The Effect of Untraditional Lipid Parameters in the Development of Coronary Artery Disease: Atherogenic Index of Plasma, Atherogenic Coefficient and Lipoprotein Combined Index

Çelik, Ersin; Çora, Ahmet Rıfkı; Karadem, Kadir Burhan

doi:10.37616/2212-5043.1266

Cited by 17 publications

(17 citation statements)

References 26 publications

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“…The exposure of interest was atherosclerotic indices including AC, CRI-I, CRI-II, AIP, LCI, the cholesterol index, non-HDL-C, and TG/HDL-C that were calculated by the following formulas ( 8 , 10 , 17 ): AC = (TC-HDL-C)/HDL-C; AIP = Log(TG/HDL-C); non-HDL-C = TC-HDL-C; CRI-I = (TC/HDL-C); CRI-II = (LDL-C/HDL-C); LCI = TC * TG * LDL-C/HDL-C; cholesterol index = LDL-C-HDL-C (TG <400mg/dl) or LDL-C-HDL-C+TG/5 (TG≥ 400mg/dl).…”

Section: Methodsmentioning

confidence: 99%

“…The exposure of interest was atherosclerotic indices including AC, CRI-I, CRI-II, AIP, LCI, the cholesterol index, non-HDL-C, and TG/HDL-C that were calculated by the following formulas (8,10,17) The study outcome was the prevalence of hypertension. Blood pressure values were obtained by trained staff using a standard mercury sphygmomanometer in a quiet environment.…”

Section: Exposure Of Interest and Outcome Measuresmentioning

confidence: 99%

“…Over the past 20 years, several unconventional lipid ratios: atherosclerosis indices, including the atherogenic coefficient (AC), Castelli's risk index I (CRI-I) and II (CRI-II), the atherogenic index of plasma (AIP), the cholesterol index, the lipoprotein combined index (LCI), non-HDL-C and TG/HDL-C, have been proposed. Meanwhile, many studies have confirmed that atherosclerotic indices is conducive to the predication of CVD risk and atherosclerosis (8)(9)(10)(11).…”

Section: Introductionmentioning

confidence: 99%

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Dyslipidemia and the Prevalence of Hypertension: A Cross-Sectional Study Based on Chinese Adults Without Type 2 Diabetes Mellitus

Cheng

Zhuang²,

Chen

2022

Front. Cardiovasc. Med.

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BackgroundIn clinical practice, it is frequently observed that patients with hypertension often coexist with dyslipidemia. However, studies on atherosclerotic indices and the prevalence of hypertension are still limited. The purpose of this study was to assess the relationship between atherosclerotic indices and the prevalence of hypertension in Chinese adults without type 2 diabetes mellitus.MethodsIn this paper, a cross-sectional study was conducted based on 117,056 adults in 11 Chinese cities (Shanghai, Beijing, Wuhan, Suzhou, Shenzhen, Changzhou, Nantong, Guangzhou, Hefei, Nanjing, and Chengdu) from 2010 to 2016. Besides, the raw data was obtained from the public database (www.Datadryad.org), while eight atherosclerosis indices namely the atherogenic coefficient (AC), Castelli's risk index I (CRI-I) and II (CRI-II), the atherogenic index of plasma (AIP), the cholesterol index, the lipoprotein combined index (LCI), non-high-density lipoprotein cholesterol (non-HDL-C) and triglycerides/high-density lipoprotein cholesterol (TG/HDL-C) were analyzed in this study. Apart from that, two groups of continuous variables were measured using the Mann-Whitney test, and categorical variables were analyzed using the Chi-square test. Differences between multiple groups of continuous variables were investigated using Kruskal-Wallis one-way analysis of variance (ANOVA) and Dunn's test. Furthermore, Spearman correlation analysis and multivariate logistic regression analyses were performed to assess the relationship between atherosclerotic indices and blood pressure levels, and the prevalence of hypertension, respectively. The results of multivariate logistic regression analyses were expressed as the odds ratio (OR) and their corresponding 95% confidence intervals (CIs). Moreover, the receiver operating characteristic (ROC) curve was depicted to further analyze the predictive value of the atherosclerotic indices on the prevalence of hypertension.ResultsThe atherosclerosis indices were higher in the hypertensive population compared to those in the normotensive population. Meanwhile, systolic blood pressure (SBP) and diastolic blood pressure (DBP) were linearly and positively correlated with atherosclerotic indices. In addition, multivariate logistic regression analysis showed that the cholesterol index and non-HDL-C were observed to be positively associated with the prevalence of hypertension (p for trend < 0.05). Moreover, the prevalence of hypertension increased by 3.7% (OR: 1.037; 95% CI: 1.009-1.065; p = 0.009) and 6.1% (OR: 1.06; 95% CI: 1.033–1.091; p < 0.001), respectively, as per 1-standard deviation (SD) increase in the cholesterol index and non-HDL-C. Beyond that, ROC analysis demonstrated that the cholesterol index and non-HDL-C have a good predictive value for the prevalence of hypertension in women, with under the ROC curve (AUC) of 0.659 and 0.684 and cut-off values of 47.94 and 134.34 mg/dl, accordingly.ConclusionsIn Chinese adults without type 2 diabetes mellitus, atherosclerotic indices were significantly higher in hypertensive populations compared with those in normotensive populations, regardless of hypertension levels. Meanwhile, SBP and DBP were linearly and positively related to atherosclerotic indices. Besides, the cholesterol index and non-HDL-C were independent risk factors for the prevalence of hypertension, and they could be adopted for effectively predicting the prevalence of hypertension in women.

