Evidence map›Paper›PMID 33004038›Full record

ArticleJournal of translational medicine2020

Prognostic utility of lipoprotein(a) combined with fibrinogen in patients with stable coronary artery disease: a prospective, large cohort study.

Yan Zhang, Jing-Lu Jin, Ye-Xuan Cao, Hui-Hui Liu, Hui-Wen Zhang, Yuan-Lin Guo, Na-Qiong Wu, Ying Gao, Qi Hua, Yan-Fang Li and 6 more

Open access · goldAbstract read
In one paragraph

Article in Journal of translational medicine, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed, 1 pooled it
1.8field-weighted citation impact, top 14% 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

6 citing papers in PubMed, 1 synthesis or guideline pooled it, 11 citations in OpenAlex.

  1. Pooled it
  2. Article
  3. Article
  4. Impact of lipoprotein(a) and fibrinogen on prognosis in patients with coronary artery disease: A retrospective cohort study.Technology and health care : official journal of the European Society for Engineering and Medicine · 2024
    Article
  5. Review
  6. 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

16 authors at 2 institutions in 1 country.

Yan ZhangDivision of Dyslipidemia, State Key Laboratory of Cardiovascular Disease, FuWai Hospital, National Center for Cardiovascular Diseases, Chinese Academy of Medical Sciences, Peking Union Medical College, BeiLiShi Road 167, Beijing, 100037, China.
Jing-Lu JinDivision of Dyslipidemia, State Key Laboratory of Cardiovascular Disease, FuWai Hospital, National Center for Cardiovascular Diseases, Chinese Academy of Medical Sciences, Peking Union Medical College, BeiLiShi Road 167, Beijing, 100037, China.
Ye-Xuan CaoDivision of Dyslipidemia, State Key Laboratory of Cardiovascular Disease, FuWai Hospital, National Center for Cardiovascular Diseases, Chinese Academy of Medical Sciences, Peking Union Medical College, BeiLiShi Road 167, Beijing, 100037, China.
Hui-Hui LiuDivision of Dyslipidemia, State Key Laboratory of Cardiovascular Disease, FuWai Hospital, National Center for Cardiovascular Diseases, Chinese Academy of Medical Sciences, Peking Union Medical College, BeiLiShi Road 167, Beijing, 100037, China.
Hui-Wen ZhangDivision of Dyslipidemia, State Key Laboratory of Cardiovascular Disease, FuWai Hospital, National Center for Cardiovascular Diseases, Chinese Academy of Medical Sciences, Peking Union Medical College, BeiLiShi Road 167, Beijing, 100037, China.
Yuan-Lin GuoDivision of Dyslipidemia, State Key Laboratory of Cardiovascular Disease, FuWai Hospital, National Center for Cardiovascular Diseases, Chinese Academy of Medical Sciences, Peking Union Medical College, BeiLiShi Road 167, Beijing, 100037, China.
Na-Qiong WuDivision of Dyslipidemia, State Key Laboratory of Cardiovascular Disease, FuWai Hospital, National Center for Cardiovascular Diseases, Chinese Academy of Medical Sciences, Peking Union Medical College, BeiLiShi Road 167, Beijing, 100037, China.
Ying GaoDivision of Dyslipidemia, State Key Laboratory of Cardiovascular Disease, FuWai Hospital, National Center for Cardiovascular Diseases, Chinese Academy of Medical Sciences, Peking Union Medical College, BeiLiShi Road 167, Beijing, 100037, China.
Qi HuaDepartment of Cardiology, Xuanwu Hospital, Capital Medical University, Beijing, China.
Yan-Fang LiDepartment of Cardiology, Beijing Anzhen Hospital, Capital Medical University, Beijing, China.
Rui-Xia XuDivision of Dyslipidemia, State Key Laboratory of Cardiovascular Disease, FuWai Hospital, National Center for Cardiovascular Diseases, Chinese Academy of Medical Sciences, Peking Union Medical College, BeiLiShi Road 167, Beijing, 100037, China.
Chuan-Jue CuiDivision of Dyslipidemia, State Key Laboratory of Cardiovascular Disease, FuWai Hospital, National Center for Cardiovascular Diseases, Chinese Academy of Medical Sciences, Peking Union Medical College, BeiLiShi Road 167, Beijing, 100037, China.
Geng LiuDivision of Dyslipidemia, State Key Laboratory of Cardiovascular Disease, FuWai Hospital, National Center for Cardiovascular Diseases, Chinese Academy of Medical Sciences, Peking Union Medical College, BeiLiShi Road 167, Beijing, 100037, China.
Qian DongDivision of Dyslipidemia, State Key Laboratory of Cardiovascular Disease, FuWai Hospital, National Center for Cardiovascular Diseases, Chinese Academy of Medical Sciences, Peking Union Medical College, BeiLiShi Road 167, Beijing, 100037, China.
Jing SunDivision of Dyslipidemia, State Key Laboratory of Cardiovascular Disease, FuWai Hospital, National Center for Cardiovascular Diseases, Chinese Academy of Medical Sciences, Peking Union Medical College, BeiLiShi Road 167, Beijing, 100037, China.
Jian-Jun LiDivision of Dyslipidemia, State Key Laboratory of Cardiovascular Disease, FuWai Hospital, National Center for Cardiovascular Diseases, Chinese Academy of Medical Sciences, Peking Union Medical College, BeiLiShi Road 167, Beijing, 100037, China. lijianjun938@126.com.ORCID 0000-0003-2536-4364
Chinese Academy of Medical Sciences & Peking Union Medical College · CNCapital Medical University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundElevated lipoprotein(a) [Lp(a)] and fibrinogen (Fib) are both associated with coronary artery disease (CAD). The atherogenicity of Lp(a) can be partly due to the potentially antifibrinolytic categories. We hypothesize that patients with higher Lp(a) and Fib may have worse outcomes.

methodsIn this prospective study, we consecutively enrolled 8,417 Chinese patients with stable CAD from March 2011 to March 2017. All subjects were divided into 9 groups according to Lp(a) (Lp(a)-Low, Lp(a)-Medium, Lp(a)-High) and Fib levels (Fib-Low, Fib-Medium, Fib-High) and followed up for CVEs, including nonfatal acute myocardial infarction, stroke, and cardiovascular mortality. Kaplan-Meier, Cox regression and C-statistic analyses were performed.

resultsDuring a median of 37.1 months' follow-up, 395 (4.7%) CVEs occurred. The occurrence of CVEs increased by Lp(a) (3.5 vs. 5.3 vs. 5.6%, p = 0.001) and Fib (4.0 vs. 4.4 vs. 6.1%, p < 0.001) categories. When further classified into 9 groups by Lp(a) and Fib levels, the CVEs were highest in the 9th (Lp(a)-High and Fib-High) compared with the 1st (Lp(a)-Low and Fib-Low) group (7.2 vs. 3.3%, p < 0.001). The highest risk of subsequent CVEs was found in the 9

conclusionCombining Fib and Lp(a) enhance the prognostic value for incident CVEs beyond Lp(a) or Fib alone.

Indexed as

Coronary Artery DiseaseLipoprotein(a)BiomarkersCohort StudiesFibrinogenHumansPrognosisProspective StudiesRisk FactorsBiomarkersFibrinogenLipoprotein(a)CADCVEsFibrinogenLp(a)

Identifiers

PMID33004038
PMCPMC7528376
OpenAlexW3090243983

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.