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.

Association between the atherogenic index of plasma trajectory and risk of heart failure among hypertensive patients: a prospective cohort study.

BACKGROUND: The atherogenic index of plasma (AIP) has been shown to be positively correlated with cardiovascular events. However, it remains unclear whether hypertensive patients with long-term high AIP levels are at greater risk of developing heart failure (HF). Therefore, the aim of this study was to investigate the association between AIP trajectory and the incidence of HF in hypertensive patients. METHODS: This prospective study included 22,201 hypertensive patients from the Kailuan Study who underwent three waves of surveys between 2006 and 2010. Participants were free of HF or cancer before or during 2010. The AIP was calculated as the logarithmic conversion ratio of triglycerides to high-density lipoprotein cholesterol. Latent mixed modeling was employed to identify different trajectory patterns for AIP during the exposure period (2006-2010). Cox proportional hazard models were then used to estimate the hazard ratio (HR) and 95% confidence interval (CI) for incident HF among different trajectory groups. RESULTS: Four distinct trajectory patterns were identified through latent mixture modeling analysis: low-stable group (n = 3,373; range, -0.82 to -0.70), moderate-low stable group (n = 12,700; range, -0.12 to -0.09), moderate-high stable group (n = 5,313; range, 0.53 to 0.58), and elevated-increasing group (n = 815; range, 1.22 to 1.56). During a median follow-up period of 9.98 years, a total of 822 hypertensive participants experienced HF. After adjusting for potential confounding factors, compared with those in the low-stable group, the HR and corresponding CI for incident HF in the elevated-increasing group, moderate-high stable group, and moderate-low stable group were estimated to be 1.79 (1.21,2.66), 1.49 (1.17,1.91), and 1.27 (1.02,1.58), respectively. These findings remained consistent across subgroup analyses and sensitivity analyses. CONCLUSION: Prolonged elevation of AIP in hypertensive patients is significantly associated with an increased risk of HF. This finding suggests that regular monitoring of AIP could aid in identifying individuals at a heightened risk of HF within the hypertensive population.

Exposure of cumulative atherogenic index of plasma and the development of prediabetes in middle-aged and elderly individuals: evidence from the CHARLS cohort study.

BACKGROUND: The impact of dynamic changes in the degree of atherosclerosis on the development of prediabetes remains unclear. This study aims to investigate the association between cumulative atherogenic index of plasma (CumAIP) exposure during follow-up and the development of prediabetes in middle-aged and elderly individuals. METHODS: A total of 2,939 prediabetic participants from the first wave of the China Health and Retirement Longitudinal Study (CHARLS) were included. The outcomes for these patients, including progression to diabetes and regression to normal fasting glucose (NFG), were determined using data from the third wave. CumAIP was calculated as the ratio of the average AIP values measured during the first and third waves to the total exposure duration. The association between CumAIP and the development of prediabetes was analyzed using multivariable Cox regression and restricted cubic spline (RCS) regression. RESULTS: During a median follow-up period of 3 years, 15.21% of prediabetic patients progressed to diabetes, and 22.12% regressed to NFG. Among the groups categorized by CumAIP quartiles, the proportion of prediabetes progressing to diabetes gradually increased (Q1: 10.61%, Q2: 13.62%, Q3: 15.65%, Q4: 20.95%), while the proportion regressing to NFG gradually decreased (Q1: 23.54%, Q2: 23.71%, Q3: 22.18%, Q4: 19.05%). Multivariable-adjusted Cox regression showed a significant positive linear correlation between high CumAIP exposure and prediabetes progression, and a significant negative linear correlation with prediabetes regression. Furthermore, in a stratified analysis, it was found that compared to married individuals, those who were unmarried (including separated, divorced, widowed, or never married) had a relatively higher risk of CumAIP-related diabetes. CONCLUSION: CumAIP is closely associated with the development of prediabetes. High CumAIP exposure not only increases the risk of prediabetes progression but also hinders its regression within a certain range. These findings suggest that monitoring and maintaining appropriate AIP levels may help prevent the deterioration of blood glucose levels.

The association of atherogenic index of plasma with cardiovascular outcomes in patients with coronary artery disease: A systematic review and meta-analysis.