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Section: Methodsmentioning

confidence: 99%

“…The exposure of interest was atherosclerotic indices including AC, CRI-I, CRI-II, AIP, LCI, the cholesterol index, non-HDL-C, and TG/HDL-C that were calculated by the following formulas (8,10,17) The study outcome was the prevalence of hypertension. Blood pressure values were obtained by trained staff using a standard mercury sphygmomanometer in a quiet environment.…”

Section: Exposure Of Interest and Outcome Measuresmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Dyslipidemia and the Prevalence of Hypertension: A Cross-Sectional Study Based on Chinese Adults Without Type 2 Diabetes Mellitus

Cheng

Zhuang²,

Chen

2022

Front. Cardiovasc. Med.

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“…Concentrations of lipoproteins: TC, HDL-C, LDL-C and TG were measured by the direct enzymatic colorimetric method, using commercial in vitro diagnostic devices (cobas c, Roche, Switzerland) whereas non-HDL-C was calculated manually (Non-HDL-C= TC-HDL-C). AIP, AC and LCI were also calculated manually using the following formulas: AIP=Log 10 (TG/ HDL-C); AC= Non-HDL-C/HDL-C; LCI= TC-TG-LDL-C/HDL-C (3,7).…”

Section: Laboratory Measurementsmentioning

confidence: 99%

“…In recent years, several novel indicators have been proposed as non-traditional cardiovascular risk factors, however their signifi cance and usefulness remains unknown (2)(3)(4)(5).…”

Section: Introductionmentioning

confidence: 99%

Prognostic significance of atherogenic index of plasma, atherogenic coefficient and lipoprotein combined index among elderly patients with non-ST-segment elevation myocardial infarction in 1-year follow-up

