The predictive value of cumulative atherogenic index of plasma (AIP) for cardiovascular outcomes: a prospective community-based cohort study.

BACKGROUND: Atherogenic index of plasma (AIP) has been reported as a critical predictor on the risks and clinical outcomes of cardiovascular diseases (CVDs), and we aimed to explore the potential predictive value of cumulative AIP on major adverse cardiac events (MACE), stroke, myocardial infarction (MI) and cardiovascular mortality. METHODS: A large-scale community-based prospective cohort was established from December 2011 to April 2012 and followed up in May to July 2014. The endpoint outcomes were obtained before December 31, 2021. AIP was calculated as the logarithmically transformed ratio of triglyceride (TG) to high-density lipoprotein cholesterol (HDL-c) and cumulative AIP was the average value of AIP in 2012 and 2014. RESULTS: An overall of 3820 participants (36.1% male) with mean (SD) age of 59.1 (8.7) years, were enrolled. Within a median follow-up of 7.5 years, a total of 371 (9.7%) participants were documented with MACE, 293 (7.7%) participants developed stroke, 68 (1.8%) suffered from MI and 65 (1.7%) experienced cardiovascular mortality. Multivariable Cox regression analysis revealed significant associations between cumulative AIP and the risk of MACE, stroke and MI. Regarding MACE, individuals with one higher unit of cumulative AIP were associated with 75% increment on the incidence of going through MACE in fully adjusted model, while categorizing participants into four groups, individuals in the highest cumulative AIP quartile were significantly associated with increased incidence of MACE (HR = 1.76, 95%CI: 1.27-2.44, p < 0.001 in fully adjusted model), stroke (HR = 1.69, 95%CI: 1.17-2.45, p = 0.005) and MI (HR = 2.82, 95%CI: 1.18-6.72, p = 0.019). But not a significant association was observed between cumulative AIP and cardiovascular mortality. In subgroup analysis, the association of cumulative AIP and the incidence of stroke was more pronounced in the elderly (HR: 0.89 vs. 2.41 for the age groups < 65 years and ≥ 65 years, p for interaction = 0.018). CONCLUSIONS: A higher cumulative AIP was significantly associated with an increased risk of MACE, stroke and MI independent of traditional cardiovascular risk factors in a community-based population, and the association of cumulative AIP and stroke was particularly pronounced in the elderly population.

Evaluation of Plasma Atherogenic Index, Triglyceride-Glucose Index and Other Lipid Ratios as Predictive Biomarkers of Coronary Artery Disease in Different Age Groups.

(1) Background: Dyslipidaemia and insulin resistance are major risk factors for coronary artery disease (CAD). This study investigated the relationship between plasma atherogenic index (PA-I), triglyceride-glucose index (TGI) and other lipid ratios with the presence and prediction of CAD among different age categories. (2) Methods: The study included 223 participants diagnosed with CAD and those with normal coronary arteries (normal group) by coronary computed tomography angiography (CCTA). Participants were categorised by age and sex: premature CAD (PCAD) for men under 55 and women under 65, and older groups as elderly. (3) Results: PA-I, Lipid Combined Index, Castelli Risk Indices, and TGI were significantly higher in the PCAD group compared to the control group (p < 0.05). ROC analysis showed that a PA-I cut-off of 0.41 had a sensitivity of 62% and a specificity of 58% for predicting PCAD, while a TGI cut-off of 8.74 had a sensitivity of 68% and a specificity of 62%. In the elderly, no significant differences in these indices were found between the CAD and normal groups. (4) Conclusions: Traditional lipid profiles and non-traditional lipid indices such as PA-I and TGI show significant differences in predicting CAD in younger populations but not in older groups. TGI and PA-I may be promising biomarkers for the prediction of PAD, although further validation is needed.

Association between atherogenic index of plasma and gestational diabetes mellitus: a prospective cohort study based on the Korean population.

BACKGROUND: Atherogenic index of plasma (AIP) is a non-traditional lipid parameter that can reflect the burden of atherosclerosis. A lipid profile resembling atherosclerosis emerged during pregnancy. Although lipid metabolism is pivotal in diabetes pathogenesis, there is no evidence linking AIP to gestational diabetes mellitus (GDM). Therefore, our objective was to explore the relationship between AIP and GDM and assess AIP's predictive capability for GDM. METHODS: This was a secondary analysis based on data from a prospective cohort study in Korea involving 585 single pregnant women. AIP was calculated as log10 (TG/HDL). We examined the relationship between AIP and GDM using logistic regression models, curve fitting, sensitivity analyses, and subgroup analyses. Receiver operating characteristic (ROC) analysis was also used to determine the ability of AIP to predict GDM. RESULTS: The average age of the participants was 32.06 ± 3.76 years. The AIP was 0.24 ± 0.20 on average. The GDM incidence was 6.15%. After adjustment for potentially confounding variables, AIP showed a positive linear relationship with GDM (P for non-linearity: 0.801, OR 1.58, 95% CI 1.27-1.97). The robustness of the connection between AIP and GDM was demonstrated by sensitivity analyses and subgroup analyses. An area under the ROC curve of 0.7879 (95% CI 0.7087-0.8671) indicates that AIP is an excellent predictor of GDM. With a specificity of 75.41% and sensitivity of 72.22%, the ideal AIP cut-off value for identifying GDM was 0.3557. CONCLUSIONS: This study revealed that the AIP at 10-14 weeks of gestation was independently and positively correlated with GDM risk. AIP could serve as an early screening and monitoring tool for pregnant women at high risk of GDM, thereby optimizing GDM prevention strategies. TRIAL REGISTRATION: ClinicalTrials.gov registration no. NCT02276144.

