Evidence map›Paper›PMID 35193553›Full record

ArticleCardiovascular diabetology2022

Atherogenic index of plasma for non-diabetic, coronary artery disease patients after percutaneous coronary intervention: a prospective study of the long-term outcomes in China.

Yitian Zheng, Chen Li, Jie Yang, Samuel Seery, Yu Qi, Wenyao Wang, Kuo Zhang, Chunli Shao, Yi-Da Tang

Open access · goldAbstract read
In one paragraph

Article in Cardiovascular diabetology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 44 papers, 4 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
44citing papers in PubMed, 4 pooled it
12.1field-weighted citation impact, top 1% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

44 citing papers in PubMed, 4 syntheses or guidelines pooled it, 76 citations in OpenAlex.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

9 authors at 3 institutions in 3 countries.

Yitian Zheng *Department of Cardiology, State Key Laboratory of Cardiovascular Disease, Fuwai Hospital, National Center for Cardiovascular Diseases, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China.
Chen Li *Department of Cardiology, State Key Laboratory of Cardiovascular Disease, Fuwai Hospital, National Center for Cardiovascular Diseases, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China.
Jie Yang *Department of Cardiology, State Key Laboratory of Cardiovascular Disease, Fuwai Hospital, National Center for Cardiovascular Diseases, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China.
Samuel SeerySchool of Humanities and Social Sciences, Chinese Academy of Medical Science & Peking Union Medical College, Beijing, China.
Yu QiDepartment of Cardiology and Institute of Vascular Medicine, Peking University Third Hospital; NHC Key Laboratory of Cardiovascular Molecular Biology and Regulatory Peptides; Key Laboratory of Molecular Cardiovascular Science, Ministry of Education; Beijing Key Laboratory of Cardiovascular Receptors Research, Beijing, 100191, China.
Wenyao WangDepartment of Cardiology and Institute of Vascular Medicine, Peking University Third Hospital; NHC Key Laboratory of Cardiovascular Molecular Biology and Regulatory Peptides; Key Laboratory of Molecular Cardiovascular Science, Ministry of Education; Beijing Key Laboratory of Cardiovascular Receptors Research, Beijing, 100191, China.
Kuo ZhangDepartment of Cardiology, State Key Laboratory of Cardiovascular Disease, Fuwai Hospital, National Center for Cardiovascular Diseases, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China.
Chunli ShaoDepartment of Cardiology and Institute of Vascular Medicine, Peking University Third Hospital; NHC Key Laboratory of Cardiovascular Molecular Biology and Regulatory Peptides; Key Laboratory of Molecular Cardiovascular Science, Ministry of Education; Beijing Key Laboratory of Cardiovascular Receptors Research, Beijing, 100191, China.
Yi-Da TangDepartment of Cardiology and Institute of Vascular Medicine, Peking University Third Hospital; NHC Key Laboratory of Cardiovascular Molecular Biology and Regulatory Peptides; Key Laboratory of Molecular Cardiovascular Science, Ministry of Education; Beijing Key Laboratory of Cardiovascular Receptors Research, Beijing, 100191, China. tangyida@bjmu.edu.cn.
Chinese Academy of Medical Sciences & Peking Union Medical College · CNPeking University · CNPeking University Third Hospital · CN

Funding

Beijing Nova Program Z201100006820002National Key R&D Program of China 2020YFC2004700National Natural Science Foundation of China 81800327National Natural Science Foundation of China 81825003National Natural Science Foundation of China 81900272National Natural Science Foundation of China 91957123Research Unit of Medical Science Research Management/Basic and Clinical Research of Metabolic Cardiovascular Diseases, Chinese Academy of Medical Sciences 2021RU003
6 · The paper itself

Abstract

backgroundNon-diabetic coronary artery disease (CAD) patients are thought to encounter metabolic dysfunction and while these changes may be imperceptible to the patient they probably influence outcomes. At present, there is no system to support patients sensing these subtle changes, nor is there an established model for prognoses. The Atherogenic Index of Plasma (AIP) index has already proven useful for atherosclerosis although further research is needed, especially for those without hyperglycemia.

methodsThis is a prospective study of 5538 non-diabetic CAD patients who had received percutaneous coronary intervention (PCI). Participants were assigned to one of three groups according to their AIP index. High AIP index cases were then compared to low index patients according to major adverse cardiac events (MACE). Restricted cubic spline (RCS) analysis was also conducted to investigate interrelations between AIP index levels and hazard ratios (HR) for MACEs.

resultsPatients with a high AIP index encountered metabolic dysfunction compared to those with a low AIP index i.e., higher Body Mass Index (BMI), Total Cholesterol (TC), Triglycerides (TG), and uric acid as well as lower HDL-C. Each of the aforementioned interrelations were significant with p values of less than 0.001. There was also a significant increase in the number of MACEs in the high AIP index group compared to the low AIP index group (HR: 1.37, 95% CI 1.04-1.81; p = 0.025). A J-shaped RCS curve highlighted a change in the HR after the 0.18 juncture (HR per SD: 1.20, 95% CI 0.96-1.50). Further subgroup analysis supported the main findings, all with HRs greater than one.

conclusionThe AIP index could be used in prognostics for non-diabetic CAD patients 2 years after PCI. The relationship between hazard ratio and the AIP index appears to be J-shaped. Although, further multi-center studies designed for non-diabetic patients with potential metabolic dysfunction should be conducted to determine the value of the AIP index.

Indexed as

Coronary Artery DiseasePercutaneous Coronary InterventionChinaCholesterol, HDLHumansProspective StudiesRisk FactorsTriglyceridesCholesterol, HDLTriglyceridesAIP indexCoronary artery diseaseMetabolic syndromeNon-diabeticPercutaneous intervention

Identifiers

PMID35193553
PMCPMC8864872
OpenAlexW4212865662

What Socratic holds

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LicenceCC BY
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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.