Small-Dense Low-Density Lipoprotein Cholesterol: A Subclinical Marker for the Primary Prevention of Coronary Heart Disease

Low-dose atorvastatin calcium combined with evolocumab: effect on regulatory proteins, lipid profiles, and cardiac function in coronary heart disease patients

OBJECTIVE

To assess the effects of combining low-dose atorvastatin calcium with evolocumab on complement regulatory protein levels, lipid profiles, and cardiac function in patients with coronary heart disease (CHD).

METHODS

A prospective randomized controlled study was conducted, with 180 CHD patients enrolled from Guang'anmen Hospital, China Academy of Chinese Medical Sciences, and the Second Hospital of Shanxi Medical University between February 2022 and April 2023. These patients were randomly assigned to either the control group (n = 90), receiving low-dose atorvastatin calcium, or the research group (n = 90), receiving a combination of low-dose atorvastatin calcium and evolocumab. The changes in cardiac function indices, levels of blood lipids and complement proteins, incidence of side effects, and cardiovascular events were compared between the two groups.

RESULTS

After treatment, both groups exhibited reductions in blood lipid levels. However, the research group demonstrated significantly lower levels of total cholesterol (TC), triglycerides (TG), and low-density lipoprotein cholesterol (LDL-C) compared to the control group (all P < 0.001). Additionally, improvements in cardiac function indices were observed in both groups, with the research group displaying greater enhancements in cardiac output (CO), stroke volume (SV), and left ventricular ejection fraction (LVEF). Furthermore, the levels of complement regulatory proteins, including CD45, CD46, CD55, and CD59, increased in both groups after treatment, with the research group exhibiting significantly higher levels (all P < 0.001). Notably, the research group also exhibited a lower incidence of cardiovascular events.

CONCLUSION

The combined use of low-dose atorvastatin calcium and evolocumab effectively modulates complement regulatory protein levels, optimizes blood lipid profiles, and enhances cardiac function in patients with CHD. This combination therapy represents a promising approach for management of CHD.

Effect of Body Mass Index on the Prognostic Value of Atherogenic Index of Plasma in Patients with Acute Coronary Syndrome Undergoing Percutaneous Coronary Intervention

(1) Background: The aim of this study was to investigate whether the prognostic value of the atherogenic index of plasma (AIP) for adverse cardiovascular events in acute coronary syndrome (ACS) patients undergoing percutaneous coronary intervention (PCI) varied across different BMI groups. (2) Methods: This study was a retrospective analysis of a prospective registry involving 1725 ACS patients undergoing PCI. The primary endpoint was a composite of all-cause death, non-fatal ischemic stroke, non-fatal spontaneous myocardial infarction (MI), and unplanned repeat revascularization. (3) Results: The study population finally consisted of 526 patients with BMI < 24 kg/m2 (age 62 ± 10 years; male 64.3%), 827 patients with 24 kg/m2 ≤ BMI < 28 kg/m2 (age 60 ± 10 years; male 81.8%), and 372 patients with BMI ≥ 28 kg/m2 (age 57 ± 11 years; male 81.2%). The AIP as a continuous variable increased the risk for the primary endpoint in ACS patients undergoing PCI with BMI < 24 kg/m2 (HR 2.506; 95% CI 1.285-4.885; p = 0.007), while it did not increase the risk in patients with BMI ≥ 24 kg/m2 (hazard ratio [HR]: 1.747; 95% CI 0.921-3.316; p = 0.088 for patients with 24 kg/m2 ≤ BMI < 28 kg/m2; and HR: 2.096; 95% CI 0.835-5.261; p = 0.115 for patients with BMI ≥ 28 kg/m2, respectively). Compared with the lowest AIP tertile, the top AIP tertile was associated with a significantly increased risk of the primary endpoint in BMI < 24 kg/m2 group (HR: 1.772, 95% CI: 1.110 to 2.828, p = 0.016). (4) Conclusions: The AIP was significantly associated with an increased risk of adverse cardiovascular events in ACS patients undergoing PCI with BMI < 24 kg/m2, but not in the patients with BMI ≥ 24 kg/m2.

The association between atherogenic index of plasma and all-cause mortality and cardiovascular disease-specific mortality in hypertension patients: a retrospective cohort study of NHANES

BACKGROUND

Atherogenic index of plasma (AIP), a marker of atherosclerosis and cardiovascular disease (CVD), was related to the all-cause mortality and CVD-specific mortality in a U-shape in general population respectively. However, no studies have investigated these associations in hypertensive populations. Herein, this study aims to explore the relationship of AIP and all-cause mortality and CVD-specific mortality in patients with hypertension in order to provide some reference for the risk hierarchical management of hypertension.

