Evidence map›Paper›PMID 32536863›Full record

ArticleFrontiers in pharmacology2020

Impact of Plasma Exposure of Statins and Their Metabolites With Major Adverse Cardiovascular Events in Chinese Patients With Coronary Artery Disease.

Xiao-Hong Zhou, Li-Yun Cai, Wei-Hua Lai, Xue Bai, Yi-Bin Liu, Qian Zhu, Guo-Dong He, Ji-Yan Chen, Min Huang, Zhi-Ling Zhou and 1 more

Open access · goldAbstract read
In one paragraph

Article in Frontiers in pharmacology, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
0.2field-weighted citation impact, top 47% 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

3 citing papers in PubMed, 4 citations in OpenAlex.

  1. Review
  2. Article
  3. Frontiers in pharmacology · 2021
    Article
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

11 authors at 4 institutions in 1 country.

Xiao-Hong ZhouGuangdong Provincial Key Laboratory of Coronary Heart Disease Prevention, Guangdong Cardiovascular Institute, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, Guangzhou, China.
Li-Yun CaiGuangdong Provincial Key Laboratory of Coronary Heart Disease Prevention, Guangdong Cardiovascular Institute, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, Guangzhou, China.
Wei-Hua LaiGuangdong Provincial Key Laboratory of Coronary Heart Disease Prevention, Guangdong Cardiovascular Institute, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, Guangzhou, China.
Xue BaiGuangdong Provincial Key Laboratory of Coronary Heart Disease Prevention, Guangdong Cardiovascular Institute, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, Guangzhou, China.
Yi-Bin LiuGuangdong Provincial Key Laboratory of Coronary Heart Disease Prevention, Guangdong Cardiovascular Institute, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, Guangzhou, China.
Qian ZhuGuangdong Provincial Key Laboratory of Coronary Heart Disease Prevention, Guangdong Cardiovascular Institute, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, Guangzhou, China.
Guo-Dong HeGuangdong Provincial Key Laboratory of Coronary Heart Disease Prevention, Guangdong Cardiovascular Institute, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, Guangzhou, China.
Ji-Yan ChenGuangdong Provincial Key Laboratory of Coronary Heart Disease Prevention, Guangdong Cardiovascular Institute, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, Guangzhou, China.
Min HuangLaboratory of Drug Metabolism and Pharmacokinetics, School of Pharmaceutical Sciences, Sun Yat-sen University, Guangzhou, China.
Zhi-Ling ZhouDepartment of Pharmacy, Zhuhai People's Hospital (Zhuhai Hospital affiliated with Jinan University), Zhuhai, China.
Shi-Long ZhongGuangdong Provincial Key Laboratory of Coronary Heart Disease Prevention, Guangdong Cardiovascular Institute, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, Guangzhou, China.
Guangdong Academy of Medical Sciences · CNGuangdong Provincial People's Hospital · CNJinan University · CNSun Yat-sen University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The selection of optimum statin intensity is inconclusive, and the association of plasma exposure of statins and metabolites with major adverse cardiovascular events (MACEs) is unclear. This study sought to compare the effect of low (quartile 1), intermediate (quartiles 2 and 3), and high (quartile 4) plasma exposure of statins and metabolites on MACE, re-ischemia events and death in patients with coronary artery disease (CAD) at 5 years. A total of 1,644 patients in atorvastatin (AT) cohort and 804 patients in rosuvastatin (RST) cohort were included, and their plasma concentration of statins and metabolites was categorized as low-, mid-, or high-group. The association between the plasma levels of statins and metabolites and the incidence of primary endpoint in patients was assessed by Cox proportional hazard models. Intensive AT exposure (Q4 > 5.32 ng/ml) was significantly associated with increased risk of death compared with low (hazard ratio [HR]: 1.522; 95% confidence interval [CI]: 1.035-1.061; P = 0.0022) or moderate exposure (HR: 2.054; 95% CI: 1.348-3.130; P = 0.0008). This association was also found in AT's five metabolites (all P < 0.01). In patients with RST treatment, moderate RST concentration (0.53-4.29 ng/ml)

Indexed as

atorvastatindeathmajor adverse cardiovascular eventsmetabolitesplasma exposurerosuvastatin

Identifiers

PMID32536863
PMCPMC7267016
OpenAlexW3029576770

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.