Developing and evaluating the construct validity of a dietary pattern predictive of plasma TMAO and choline.

BACKGROUND AND AIMS: The metabolism of choline (highly present in animal products) can produce trimethylamine N-oxide (TMAO), a metabolite with atherosclerotic effects; however, dietary fiber may suppress this metabolic pathway. This study aimed to develop a dietary pattern predictive of plasma TMAO and choline concentrations using reduced rank regression (RRR) and to evaluate its construct validity. METHODS AND RESULTS: Diet and plasma concentrations of choline (µmol/L) and TMAO (µmol/L) were assessed in 1724 post-menopausal women who participated in an ancillary study within the Women's Health Initiative Observational Study (1993-1998). The TMAO dietary pattern was developed using RRR in half of the sample (Training Sample) and applied to the other half of the sample (Validation Sample) to evaluate its construct validity. Energy-adjusted food groups were the predictor variables and plasma choline and TMAO, the response variables. ANCOVA and linear regression models were used to assess associations between each biomarker and the dietary pattern score. Discretionary fat, potatoes, red meat, and eggs were positively associated with the dietary pattern, while yogurt, fruits, added sugar, and starchy vegetables were inversely associated. Mean TMAO and choline concentrations significantly increased across increasing quartiles of the dietary pattern in the Training and Validation samples. Positive associations between the biomarkers and the TMAO dietary pattern were also observed in linear regression models (Validation Sample: TMAO, adjusted beta-coefficient = 0.037 (p-value = 0.0088); Choline, adjusted beta-coefficient = 0.011 (p-value = 0.0224). CONCLUSION: We established the TMAO dietary pattern, a dietary pattern reflecting the potential of the diet to contribute to plasma concentrations of TMAO and choline.

High-density lipoprotein cholesterol abnormalities correlate with severe fatigue in major depressive disorder: A cross-sectional study.

OBJECTIVES: This cross-sectional study aimed to characterize the differences of metabolic profiles and atherogenicity between various levels of fatigue severity in patients with major depressive disorder (MDD), and examine the extent to which metabolic abnormality correlates with fatigue severity. METHODS: We recruited 119 patients with MDD and assessed fatigue severity using Krupp's Fatigue Severity Scale. Blood samples were collected to determine plasma levels of fasting glucose, high-density lipoprotein cholesterol (HDL-C), triglycerides, total cholesterol and low-density lipoprotein cholesterol. The atherogenic index of plasma (AIP) was calculated as log10 (triglycerides/HDL-C). RESULTS: MDD with severe fatigue were more likely to be younger (43.3 ± 10.3 years vs. 49.4 ± 8.5 years, p = 0.001), had a younger age of onset (34.7 ± 9.7 years vs. 40.7 ± 9.5 years, p = 0.001), demonstrated higher HAMD scores (18.0 ± 7.6 vs. 10.9 ± 7.5, p < 0.001), as well as lower HDL-C levels (48.5 ± 10.8 vs. 55.3 ± 13.9, p = 0.003), a greater prevalence of low HDL-C (43.9% vs. 22.6%, p = 0.015) and higher AIP levels (0.4 ± 0.3 vs. 0.3 ± 0.3, p = 0.046). Both a decreased plasma HDL-C level (OR = 0.95, 95% CI = 0.91-0.99, p = 0.009) and a diagnosis of low HDL-C (OR = 3.29, 95% CI = 1.27-8.57, p = 0.015) were significantly correlated with an increased risk of fatigue severity. CONCLUSION: HDL-C could potentially protect patients with MDD from severe fatigue and the associated risk of cardiovascular disease.

The Predictive Value of Atherogenic Index of Plasma, Non- High Density Lipoprotein Cholesterol (Non-HDL-C), Non-HDL-C/HDL-C, and Lipoprotein Combine Index for Stroke Incidence and Prognosis in Maintenance Hemodialysis Patients.

