Evidence map›Paper›PMID 40709335›Full record

ArticleFrontiers in nutrition2025

The predictive value of hsCRP/HDL-C ratio for cardiometabolic multimorbidity in middle-aged and elderly people: evidence from a large national cohort study.

Shiyang Li, Yuyong Liu, Guangyan Sun, Jie Zhou, Deyun Luo, Guangming Mao, Wenhao Xu

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Article in Frontiers in nutrition, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing 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

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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

7 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

7 authors.

Shiyang LiDepartment of Geriatrics, Panzhihua Central Hospital, Panzhihua, China.
Yuyong LiuDepartment of Geriatrics, Panzhihua Central Hospital, Panzhihua, China.
Guangyan SunIntervention Center, Panzhihua Central Hospital, Panzhihua, China.
Jie ZhouDepartment of Geriatrics, Panzhihua Central Hospital, Panzhihua, China.
Deyun LuoDepartment of Geriatrics, Panzhihua Central Hospital, Panzhihua, China.
Guangming MaoPanzhihua Central Hospital, Panzhihua, China.
Wenhao XuPanzhihua Central Hospital, Panzhihua, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Cardiovascular disease is associated with inflammation and dysregulated lipid metabolism. This study aimed to investigate the predictive value of high-sensitive C-reactive protein to high-density lipoprotein cholesterol ratio (CHR) in assessing the risk of developing cardiometabolic multi-morbidity (CMM) within the Chinese population. Methods: A cohort of 8,187 participants were selected from the China Health and Retirement Longitudinal Study (CHARLS) and divided into four groups based on the quartile of CHR. To evaluate the association between CHR and CMM, we employed multivariable Cox proportional hazards regression, logistic regression, and restricted cubic splines (RCS) analysis. Subgroup analyses and interaction tests were conducted to further explore these relationships. Results: The mean age of the included participants was 58.64 ± 9.66 years, with 53.7% being female. Over a median follow-up period of 109 months, 858 participants (10.5%) were diagnosed with new-onset CMM. The incidence of CMM across CHR quartiles Q1, Q2, Q3, and Q4 were 6.4, 9.4, 12.0, and 14.2%, respectively. Compared to the lowest quartile, the fully adjusted hazard ratio (with 95% confidence intervals) for CMM for quartiles Q2-Q4 were 1.43 (1.14-1.79), 1.67 (1.35-2.07), and 1.91 (1.55-2.37), respectively. Per 0.01 unit increase in CHR correlates with a 38% increase in the risk of CMM (HR = 1.38, 95% CI = 1.08-1.77, Conclusion: A higher CHR was positively associated with the risk of CMM. Our findings suggest that CHR, when considered alongside other risk factors, could serve as a valuable biomarker for identifying individuals at heightened risk of developing CMM.

Indexed as

cardiometabolic multimorbidityCHARLShigh-density lipoprotein cholesterol ratiohigh-sensitive C-reactive proteinrisk

Identifiers

PMID40709335
PMCPMC12286803

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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.