Evidence map›Paper›PMID 39534057›Full record

ArticleJournal of inflammation research2024

Association Between High-Sensitivity C-Reactive Protein Trajectories and the Incidence of Metabolic Syndrome:A Retrospective Cohort Study.

JianJiang Pan, XiXuan Cai, JieRu Chen, MingYing Xu, JingYu Hu, YueChun Mao, Tao Chen, LuSha Li, MengQi Jin, LiYing Chen

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 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. 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

10 authors.

JianJiang Pan *Department of General Practice, Sir Run Run Shaw Hospital, School of Medicine, Zhejiang University, Hangzhou, Zhejiang, 310020, People's Republic of China.
XiXuan Cai *Department of General Practice, Sir Run Run Shaw Hospital, School of Medicine, Zhejiang University, Hangzhou, Zhejiang, 310020, People's Republic of China.
JieRu ChenDepartment of General Practice, Sir Run Run Shaw Hospital, School of Medicine, Zhejiang University, Hangzhou, Zhejiang, 310020, People's Republic of China.
MingYing XuDepartment of General Practice, Sir Run Run Shaw Hospital, School of Medicine, Zhejiang University, Hangzhou, Zhejiang, 310020, People's Republic of China.ORCID 0009-0007-6129-0223
JingYu HuDepartment of General Practice, Sir Run Run Shaw Hospital, School of Medicine, Zhejiang University, Hangzhou, Zhejiang, 310020, People's Republic of China.
YueChun MaoDepartment of General Practice, Sir Run Run Shaw Hospital, School of Medicine, Zhejiang University, Hangzhou, Zhejiang, 310020, People's Republic of China.
Tao ChenDepartment of General Practice, Jianqiao Community Health Service Center, Hangzhou, Zhejiang, 310021, People's Republic of China.
LuSha LiDepartment of General Practice, Sir Run Run Shaw Hospital, School of Medicine, Zhejiang University, Hangzhou, Zhejiang, 310020, People's Republic of China.
MengQi JinDepartment of General Practice, Sir Run Run Shaw Hospital, School of Medicine, Zhejiang University, Hangzhou, Zhejiang, 310020, People's Republic of China.
LiYing ChenDepartment of General Practice, Sir Run Run Shaw Hospital, School of Medicine, Zhejiang University, Hangzhou, Zhejiang, 310020, People's Republic of China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Purpose: Understanding the role of systemic inflammation in the development of Metabolic Syndrome (MetS) is crucial for identifying individuals at a higher risk of this cluster of conditions that increase the risk of heart disease, stroke, and diabetes. Patients and Methods: A retrospective cohort study was conducted with 4,312 participants who were free from MetS at the study's onset and had high-sensitivity C-reactive protein (hsCRP) levels measured. Latent class trajectory modeling was utilized to identify distinct hsCRP trajectory patterns. Multivariable regression and proportional hazards analyses were employed to evaluate the predictive value of hsCRP trajectories for the development of MetS. Results: During the 1.63-year follow-up period, 1,308 participants developed metabolic syndrome (MetS). Individuals with high hsCRP levels exhibited a significantly increased risk of developing MetS compared to those with low hsCRP levels (HR = 1.062, 95% CI 1.103-1.113). The hsCRP trajectory analysis identified three distinct groups: low-stable, increasing, and decreasing. The decreasing and increasing hsCRP trajectory groups demonstrated a 1.408-fold (95% CI 1.115-1.779) and a 1.618-fold (95% CI 1.288-2.033) increased risk of MetS, respectively. Conclusion: This study suggests that participants with higher baseline hsCRP levels and increasing hsCRP trajectories are associated with a progression toward MetS. Long-term hsCRP trajectories may serve as useful tools for identifying individuals at higher risk of MetS who could benefit from targeted preventive and therapeutic interventions.

Indexed as

high-sensitivity C-reactive proteinmetabolic syndromeretrospective cohort studyrisk predictiontrajectory analysis

Identifiers

PMID39534057
PMCPMC11556323

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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.