Purpose: The serum lipid level is strongly associated with atherosclerosis. However, research on the relationship between lipid-derived indices and acute ischemic stroke (AIS) occurrence in hemodialysis populations is limited. This study aimed to explore the predictive value of lipid-derived indices, including atherogenic index of plasma (AIP), Non- high density lipoprotein cholesterol (Non-HDL-C), Non-HDL-C/HDL-C, and lipoprotein combine index (LCI) in clinical practice for the occurrence and prognosis of AIS in hemodialysis patients. Methods: A total of 451 patients undergoing maintenance hemodialysis were screened and 350 were enrolled in this study. The lipid parameters exhibit a progressive increase across the tertiles, with values rising from Q1 through Q3. Enrolled patients were divided into three groups (Q1, Q2, and Q3) based on tertiles of AIP, Non-HDL-C, Non-HDL-C/HDL-C, and LCI values. Kaplan-Meier curves were performed to investigate the association between the AIP, Non-HDL-C, Non-HDL-C/HDL-C, LCI and AIS-free survival in hemodialysis patients. Chi-square analysis was used to explore the association between the AIP, Non-HDL-C, Non-HDL-C/HDL-C, LCI and AIS outcomes in hemodialysis patients. AIS outcomes were assessed using the modified Rankin Scale (mRS). Results: Kaplan-Meier analysis revealed that the AIS-free survival rates were significantly higher in the Q1 group compared to Q2 and Q3 groups for AIP, Non-HDL-C, Non-HDL-C/HDL-C, and LCI. Log rank tests showed statistically significant differences between the Q1 group and the Q2 and Q3 groups (p < 0.05 for all). The proportion of patients with a good outcome mRS was higher in the Q1 group compared to the Q2-Q3 groups (AIP: 0.818 vs 0.792; Non- HDL-C: 0.866 vs 0.767; Non- HDL-C/HDL-C: 0.867 vs 0.767; LCI: 0.938 vs 0.750). Conclusion: The four lipid-derived parameters are effective predictors of AIS in patients undergoing hemodialysis, and AIP has a strongest correlation with the risk of AIS. Hemodialysis patients with elevated levels of the four lipid-derived indices had a higher incidence of AIS and poorer functional outcomes compared to those with lower levels. Our conclusions may require confirmation by further research in the future.

Time-course atherogenic blood lipid response to statin discontinuation in dyslipidemic adults.

BACKGROUND AND AIMS: Half of dyslipidemic patients sometimes discontinue statin medication. It is unclear if blood atherogenic risk increases right after statin discontinuation or if there is a lingering protective effect. We sought to determine if a legacy effect prevented blood lipid increases during the first stages of statin cessation. METHODS AND RESULTS: Atherogenic blood lipid profile was measured in 10 overweight (BMI 31 ± 3 kg m-2) middle-aged males (62 ± 7 years old), statin users, while fasted and postprandially. Trials were conducted before (i.e., Day 0) and after 4, 7, 15, and 30 days of statin withdrawal and 20 days after statins reloading (Day 50). Four days after statin discontinuation, blood fasting LDL-c, total cholesterol (CHOL), and triglyceride (TG) concentrations increased by 30%, 18%, and 17%, respectively (P < 0.05). The increases in LDL-c, CHOL, and TG peaked after 7-15 days at 79%, 48%, and 34% of basal levels (P < 0.001), respectively. There were no significant correlations between the increases in blood lipids and the dose or years under statin treatment (P = 0.156-0.575). Twenty days after resuming statins, blood LDL-c (2.79 ± 1.06 vs 2.20 ± 0.50 mmol L-1; P = 0.568), CHOL (4.85 ± 1.41 vs 4.25 ± 0.83 mmol L-1; P = 0.747), and TG (1.47 ± 0.60 vs 1.50 ± 0.68 mmol L-1; P = 0.782), returned to basal levels. CONCLUSIONS: Our data does not support a statin lingering/legacy effect in blood lipids since they dangerously increased after only 4 days of statin withdrawal in every patient, regardless of dose and years under treatment. Reloading statins restored blood lipids, evidencing a reproducible biological effect at the whole-body level.

Association between the atherogenic index of plasma and coronary collateral circulation in patients with chronic total occlusion.

BACKGROUND: The atherogenic index of plasma (AIP) is considered an independent risk factor for coronary artery disease (CAD). The present study investigated whether AIP correlates with the formation of coronary collateral circulation (CCC) in CAD patients with chronic total occlusion (CTO). METHODS: This retrospective study included 1093 CAD patients with CTO confirmed by coronary angiography from January 2020 to December 2020 at Beijing Anzhen Hospital. Based on the Rentrop scoring system, the patients were divided into the good CCC group and the poor CCC group. AIP was calculated by log (triglyceride/high-density lipoprotein cholesterol). Meanwhile, the study population was further divided into four groups according to the quartiles of AIP. RESULTS: Patients in the poor CCC group exhibited significantly higher AIP compared to those in the good CCC group (0.31 ± 0.27 vs. 0.14 ± 0.24, p < 0.001). Multivariate logistic regression analysis revealed an independent association between AIP and poor CCC, regardless of whether AIP was treated as a continuous or categorical variable (p < 0.001), after adjusting for confounding factors. Besides, this association remained consistent across most subgroups. The incorporation of AIP into the baseline model significantly enhanced the accuracy of identifying poor CCC [area under the curve (AUC): baseline model, 0.661 vs. baseline model + AIP, 0.721, p for comparison < 0.001]. CONCLUSIONS: Elevated AIP is independently associated with an increased risk of poor CCC in CAD patients with CTO, and AIP may improve the ability to identify poor CCC in clinical practice.

Nonlinear association between atherogenic index of plasma and type 2 diabetes mellitus in overweight and obesity patients: evidence from Chinese medical examination data.

