Predictive value of atherogenic index of plasma and atherogenic index of plasma combined with low-density lipoprotein cholesterol for the risk of acute myocardial infarction.

Autor:	Chen M; Department of Cardiology, The Second People's Hospital of Hefei, Hefei Hospital Affiliated to Anhui Medical University, Hefei, China., Fang CY; Department of Cardiology, The Second People's Hospital of Hefei, Hefei Hospital Affiliated to Anhui Medical University, Hefei, China., Guo JC; Department of Cardiology, The Third Affiliated Hospital of Anhui Medical University (The First People's Hospital of Hefei), Hefei, China., Pang LM; Department of Endocrinology, Hefei BOE Hospital, Hefei, China., Zhou Y; Department of Cardiology, The Third Affiliated Hospital of Anhui Medical University (The First People's Hospital of Hefei), Hefei, China., Hong Y; Department of Cardiology, The Third Affiliated Hospital of Anhui Medical University (The First People's Hospital of Hefei), Hefei, China., Yang LF; Department of Cardiology, The Second People's Hospital of Hefei, Hefei Hospital Affiliated to Anhui Medical University, Hefei, China., Zhang J; Department of Cardiology, The Second People's Hospital of Hefei, Hefei Hospital Affiliated to Anhui Medical University, Hefei, China., Zhang T; Department of Cardiology, The Second People's Hospital of Hefei, Hefei Hospital Affiliated to Anhui Medical University, Hefei, China., Zhou BF; Department of Cardiology, The Third Affiliated Hospital of Anhui Medical University (The First People's Hospital of Hefei), Hefei, China., Hu GQ; Department of Cardiology, The Second Affiliated Hospital of Anhui Medical University, Hefei, China.
Jazyk:	angličtina
Zdroj:	Frontiers in cardiovascular medicine [Front Cardiovasc Med] 2023 May 26; Vol. 10, pp. 1117362. Date of Electronic Publication: 2023 May 26 (Print Publication: 2023).
DOI:	10.3389/fcvm.2023.1117362
Abstrakt:	Background and Aims: Acute myocardial infarction (AMI) is a prevalent medical condition associated with significant morbidity and mortality rates. The principal underlying factor leading to myocardial infarction is atherosclerosis, with dyslipidemia being a key risk factor. Nonetheless, relying solely on a single lipid level is insufficient for accurately predicting the onset and progression of AMI. The present investigation aims to assess established clinical indicators in China, to identify practical, precise, and effective tools for predicting AMI. Methods: The study enrolled 267 patients diagnosed with acute myocardial infarction as the experimental group, while the control group consisted of 73 hospitalized patients with normal coronary angiography. The investigators collected general clinical data and relevant laboratory test results and computed the Atherogenic Index of Plasma (AIP) for each participant. Using acute myocardial infarction status as the dependent variable and controlling for confounding factors such as smoking history, fasting plasma glucose (FPG), low-density lipoprotein cholesterol (LDL-C), blood pressure at admission, and diabetes history, the researchers conducted multivariate logistic regression analysis with AIP as an independent variable. Receiver operating characteristic (ROC) curves were employed to determine the predictive value of AIP and AIP combined with LDL-C for acute myocardial infarction. Result: The results of the multivariate logistic regression analysis indicated that the AIP was an independent predictor of acute myocardial infarction. The optimal cut-off value for AIP to predict AMI was -0.06142, with a sensitivity of 81.3%, a specificity of 65.8%, and an area under the curve (AUC) of 0.801 (95% confidence interval [CI]: 0.743-0.859, P  < 0.001). When AIP was combined with LDL-C, the best cut-off value for predicting acute myocardial infarction was 0.756107, with a sensitivity of 79%, a specificity of 74%, and an AUC of 0.819 (95% CI: 0.759-0.879, P  < 0.001). Conclusions: The AIP is considered an autonomous determinant of risk for AMI. Utilizing the AIP index alone, as well as in conjunction with LDL-C, can serve as effective predictors of AMI. Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest. (© 2023 Chen, Fang, Guo, Pang, Zhou, Hong, Yang, Zhang, Zhang, Zhou and Hu.)
Databáze:	MEDLINE
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