Risk factors for coronary artery disease in young patients with stable angina pectoris

The Role of «Novel» Biomarkers of Systemic Inflammation in the Development of Early Hospital Events after Aortic Valve Replacement in Patients with Aortic Stenosis

INTRODUCTION

The pathogenesis of aortic stenosis includes the processes of chronic inflammation, calcification, lipid metabolism disorders, and congenital structural changes. The goal of our study was to determine the predictive value of novel biomarkers of systemic inflammation and some hematological indices based on the numbers of leukocytes and their subtypes in the development of early hospital medical conditions after mechanical aortic valve replacement in patients with aortic stenosis.

MATERIALS AND METHODS

This was a cohort study involving 363 patients who underwent surgical intervention for aortic valve pathology between 2014 and 2020. The following markers of systemic inflammation and hematological indices were studied: SIRI (Systemic Inflammation Response Index), SII (Systemic Inflammation Index), AISI (Aggregate Index of Systemic Inflammation), NLR (Neutrophil/Lymphocyte Ratio), PLR (Platelet/Lymphocyte Ratio), and MLR (Monocyte/Lymphocyte Ratio). Associations of the levels of these biomarkers and indices with the development of in-hospital death, acute kidney injury, postoperative atrial fibrillation, stroke/acute cerebrovascular accident, and bleeding were calculated.

RESULTS

According to an ROC analysis, an SIRI > 1.5 (p < 0.001), an SII > 718 (p = 0.002), an AISI > 593 (p < 0.001), an NLR > 2.48 (p < 0.001), a PLR > 132 (p = 0.004), and an MLR > 0.332 (p < 0.001) were statistically significantly associated with in-hospital death. Additionally, an SIRI > 1.5 (p < 0.001), an NLR > 2.8 (p < 0.001), and an MLR > 0.392 (p < 0.001) were associated with bleeding in the postoperative period. In a univariate logistic regression, SIRI, SII, AISI, and NLR were statistically significant independent factors associated with in-hospital death. In a multivariate logistic regression model, SIRI was the most powerful marker of systemic inflammation.

CONCLUSION

SIRI, SII, AISI, and NLR as novel biomarkers of systemic inflammation were associated with in-hospital mortality. Of all markers and indices of systemic inflammation in our study, SIRI was the strongest predictor of a poor outcome in the multivariate regression model.

Disease burden and risk factors of ischemic heart disease in China during 1990-2019 based on the Global Burden of Disease 2019 report: A systematic analysis

Objective

The aim of this study was to identify the disease burden and risk factors of ischemic heart disease (IHD) in China, during 1990-2019, through a systematic analysis using the Global Burden of Disease (GBD) 2019 report in order to provide first-hand information for primary and secondary prevention of IHD in China.

Methods

Data on the rates of incidence, death, years of life lost (YLLs), years lived with disability (YLDs), and disability-adjusted life years (DALYs) of IHD were obtained from GBD2019 to determine the disease burden and risk factors of IHD in China.

Results

The rates of incidence, death, YLLs, YLDs, and DALYs of IHD in China increased at different levels during 1990-2019. The annual rate of change in incidence, death, YLLs, YLDs, and DALYs of IHD were 1.31%, 1.57%, 0.93%, 1.14%, and 0.94%, respectively. In 2019, the YLDs of IHD in Chinese women were higher, while the rates of incidence and death, YLLs, and DALYs were lower in Chinese women than in Chinese men. The disease burden of IHD had significant age differences, and people aged ≥70 years had the highest disease burden. A total of 24 risk factors were associated with the rates of death and DALYs of IHD, and the five most significant risk factors were high systolic blood pressure, high LDL cholesterol (LDL-C), smoking, ambient particulate matter pollution, and intake of a high-sodium diet. From 1990 to 2019, a high annual rate of change in IHD-related deaths and DALYs was observed due to ambient particulate matter pollution, high body mass index (BMI), and intake of a diet high in processed meat.

