Natriuretic Peptides in the Regulation of Cardiac Tolerance to Ischemia/Reperfusion and Postinfarction Heart Remodeling

In the past 10 years, mortality from acute myocardial infarction has not decreased despite the widespread introduction of percutaneous coronary intervention. The reason for this situation is the absence in clinical practice of drugs capable of preventing reperfusion injury of the heart with high efficiency. In this regard, noteworthy natriuretic peptides (NPs) which have the infarct-limiting effect, prevent reperfusion cardiac injury, prevent adverse post-infarction remodeling of the heart. Atrial natriuretic peptide does not have the infarct-reducing effect in rats with alloxan-induced diabetes mellitus. NPs have the anti-apoptotic and anti-inflammatory effects. There is indirect evidence that NPs inhibit pyroptosis and autophagy. Published data indicate that NPs inhibit reactive oxygen species production in cardiomyocytes, aorta, heart, kidney and the endothelial cells. NPs can suppress aldosterone, angiotensin II, endothelin-1 synthesize and secretion. NPs inhibit the effects aldosterone, angiotensin II on the post-receptor level through intracellular signaling events. NPs activate guanylyl cyclase, protein kinase G and protein kinase A, and reduce phosphodiesterase 3 activity. NO-synthase and soluble guanylyl cyclase are involved in the cardioprotective effect of NPs. The cardioprotective effect of natriuretic peptides is mediated via activation of kinases (AMPK, PKC, PI3 K, ERK1/2, p70s6 k, Akt) and inhibition of glycogen synthase kinase 3β. The cardioprotective effect of NPs is mediated via sarcolemmal K_ATP channel and mitochondrial K_ATP channel opening. The cardioprotective effect of brain natriuretic peptide is mediated via MPT pore closing. The anti-fibrotic effect of NPs may be mediated through inhibition TGF-β1 expression. Natriuretic peptides can inhibit NF-κB activity and activate GATA. Hemeoxygenase-1 and peroxisome proliferator-activated receptor γ may be involved in the infarct-reducing effect of NPs. NPs exhibit the infarct-limiting effect in patients with acute myocardial infarction. NPs prevent post-infarction remodeling of the heart. To finally resolve the question of the feasibility of using NPs in AMI, a multicenter, randomized, blind, placebo-controlled study is needed to assess the effect of NPs on the mortality of patients after AMI.

Altered hematological, biochemical and immunological parameters as predictive biomarkers of severity in experimental myocardial infarction

Preclinical studies in cardiovascular medicine are necessary to translate basic research to the clinic. The porcine model has been widely used to understand the biological mechanisms involved in cardiovascular disorders for which purpose different closed-chest models have been developed in the last years to mimic the pathophysiological events seen in human myocardial infarction. In this work, we studied hematological, biochemical and immunological parameters, as well as Magnetic resonance derived cardiac function measurements obtained from a swine myocardial infarction model. We identified some blood parameters which were significantly altered after myocardial infarction induction. More importantly, these parameters (gamma-glutamyl transferase, glutamic pyruvic transaminase, red blood cell counts, hemoglobin concentration, hematocrit, platelet count and plateletcrit) correlated positively with cardiac function, infarct size and/or cardiac enzymes (troponin I and creatine kinase-MB). Thus several blood-derived parameters have allowed us to predict the severity of myocardial infarction in a clinically relevant animal model. Therefore, here we provide a simple, affordable and reliable way that could prove useful in the follow up of myocardial infarction and in the evaluation of new therapeutic strategies in this animal model.