DRWILA¹,

ROSTOFF²,

NESSLER³

et al. 2022

BLL

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OBJECTIVES: Coronary artery disease (CAD) remains a leading cause of death in elderly patients. Recently, novel lipoproteins-Atherogenic Index of Plasma (AIP), Atherogenic Coeffi cient (AC) and Lipoprotein Combine Index (LCI) have been suggested as CAD risk factors; their clinical usefulness, however, remains unknown. The aim of the study was to assess the predictive value of AIP, AC and LCI concerning incidence of major adverse cardiovascular events (MACE) and all-cause mortality in 1-year follow-up. METHODS: For the study, 1,083 patients, aged 60 or older, with NSTEMI were enrolled and divided into two groups: young-old and old-old. RESULTS: MACE occurred in 11.8 % of the patients; LCI showed a borderline signifi cance, but only in univariate analysis. Analysis in groups revealed ambiguous results. None of the examined indices was a predictor of MACE in the young-old group whereas all three of them were signifi cant, but negative predictors in the old-old group. Finally, all-cause mortality at follow-up was 14.9 %. AC predicted 1-year mortality in the whole study population (OR = 1.1 (95% CI: 1-1.2; p = 0.02), but was insignifi cant in the multivariable model. Additionally, it was an independent predictor in the old-old group, but with borderline signifi cance (OR = 1.14 (95% CI: 1-1.3, p = 0.036). CONCLUSIONS: AIP, AC and LCI should not be used as predictors of MACE and 1-year mortality among elderly patients with NSTEMI (Tab. 5, Ref. 23).

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Tracking between cardiovascular-related measures at 4 and 8 years of age in the INMA-Asturias cohort

et al. 2023

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Identifying cardiovascular-related measures that track from early childhood into later ages may help inform early prevention targets for cardiovascular disease. In this study, the tracking of triglycerides (TG), high-density cholesterol (HDL-c), atherogenic coefficient (AC), waist circumference to height ratio (WC/Height), mean arterial pressure (MAP), and homeostatic model assessment of insulin resistance (HOMA-IR) was examined in the INMA-Asturias cohort between 4 and 8 years of age. The analysis was conducted in 307 children who participated in the INMA-Asturias cohort (Spain) at 4 and at 8 years of age. Quantile regression models were used to evaluate tracking between measures at both ages, with each measure at 8 years as the dependent variable and the rank transformation of the same measure at 4 years as the independent variable. We found a positive association between HDL-c rank at 4 years and higher quantiles of the HDL-c distribution at 8 years, with an increase of 2.93 mg/dL (95% CI: 1.98, 3.87) per decile in the 0.9 quantile. A positive association was also found for WC/Height, with an increase of 0.008 (95% CI: 0.004, 0.012) per decile in the 0.9 quantile. We observed that tracking for AC increased in the higher quantiles of the distribution at 8 years, with an increase of 0.11 (95% CI: 0.09, 0.14) in the 0.6 quantile compared to an effect of 0.15 (95% CI: 0.09, 0.21) in the 0.9 quantile. Conclusions: Adult markers of dyslipidemia and central obesity tracked between ages 4 and 8 years. For AC, tracking increased in the higher quantiles of the distribution. What is Known:• Atherosclerosis begins in early life, so preventive efforts that start in childhood may delay progression to clinical disease. Determine what cardiovascular risk factors track into time since childhood bring the opportunity to identified those subjects at risk for later cardiovascular disease.• The study of risk factors in health populations and, particularly in children, copes with not clear and/or controversial thresholds definition. This makes it challenging to study tracking in pediatric ages. What is New:• Quantile regression is a useful tool for assessing the tracking of risk factors for which there are no clinically meaningful thresholds. The increasing trend observed in the tracking of dyslipidemia suggests the possible difficulty that children with abnormal values at 4 years of age might have in normalizing them in future years.• The findings of this article may help to determine which cardiovascular-related measures could be screened and followed-up in children.

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The Effect of Untraditional Lipid Parameters in the Development of Coronary Artery Disease: Atherogenic Index of Plasma, Atherogenic Coefficient and Lipoprotein Combined Index

Cited by 17 publications

References 26 publications

Dyslipidemia and the Prevalence of Hypertension: A Cross-Sectional Study Based on Chinese Adults Without Type 2 Diabetes Mellitus

Dyslipidemia and the Prevalence of Hypertension: A Cross-Sectional Study Based on Chinese Adults Without Type 2 Diabetes Mellitus

Prognostic significance of atherogenic index of plasma, atherogenic coefficient and lipoprotein combined index among elderly patients with non-ST-segment elevation myocardial infarction in 1-year follow-up

Tracking between cardiovascular-related measures at 4 and 8 years of age in the INMA-Asturias cohort

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