BACKGROUND: The atherogenic index of plasma (AIP) is closely associated with the onset of diabetes, with obesity being a significant risk factor for type 2 diabetes mellitus (T2DM). However, the association between the AIP and T2DM in overweight and obese populations has been infrequently studied. Therefore, this study aimed to explore this association in overweight and obese individuals with T2DM. METHODS: This cross-sectional analysis utilized data from 40,633 participants with a body mass index (BMI) ≥ 24 kg/m2 who were screened from January 2018 to December 2023 at Henan Provincial People's Hospital. Participants were categorized into groups of overweight and obese individuals with and without diabetes according to the T2DM criteria. The AIP, our dependent variable, was calculated using the formula log10 [(TG mol/L)/HDL-C (mol/L)]. We investigated the association between the AIP and T2DM in overweight and obese individuals using multivariate logistic regression, subgroup analysis, generalized additive models, smoothed curve fitting, and threshold effect analysis. Additionally, mediation analysis evaluated the role of inflammatory cells in AIP-related T2DM. RESULTS: Overweight and obese patients with T2DM exhibited higher AIP levels than those without diabetes. After adjusting for confounders, our results indicated a significant association between the AIP and the risk of T2DM in overweight and obese individuals (odds ratio (OR) = 5.17, 95% confidence interval (CI) 4.69-5.69). Notably, participants with a high baseline AIP (Q4 group) had a significantly greater risk of T2DM than those in the Q1 group, with an OR of 3.18 (95% CI 2.94-3.45). Subgroup analysis revealed that the association between the AIP and T2DM decreased with increasing age (interaction P < 0.001). In overweight and obese populations, the association between AIP and T2DM risk displayed a J-shaped nonlinear pattern, with AIP > - 0.07 indicating a significant increase in T2DM risk. Various inflammatory cells, including neutrophils, leukocytes, and monocytes, mediated 4.66%, 4.16%, and 1.93% of the associations, respectively. CONCLUSION: In overweight and obese individuals, the AIP was independently associated with T2DM, exhibiting a nonlinear association. Additionally, the association between the AIP and T2DM decreased with advancing age. Multiple types of inflammatory cells mediate this association.

Is plasma atherogenic index or LDL/HDL ratio more predictive of peripheral arterial disease complexity?

INTRODUCTION: The most basic and well-known cause of peripheral arterial disease (PAD) is atherosclerosis. One of the main factors causing atherosclerosis is dyslipidemia. We will evaluate whether specific ratios of dyslipidemia, such as the atherogenic plasma index (AIP) and LDL/HDL ratio, which have recently been used in practice, can help us to predict the complexity of PAD in the clinic. METHODS: A total of 305 patients with PAD admitted to our clinic were retrospectively included in this study. After evaluation according to angiography images using TASC-II classification, patients were divided into TASC A-B and TASC C-D. AIP was evaluated with the following formula: Log (TG/HDL). Cut-off values for AIP and LDL/HDL were determined on the ROC (receiver operating characteristic) curve. Logistic regression analysis were conducted to predict peripheral arterial disease complexity. RESULTS: The mean ages of Group 1 (n:180, 68.3% male) and Group 2 (n:125, 77.6% male) patients were 64.10 ± 12.39 and 64.94 ± 11.12 years, respectively. The prevalence of diabetes mellitus (DM, p < 0.016) and coronary artery disease (CAD, p < 0.001) was higher in group 2. Group 2 had higher TG (p = 0.045), LDL-C (p = 0.004), AIP (p = 0.010), LDL/HDL (p < 0.001), and lower HDL-C (p = 0.015). In multivariate logistic regression analysis evaluating parameters in predicting PAD complexity, DM (OR: 1.66 Cl 95%: 1.01-2.73 p = 0.045), CAD (OR: 2.86 Cl 95%: 1.75-4.69 p < 0.001) and LDL/HDL (OR: 1.47 Cl 95%: 1.10-1.96 p = 0.008) were independent variables. CONCLUSION: In our study, we compared LDL/HDL ratio and AIP in PAD for the first time in the literature and showed that LDL/HDL ratio is a more valuable ratio and an independent predictor of PAD complexity.

Non-linear association of atherogenic index of plasma with bone mineral density a cross-sectional study.

INTRODUCTION: Although there has been abundant evidence of the association between dyslipidemia as a single factor and osteoporosis, the non-linear relationship between osteoporosis and the Atherogenic Index of Plasma (AIP) has not yet been thoroughly investigated. This study aimed to investigate the complex relationship between AIP and bone mineral density (BMD) to elucidate their interrelationship. METHODS: An analysis of 2007-2018 National Health and Nutrition Survey (NHANES) data was conducted for this study. The study enrolled 5,019 participants. Logarithmically multiplying triglycerides and high-density lipoprotein cholesterol yields the AIP (base 10). The measured variables consisted of BMD in the total femur (TF), femoral neck (FN), and lumbar spine (LS). The association between AIP and BMD was examined using a range of statistical models, such as weighted multivariable logistic regression, generalized additive model, etc. RESULTS: It was found that AIP was positively associated with BMD after adjusting for age, gender, race, socioeconomic status, degree of education, income, Consuming alcoholic beverages, osteoporosis status (Yes or No), ALT, AST, serum creatinine, and total calcium levels. Further studies supported the association link between elevated BMD and AIP. Furthermore, compared to men, females had a higher positive connection between AIP and BMD. In general, there was a curve in the reverse L-shape seen, with a point of change around 0.877, indicating a relationship between AIP and TF BMD. Moreover, a curve exhibiting an L-formed pattern, with a point of inflection at around 0.702, was seen between AIP and FN BMD. In addition, a J-shaped curve was seen, with a point of inflection at 0.092, which demonstrates the association between AIP and LS BMD. CONCLUSION: The AIP and TF BMD curves resemble inverted L shapes, as do the AIP and FN BMD curves. The relationship between AIP and LS BMD was further demonstrated by a J-shaped curve. The results indicate a possible association between AIP and bone mineral density, which should be explored in more detail.