BACKGROUND: Atherogenic index of plasma (AIP) represents a novel marker in the current era of cardiovascular diseases. In this meta-analysis, we aimed to evaluate the association of AIP with cardiovascular prognosis in patients with coronary artery disease (CAD). METHODS: PubMed, Scopus, and Web of Science databases were searched from inception through 2024. The primary outcome was major cardiovascular events (MACE). The secondary outcomes included all-causes death, cardiovascular death, myocardial infarction (MI), stroke, revascularization, and no-reflow phenomenon. AIP was determined by taking the logarithm of the ratio of triglyceride (TG) to high-density lipoprotein cholesterol (HDL-C). The data analysis was represented using the risk ratio (RR) along with a 95% confidence interval (CI). RESULTS: Sixteen studies with a total number of 20,833 patients met the eligible criteria. The pooled-analysis showed a significant increased risk of MACE in the highest AIP group compared with the lowest AIP group (RR = 1.63; 95% CI, 1.44-1.85; P < 0.001). A similar result was observed when AIP was regarded as a continuous variable (RR = 1.54; 95% CI, 1.30-1.83; P < 0.001). Besides, elevated AIP was associated with increased risk of cardiovascular death (RR = 1.79; 95% CI, 1.09-2.78; P = 0.02), MI (RR = 2.21; 95% CI, 1.55-3.13; P < 0.001), revascularization (RR = 1.62; 95% CI, 1.34-1.97; P < 0.001), no-reflow phenomenon (RR = 3.12 95% CI, 1.09-8.96; P = 0.034), and stent thrombosis (RR = 13.46; 95%CI, 1.39-129.02; P = 0.025). However, AIP was not significantly associated with the risk of all-causes death and stroke among patients with CAD. CONCLUSIONS: The results of this study demonstrated that increased AIP is an independent prognostic factors in patients with CAD. Further research is warranted to elucidate the potential development of targeted interventions to modify AIP levels and improve patient outcomes.

Association between atherogenic index of plasma and all-cause mortality and specific-mortality: a nationwide population­based cohort study.

BACKGROUND: Atherogenic index of plasma (AIP), a marker of atherosclerosis and cardiovascular disease (CVD). However, few studies have investigated association between AIP and all-cause mortality and specific-mortality in the general population. METHODS: This study included data from 14,063 American adults. The exposure variable was the AIP, which was defined as log10 (triglycerides/high-density lipoprotein cholesterol). The outcome variables included all-cause mortality and specific-mortality. Survey-weighted cox regressions were performed to evaluate the relation between AIP and all-cause mortality and specific-mortality. Weighted restricted cubic spline was conducted to examin the non-linear relationship. RESULTS: During 10 years of follow-up, we documented 2,077, 262, 854, and 476 cases of all-cause mortality, diabetes mortality, CVD mortality and cancer mortality, respectively. After adjustment for potential confounders, we found that atherogenic index of plasma (AIP) was significantly associated with an increased risk of diabetes mortality when comparing the highest to the lowest quantile of AIP in female (p for trend = 0.001) or participants older than 65 years (p for trend = 0.002). AIP was not significantly associated with all-cause mortality, CVD mortality and cancer mortality (p > 0.05). Moreover, a non-linear association was observed between AIP and all-cause mortality in a U-shape (p for non-linear = 0.0011), while a linear relationship was observed with diabetes mortality and non-diabetes mortality (p for linear < 0.0001). CONCLUSIONS: In this study, there is a no significant association between high AIP levels and a high risk of all-cause and cardiovascular mortality. Besides, a higher AIP was significantly associated with an increased risk of diabetes mortality, which only found in women older than 65 years. AIP was associated with all-cause mortality in a U-shape. This association could be explained by the finding that higher AIP predicted a higher risk of death from diabetes, and that lower AIP predicted a higher risk of death from non-diabetes causes.

We used a large national database and a prospective cohort study with a long follow-up period. Higher AIP was significantly associated with an increased risk of diabetes mortality, only in women older than 65 years. There is a no significant association between high AIP levels and a high risk of all-cause and cardiovascular mortality. AIP was associated with all-cause mortality in a U-shape. This finding suggest that controlling AIP levels may have a positive effect on reducing diabetes mortality.

