Evidence map›Paper›PMID 33581713›Full record

ArticleCardiovascular diabetology2021

The predictive utility of circulating PCSK9 levels on diabetes mellitus.

Jia Peng, Cheng-Gang Zhu, Jian-Jun Li

Open access · goldFull text readComment
In one paragraph

Article in Cardiovascular diabetology, 2021. 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
1.3field-weighted citation impact, top 22% 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, 7 citations in OpenAlex.

  1. Article
  2. Article
  3. Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

3 authors at 1 institution in 1 country.

Jia PengState Key Laboratory of Cardiovascular Diseases, FuWai Hospital, National Center for Cardiovascular Diseases, Chinese Academy of Medical Sciences and Peking Union Medical College, No 167 BeiLiShi Road, XiCheng District, Beijing, 100037, China.
Cheng-Gang ZhuState Key Laboratory of Cardiovascular Diseases, FuWai Hospital, National Center for Cardiovascular Diseases, Chinese Academy of Medical Sciences and Peking Union Medical College, No 167 BeiLiShi Road, XiCheng District, Beijing, 100037, China.
Jian-Jun LiState Key Laboratory of Cardiovascular Diseases, FuWai Hospital, National Center for Cardiovascular Diseases, Chinese Academy of Medical Sciences and Peking Union Medical College, No 167 BeiLiShi Road, XiCheng District, Beijing, 100037, China. lijianjun938@126.com.ORCID 0000-0003-2536-4364
Chinese Academy of Medical Sciences & Peking Union Medical College · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Increasing data including ours have suggested that proprotein convertase subtilisin/kexin type 9 (PCSK9), a novel regulator of cholesterol metabolism, may also play an important role in the development of type 2 diabetes mellitus (T2DM) and is associated with clinical outcomes in diabetic patients. Previous studies revealed that elevated plasma PCSK9 levels had a higher incidence of new-onset T2DM. Moreover, the results of available epidemiological, preclinical, and clinical studies have indicated that plasma PCSK9 concentration is correlated with glycemic parameters and can predict the adverse cardiovascular events in diabetic patients with coronary artery disease. However, there is currently no general agreement about the association of PCSK9 with T2DM. The usefulness of the circulating PCSK9 concentration as a predictor for the risk of new-onset T2DM should be clinically prudential.

Indexed as

Coronary Artery DiseaseDiabetes Mellitus, Type 2Blood GlucoseHumansProprotein Convertase 9Blood GlucosePCSK9 protein, humanProprotein Convertase 9Proprotein convertase subtilisin/kexin type 9RisksType 2 diabetes mellitus

Identifiers

PMID33581713
PMCPMC7881449
OpenAlexW3132991516

What OpenQuestion holds

Textfull text, public
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.