Association between the atherogenic index of plasma and left ventricular hypertrophy in patients with obstructive sleep apnea: a retrospective cross-sectional study.

BACKGROUND: The atherogenic index of plasma (AIP) is a simple and reliable marker of insulin resistance and is closely associated with various cardiovascular diseases (CVDs). However, the relationships between AIP and left ventricular (LV) geometric indicators have not been adequately assessed. This study was carried out to investigate the association between AIP and LV geometric abnormalities in obstructive sleep apnea (OSA) patients. METHODS: This retrospective cross-sectional study included a total of 618 OSA patients (57.3 ± 12.4 years, 73.1% males, BMI 28.1 ± 4.2 kg/m2) who underwent echocardiography. Patients with OSA were diagnosed with clinical symptoms and an apnea-hypopnea index ≥ 5.0. LV hypertrophy (LVH) was defined as left ventricular mass index (LVMIh2.7) ≥ 50.0 g/m2.7 for men and 47.0 g/m2.7 for women. AIP was calculated as log10 (TG/HDL-C). RESULTS: Compared with the non-LVH group, AIP was significantly higher in the LVH group (0.19 ± 0.29 vs 0.24 ± 0.28, P = 0.024) and the concentric LVH group (0.18 ± 0.29, 0.19 ± 0.30, 0.20 ± 0.26 and 0.29 ± 0.29 in the control, concentric remodeling, eccentric hypertrophy and concentric hypertrophy groups, respectively, P = 0.021). Meanwhile, in the group of patients with the highest AIP tertile, the levels of LVMIh2.7 (42.8 ± 10.5, 43.2 ± 9.3 and 46.1 ± 12.1 in the T1, T2 and T3 groups, respectively, P = 0.003), and the prevalence of LVH (25.2%, 24.0% and 34.6% in the T1, T2 and T3 groups, respectively, P = 0.032) and concentric LVH (10.7%, 9.8% and 20.2% in the T1, T2 and T3 groups, respectively, P = 0.053) were higher compared with those in the other groups. Positive correlations between AIP and LV geometric indicators including the LVMIh2.7, LVMIBSA, LV mass (LVM), diastolic left ventricular inner diameter (LVIDd), diastolic left ventricular posterior wall thickness (PWTd) and diastolic interventricular septal thickness (IVSTd), were revealed according to correlation analysis (P < 0.05). Furthermore, AIP was independently associated with LVMIh2.7 according to multivariate linear regression model (ß = 0.125, P = 0.001). Notably, AIP remained independently associated with an elevated risk of LVH [odds ratio (OR) = 1.317 per 1 standard deviation (SD) increment, 95% confidence interval (CI): 1.058 - 1.639, P = 0.014) and concentric LVH (OR = 1.545 per 1 SD increment, 95% CI: 1.173 - 2.035, P = 0.002) after fully adjusting for all confounding risk factors by multivariate logistic regression analyses. CONCLUSIONS: AIP was independently associated with an increased risk of LVH and concentric LVH in OSA patients. Therefore, AIP, as a practical and cost-effective test, might be useful in monitoring hypertrophic remodeling of the heart and improving CVDs risk stratification in clinical management of OSA.

Roles of Nontraditional Lipid Parameters for Predicting Restenosis in Patients with Intracranial Atherosclerotic Stenosis After Endovascular Treatment.

PURPOSE: Nontraditional lipid parameters are associated with intracranial atherosclerotic stenosis (ICAS) progression. This study aimed to investigate the association of nontraditional lipid parameters with the risk of restenosis in patients with ICAS after endovascular treatment (EVT). METHODS: This study retrospectively enrolled consecutive patients with symptomatic ICAS after successful EVT followed by at least 3 months of angiography. Participants were divided into restenosis or non-restenosis groups based on the angiographic follow-up results. The nontraditional lipid parameters were calculated from conventional lipid parameters. The COX regression models and restricted cubic splines (RCS) were used to explore the association between nontraditional lipid parameters and restenosis. RESULTS: This study recruited 222 cases with 224 lesions eligible for our study, of which 56 (25%) had restenosis. Compared with the non-restenosis group, patients in the restenosis group had higher levels of the atherogenic index of plasma (AIP) (0.211, interquartile range, IQR, 0.065-0.404 vs. 0.083, IQR, -0.052-0.265, P = 0.001), remnant cholesterol (RC) (0.55, IQR, 0.33-0.77 vs. 0.30, IQR, 0.18-0.49, P < 0.001) and Castelli's index­I (CRI-I) (4.13, IQR, 3.39-5.34 vs. 3.74, IQR, 2.94-4.81, P = 0.030). In the multivariable COX regression analysis, a 0.1 unit increase of AIP was an independent risk factor for restenosis (hazard ratio, HR = 1.20, 95% confidence interval, CI 1.05-1.35, P = 0.005) whereas such an association was not observed for RC (HR = 1.01, 95% CI 0.90-1.15, P = 0.835). The restricted cubic spline (RCS) plot revealed a linear relationship between AIP and restenosis (P for nonlinear = 0.835) but a nonlinear relationship for RC (P for nonlinear = 0.012). Patients were stratified according to tertiles (T) of AIP and RC and the risk of restenosis increased in T3 compared to T1 (HR = 3.21, 95% CI 1.35-7.62, P = 0.008 and HR = 2.99, 95% CI 1.11-8.03, P = 0.030, respectively). Furthermore, this association remained stable within each LDL­C level subgroup. CONCLUSION: The AIP and RC were positively and independently associated with restenosis in patients with ICAS after EVT.