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.

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.

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.

Associations between cardiometabolic indices and the risk of diabetic kidney disease in patients with type 2 diabetes.

BACKGROUND: This study was designed to assess the associations between emerging cardiometabolic indices-the atherogenic index of plasma (AIP), the stress hyperglycemia ratio (SHR), the triglyceride-glucose (TyG) index, and the homeostasis model assessment of insulin resistance (HOMA-IR)-and the incidence of diabetic kidney disease (DKD) in type 2 diabetes (T2D) patients. METHODS: We consecutively enrolled 4351 T2D patients. The AIP, SHR, TyG index, and HOMA-IR were calculated from baseline parameters. DKD was defined as a urine albumin/creatinine ratio > 30 mg/g or an eGFR < 60 mL/min per 1.73 m. All participants were categorized into tertiles based on the cardiometabolic indices. Multivariate logistic regression models, restricted cubic splines, and receiver operating characteristic (ROC) curves were used for analysis. RESULTS: A total of 1371 (31.5%) patients were diagnosed with DKD. A restricted cubic spline showed a J-shaped association of the AIP and TyG index with DKD, a log-shaped association between HOMA-IR and DKD, and a U-shaped association between the SHR and DKD incidence. Multivariate logistic regression revealed that individuals in the highest tertile of the four cardiometabolic indices had a significantly greater risk of DKD than did those in the lowest tertile (AIP: OR = 1.08, 95% CI = 1.02-1.14, P = 0.005; SHR: OR = 1.42, 95% CI = 1.12-1.81, P = 0.004; TyG index: OR = 1.86, 95% CI = 1.42-2.45, P < 0.001; HOMA-IR: OR = 2.24, 95% CI = 1.52-3.30, P < 0.001). The receiver operating characteristic curves showed that the HOMA-IR score was better than other indices at predicting the risk of DKD, with an optimal cutoff of 3.532. CONCLUSIONS: Elevated AIP, SHR, TyG index and HOMA-IR are associated with a greater risk of DKD in patients with T2D. Among these indices, the HOMA-IR score demonstrated the strongest association with and predictive value for DKD incidence.

Associations of the triglyceride-glucose index and atherogenic index of plasma with the severity of new-onset coronary artery disease in different glucose metabolic states.

BACKGROUND: The triglyceride-glucose (TyG) index is considered a dependable biomarker for gauging insulin resistance. The atherogenic index of plasma (AIP) represents a marker reflecting atherosclerosis. However, there is currently no study specifically exploring the associations of these two biomarkers with the severity of new-onset coronary artery disease (CAD) under different glucose metabolic states. Therefore, this study aims to evaluate the correlations of these two biomarkers with CAD severity in patients newly diagnosed with CAD under various glucose metabolism conditions. METHOD: Totally 570 subjects first administered coronary angiography were enrolled, including 431 first diagnosed CAD patients and 139 non-CAD patients. CAD severity  was gauged by the quantity of narrowed arteries (single-vessel and multi-vessel CAD). According to WHO diabetes guidelines, glucose metabolic states were divided into normal glucose regulation (NGR), pre-diabetes mellitus (Pre-DM), and diabetes mellitus (DM). The relationships of the TyG index and AIP with CAD severity were validated by logistic regression analysis, including adjustment for traditional cardiovascular risk elements and medical treatments. Their predictive efficacy for CAD was evaluated by receiver operating characteristic (ROC) curves. RESULT: The TyG index and AIP were independently correlated with CAD in accordance with logistic regression analysis (both P < 0.05). Regardless of the glucose metabolic states, there was no statistical correlation between the TyG index and CAD severity. However, AIP in NGR patients was significantly related to CAD severity (P < 0.05). The areas under the curve of the TyG index and AIP for predicting CAD were 0.682 and 0.642 (both P < 0.001), respectively, and their optimal cut-off values were 3.210 (Youden index: 0.305) and 0.095 (Youden index:0.246), respectively. CONCLUSION: The TyG index and AIP have significant associations with CAD. The TyG index had no association with CAD severity, regardless of glucose metabolic states. AIP exhibited a discernible link with CAD severity in NGR patients, but not in the pre-DM or DM populations. The TyG index and AIP have similar predictive values for new-onset CAD.