METHODS

Demographic and clinical data of 17,382 adult patients with hypertension were extracted from the National Health and Nutrition Examination Survey (NHANES) database in 2005-2018 in this retrospective cohort study. We used weighted univariate COX regression analysis to screen the covariates, and that weighted univariate and multivariate COX regression analyses to explore the association between AIP and all-cause mortality and CVD-specific mortality with hazard ratios (HRs) and 95% confidence intervals (CIs). Subgroup analyses of age, gender, body mass index (BMI), CVD, diabetes mellitus (DM), antihyperlipidemic agents use, and hypotensive drugs use were also performed for further exploration of these relationships.

RESULTS

The average follow-up time was 97.10 months. A total of 2,844 patients died, and 971 of them died due to CVD. After adjusting for age, race, education level, marital status, poverty-income ratio (PIR), smoking, BMI, physical activity, antihyperlipidemic agents, DM, CVD, hypotensive drugs, estimated glomerular filtration rate (eGFR), and total energy intake, we found that both low [HR = 1.18, 95%CI: (1.07-1.32)] and high [HR = 1.17, 95%CI: (1.03-1.33)] levels of AIP were linked to an increased risk of all-cause mortality, and the U-shape association between AIP and CVD-specific mortality was also found [low AIP level: HR = 1.26, 95%CI: (1.05-1.51); high AIP level: HR = 1.26, 95%CI: (1.06-1.49)]. Furthermore, these relationships were existed in patients whose BMI > 25, were non-Hispanic White, with non-CVD, non-DM, non-antihyperlipidemic agents, and used hypertension drug (all P < 0.05).

CONCLUSION

AIP was associated with both all-cause mortality and CVD-specific mortality in patients with hypertension, but the specific role of AIP in prognosis in hypertensive populations is needed further exploration.

Predictive importance of the visceral adiposity index and atherogenic index of plasma of all-cause and cardiovascular disease mortality in middle-aged and elderly Lithuanian population

Background

Two indices: visceral adiposity index (VAI) and atherogenic index of plasma (AIP) during several recent years were implemented into epidemiological studies for predicting of cardiovascular diseases (CVD) and mortality risk. Our study aimed to evaluate the association of VAI and AIP with the risk of all-cause and CVD mortality among the Lithuanian urban population aged 45–72 years.

Methods

In the baseline survey (2006–2008), 7,115 men and women 45–72 years of age were examined within the framework of the international study Health, Alcohol and Psychosocial Factors in Eastern Europe (HAPIEE). Six thousand six hundred and seventy-one participants (3,663 women and 3,008 men) were available for statistical analysis (after excluding 429 respondents with the missed information on study variables) and for them, VAI and AIP were calculated. The questionnaire evaluated lifestyle behaviors, including smoking and physical activity. All participants in the baseline survey were followed up for all-cause and CVD mortality events until December 31st, 2020. Multivariable Cox regression models were applied for statistical data analysis.

Results

After accounting for several potential confounders, higher levels of VAI (compared 5th quintile to 1st quintile) were associated with significantly higher CVD mortality in men [Hazards ratio (HR) = 1.38] and all-cause mortality in women (HR = 1.54) after 10-year follow-up. CVD mortality significantly increased in men with 0 the highest AIP quintile compared with that for the lowest quintile (HR = 1.40). In women, all-cause mortality was significantly higher for the 4th quintile of AIP as compared with the 1st quintile (HR = 1.36).

Conclusions

High-risk VAI levels were statistically significantly associated with all-cause mortality risk in men and women groups. The higher AIP level (5th quintile vs. 1st quintile—in men and 4th quintile vs. 1st quintile—in women) was significantly associated with increased mortality from CVD in the men group and increased all-cause mortality in the women group.