[Targeting dyslipidaemia in primary prevention of cardiovascular disease]. / Cibler les dyslipidémies en prévention primaire des maladies cardiovasculaires.

Prevention of cardiovascular disease remains a key-objective from a health care point of view. The present article focuses on primary prevention, i.e. to prevent a first cardiovascular event among at-risk people. The first step is to evaluate the cardiovascular risk level (low to moderate, high, very high), which allows to fix target goals. It is especially the case regarding the management of dyslipidaemias. Lipid abnormalities are considered as a major coronary risk factor (especially, LDL or even better non-HDL cholesterol according to recent guidelines). Theoretically, it is quite easy to control this risk factor thanks to available lipid-lowering drugs, yet this goal remains insufficiently reached in clinical practice. The second step is to prescribe, in addition to life-style measures, the best pharmacological treatment. In most cases, it is a statin that should be well titrated, eventually combined with ezetimibe and/or bempedoic acid, to reach the set objectives. Finally, it is important to convince the at-risk individual by providing the valuable information regarding the benefits/risks ratio of the therapy and to verify a good drug compliance in the long run. Indeed, as dyslipidaemia is asymptomatic, people in primary prevention too easily tend to neglect (and eventually stop) the valuable therapy, also because statins have been widely (yet unfairly) criticized by some people in recent years.

La prévention des maladies cardiovasculaires reste un objectif prioritaire de santé publique. Cet article fait le point sur la prévention primaire, à savoir prévenir un premier événement chez des personnes considérées comme à risque. La première étape consiste à évaluer le niveau du risque (faible à modéré, élevé, très élevé), ce qui permet de fixer des objectifs thérapeutiques. C'est particulièrement le cas en ce qui concerne la prise en charge des dyslipidémies. Celles-ci sont considérées comme un facteur de risque coronarien majeur (en particulier l'augmentation du cholestérol LDL, ou encore mieux du non-HDL d'après les dernières recommandations). Ce facteur de risque est, en théorie, assez facilement modifiable avec les médicaments à notre disposition, mais reste insuffisamment contrôlé dans la pratique clinique. La seconde étape consiste à prescrire, en complément des mesures hygiéno-diététiques, le traitement pharmacologique le plus adéquat, en général une statine correctement titrée et éventuellement combinée à de l'ézétimibe et/ou à de l'acide bempédoïque, pour atteindre les objectifs fixés. Il convient, enfin, de convaincre la personne à risque en lui expliquant le rapport bénéfices/risques du traitement proposé et de s'assurer qu'une bonne observance thérapeutique soit maintenue au long cours. En effet, comme la dyslipidémie est asymptomatique, la personne en prévention primaire a trop facilement tendance à négliger, voire abandonner, ce traitement, d'autant plus que les statines ont été largement (mais injustement) décriées par certains ces dernières années.

Diet-related inflammation is positively associated with atherogenic indices.

Current evidence suggests that non-traditional serum lipid ratios are more effective than traditional serum lipid parameters in predicting vascular diseases, and both of them are associated with dietary patterns. Therefore, this study aimed to investigate the relationship between the dietary inflammatory index (DII) and atherogenic indices using traditional serum lipid parameters (triglyceride (TG), total cholesterol (TC), LDL cholesterol (LDL-c), high-density lipoprotein cholesterol (HDL-c)) and non-traditional serum lipid ratios (atherogenic index of plasma (AIP), Castelli's index-I (CRI_I), Castelli's index-II (CRI_II), the lipoprotein combination index (LCI), and the atherogenic coefficient (AC)). Basic information from the Ravansar Non-Communicable Diseases cohort study was utilized in the present cross-sectional observational study. The study included 8870 adults aged 35-65 years. A validated food frequency questionnaire (FFQ) was used to measure DII. We compared the distributions of outcomes by DII score groups using multivariable linear regression. The difference between DII score groups was evaluated by the Bonferroni test. The mean ± SD DII was - 2.5 ± 1.43, and the prevalence of dyslipidemia was 44%. After adjusting for age, sex, smoking status, alcohol consumption status, physical activity, systolic blood pressure (SBP), diastolic blood pressure (DBP), fasting blood sugar (FBS), body mass index (BMI) and socioeconomic status (SES), participants in the highest quartile of DII had a greater risk for CRI_I (ß = 0.11, CI 0.05, 0.18), CRI_II (ß = 0.06, CI 0.01, 0.11), LCI (ß = 0.11, CI 288.12, 8373.11), AC (ß = 0.11, CI 0.05, 0.17) and AIP (ß = 0.06, CI 0.02, 0.10). Moreover, according to the adjusted logistic regression model, the risk of dyslipidemia significantly increased by 24% (OR: 1.24, 95% CI 1.08-1.41), 7% (OR: 1.07, 95% CI 0.94, 1.21) and 3% (OR: 1.03, 95% CI 0.91, 1.16) in Q4, Q3 and Q2 of the DII, respectively. Finally, diet-related inflammation, as estimated by the DII, is associated with a higher risk of CRI-I, CRI-II, LCI, AC, and AIP and increased odds of dyslipidemia.