Multiple triglyceride-derived metabolic indices and incident cardiovascular outcomes in patients with type 2 diabetes and coronary heart disease.

BACKGROUND: Triglyceride (TG) and its related metabolic indices are recognized as important biomarker gauging cardiovascular diseases. This study aimed to explore the association between multiple TG-derived metabolic indices including the atherogenic index of plasma (AIP), triglyceride-glucose (TyG) index, triglyceride glucose-body mass index (TyG-BMI) and cardiovascular outcomes to identify valuable predictors for cardiovascular prognosis in patients with type 2 diabetes (T2DM) and coronary heart disease (CHD). METHODS: Data of 1034 patients with T2DM and CHD from China-Japan Friendship Hospital between January 2019 and March 2022 were collected and analyzed. Multivariate Cox proportional hazards models and restricted cubic spline (RCS) analysis were conducted to examine the associations between AIP, TyG index, TyG-BMI and major adverse cardiac and cerebrovascular events (MACCEs). The area under the receiver operating characteristic (ROC) curve (AUC) was used to screen the most valuable predictor. Kaplan-Meier curve analysis was employed to examine the relationship between the predictor and prognosis. The goodness-of-fit of models was evaluated using the calibration curve and χ2 likelihood ratio test. Subgroup analysis and interaction test were performed to control for confounding factors. RESULTS: The overall incidence of MACCEs was 31.04% during a median of 13.3 months of follow-up. The results showed that AIP, TyG index and TyG-BMI were all positively correlated with the risk of MACCEs in patients with T2DM and CHD (P < 0.05). Furthermore, ROC (AUC = 0.899) suggested that AIP had the strongest ability to predict the risk of MACCEs, and the highest AIP values enhanced the risk by 83.5% in the population. RCS model demonstrated that AIP was nonlinearly associated with the incident cardiovascular outcomes (P for nonlinear = 0.0118). The Kaplan-Meier analysis for MACCEs grouped by the AIP tertiles indicated that the probability of cumulative incidences of MACCEs was significantly higher in patients with a higher AIP (all Log rank P < 0.001). Meanwhile, the calibration curve demonstrated an excellent goodness-of-fit of the multivariate model (χ2 = 13.210, P = 0.105). Subgroup analysis revealed that the trend of positive association of AIP with cardiovascular risk was similar across subgroups except in non-hypertensive individuals. CONCLUSION: Our study, for the first time, may provide valuable information that multiple TG-derived metabolic indices play a crucial role in the risk of MACCEs and it is recommended to monitor the AIP for lipid management in patients with established T2DM and CHD.

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.

The evaluation value of atherogenic index of plasma and high-sensitivity C-reactive protein for the degree of coronary artery lesion in premature coronary artery disease.

BACKGROUND: Premature coronary artery disease (PCAD) is prevailing. We aimed to investigate the evaluation value of atherogenic index of plasma (AIP) and high-sensitivity C-reactive protein (hs-CRP) for the occurrence and severity of coronary artery lesion in PCAD patients. METHODS: PCAD (PACD group)/non-PCAD (control group) patients were enrolled. The coronary artery lesion degree was evaluated using Gensini score (GS). PCAD patients were allocated into the low/medium/high GS groups, with general clinical baseline data analyzed. Plasma hs-CRP/AIP levels were compared in PCAD patients with different disease degree. Correlations between plasma hs-CRP/AIP with Gensini score, independent risk factors affecting the occurrence of PCAD, and the predictive value of hs-CRP/AIP/their combination for the occurrence and degree of PCAD were evaluated by Spearman correlation analysis/Logistic multivariate regression/receiver operating characteristic (ROC) curve. The differences in the area under the curve (AUC) were compared using MedCalc-Comparison of ROC curves. RESULTS: Plasma hs-CRP/AIP levels in the PCAD group were increased. Plasma hs-CRP/AIP levels varied significantly among PCAD patients with different disease degree. Plasma hs-CRP/AIP levels were markedly positively correlated with the Gensini score. Smoking history/homocysteine/fasting blood-glucose/hs-CRP/AIP were all independent risk factors affecting PCAD occurrence. The AUC of hs-CRP and AIP combination predicting the occurrence of PCAD was 0.950 (90.80% sensitivity/93.33% specificity). hs-CRP/AIP combination assisted in predicting the disease degree in PCAD patients. CONCLUSIONS: AIP and hs-CRP are independent risk factors for the occurrence of PCAD, and their combination has high predictive value for PCAD occurrence and disease degree, which are both positively correlated with coronary artery lesion degree.