Metabolomics Analysis Reveals the Effects of Compound Fuzhuan Brick Tea (CFBT) on Regulating Dyslipidemia and Metabolic Disorders in Mice Induced by High-Fat Diet

Background: It is well known that obesity induced by high-fat diet (HFD) poses a serious threat to people’s health. Fuzhuan brick tea, one of the most popular beverages, is reported to possess a significant effect on regulating lipid metabolism, attributed to its many bioactive ingredients. However, the efficacy and mechanism of compound Fuzhuan brick tea (CFBT) made from Fuzhuan brick tea and other six Chinese herbal medicines are still not well defined. Methods: Sixty mice were divided into six groups: normal control group (CK), high-fat model group (NK), positive control group with anti-hyperlipidemic drug (YK), CFBT at low-(FL), medium-(FM) and high-(FH) dosage. Intervening for 30 days, conventional indexes analysis combined with metabolomics were performed to evaluate the changes in biochemical indexes and liver metabolic profiles in mice submitted to HFD. Results: CFBT treatment was able to ameliorate obesity, serum biochemical parameters, antioxidant activity and hepatic steatosis. In addition, significant alterations in the liver tissue metabolic profiles were observed, with most of these associated with inflammation, glucose and lipid metabolism. Conclusions: This study provides evidence that consumption of CFBT is capable of preventing dyslipidemia, reducing weight gain, restoring liver injury, as well as improving metabolic disorders.

Study on the value of small dense low-density lipoprotein in predicting cardiovascular and cerebrovascular events in the high-risk stroke population

Background

Lipid management in people at high risk of stroke is an important measurement to prevent the occurrence of stroke. The study aims to investigate the association between sdLDL and cardiovascular and cerebrovascular events in high‐risk stroke populations.

Methods

This was a prospective study. Screened from 15,933 individuals aged >40 years in April 2013 and followed up at 3rd, 6th, 12th, and 24th months, 823 participants met the screening criteria and were investigated for clinical data and biochemical parameters.

Results

A total of 286 subjects had varying degrees of carotid stenosis, and 18 subjects experienced cardiovascular and cerebrovascular events during the two‐year follow‐up period. There was no positive correlation between sdLDL and carotid stenosis. Carotid stenosis and extent of carotid stenosis involvement did not predict cardiovascular and cerebrovascular events in patients with high‐risk stroke, while sdLDL did. The sdLDL level in the events group was significantly higher than those in the no event group (p = 0.002). In the events group, the risk of events in the fourth quartile of sdLDL was 10.136 times higher than in the first quartile (HR = 10.136, 95% CI: 1.298–79.180, p = 0.027).

Conclusions

sdLDL was positively correlated with the incidence of cardiovascular and cerebrovascular events, which can predict the occurrence of an event and provide a scientific basis for early prevention.

Atherogenic Index of Plasma and Coronary Artery Disease in the Adult Population: A Meta-Analysis

Background: The atherogenic index of plasma (AIP), which is the logarithm of the ratio between the triglyceride and high-density lipoprotein cholesterol (TG/HDL-C) concentrations in molar units, is correlated with the burden of atherosclerosis. This study aimed to evaluate the association between the AIP and coronary artery disease (CAD) in the adult population by performing a meta-analysis. Methods: Observational studies relevant for this meta-analysis were identified by searching the PubMed, Embase, and Web of Science databases. Only studies using multivariate analysis were considered. A random-effects model, which incorporates potential intra-study heterogeneity, was applied to combine the results. Results: Ten observational studies were included. In studies with the AIP analyzed as a continuous variable, a higher AIP was associated with a higher odds of CAD (adjusted risk ratio [RR] per 1-standard deviation [SD] increment of AIP: 2.10, 95% confidence interval [CI]: 1.51-2.93, P < 0.001, I² = 90%). Further analysis of studies with the AIP analyzed as a categorical variable showed a higher odds of CAD (adjusted RR: 2.35, 95% CI: 1.88-2.93, P < 0.001, I² = 37%) in the participants with the highest versus the lowest AIP value. Subgroup analyses demonstrated consistent results in asymptomatic and symptomatic populations as well as in male and female participants (all between-group P values > 0.05). Discussion: Current evidence, mostly from cross-sectional studies, suggests that a higher AIP value may be independently associated with CAD in the adult population.

Efficient Automated Disease Diagnosis Using Machine Learning Models

Recently, many researchers have designed various automated diagnosis models using various supervised learning models. An early diagnosis of disease may control the death rate due to these diseases. In this paper, an efficient automated disease diagnosis model is designed using the machine learning models. In this paper, we have selected three critical diseases such as coronavirus, heart disease, and diabetes. In the proposed model, the data are entered into an android app, the analysis is then performed in a real-time database using a pretrained machine learning model which was trained on the same dataset and deployed in firebase, and finally, the disease detection result is shown in the android app. Logistic regression is used to carry out computation for prediction. Early detection can help in identifying the risk of coronavirus, heart disease, and diabetes. Comparative analysis indicates that the proposed model can help doctors to give timely medications for treatment.