Atherogenic Index of Plasma as an Early Marker of Chronic Kidney Disease and Liver Injury in Type 2 Diabetes.

Background: Diabetic kidney disease (DKD) is the main cause of end-stage renal disease and has a high mortality rate. Currently, no effective treatments are available to reduce the progression of kidney damage associated with diabetes. Objectives: To explore the influence and predictive value of the atherogenic index of plasma (AIP) on early chronic kidney disease and liver injury in patients with type 2 diabetes mellitus (T2DM). Methods: Medical records of 1057 hospitalized adult patients with T2DM between January 2021 and December 2022 were collected. The predictive value of AIP, renal function, and liver injury in patients with T2DM were analyzed using Pearson's correlation, multiple logistic regression, and receiver operating characteristic (ROC) curve analyses. Results: AIP was a sensitive indicator of early liver and kidney injury in patients with T2DM. Patients in the DKD group showed increased AIP that positively correlated with serum creatinine, uric acid, and ß2-microglobulin levels. Increased AIP negatively correlated with estimated glomerular filtration rate (eGFR). AIP significantly correlated with alanine aminotransferase and aspartate aminotransferase levels and glutamyl transpeptidase-to-platelet ratio (GPR). An eGFR of 60-100 mL/min/1.73 m2 significantly increased the risk of DKD as the AIP increased. At lower GPR levels, the risk of DKD significantly increased with increasing AIP. However, no significant difference was found between the 2 groups when the GPR was >0.1407. The ROC curve analysis showed that AIP could predict early liver injury. Conclusions: AIP is directly involved in early liver and kidney injury in T2DM and may be a sensitive indicator for early detection.

Diabetes and its complications are a global public health concern. Diabetic kidney disease (DKD) is the main cause of end-stage renal disease, and metabolism-related disease factors are found throughout the progression of DKD. This study identified common sensitive indicators of early metabolism-related damage to liver and kidney function in patients with T2DM.

Triglyceride-rich lipoproteins and cardiovascular diseases.

The global prevalence of cardiovascular diseases (CVD) continues to rise steadily, making it a leading cause of mortality worldwide. Atherosclerosis (AS) serves as a primary driver of these conditions, commencing silently at an early age and culminating in adverse cardiovascular events that severely impact patients' quality of life or lead to fatality. Dyslipidemia, particularly elevated levels of low-density lipoprotein cholesterol (LDL-C), plays a pivotal role in AS pathogenesis as an independent risk factor. Research indicates that abnormal LDL-C accumulation within arterial walls acts as a crucial trigger for atherosclerotic plaque formation. As the disease progresses, plaque accumulation may rupture or dislodge, resulting in thrombus formation and complete blood supply obstruction, ultimately causing myocardial infarction, cerebral infarction, and other common adverse cardiovascular events. Despite adequate pharmacologic therapy targeting LDL-C reduction, patients with cardiometabolic abnormalities remain at high risk for disease recurrence, highlighting the importance of addressing lipid risk factors beyond LDL-C. Recent attention has focused on the causal relationship between triglycerides, triglyceride-rich lipoproteins (TRLs), and their remnants in AS risk. Genetic, epidemiologic, and clinical studies suggest a causal relationship between TRLs and their remnants and the increased risk of AS, and this dyslipidemia may be an independent risk factor for adverse cardiovascular events. Particularly in patients with obesity, metabolic syndrome, diabetes, and chronic kidney disease, disordered TRLs and its remnants levels significantly increase the risk of atherosclerosis and cardiovascular disease development. Accumulation of over-synthesized TRLs in plasma, impaired function of enzymes involved in TRLs lipolysis, and impaired hepatic clearance of cholesterol-rich TRLs remnants can lead to arterial deposition of TRLs and its remnants, promoting foam cell formation and arterial wall inflammation. Therefore, understanding the pathogenesis of TRLs-induced AS and targeting it therapeutically could slow or impede AS progression, thereby reducing cardiovascular disease morbidity and mortality, particularly coronary atherosclerotic heart disease.

Association between atherogenic index of plasma and new-onset stroke in individuals with different glucose metabolism status: insights from CHARLS.