The association of in-utero exposure to air pollution and atherogenic index of plasma in newborns.

BACKGROUND: Prenatal exposure to particulate matter (PM) and traffic was associated with the programming of cardiovascular diseases (CVDs) in early life. However, the exact underlying mechanisms are not fully understood. Therefore, we aimed to evaluate the association between in-utero exposure to PMs and traffic indicators with the atherogenic index of plasma (AIP) in newborns, which is a precise index reflecting an enhancement of lipid risk factors for CVDs. METHODS: In this cross-sectional study, a total of 300 mother-newborn pairs were enrolled in Sabzevar, Iran. Spatiotemporal land-use regression models were used to estimate the level of PM1, PM2.5 and PM10 at the mother's residential address. The total length of streets in different buffers (100,300 and 500m) and proximity to major roads were calculated as indicators of traffic. The AIP of cord blood samples was calculated using an AIP calculator. Multiple linear regression models were used to examine the association of PM concentrations as well as traffic indicators with AIP controlled for relevant covariates. RESULTS: PM2.5 exposure was significantly associated with higher levels of AIP in newborns. Each interquartile range (IQR) increment of PM2.5 concentration at the mothers' residential addresses was associated with a 5.3% (95% confidence interval (CI): 0.0, 10.6%, P = 0.04) increase in the AIP. Associations between PM1, PM10 and traffic indicators with cord blood level of AIP were positive but not statistically significant. CONCLUSION: Our findings showed that in utero exposure to PM2.5 may be associated with CVDs programming through the increase of atherogenic lipids.

Association between atherogenic index of plasma and asymptomatic intracranial arterial stenosis in middle-aged and elderly women: A cross-sectional study in Shandong, China.

BACKGROUND AND AIMS: The atherogenic index of plasma (AIP) is associated with progression of atherosclerosis and used to describe how pro- or anti-atherogenic components are balanced. However, the association of AIP with asymptomatic intracranial arterial stenosis (aICAS) is uncertain. The purpose of this study is to investigate the association between AIP and aICAS in rural China. METHODS AND RESULTS: A total of 1990 participants aged ≥40 years free of stroke or transient ischemic attack were enrolled in this study. The presence of aICAS was examined by Transcranial Doppler ultrasound and confirmed by magnetic resonance angiography. The adjusted AIP (aAIP) was calculated according to the ratio of TG and HDL-C and further separated into 4 quartiles. Multiple logistic regression was used to investigate the association between aAIP and aICAS, and the dose-response relationship was explored by restricted cubic spline. After adjusting for conventional confounders, aAIP was significantly higher in the aICAS group than that in the non-aICAS group. Furthermore, the common odds ratios for aICAS risk increased with increasing aAIP quartiles. Multivariate logistic regression revealed that aAIP was independently associated with aICAS in female or middle-aged and elderly (age ≥50 years), and superior to other lipid profiles. Multiple-adjusted spline regression showed the dose-response association between aAIP levels and aICAS prevalence. CONCLUSIONS: AIP might be independently and positively associated with the prevalence of aICAS in middle-aged and elderly women, which might be superior to traditional and nontraditional lipid profiles in rural China.

Predicting coronary artery severity in patients undergoing coronary computed tomographic angiography: Insights from pan-immune inflammation value and atherogenic index of plasma.