Conclusion

The results of the study revealed that the disease burden of IHD in China was on the rise, especially in people aged ≥70 years. The main disease burden of IHD in male patients was premature death and that in female patients was disability. Environmental, behavioral, and metabolic factors were considered the three main risks of the disease burden of IHD, with metabolic factors having the greatest impact. Therefore, periodic health check-ups and high-risk factor interventions for key populations should be strengthened from the grassroots level, which are conducive to further reducing the disease burden of IHD in China.

Value of the systemic immune-inflammation index in predicting poor postoperative outcomes and the short-term prognosis of heart valve diseases: a retrospective cohort study

OBJECTIVE

Systemic immune-inflammation index (SII) is a novel biomarker that can predict poor outcomes in tumours, nervous system diseases and chronic heart failure. Here, we investigated the predictive value of SII on the poor postoperative outcomes and short-term prognosis of heart valve diseases (HVDs).

DESIGN, SETTING AND PARTICIPANTS

This retrospective cohort study enrolled all consecutive patients with HVDs (aortic stenosis, aortic regurgitation, mitral stenosis and mitral regurgitation) who underwent surgery (valve replacement or valve repair) at the Affiliated Hospital of North Sichuan Medical College between 2017 and 2020.

MAIN OUTCOMES AND MEASURES

Major complications in the perioperative period, all-cause mortality within 30 days and readmission within 30 days.

RESULTS

A total of 431 patients with HVDs were enrolled in this study, including 202 males and 229 females, aged 58.9±27.3 years. SII levels of patients in the poor outcomes group were significantly higher than those of patients in the favourable outcomes group (658.40±436.29 vs 335.72±174.76, respectively; p<0.001). Multivariate logistic regression analysis showed that age (OR 1.064, 95% CI 1.026 to 1.104, p=0.025), SII (OR 1.034, 95% CI 1.012 to 1.631, p=0.008) and aortic cross-clamping time (OR 1.013, 95% CI 1.004 to 1.023, p=0.006) were independent risk factors for poor outcomes and short-term prognosis in patients with HVD. The area under the curve of poor outcomes predicted by SII in patients with HVD was 0.806 (95% CI 0.763 to 0.848) and the optimised cut-off value 423.8×10⁹ /L, with a sensitivity of 70.3% and specificity of 81.1%. The incidence of poor outcomes (p<0.001), 30-day mortality (p<0.001) and 30-day readmission rate (p=0.026) in the high SII group was significantly higher than that in the low SII group.

CONCLUSIONS

SII is closely related to poor postoperative outcomes and short-term prognosis of HVD and can serve as an independent predictive factor.

Glycosylated hemoglobin A1c predicts coronary artery disease in non-diabetic patients

Background

In primary care, there is a need for simple and cost‐effective tool that will allow the determination of the risk of coronary artery disease (CAD). We aimed to research the value of glycosylated hemoglobin (HbA1c) in the prediction of coronary artery disease.

Methods

Patients admitted to the outpatient clinic of the Cardiology for angiography were retrospectively screened. Patients with diabetes or with HbA1c of 6.5 or above were excluded. Comparative HbA1c data were obtained according to the stenosis groups. Logistic regression analysis was used to investigate the risk factors affecting stenosis positivity.

Results

Of the study group, 120 patients were without any stenosis in any coronary artery, 56 patients were with >50% stenosis in one coronary artery, and 71 patients were with >50% stenosis in more than one coronary artery. There was a statistically significant difference between HbA1c measurements according to the degree of stenosis (P = .001 and P < .01, respectively). The odd ratio for HbA1c was 6.260 (95% CI: 3,160‐12,401). According to the stenosis positivity, the cutoff point for HbA1c was found to be 5.6 and above. In the regression analysis, HbA1c was an independent risk factor for CAD. One unit increase in HbA1c level increases the risk of stenosis up to 12.4‐fold (95% CI: 5,990‐25,767).

Conclusion

The study showed HbA1c can be used as an independent marker in determining the probability and severity of coronary artery disease in non‐diabetic individuals and as a useful marker in primary care predicting CAD.