BACKGROUND: Circulating atherogenic index of plasma (AIP) levels has been proposed as a novel biomarker for dyslipidemia and as a predictor of insulin resistance (IR) risk. However, the association between AIP and the incidence of new-onset stroke, particularly in individuals with varying glucose metabolism status, remains ambiguous. METHODS: A total of 8727 participants aged 45 years or older without a history of stroke from the China Health and Retirement Longitudinal Study (CHARLS) were included in this study. The AIP was calculated using the formula log [Triglyceride (mg/dL) / High-density lipoprotein cholesterol (mg/dL)]. Participants were divided into four groups based on their baseline AIP levels: Q1 (AIP ≤ 0.122), Q2 (0.122 < AIP ≤ 0.329), Q3 (0.329 < AIP ≤ 0.562), and Q4 (AIP > 0.562). The primary endpoint was the occurrence of new-onset stroke events. The Kaplan-Meier curves, multivariate Cox proportional hazard models, and Restricted cubic spline analysis were applied to explore the association between baseline AIP levels and the risk of developing a stroke among individuals with varying glycemic metabolic states. RESULTS: During an average follow-up of 8.72 years, 734 participants (8.4%) had a first stroke event. The risk for stroke increased with each increasing quartile of baseline AIP levels. Kaplan-Meier curve analysis revealed a significant difference in stroke occurrence among the AIP groups in all participants, as well as in those with prediabetes mellitus (Pre-DM) and diabetes mellitus (DM) (all P values < 0.05). After adjusting for potential confounders, the risk of stroke was significantly higher in the Q2, Q3, and Q4 groups than in the Q1 group in all participants. The respective hazard ratios (95% confidence interval) for stroke in the Q2, Q3, and Q4 groups were 1.34 (1.05-1.71), 1.52 (1.19-1.93), and 1.84 (1.45-2.34). Furthermore, high levels of AIP were found to be linked to an increased risk of stroke in both pre-diabetic and diabetic participants across all three Cox models. However, this association was not observed in participants with normal glucose regulation (NGR) (p > 0.05). Restricted cubic spline analysis also demonstrated that higher baseline AIP levels were associated with higher hazard ratios for stroke in all participants and those with glucose metabolism disorders. CONCLUSIONS: An increase in baseline AIP levels was significantly associated with the risk of stroke in middle-aged and elderly individuals, and exhibited distinct characteristics depending on the individual's glucose metabolism status.

Atherogenic index of plasma: a new indicator for assessing the short-term mortality of patients with acute decompensated heart failure.

Objective: Arteriosclerosis is a primary causative factor in cardiovascular diseases. This study aims to explore the correlation between the atherogenic index of plasma (AIP) and the 30-day mortality rate in patients with acute decompensated heart failure (ADHF). Methods: A total of 1,248 ADHF patients recruited from the Jiangxi-Acute Decompensated Heart Failure1 (JX-ADHF1) cohort between 2019 and 2022 were selected for this study. The primary outcome was the 30-day mortality rate. Multivariable Cox regression, restricted cubic splines (RCS), and stratified analyses were utilized to assess the relationship between AIP and the 30-day mortality rate in ADHF patients. Mediation models were employed for exploratory analysis of the roles of inflammation, oxidative stress, and nutrition in the association between AIP and the 30-day mortality rate in ADHF patients. Results: During the 30-day follow-up, 42 (3.37%) of the ADHF patients died. The mortality rates corresponding to the quartiles of AIP were as follows: Q1: 1.28%, Q2: 2.88%, Q3: 2.88%, Q4: 6.41%. The multivariable Cox regression revealed a positive correlation between high AIP and the 30-day mortality rate in ADHF patients [Hazard ratio (HR) 3.94, 95% confidence interval (CI): 1.08-14.28], independent of age, gender, heart failure type, cardiac function classification, and comorbidities. It is important to note that there was a U-shaped curve association between AIP (<0.24) and the 30-day mortality rate before the fourth quartile, with the lowest 30-day mortality risk in ADHF patients around an AIP of -0.1. Furthermore, mediation analysis suggested significant mediating effects of inflammation and nutrition on the 30-day mortality rate in ADHF patients related to AIP, with inflammation accounting for approximately 24.29% and nutrition for about 8.16% of the mediation effect. Conclusion: This retrospective cohort analysis reveals for the first time the association between AIP and the 30-day mortality rate in ADHF patients. According to our findings, maintaining an AIP around -0.1 in ADHF patients could be crucial for improving poor prognoses from a medical perspective. Additionally, for ADHF patients with high AIP, it is important to assess and, if necessary, enhance nutritional support and anti-inflammatory treatment.

Association between the atherogenic index of plasma and bone mineral density among adult women: NHANES (2011-2018).

Background: Studies on the relationship between the atherogenic index of plasma (AIP) and bone mineral density (BMD) among adult women in the United States are limited. The purpose of this study was to explore this association using a sizable, nationally representative sample. Methods: Data from the 2011 to 2018 National Health and Nutrition Examination Survey (NHANES) were used in this observational study. The AIP was computed as log10 (triglycerides/high-density lipoprotein cholesterol). Total BMD was measured via dual-energy X-ray densitometry. We constructed multiple linear regression models to evaluate the correlation between the AIP and BMD. The non-linear relationship was characterized by smooth curve fitting and generalized additive models. We also conducted subgroup and interaction analyses. Results: In this study, we included 2,362 adult women with a mean age of 38.13 ± 12.42 years. The results of multiple linear regression analysis, the AIP and total BMD showed a negative association (ß = -0.021, 95%CI: -0.037, -0.006). The curve fitting analysis and threshold effect analysis showed a non-linear relationship between the two variables, and the inflection point of the AIP was found to be -0.61. The total BMD decreased significantly when the AIP reached this value (ß = -0.03, 95%CI: -0.04, -0.01). The results of the subgroup analysis showed that AIP and total BMD had a strong negative relationship in participants who were below 45 years old (ß = -0.023; 95% CI: -0.041, -0.004), overweight (BMI ≥ 25 kg/m2) (ß = -0.022; 95% CI: -0.041, -0.002), had a higher education level (ß = -0.025; 95% CI: -0.044, -0.006), and had no partners (ß = -0.014; 95% CI: -0.06, -0.009). Conclusions: We found a negative correlation between the AIP and total BMD. Clinicians should pay attention to patients with high AIP, which might indicate a low BMD and has reference significance in preventing osteoporosis.