BACKGROUND AND AIMS: Coronary computed tomographic angiography (CCTA) is pivotal in diagnosing coronary artery disease (CAD). We explored the link between CAD severity and two biomarkers, Pan-Immune Inflammation Value (PIV) and Atherogenic Index of Plasma (AIP), in stable CAD patients. METHODS AND RESULTS: A retrospective observational study of 409 CCTA patients with stable angina pectoris. Logistic regression identified predictors of severe CAD, stratified by CAD-RADS score. Receiver Operating Characteristic (ROC) curves evaluated predictive performance. PIV and AIP were significant predictors of severe CAD (PIV: OR 1.002, 95% CI: 1.000-1.004, p < 0.021; AIP: OR 0.963, 95% CI: 0.934-0.993, p < 0.04). AUC values for predicting severe CAD were 0.563 (p < 0.001) for PIV and 0.625 (p < 0.05) for AIP. Combined with age, AUC improved to 0.662 (p < 0.02). CONCLUSIONS: PIV and AIP were associated with severe CAD, with AIP demonstrating superior predictive capability. Incorporating AIP into risk assessment could enhance CAD prediction, offering a cost-effective and accessible method for identifying individuals at high risk of coronary atherosclerosis.

Gender differences in the association between changes in the atherogenic index of plasma and cardiometabolic diseases: a cohort study.

OBJECTIVE: The relationship between changes in Atherogenic Index of Plasma (AIP) and cardiometabolic diseases (CMD) in middle-aged and elderly individuals remains unclear. This study aims to explore the association between changes in AIP and CMD. METHODS: This study included 3,791 individuals aged over 45 years from CHARLS. Participants were divided into four groups using the K-Means clustering method. Cumulative AIP was used as a quantitative indicator reflecting changes in AIP. Differences in baseline data and CMD incidence rates among these four groups were compared. Multifactorial logistic regression models were used to assess the relationship between changes in AIP and CMD, and subgroup analysis and interaction tests were conducted to evaluate potential relationships between changes in AIP and CMD across different subgroups. Restricted cubic splines (RCS) were used to assess the dose-response relationship between cumulative AIP and CMD. RESULTS: Changes in AIP were independently and positively associated with CMD. In males, the risk significantly increased in class4 compared to class1 (OR 1.75, 95%CI 1.12-2.73). In females, changes in AIP were not significantly associated with CMD. Cumulative AIP was positively correlated with CMD (OR 1.15, 95%CI 1.01-1.30), with significant gender differences in males (OR 1.29, 95%CI 1.07-1.55) and females (OR 1.03, 95%CI 0.87-1.23) (p for interaction = 0.042). In addition, a linear relationship was observed between cumulative AIP and CMD in male. CONCLUSION: Substantial changes in AIP may increase the risk of CMD in middle-aged and elderly Chinese males. Dynamic monitoring of AIP is of significant importance for the prevention and treatment of CMD.

Nonlinear association between atherogenic index of plasma and chronic kidney disease: a nationwide cross-sectional study.

BACKGROUND: The interplay between metabolic disorders and chronic kidney disease (CKD) has been well-documented. However, the connection between CKD and atherogenic index of plasma (AIP) remains understudied. This research delves into the correlation between these two factors, aiming to shed new light on their potential association. METHODS: The relationship between AIP and CKD was evaluated using a weighted multivariate logistic regression model, and the curvilinear relationship between AIP and CKD was explored through smooth curve fitting. We engaged a recursive partitioning algorithm in conjunction with a two-stage linear regression model to precisely determine the inflection point. By conducting stratified analyses, the heterogeneity within subpopulations was explored. RESULTS: In the regression model that accounted for all covariates, ORs (95% CI) for the association between CKD and AIP were 1.12 (0.91, 1.36), indicating no significant association between AIP and CKD. However, sensitivity analyses suggested that the relationship between them may be non-linear. Smooth curve analysis confirmed the non-linear relationship between AIP and CKD, identifying an inflection point at -0.55. Below this threshold, AIP exhibited a significant inverse correlation with CKD. Conversely, above this threshold, a pronounced positive correlation was detected. Stratified analyses elucidated that a non-linear association between AIP and CKD was observed among female participants and those aged 50 and above. CONCLUSION: We found a curvilinear relationship between chronic kidney disease and atherogenic index of plasma.

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.