Evidence map›Paper›PMID 39720698›Full record

ArticleJournal of inflammation research2024

A Synergistic Effect of Remnant Cholesterol and C-Reactive Protein on Predicting the Severity of Coronary Artery Disease.

Zhen Zhang, Qiang Chen, Qiping Chen, Jun Hou, Xin Li, Jinjuan Fu, Yan Luo, Hong Su, Yu Long, Qiao Feng and 6 more

Abstract read
In one paragraph

Article in Journal of inflammation research, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing papers in PubMed
–field-weighted citation impact
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

8 citing papers in PubMed.

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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

16 authors.

Zhen Zhang *Department of Cardiology, College of Medicine, Southwest Jiaotong University, Chengdu Cardiovascular Disease Research Institute, The Third People's Hospital of Chengdu, Chengdu, Sichuan, People's Republic of China.
Qiang Chen *Department of Cardiology, China-Japan Friendship Hospital, Chinese Academy of Medical Sciences, Peking Union Medical College, Beijing, People's Republic of China.
Qiping Chen *Department of Cardiology, Sichuan Provincial Third People's Hospital, Affiliated Hospital of Sichuan Nursing Vocational College, Chengdu, Sichuan, People's Republic of China.
Jun HouDepartment of Cardiology, College of Medicine, Southwest Jiaotong University, Chengdu Cardiovascular Disease Research Institute, The Third People's Hospital of Chengdu, Chengdu, Sichuan, People's Republic of China.
Xin LiDepartment of Cardiology, College of Medicine, Southwest Jiaotong University, Chengdu Cardiovascular Disease Research Institute, The Third People's Hospital of Chengdu, Chengdu, Sichuan, People's Republic of China.
Jinjuan FuDepartment of Cardiology, College of Medicine, Southwest Jiaotong University, Chengdu Cardiovascular Disease Research Institute, The Third People's Hospital of Chengdu, Chengdu, Sichuan, People's Republic of China.
Yan LuoDepartment of Cardiology, College of Medicine, Southwest Jiaotong University, Chengdu Cardiovascular Disease Research Institute, The Third People's Hospital of Chengdu, Chengdu, Sichuan, People's Republic of China.
Hong SuDepartment of Cardiology, College of Medicine, Southwest Jiaotong University, Chengdu Cardiovascular Disease Research Institute, The Third People's Hospital of Chengdu, Chengdu, Sichuan, People's Republic of China.
Yu LongDepartment of Cardiology, College of Medicine, Southwest Jiaotong University, Chengdu Cardiovascular Disease Research Institute, The Third People's Hospital of Chengdu, Chengdu, Sichuan, People's Republic of China.
Qiao FengDepartment of Cardiology, College of Medicine, Southwest Jiaotong University, Chengdu Cardiovascular Disease Research Institute, The Third People's Hospital of Chengdu, Chengdu, Sichuan, People's Republic of China.
Xiufen PengDepartment of Cardiology, College of Medicine, Southwest Jiaotong University, Chengdu Cardiovascular Disease Research Institute, The Third People's Hospital of Chengdu, Chengdu, Sichuan, People's Republic of China.
Maoling JiangDepartment of Cardiology, College of Medicine, Southwest Jiaotong University, Chengdu Cardiovascular Disease Research Institute, The Third People's Hospital of Chengdu, Chengdu, Sichuan, People's Republic of China.
Daiqian WuDepartment of Cardiology, College of Medicine, Southwest Jiaotong University, Chengdu Cardiovascular Disease Research Institute, The Third People's Hospital of Chengdu, Chengdu, Sichuan, People's Republic of China.
Hanxiong LiuDepartment of Cardiology, College of Medicine, Southwest Jiaotong University, Chengdu Cardiovascular Disease Research Institute, The Third People's Hospital of Chengdu, Chengdu, Sichuan, People's Republic of China.
Lin CaiDepartment of Cardiology, College of Medicine, Southwest Jiaotong University, Chengdu Cardiovascular Disease Research Institute, The Third People's Hospital of Chengdu, Chengdu, Sichuan, People's Republic of China.ORCID 0000-0003-3146-2251
Shiqiang XiongDepartment of Cardiology, College of Medicine, Southwest Jiaotong University, Chengdu Cardiovascular Disease Research Institute, The Third People's Hospital of Chengdu, Chengdu, Sichuan, People's Republic of China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Increased levels of remnant cholesterol (RC) and inflammation are linked to higher risks of atherosclerotic cardiovascular disease. Whether a combination of C-reactive protein (CRP) and RC improves the predictive ability for evaluating the severity of coronary artery lesions remains unknown. Methods: A total of 1675 patients with coronary artery disease were stratified according to the Synergy Between Percutaneous Coronary Intervention (SYNTAX) score (SYNTAX score ≤22 versus SYNTAX score >22). Logistic regression and restricted cubic spline models were used to evaluate the relationship between RC, CRP and the severity of coronary artery lesions. Multivariate logistic regression was used to identify predictors of a mid/high SYNTAX score (SYNTAX score >22). The predictive value of RC combined with CRP was estimated by the ROC curve, continuous net reclassification improvement (NRI) and integrated discrimination improvement (IDI). Results: The multivariable-adjusted odds ratios (95% CIs) for the highest versus lowest quartile of RC were 2.143 (1.450-3.166) for a mid/high SYNTAX score (SYNTAX score >22). The association of RC with severity of coronary artery lesions was maintained significant in the subsample of patients, regardless of traditional cardiovascular risk factors like LDL-C levels and glycemic metabolism status. Moreover, the addition of CRP and RC to the baseline risk model had an incremental effect on the predictive value for a mid/high SYNTAX score (increase in C‑statistic value from 0.650 to 0.698; IDI 0.03; NRI 0.306; all P < 0.01). Conclusion: Elevated RC levels were significantly associated with the severity of coronary artery lesions even in patients with optimal low-density lipoprotein cholesterol levels. Adjustment of the RC by CRP further improved the predictive ability for the severity of coronary artery lesions. The combination of RC and CRP might serve as a noninvasive predictor of CAD complexity and could potentially influence the management and therapeutic approach.

Indexed as

coronary angiographycoronary artery diseaseC-reactive proteininflammationremnant cholesterolsSYNTAX score

Identifiers

PMID39720698
PMCPMC11668247

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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 OpenQuestion graph.