Individual lifetime benefit from low-dose colchicine in patients with chronic coronary artery disease

A Prediction Model Based on Systemic Immune-Inflammatory Index Combined with Other Predictors for Major Adverse Cardiovascular Events in Acute Myocardial Infarction Patients

Objective

To evaluate the prognostic value of the systemic immune-inflammatory index (SII) for predicting in-hospital major adverse cardiovascular events (MACEs) in patients with acute myocardial infarction (AMI) and establish a relevant nomogram.

Methods

This study included 954 AMI patients. We examined three inflammatory factors (SII, platelet to lymphocyte ratio (PLR) and neutrophil to lymphocyte ratio (NLR)) to see which one predicts in-hospital MACEs better. The predictors were subsequently screened using bidirectional stepwise regression method, and a MACE nomogram was constructed via logistic regression analysis. The predictive value of the model was evaluated using the area under the curve (AUC), sensitivity and specificity. In addition, the clinical utility of the nomogram was evaluated using decision curve analysis. We also compared the nomogram with the Global Registry of Acute Coronary Events (GRACE) scoring system.

Results

334 (35.0%) patients had MACEs. The SII (AUC =0.684) had a greater predictive value for in-hospital MACEs in AMI patients than the PLR (AUC =0.597, P<0.001) or NLR (AUC=0.654, P=0.01). The area under the curve (AUC) of the SII-based multivariable model for predicting MACEs, which was based on the SII, Killip classification, left ventricular ejection fraction, age, urea nitrogen (BUN) concentration and electrocardiogram-based diagnosis, was 0.862 (95% CI: 0.833-0.891). Decision curve and calibration curve analysis revealed that SII-based multivariable model demonstrated a good fit and calibration and provided positive net benefits than the model without SII. The predictive value of the SII-based multivariable model was greater than that of the GRACE scoring system (P<0.001).

Conclusion

SII is a promising, reliable biomarker for identifying AMI patients at high risk of in-hospital MACEs, and SII-based multivariable model may serve as a quick and easy tool to identify these patients.

Colchicine protects against the development of experimental abdominal aortic aneurysm

Abdominal aortic aneurysm (AAA) is characterized by at least 1.5-fold enlargement of the infrarenal aorta, a ruptured AAA is life-threatening. Colchicine is a medicine used to treat gout and familial Mediterranean fever, and recently, it was approved to reduce the risk of cardiovascular events in adult patients with established atherosclerotic disease. With an AAA mice model created by treatment with porcine pancreatic elastase (PPE) and β-aminopropionitrile (BAPN), this work was designed to explore whether colchicine could protect against the development of AAA. Here, we showed that colchicine could limit AAA formation, as evidenced by the decreased total aortic weight per body weight, AAA incidence, maximal abdominal aortic diameter and collagen deposition. We also found that colchicine could prevent the phenotypic switching of vascular smooth muscle cells from a contractile to synthetic state during AAA. In addition, it was demonstrated that colchicine was able to reduce vascular inflammation, oxidative stress, cell pyroptosis and immune cells infiltration to the aortic wall in the AAA mice model. Finally, it was proved that the protective action of colchicine against AAA formation was mainly mediated by preventing immune cells infiltration to the aortic wall. In summary, our findings demonstrated that colchicine could protect against the development of experimental AAA, providing a potential therapeutic strategy for AAA intervention in the clinic.